diff --git a/datasets/PACE_OCI_L3B_AVW_NRT_2.0.json b/datasets/PACE_OCI_L3B_AVW_NRT_2.0.json
index 2d1eb26602..cf833db68b 100644
--- a/datasets/PACE_OCI_L3B_AVW_NRT_2.0.json
+++ b/datasets/PACE_OCI_L3B_AVW_NRT_2.0.json
@@ -1,7 +1,7 @@
{
"type": "Collection",
"id": "PACE_OCI_L3B_AVW_NRT_2.0",
- "stac_version": "1.0.0",
+ "stac_version": "1.1.0",
"description": "The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.",
"links": [
{
@@ -58,20 +58,6 @@
"title": "Collection Items"
}
],
- "provider": [
- {
- "name": "OB_CLOUD",
- "roles": [
- "producer"
- ]
- },
- {
- "name": "NASA EOSDIS",
- "roles": [
- "host"
- ]
- }
- ],
"title": "PACE OCI Level-3 Global Binned Apparent Visible Wavelength (AVW) - Near Real Time (NRT) Data, version 2.0",
"extent": {
"spatial": {
@@ -100,6 +86,20 @@
"Ocean Optics",
"Ocean Color"
],
+ "providers": [
+ {
+ "name": "OB_CLOUD",
+ "roles": [
+ "producer"
+ ]
+ },
+ {
+ "name": "NASA EOSDIS",
+ "roles": [
+ "host"
+ ]
+ }
+ ],
"summaries": {
"platform": [
"PACE"
diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json
index 36ed5289a3..fee81b57cb 100644
--- a/nasa_cmr_catalog.json
+++ b/nasa_cmr_catalog.json
@@ -115728,7 +115728,7 @@
{
"id": "KOPRI-KPDC-00000589_1",
"title": "Air temperature and humidity in Cambridge Bay, Canada in 2012",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2012-07-11",
"end_date": "2013-08-04",
"bbox": "-180, -90, 180, 90",
@@ -115741,7 +115741,7 @@
{
"id": "KOPRI-KPDC-00000589_1",
"title": "Air temperature and humidity in Cambridge Bay, Canada in 2012",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2012-07-11",
"end_date": "2013-08-04",
"bbox": "-180, -90, 180, 90",
@@ -115780,7 +115780,7 @@
{
"id": "KOPRI-KPDC-00000592_1",
"title": "Air temperature and humidity in Cambridge Bay, Canada in 2013",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2013-08-01",
"end_date": "2014-06-30",
"bbox": "-180, -90, 180, 90",
@@ -115793,7 +115793,7 @@
{
"id": "KOPRI-KPDC-00000592_1",
"title": "Air temperature and humidity in Cambridge Bay, Canada in 2013",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2013-08-01",
"end_date": "2014-06-30",
"bbox": "-180, -90, 180, 90",
@@ -115806,7 +115806,7 @@
{
"id": "KOPRI-KPDC-00000593_1",
"title": "Air temperature and humidity in Cambridge Bay, Canada in 2014",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-06-01",
"end_date": "2015-08-31",
"bbox": "-180, -90, 180, 90",
@@ -115819,7 +115819,7 @@
{
"id": "KOPRI-KPDC-00000593_1",
"title": "Air temperature and humidity in Cambridge Bay, Canada in 2014",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2014-06-01",
"end_date": "2015-08-31",
"bbox": "-180, -90, 180, 90",
@@ -116170,7 +116170,7 @@
{
"id": "KOPRI-KPDC-00000620_1",
"title": "2015-2016 JBS_micro-climate data_HOBO_soil temp.,PAR,air temp.,relative humidity",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2015-02-09",
"end_date": "2015-02-13",
"bbox": "164.191389, -74.632806, 164.229972, -74.613",
@@ -116183,7 +116183,7 @@
{
"id": "KOPRI-KPDC-00000620_1",
"title": "2015-2016 JBS_micro-climate data_HOBO_soil temp.,PAR,air temp.,relative humidity",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2015-02-09",
"end_date": "2015-02-13",
"bbox": "164.191389, -74.632806, 164.229972, -74.613",
@@ -116222,7 +116222,7 @@
{
"id": "KOPRI-KPDC-00000623_1",
"title": "Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2015",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2015-03-01",
"end_date": "2016-02-01",
"bbox": "-58.789338, -62.240538, -58.721474, -62.220364",
@@ -116235,7 +116235,7 @@
{
"id": "KOPRI-KPDC-00000623_1",
"title": "Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2015",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2015-03-01",
"end_date": "2016-02-01",
"bbox": "-58.789338, -62.240538, -58.721474, -62.220364",
@@ -117314,7 +117314,7 @@
{
"id": "KOPRI-KPDC-00000707_3",
"title": "3D floorplan for CAD of Jang Bogo Station",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-01-01",
"end_date": "2011-01-31",
"bbox": "164.228817, -74.624017, 164.228817, -74.624017",
@@ -117327,7 +117327,7 @@
{
"id": "KOPRI-KPDC-00000707_3",
"title": "3D floorplan for CAD of Jang Bogo Station",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2011-01-01",
"end_date": "2011-01-31",
"bbox": "164.228817, -74.624017, 164.228817, -74.624017",
@@ -117535,7 +117535,7 @@
{
"id": "KOPRI-KPDC-00000723_1",
"title": "Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2012",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-58.766667, -62.216667, -58.766667, -62.216667",
@@ -117548,7 +117548,7 @@
{
"id": "KOPRI-KPDC-00000723_1",
"title": "Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2012",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-58.766667, -62.216667, -58.766667, -62.216667",
@@ -117561,7 +117561,7 @@
{
"id": "KOPRI-KPDC-00000724_1",
"title": "Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2013",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-58.766667, -62.216667, -58.766667, -62.216667",
@@ -117574,7 +117574,7 @@
{
"id": "KOPRI-KPDC-00000724_1",
"title": "Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2013",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-58.766667, -62.216667, -58.766667, -62.216667",
@@ -118055,7 +118055,7 @@
{
"id": "KOPRI-KPDC-00000760_1",
"title": "Air borne Ice radar survey data of Korean route from David glacier, Antarctica in 2016-2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2016-12-28",
"end_date": "2017-02-15",
"bbox": "153.936483, -75.389942, 159.216086, -75.059956",
@@ -118068,7 +118068,7 @@
{
"id": "KOPRI-KPDC-00000760_1",
"title": "Air borne Ice radar survey data of Korean route from David glacier, Antarctica in 2016-2017",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-12-28",
"end_date": "2017-02-15",
"bbox": "153.936483, -75.389942, 159.216086, -75.059956",
@@ -118159,7 +118159,7 @@
{
"id": "KOPRI-KPDC-00000767_1",
"title": "2016-2017 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-01-14",
"end_date": "2017-01-27",
"bbox": "-58.788436, -62.240056, -58.719694, -62.218583",
@@ -118172,7 +118172,7 @@
{
"id": "KOPRI-KPDC-00000767_1",
"title": "2016-2017 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2016-01-14",
"end_date": "2017-01-27",
"bbox": "-58.788436, -62.240056, -58.719694, -62.218583",
@@ -118211,7 +118211,7 @@
{
"id": "KOPRI-KPDC-00000770_1",
"title": "Aerosol Number Concentration (>10nm) from King Sejong Station collected in 2010-2016.",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2010-01-01",
"end_date": "2016-12-31",
"bbox": "-58.78, -62.22, -58.78, -62.22",
@@ -118224,7 +118224,7 @@
{
"id": "KOPRI-KPDC-00000770_1",
"title": "Aerosol Number Concentration (>10nm) from King Sejong Station collected in 2010-2016.",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-01-01",
"end_date": "2016-12-31",
"bbox": "-58.78, -62.22, -58.78, -62.22",
@@ -118289,7 +118289,7 @@
{
"id": "KOPRI-KPDC-00000775_1",
"title": "Aerosol Size Distribution from King Sejong Station collected in 2010-2016.",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2010-01-01",
"end_date": "2016-12-31",
"bbox": "-58.78, -62.22, -58.78, -62.22",
@@ -118302,7 +118302,7 @@
{
"id": "KOPRI-KPDC-00000775_1",
"title": "Aerosol Size Distribution from King Sejong Station collected in 2010-2016.",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-01-01",
"end_date": "2016-12-31",
"bbox": "-58.78, -62.22, -58.78, -62.22",
@@ -118523,7 +118523,7 @@
{
"id": "KOPRI-KPDC-00000792_3",
"title": "Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2016",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2016-01-10",
"end_date": "2017-02-02",
"bbox": "-58.789338, -62.240538, -58.721474, -62.220364",
@@ -118536,7 +118536,7 @@
{
"id": "KOPRI-KPDC-00000792_3",
"title": "Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2016",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-01-10",
"end_date": "2017-02-02",
"bbox": "-58.789338, -62.240538, -58.721474, -62.220364",
@@ -119680,7 +119680,7 @@
{
"id": "KOPRI-KPDC-00000879_1",
"title": "Air temperature and air humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2016-06-19",
"end_date": "2017-06-18",
"bbox": "-105.133333, 69.1, -105.133333, 69.1",
@@ -119693,7 +119693,7 @@
{
"id": "KOPRI-KPDC-00000879_1",
"title": "Air temperature and air humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2017",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-06-19",
"end_date": "2017-06-18",
"bbox": "-105.133333, 69.1, -105.133333, 69.1",
@@ -120590,7 +120590,7 @@
{
"id": "KOPRI-KPDC-00000947_1",
"title": "Advanced Very High Resolution Radiometer (AVHRR) around the Jang Bogo Station, 2015-2016",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2015-03-03",
"end_date": "2016-02-15",
"bbox": "164.233333, -74.616667, 164.233333, -74.616667",
@@ -120603,7 +120603,7 @@
{
"id": "KOPRI-KPDC-00000947_1",
"title": "Advanced Very High Resolution Radiometer (AVHRR) around the Jang Bogo Station, 2015-2016",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2015-03-03",
"end_date": "2016-02-15",
"bbox": "164.233333, -74.616667, 164.233333, -74.616667",
@@ -121253,7 +121253,7 @@
{
"id": "KOPRI-KPDC-00000999_2",
"title": "2018 Multibeam bathymetry data in the Ross Sea, Antarctica",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-03-13",
"end_date": "",
"bbox": "164.4, -75.5, 165.9, -75.1",
@@ -121266,7 +121266,7 @@
{
"id": "KOPRI-KPDC-00000999_2",
"title": "2018 Multibeam bathymetry data in the Ross Sea, Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2018-03-13",
"end_date": "",
"bbox": "164.4, -75.5, 165.9, -75.1",
@@ -122618,7 +122618,7 @@
{
"id": "KOPRI-KPDC-00001102_3",
"title": "All-Sky airglow image, King Sejong Station, Antarctica, 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2017-10-01",
"bbox": "-58.7766, -62.2206, -58.7766, -62.2206",
@@ -122631,7 +122631,7 @@
{
"id": "KOPRI-KPDC-00001102_3",
"title": "All-Sky airglow image, King Sejong Station, Antarctica, 2017",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2017-10-01",
"bbox": "-58.7766, -62.2206, -58.7766, -62.2206",
@@ -122722,7 +122722,7 @@
{
"id": "KOPRI-KPDC-00001108_4",
"title": "All-sky aurora (proton) image at Jang Bogo Station, Antarctica, 2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2018-01-01",
"end_date": "2018-12-31",
"bbox": "164.2273, -74.6202, 164.2273, -74.6202",
@@ -122735,7 +122735,7 @@
{
"id": "KOPRI-KPDC-00001108_4",
"title": "All-sky aurora (proton) image at Jang Bogo Station, Antarctica, 2018",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-01-01",
"end_date": "2018-12-31",
"bbox": "164.2273, -74.6202, 164.2273, -74.6202",
@@ -122787,7 +122787,7 @@
{
"id": "KOPRI-KPDC-00001112_4",
"title": "All-sky aurora (proton) image, Longyearbyen, Norway, 2018",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-01-01",
"end_date": "2018-02-28",
"bbox": "16.040746, 78.147909, 16.040746, 78.147909",
@@ -122800,7 +122800,7 @@
{
"id": "KOPRI-KPDC-00001112_4",
"title": "All-sky aurora (proton) image, Longyearbyen, Norway, 2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2018-01-01",
"end_date": "2018-02-28",
"bbox": "16.040746, 78.147909, 16.040746, 78.147909",
@@ -123034,7 +123034,7 @@
{
"id": "KOPRI-KPDC-00001129_1",
"title": "Air temperature and humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2018",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-06-19",
"end_date": "2018-06-18",
"bbox": "-105.133333, 69.1, -105.133333, 69.1",
@@ -123047,7 +123047,7 @@
{
"id": "KOPRI-KPDC-00001129_1",
"title": "Air temperature and humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2017-06-19",
"end_date": "2018-06-18",
"bbox": "-105.133333, 69.1, -105.133333, 69.1",
@@ -123411,7 +123411,7 @@
{
"id": "KOPRI-KPDC-00001157_3",
"title": "All-Sky airglow image, Jang Bogo Station, Antarctica, 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2017-10-01",
"bbox": "164.2273, -74.6202, 164.2273, -74.6202",
@@ -123424,7 +123424,7 @@
{
"id": "KOPRI-KPDC-00001157_3",
"title": "All-Sky airglow image, Jang Bogo Station, Antarctica, 2017",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2017-10-01",
"bbox": "164.2273, -74.6202, 164.2273, -74.6202",
@@ -124178,7 +124178,7 @@
{
"id": "KOPRI-KPDC-00001219_3",
"title": "Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2017",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2017-12-31",
"bbox": "-58.78, -62.22, -58.78, -62.22",
@@ -124191,7 +124191,7 @@
{
"id": "KOPRI-KPDC-00001219_3",
"title": "Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2017-12-31",
"bbox": "-58.78, -62.22, -58.78, -62.22",
@@ -124737,7 +124737,7 @@
{
"id": "KOPRI-KPDC-00001265_3",
"title": "All-sky aurora (proton) image, KHO Longyearbyen, 2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2019-04-15",
"bbox": "16.03412, 78.15174, 16.03412, 78.15174",
@@ -124750,7 +124750,7 @@
{
"id": "KOPRI-KPDC-00001265_3",
"title": "All-sky aurora (proton) image, KHO Longyearbyen, 2019",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2019-04-15",
"bbox": "16.03412, 78.15174, 16.03412, 78.15174",
@@ -124880,7 +124880,7 @@
{
"id": "KOPRI-KPDC-00001275_3",
"title": "All-sky airglow image, King Sejong Station, 2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-03-11",
"end_date": "2019-09-30",
"bbox": "-58.78804, -62.22268, -58.78804, -62.22268",
@@ -124893,7 +124893,7 @@
{
"id": "KOPRI-KPDC-00001275_3",
"title": "All-sky airglow image, King Sejong Station, 2019",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-03-11",
"end_date": "2019-09-30",
"bbox": "-58.78804, -62.22268, -58.78804, -62.22268",
@@ -126830,7 +126830,7 @@
{
"id": "KOPRI-KPDC-00001423_2",
"title": "2019 Arctic Araon Cruise (ARA10C) sediment cores (multiple, gravity, and box cores)",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-08-29",
"end_date": "2019-09-20",
"bbox": "167.676767, 73.69587, 179.98125, 77.132017",
@@ -126843,7 +126843,7 @@
{
"id": "KOPRI-KPDC-00001423_2",
"title": "2019 Arctic Araon Cruise (ARA10C) sediment cores (multiple, gravity, and box cores)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-08-29",
"end_date": "2019-09-20",
"bbox": "167.676767, 73.69587, 179.98125, 77.132017",
@@ -127792,7 +127792,7 @@
{
"id": "KOPRI-KPDC-00001498_2",
"title": "Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2019",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-01-19",
"end_date": "2020-01-26",
"bbox": "-58.789338, -62.240538, -58.721474, -62.220364",
@@ -127805,7 +127805,7 @@
{
"id": "KOPRI-KPDC-00001498_2",
"title": "Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-01-19",
"end_date": "2020-01-26",
"bbox": "-58.789338, -62.240538, -58.721474, -62.220364",
@@ -127922,7 +127922,7 @@
{
"id": "KOPRI-KPDC-00001508_4",
"title": "All-sky aurora (proton) image, KHO Longyearbyen, 2020",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2020-01-01",
"end_date": "2020-10-19",
"bbox": "16.12, 78.48, 16.12, 78.48",
@@ -127935,7 +127935,7 @@
{
"id": "KOPRI-KPDC-00001508_4",
"title": "All-sky aurora (proton) image, KHO Longyearbyen, 2020",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2020-01-01",
"end_date": "2020-10-19",
"bbox": "16.12, 78.48, 16.12, 78.48",
@@ -128000,7 +128000,7 @@
{
"id": "KOPRI-KPDC-00001512_2",
"title": "2019/20 season Korean Route Traverse based GPS GIS data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-11-07",
"end_date": "2020-01-18",
"bbox": "149.040453, -77.04815, 164.228789, -74.62405",
@@ -128013,7 +128013,7 @@
{
"id": "KOPRI-KPDC-00001512_2",
"title": "2019/20 season Korean Route Traverse based GPS GIS data",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-11-07",
"end_date": "2020-01-18",
"bbox": "149.040453, -77.04815, 164.228789, -74.62405",
@@ -128312,7 +128312,7 @@
{
"id": "KOPRI-KPDC-00001535_2",
"title": "2019/20 season Korean Route Traverse heavy machine fuel consumption in Antarctica",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-11-07",
"end_date": "2020-12-18",
"bbox": "149.0976, -77.04815, 164.228789, -74.62405",
@@ -128325,7 +128325,7 @@
{
"id": "KOPRI-KPDC-00001535_2",
"title": "2019/20 season Korean Route Traverse heavy machine fuel consumption in Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-11-07",
"end_date": "2020-12-18",
"bbox": "149.0976, -77.04815, 164.228789, -74.62405",
@@ -128624,7 +128624,7 @@
{
"id": "KOPRI-KPDC-00001564_4",
"title": "2016-8 KOPRI North Greenland Sirius Passet collection (modified)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2016-07-20",
"end_date": "2018-07-19",
"bbox": "-42.228333, 82.793333, -42.228333, 82.793333",
@@ -128637,7 +128637,7 @@
{
"id": "KOPRI-KPDC-00001564_4",
"title": "2016-8 KOPRI North Greenland Sirius Passet collection (modified)",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-07-20",
"end_date": "2018-07-19",
"bbox": "-42.228333, 82.793333, -42.228333, 82.793333",
@@ -129404,7 +129404,7 @@
{
"id": "KOPRI-KPDC-00001632_1",
"title": "A study on the distribution characteristics of stable oxygen isotope in the Amundsen Sea in 2011",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2010-12-20",
"end_date": "2011-01-20",
"bbox": "-145, -74.6, -112, -72.5",
@@ -129417,7 +129417,7 @@
{
"id": "KOPRI-KPDC-00001632_1",
"title": "A study on the distribution characteristics of stable oxygen isotope in the Amundsen Sea in 2011",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-12-20",
"end_date": "2011-01-20",
"bbox": "-145, -74.6, -112, -72.5",
@@ -129911,7 +129911,7 @@
{
"id": "KOPRI-KPDC-00001671_3",
"title": "2018&19 Multibeam data of Terra Nova Bay (around Jang Bogo station)",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-02-14",
"end_date": "2019-02-15",
"bbox": "163.984928, -74.73604, 164.57053, -74.610485",
@@ -129924,7 +129924,7 @@
{
"id": "KOPRI-KPDC-00001671_3",
"title": "2018&19 Multibeam data of Terra Nova Bay (around Jang Bogo station)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2019-02-14",
"end_date": "2019-02-15",
"bbox": "163.984928, -74.73604, 164.57053, -74.610485",
@@ -131718,7 +131718,7 @@
{
"id": "KOPRI-KPDC-00001817_2",
"title": "All-sky airglow image, King Sejong Station, 2021",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2021-02-01",
"end_date": "2021-08-31",
"bbox": "-58.47, -62.13, -58.47, -62.13",
@@ -131731,7 +131731,7 @@
{
"id": "KOPRI-KPDC-00001817_2",
"title": "All-sky airglow image, King Sejong Station, 2021",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2021-02-01",
"end_date": "2021-08-31",
"bbox": "-58.47, -62.13, -58.47, -62.13",
@@ -132147,7 +132147,7 @@
{
"id": "KOPRI-KPDC-00001851_2",
"title": "All-sky aurora (electron) image, Jang Bogo Station, 2021",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2021-03-01",
"end_date": "2021-09-30",
"bbox": "164.2, -74.623333, 164.2, -74.623333",
@@ -132160,7 +132160,7 @@
{
"id": "KOPRI-KPDC-00001851_2",
"title": "All-sky aurora (electron) image, Jang Bogo Station, 2021",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2021-03-01",
"end_date": "2021-09-30",
"bbox": "164.2, -74.623333, 164.2, -74.623333",
@@ -132745,7 +132745,7 @@
{
"id": "KOPRI-KPDC-00001905_1",
"title": "2015 ARA06C-01JPC: Lipid biomarkers (HBIs, sterols) from core sediments",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_KOPRI STAC Catalog",
"state_date": "2021-01-01",
"end_date": "2021-12-31",
"bbox": "-166.428882, 73.620361, -166.428882, 73.620361",
@@ -132758,7 +132758,7 @@
{
"id": "KOPRI-KPDC-00001905_1",
"title": "2015 ARA06C-01JPC: Lipid biomarkers (HBIs, sterols) from core sediments",
- "catalog": "AMD_KOPRI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2021-01-01",
"end_date": "2021-12-31",
"bbox": "-166.428882, 73.620361, -166.428882, 73.620361",
@@ -133525,7 +133525,7 @@
{
"id": "L2C_Wind_products_5.0",
"title": "Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ESA STAC Catalog",
"state_date": "2020-07-09",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -133538,7 +133538,7 @@
{
"id": "L2C_Wind_products_5.0",
"title": "Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing",
- "catalog": "ESA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2020-07-09",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -133772,7 +133772,7 @@
{
"id": "LAI_Woody_Plants_1231_1",
"title": "A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1932-01-01",
"end_date": "2011-12-31",
"bbox": "-164.78, -54.2, 175.62, 78.42",
@@ -133785,7 +133785,7 @@
{
"id": "LAI_Woody_Plants_1231_1",
"title": "A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1932-01-01",
"end_date": "2011-12-31",
"bbox": "-164.78, -54.2, 175.62, 78.42",
@@ -135397,7 +135397,7 @@
{
"id": "LGB_10m_traverse_1",
"title": "10 m firn temperature data: LGB traverses 1990-95",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1989-11-01",
"end_date": "1995-02-28",
"bbox": "54, -77, 78, -69",
@@ -135410,7 +135410,7 @@
{
"id": "LGB_10m_traverse_1",
"title": "10 m firn temperature data: LGB traverses 1990-95",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1989-11-01",
"end_date": "1995-02-28",
"bbox": "54, -77, 78, -69",
@@ -136814,7 +136814,7 @@
{
"id": "Lake_Wetland_Classes_UAVSAR_1883_1",
"title": "ABoVE: Lake and Wetland Classification from L-band SAR, Alaska and Canada, 2017-2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2019-09-19",
"bbox": "-149.16, 53.71, -107.86, 67.91",
@@ -136827,7 +136827,7 @@
{
"id": "Lake_Wetland_Classes_UAVSAR_1883_1",
"title": "ABoVE: Lake and Wetland Classification from L-band SAR, Alaska and Canada, 2017-2019",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-01-01",
"end_date": "2019-09-19",
"bbox": "-149.16, 53.71, -107.86, 67.91",
@@ -137191,7 +137191,7 @@
{
"id": "Level_2A_aerosol_cloud_optical_products_3.0",
"title": "Aeolus L2A Aerosol/Cloud optical product",
- "catalog": "ESA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2021-05-26",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -137204,7 +137204,7 @@
{
"id": "Level_2A_aerosol_cloud_optical_products_3.0",
"title": "Aeolus L2A Aerosol/Cloud optical product",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ESA STAC Catalog",
"state_date": "2021-05-26",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -142807,7 +142807,7 @@
{
"id": "MFLL_XCO2_Range_10Hz_1892_1",
"title": "ACT-America: L2 Remotely Sensed Column-avg CO2 by Airborne Lidar, Lite, Eastern USA",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-05-27",
"end_date": "2018-05-20",
"bbox": "-106.05, 27.23, -71.91, 49.11",
@@ -142820,7 +142820,7 @@
{
"id": "MFLL_XCO2_Range_10Hz_1892_1",
"title": "ACT-America: L2 Remotely Sensed Column-avg CO2 by Airborne Lidar, Lite, Eastern USA",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2016-05-27",
"end_date": "2018-05-20",
"bbox": "-106.05, 27.23, -71.91, 49.11",
@@ -142976,7 +142976,7 @@
{
"id": "MI2010_11_Alien-plant-survey_JDS_1",
"title": "Alien plant survey Macquarie Island 2010_11",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-10-13",
"end_date": "2011-01-31",
"bbox": "158.8, -54.7, 158.9, -54.6",
@@ -142989,7 +142989,7 @@
{
"id": "MI2010_11_Alien-plant-survey_JDS_1",
"title": "Alien plant survey Macquarie Island 2010_11",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2010-10-13",
"end_date": "2011-01-31",
"bbox": "158.8, -54.7, 158.9, -54.6",
@@ -144705,7 +144705,7 @@
{
"id": "MI_alk_clones_1",
"title": "Alkane mono-oxygenase clone library from Macquarie Island soil",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2008-01-01",
"end_date": "2008-03-30",
"bbox": "158.93, -54.491, 158.931, -54.49",
@@ -144718,7 +144718,7 @@
{
"id": "MI_alk_clones_1",
"title": "Alkane mono-oxygenase clone library from Macquarie Island soil",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2008-01-01",
"end_date": "2008-03-30",
"bbox": "158.93, -54.491, 158.931, -54.49",
@@ -148342,19 +148342,6 @@
"description": "This multilayer data set includes standard MODIS Collection 6.1 ice surface temperature (IST) and derived melt map, as well as MODIS Collection 6.0 albedo and water vapor for Greenland, at a spatial resolution of 0.78 km. These fields enable the relationship between IST and surface melt to be evaluated by researchers studying surface changes on the Greenland ice sheet. Water vapor is included to assist with evaluating the accuracy of the IST data and the model output. Also included is an ice mask and a basins mask for delineating drainage basins in Greenland. Surface temperature is a fundamental input for dynamical ice sheet models because it is a component of the ice sheet radiation budget and mass balance. Surface temperature also influences ice sheet processes, such as surface melt. This data set may be used as a resource for model-validation studies such as comparing MERRA-2 surface temperature with MODIS IST, and for comparing MODIS IST, albedo and water vapor with products from sensors on other satellites such as VIIRS and AIRS The temporal coverage for this data set spans 1 March 2000 through 31 December 2019, with the exception of the IST data, which has been extended through 31 Aug 2021.",
"license": "proprietary"
},
- {
- "id": "MODISA_L1_1",
- "title": "Aqua MODIS Level-1 Data",
- "catalog": "OB_DAAC STAC Catalog",
- "state_date": "2002-07-04",
- "end_date": "",
- "bbox": "-180, 90, -180, 90",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1570116979-OB_DAAC.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1570116979-OB_DAAC.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/MODISA_L1_1",
- "description": "MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.",
- "license": "proprietary"
- },
{
"id": "MODISA_L1_1",
"title": "Aqua MODIS Level-1A Data, version 1",
@@ -148368,6 +148355,19 @@
"description": "MODIS (or Moderate-Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.",
"license": "proprietary"
},
+ {
+ "id": "MODISA_L1_1",
+ "title": "Aqua MODIS Level-1 Data",
+ "catalog": "OB_DAAC STAC Catalog",
+ "state_date": "2002-07-04",
+ "end_date": "",
+ "bbox": "-180, 90, -180, 90",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1570116979-OB_DAAC.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1570116979-OB_DAAC.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/MODISA_L1_1",
+ "description": "MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.",
+ "license": "proprietary"
+ },
{
"id": "MODISA_L1_GEO_1",
"title": "Aqua MODIS Geolocation Product Data, version 1",
@@ -153675,7 +153675,7 @@
{
"id": "MaineInvasives",
"title": "A Historical Record of Sponges, Bryozoa and Ascidians on the Coast of Maine: 1843-1980 (Bigelow Laboratory for Ocean Sciences)",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1843-01-01",
"end_date": "1980-12-31",
"bbox": "-70.7, 42.6, -66.9, 45.2",
@@ -153688,7 +153688,7 @@
{
"id": "MaineInvasives",
"title": "A Historical Record of Sponges, Bryozoa and Ascidians on the Coast of Maine: 1843-1980 (Bigelow Laboratory for Ocean Sciences)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1843-01-01",
"end_date": "1980-12-31",
"bbox": "-70.7, 42.6, -66.9, 45.2",
@@ -153779,7 +153779,7 @@
{
"id": "Marine_Virus_Southern_Ocean_Evans_IPY71_NL_1",
"title": "Abundances of algae, bacteria, viruses, and heterotrophic nanoflagellates in the Southern Ocean and determination of grazing and viral lysis of the algae",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-01-16",
"end_date": "2007-02-18",
"bbox": "140, -54, 155, -43",
@@ -153792,7 +153792,7 @@
{
"id": "Marine_Virus_Southern_Ocean_Evans_IPY71_NL_1",
"title": "Abundances of algae, bacteria, viruses, and heterotrophic nanoflagellates in the Southern Ocean and determination of grazing and viral lysis of the algae",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2007-01-16",
"end_date": "2007-02-18",
"bbox": "140, -54, 155, -43",
@@ -153857,7 +153857,7 @@
{
"id": "MassGIS_GISDATA.COQHMOSAICSCDS_POLY",
"title": "2001 MrSID Mosaics CD-ROM Index",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2006-08-03",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -153870,7 +153870,7 @@
{
"id": "MassGIS_GISDATA.COQHMOSAICSCDS_POLY",
"title": "2001 MrSID Mosaics CD-ROM Index",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2006-08-03",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -153883,7 +153883,7 @@
{
"id": "MassGIS_GISDATA.COQHMOSAICSDVDS_POLY.xm",
"title": "2001 MrSID Mosaics DVD Index",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2007-02-01",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -153896,7 +153896,7 @@
{
"id": "MassGIS_GISDATA.COQHMOSAICSDVDS_POLY.xm",
"title": "2001 MrSID Mosaics DVD Index",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-02-01",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -153935,7 +153935,7 @@
{
"id": "MassGIS_GISDATA.COQMOSAICS2005_POLY",
"title": "2005 MrSID Mosaics Index",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2006-08-03",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -153948,7 +153948,7 @@
{
"id": "MassGIS_GISDATA.COQMOSAICS2005_POLY",
"title": "2005 MrSID Mosaics Index",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2006-08-03",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -154039,7 +154039,7 @@
{
"id": "MassGIS_GISDATA.IMG_COQ2001",
"title": "1:5,000 Color Ortho Imagery",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2001-04-01",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -154052,7 +154052,7 @@
{
"id": "MassGIS_GISDATA.IMG_COQ2001",
"title": "1:5,000 Color Ortho Imagery",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2001-04-01",
"end_date": "",
"bbox": "-73.54455, 41.19853, -69.8716, 42.908627",
@@ -154091,7 +154091,7 @@
{
"id": "MassGIS_GISDATA.VCPEATLAND_POLY",
"title": "Acidic Peatland Community Systems",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-04-01",
"end_date": "",
"bbox": "-71.36416, 41.53563, -70.51623, 42.859413",
@@ -154104,7 +154104,7 @@
{
"id": "MassGIS_GISDATA.VCPEATLAND_POLY",
"title": "Acidic Peatland Community Systems",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2003-04-01",
"end_date": "",
"bbox": "-71.36416, 41.53563, -70.51623, 42.859413",
@@ -154195,7 +154195,7 @@
{
"id": "Maxwell_Bay_Beaches_data",
"title": "Ages and Elevations of Raised Beaches around Maxwell Bay, South Shetland Islands",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "0500-01-01",
"end_date": "2007-04-30",
"bbox": "-59, -62.3, -58.833, -62.1",
@@ -154208,7 +154208,7 @@
{
"id": "Maxwell_Bay_Beaches_data",
"title": "Ages and Elevations of Raised Beaches around Maxwell Bay, South Shetland Islands",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "0500-01-01",
"end_date": "2007-04-30",
"bbox": "-59, -62.3, -58.833, -62.1",
@@ -154351,7 +154351,7 @@
{
"id": "Meteorology_Log_Commonwealth_Bay_1977_1978_1",
"title": "A log of meteorological observations made at Commonwealth Bay between 1977 and 1978",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1977-01-01",
"end_date": "1978-12-31",
"bbox": "142.5, -67, 142.5, -67",
@@ -154364,7 +154364,7 @@
{
"id": "Meteorology_Log_Commonwealth_Bay_1977_1978_1",
"title": "A log of meteorological observations made at Commonwealth Bay between 1977 and 1978",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1977-01-01",
"end_date": "1978-12-31",
"bbox": "142.5, -67, 142.5, -67",
@@ -154377,7 +154377,7 @@
{
"id": "Methane_Ebullition_Lakes_AK_1861_1",
"title": "ABoVE: Methane Ebullition Hotspots in Frozen Lakes near Fairbanks, Alaska, Oct 2014",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-147.94, 64.86, -147.77, 64.94",
@@ -154390,7 +154390,7 @@
{
"id": "Methane_Ebullition_Lakes_AK_1861_1",
"title": "ABoVE: Methane Ebullition Hotspots in Frozen Lakes near Fairbanks, Alaska, Oct 2014",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-147.94, 64.86, -147.77, 64.94",
@@ -156561,7 +156561,7 @@
{
"id": "NBId0001_101",
"title": "Africa Outline, Integrated Terrain Units, Agric. Landuse, Soils, Vegetation",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -156574,7 +156574,7 @@
{
"id": "NBId0001_101",
"title": "Africa Outline, Integrated Terrain Units, Agric. Landuse, Soils, Vegetation",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -156613,7 +156613,7 @@
{
"id": "NBId0007_101",
"title": "Africa Administrative Units (GIS Coverage of Administrative Boundaries)",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156626,7 +156626,7 @@
{
"id": "NBId0007_101",
"title": "Africa Administrative Units (GIS Coverage of Administrative Boundaries)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156678,7 +156678,7 @@
{
"id": "NBId0018_101",
"title": "Africa FAO Major Infrastructure and Human Settlements (GIS Coverage)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156691,7 +156691,7 @@
{
"id": "NBId0018_101",
"title": "Africa FAO Major Infrastructure and Human Settlements (GIS Coverage)",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156808,7 +156808,7 @@
{
"id": "NBId0025_101",
"title": "Africa Soil Classification by Zobler",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156821,7 +156821,7 @@
{
"id": "NBId0025_101",
"title": "Africa Soil Classification by Zobler",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156834,7 +156834,7 @@
{
"id": "NBId0036_101",
"title": "Africa Lakes and Rivers (World Data Bank II)",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156847,7 +156847,7 @@
{
"id": "NBId0036_101",
"title": "Africa Lakes and Rivers (World Data Bank II)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156886,7 +156886,7 @@
{
"id": "NBId0043_101",
"title": "Africa Integrated Elevation and Bathymetry",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156899,7 +156899,7 @@
{
"id": "NBId0043_101",
"title": "Africa Integrated Elevation and Bathymetry",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156912,7 +156912,7 @@
{
"id": "NBId0044_101",
"title": "Africa Ocean Mask",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -156925,7 +156925,7 @@
{
"id": "NBId0044_101",
"title": "Africa Ocean Mask",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-30, -45, 60, 40",
@@ -157185,7 +157185,7 @@
{
"id": "NBId0203_101",
"title": "Africa Water Balance high/lowland crops, 1987",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157198,7 +157198,7 @@
{
"id": "NBId0203_101",
"title": "Africa Water Balance high/lowland crops, 1987",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157276,7 +157276,7 @@
{
"id": "NBId0216_101",
"title": "Africa Number of Wet Days per Year and Wind Velocity, 1984",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157289,7 +157289,7 @@
{
"id": "NBId0216_101",
"title": "Africa Number of Wet Days per Year and Wind Velocity, 1984",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157302,7 +157302,7 @@
{
"id": "NBId0218_101",
"title": "Africa Surface Hydrography, 1984",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157315,7 +157315,7 @@
{
"id": "NBId0218_101",
"title": "Africa Surface Hydrography, 1984",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157406,7 +157406,7 @@
{
"id": "NBId0236_101",
"title": "Africa Cattle Type (East Coast Fever Project), 1989",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157419,7 +157419,7 @@
{
"id": "NBId0236_101",
"title": "Africa Cattle Type (East Coast Fever Project), 1989",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-20, -35, 55, 40",
@@ -157536,7 +157536,7 @@
{
"id": "NCAR_DS474.0",
"title": "AARI Russian North Polar Drifting Station Data, from NSIDC",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1937-05-01",
"end_date": "1991-03-31",
"bbox": "-180, -90, 180, 90",
@@ -157549,7 +157549,7 @@
{
"id": "NCAR_DS474.0",
"title": "AARI Russian North Polar Drifting Station Data, from NSIDC",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1937-05-01",
"end_date": "1991-03-31",
"bbox": "-180, -90, 180, 90",
@@ -157562,7 +157562,7 @@
{
"id": "NCAR_DS510.5",
"title": "A Quality-Controlled Dataset for Long-Term U.S. Snowfall Trends",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1890-01-01",
"end_date": "2007-05-31",
"bbox": "-180, -90, 180, 90",
@@ -157575,7 +157575,7 @@
{
"id": "NCAR_DS510.5",
"title": "A Quality-Controlled Dataset for Long-Term U.S. Snowfall Trends",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1890-01-01",
"end_date": "2007-05-31",
"bbox": "-180, -90, 180, 90",
@@ -157588,7 +157588,7 @@
{
"id": "NCAR_DS744.7",
"title": "ADEOS Scatterometer Winds, Level 2B",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-06-04",
"end_date": "2002-06-27",
"bbox": "-180, -90, 180, 90",
@@ -157601,7 +157601,7 @@
{
"id": "NCAR_DS744.7",
"title": "ADEOS Scatterometer Winds, Level 2B",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2002-06-04",
"end_date": "2002-06-27",
"bbox": "-180, -90, 180, 90",
@@ -157614,7 +157614,7 @@
{
"id": "NCAR_DS871.0",
"title": "ADAPTE: Minimum and Maximum Temperature and Relative Humidity for Latin American Cities Data",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2000-01-01",
"end_date": "2006-12-31",
"bbox": "-180, -90, 180, 90",
@@ -157627,7 +157627,7 @@
{
"id": "NCAR_DS871.0",
"title": "ADAPTE: Minimum and Maximum Temperature and Relative Humidity for Latin American Cities Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2000-01-01",
"end_date": "2006-12-31",
"bbox": "-180, -90, 180, 90",
@@ -158823,7 +158823,7 @@
{
"id": "NESP_2015_SRW_3",
"title": "2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2015-02-09",
"end_date": "2015-07-09",
"bbox": "113.02734, -36.59789, 138.69141, -29.993",
@@ -158836,7 +158836,7 @@
{
"id": "NESP_2015_SRW_3",
"title": "2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2015-02-09",
"end_date": "2015-07-09",
"bbox": "113.02734, -36.59789, 138.69141, -29.993",
@@ -158875,7 +158875,7 @@
{
"id": "NESP_2017_SRW_1",
"title": "2017 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-08-23",
"end_date": "2017-08-27",
"bbox": "113.02734, -36.59789, 138.69141, -29.993",
@@ -158888,7 +158888,7 @@
{
"id": "NESP_2017_SRW_1",
"title": "2017 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2017-08-23",
"end_date": "2017-08-27",
"bbox": "113.02734, -36.59789, 138.69141, -29.993",
@@ -159031,7 +159031,7 @@
{
"id": "NGA178\n _1.0",
"title": "Advanced Terrestrial Simulator",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -159044,7 +159044,7 @@
{
"id": "NGA178\n _1.0",
"title": "Advanced Terrestrial Simulator",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -159057,7 +159057,7 @@
{
"id": "NGA183\n _1.0",
"title": "Active Layer Hydrology in an Arctic Tundra Ecosystem: Quantifying Water Sources and Cycling Using Water Stable Isotopes: Supporting Data",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -159070,7 +159070,7 @@
{
"id": "NGA183\n _1.0",
"title": "Active Layer Hydrology in an Arctic Tundra Ecosystem: Quantifying Water Sources and Cycling Using Water Stable Isotopes: Supporting Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -159083,7 +159083,7 @@
{
"id": "NGA232\n _1.0",
"title": "A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -159096,7 +159096,7 @@
{
"id": "NGA232\n _1.0",
"title": "A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -159226,7 +159226,7 @@
{
"id": "NIPR-GEO-1",
"title": "Airborne Magnetic Survey Data in Antarctica by JARE",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1980-01-01",
"end_date": "",
"bbox": "20, -72, 60, -68",
@@ -159239,7 +159239,7 @@
{
"id": "NIPR-GEO-1",
"title": "Airborne Magnetic Survey Data in Antarctica by JARE",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1980-01-01",
"end_date": "",
"bbox": "20, -72, 60, -68",
@@ -159252,7 +159252,7 @@
{
"id": "NIPR_GEO_SEIS_SEAL_MIZUHO",
"title": "Acitve source digital seismic waveforms by SEAL exploration",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2000-01-01",
"end_date": "",
"bbox": "38, -70, 45, -68",
@@ -159265,7 +159265,7 @@
{
"id": "NIPR_GEO_SEIS_SEAL_MIZUHO",
"title": "Acitve source digital seismic waveforms by SEAL exploration",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2000-01-01",
"end_date": "",
"bbox": "38, -70, 45, -68",
@@ -161605,7 +161605,7 @@
{
"id": "NSF-ANT04-39906_1",
"title": "Abandoned Elephant Seal Colonies in Antarctica: Integration of Genetic, Isotopic, and Geologic Approaches toward Understanding Holocene Environmental Change",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-09-15",
"end_date": "2009-08-31",
"bbox": "162, -78, 168, -72",
@@ -161618,7 +161618,7 @@
{
"id": "NSF-ANT04-39906_1",
"title": "Abandoned Elephant Seal Colonies in Antarctica: Integration of Genetic, Isotopic, and Geologic Approaches toward Understanding Holocene Environmental Change",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2005-09-15",
"end_date": "2009-08-31",
"bbox": "162, -78, 168, -72",
@@ -161722,7 +161722,7 @@
{
"id": "NSF-ANT06-36928",
"title": "A VLF Beacon Transmitter at South Pole",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2007-09-15",
"end_date": "2011-08-31",
"bbox": "-180, -90, 180, -90",
@@ -161735,7 +161735,7 @@
{
"id": "NSF-ANT06-36928",
"title": "A VLF Beacon Transmitter at South Pole",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-09-15",
"end_date": "2011-08-31",
"bbox": "-180, -90, 180, -90",
@@ -161891,7 +161891,7 @@
{
"id": "NSF-ANT09-44358",
"title": "Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels - NSF-ANT09-44358",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-09-15",
"end_date": "2015-08-31",
"bbox": "165.9, -77.6, 169.4, -76.9",
@@ -161904,7 +161904,7 @@
{
"id": "NSF-ANT09-44358",
"title": "Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels - NSF-ANT09-44358",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2010-09-15",
"end_date": "2015-08-31",
"bbox": "165.9, -77.6, 169.4, -76.9",
@@ -161917,7 +161917,7 @@
{
"id": "NSF-ANT09-44411",
"title": "Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-09-15",
"end_date": "2015-08-31",
"bbox": "-180, -90, 180, -60",
@@ -161930,7 +161930,7 @@
{
"id": "NSF-ANT09-44411",
"title": "Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2010-09-15",
"end_date": "2015-08-31",
"bbox": "-180, -90, 180, -60",
@@ -161995,7 +161995,7 @@
{
"id": "NSF-ANT10-43485_1",
"title": "A New Reconstruction of the Last West Antarctic Ice Sheet Deglaciation in the Ross Sea",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-07-01",
"end_date": "2015-06-30",
"bbox": "-160, -78, -150, -68",
@@ -162008,7 +162008,7 @@
{
"id": "NSF-ANT10-43485_1",
"title": "A New Reconstruction of the Last West Antarctic Ice Sheet Deglaciation in the Ross Sea",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2011-07-01",
"end_date": "2015-06-30",
"bbox": "-160, -78, -150, -68",
@@ -162073,7 +162073,7 @@
{
"id": "NSF-ANT10-43621",
"title": "A Comparison of Conjugate Auroral Electojet Indices",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2011-06-01",
"end_date": "2013-05-31",
"bbox": "-180, -79.5, 180, -54.5",
@@ -162086,7 +162086,7 @@
{
"id": "NSF-ANT10-43621",
"title": "A Comparison of Conjugate Auroral Electojet Indices",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-06-01",
"end_date": "2013-05-31",
"bbox": "-180, -79.5, 180, -54.5",
@@ -163347,7 +163347,7 @@
{
"id": "NSIDC-0326_1",
"title": "Ablation Rates of Taylor Glacier, Antarctica",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-11-19",
"end_date": "2011-01-12",
"bbox": "160.1, -77.9, 162.2, -77.6",
@@ -163360,7 +163360,7 @@
{
"id": "NSIDC-0326_1",
"title": "Ablation Rates of Taylor Glacier, Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2002-11-19",
"end_date": "2011-01-12",
"bbox": "160.1, -77.9, 162.2, -77.6",
@@ -164153,7 +164153,7 @@
{
"id": "NSIDC-0634_1",
"title": "Alaska Tidewater Glacier Terminus Positions, Version 1",
- "catalog": "NSIDCV0 STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1948-01-01",
"end_date": "2012-12-31",
"bbox": "-151, 56.5, -132, 61.5",
@@ -164166,7 +164166,7 @@
{
"id": "NSIDC-0634_1",
"title": "Alaska Tidewater Glacier Terminus Positions, Version 1",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NSIDCV0 STAC Catalog",
"state_date": "1948-01-01",
"end_date": "2012-12-31",
"bbox": "-151, 56.5, -132, 61.5",
@@ -164972,7 +164972,7 @@
{
"id": "NWT_Burn_Severity_Maps_1694_1",
"title": "ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2014-05-01",
"end_date": "2015-10-01",
"bbox": "-124.03, 58.29, -108.83, 65.55",
@@ -164985,7 +164985,7 @@
{
"id": "NWT_Burn_Severity_Maps_1694_1",
"title": "ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-05-01",
"end_date": "2015-10-01",
"bbox": "-124.03, 58.29, -108.83, 65.55",
@@ -167000,7 +167000,7 @@
{
"id": "OCTS_L1_1",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data",
- "catalog": "OB_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167013,7 +167013,7 @@
{
"id": "OCTS_L1_1",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_DAAC STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167104,7 +167104,7 @@
{
"id": "OCTS_L2_OC_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Ocean Color (OC) Regional Data",
- "catalog": "OB_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167117,7 +167117,7 @@
{
"id": "OCTS_L2_OC_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Ocean Color (OC) Regional Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_DAAC STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167182,7 +167182,7 @@
{
"id": "OCTS_L3b_CHL_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Chlorophyll (CHL) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167195,7 +167195,7 @@
{
"id": "OCTS_L3b_CHL_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Chlorophyll (CHL) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167234,7 +167234,7 @@
{
"id": "OCTS_L3b_IOP_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Inherent Optical Properties (IOP) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167247,7 +167247,7 @@
{
"id": "OCTS_L3b_IOP_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Inherent Optical Properties (IOP) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167338,7 +167338,7 @@
{
"id": "OCTS_L3b_PAR_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Photosynthetically Active Radiation (PAR) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167351,7 +167351,7 @@
{
"id": "OCTS_L3b_PAR_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Photosynthetically Active Radiation (PAR) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167390,7 +167390,7 @@
{
"id": "OCTS_L3b_PIC_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Particulate Inorganic Carbon (PIC) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167403,7 +167403,7 @@
{
"id": "OCTS_L3b_PIC_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Particulate Inorganic Carbon (PIC) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167416,7 +167416,7 @@
{
"id": "OCTS_L3b_POC_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Binned Data",
- "catalog": "OB_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167429,7 +167429,7 @@
{
"id": "OCTS_L3b_POC_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Binned Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_DAAC STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167442,7 +167442,7 @@
{
"id": "OCTS_L3b_POC_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Particulate Organic Carbon (POC) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167455,7 +167455,7 @@
{
"id": "OCTS_L3b_POC_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Binned Particulate Organic Carbon (POC) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167546,7 +167546,7 @@
{
"id": "OCTS_L3m_CHL_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Mapped Chlorophyll (CHL) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167559,7 +167559,7 @@
{
"id": "OCTS_L3m_CHL_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Mapped Chlorophyll (CHL) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167624,7 +167624,7 @@
{
"id": "OCTS_L3m_KD_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_DAAC STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167637,7 +167637,7 @@
{
"id": "OCTS_L3m_KD_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data",
- "catalog": "OB_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167650,7 +167650,7 @@
{
"id": "OCTS_L3m_KD_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167663,7 +167663,7 @@
{
"id": "OCTS_L3m_KD_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167702,7 +167702,7 @@
{
"id": "OCTS_L3m_PAR_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_CLOUD STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167715,7 +167715,7 @@
{
"id": "OCTS_L3m_PAR_2022.0",
"title": "ADEOS-I OCTS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0",
- "catalog": "OB_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-10-31",
"end_date": "1997-06-29",
"bbox": "-180, -90, 180, 90",
@@ -167780,7 +167780,7 @@
{
"id": "OCTS_L3m_POC_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Mapped Data",
- "catalog": "OB_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167793,7 +167793,7 @@
{
"id": "OCTS_L3m_POC_2014",
"title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Mapped Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_DAAC STAC Catalog",
"state_date": "1996-11-01",
"end_date": "1997-06-30",
"bbox": "-180, -90, 180, 90",
@@ -167910,7 +167910,7 @@
{
"id": "OFR_94-212",
"title": "A Compilation of Sulfur Dioxide and Carbon Dioxide Emission-Rate Data from Mount St. Helens during 1980-88 USGS Open File Report 94-212",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1980-05-01",
"end_date": "1988-09-06",
"bbox": "-122, 46, -122, 46",
@@ -167923,7 +167923,7 @@
{
"id": "OFR_94-212",
"title": "A Compilation of Sulfur Dioxide and Carbon Dioxide Emission-Rate Data from Mount St. Helens during 1980-88 USGS Open File Report 94-212",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1980-05-01",
"end_date": "1988-09-06",
"bbox": "-122, 46, -122, 46",
@@ -167936,7 +167936,7 @@
{
"id": "OFR_95-55",
"title": "A Compilation of Sulphur Dioxide and Carbon Dioxide Emission-Rate Data from Cook Inlet Volcanoes, Alaska During the Period from 1990 to 1994",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-03-20",
"end_date": "1994-07-07",
"bbox": "-154, 56, -152, 62",
@@ -167949,7 +167949,7 @@
{
"id": "OFR_95-55",
"title": "A Compilation of Sulphur Dioxide and Carbon Dioxide Emission-Rate Data from Cook Inlet Volcanoes, Alaska During the Period from 1990 to 1994",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-03-20",
"end_date": "1994-07-07",
"bbox": "-154, 56, -152, 62",
@@ -170364,19 +170364,6 @@
"description": "This Level-2G daily global gridded product OMSO2G is based on the pixel level OMI Level-2 SO2 product OMSO2. OMSO2G data product is a special Level-2 gridded product where pixel level products are binned into 0.125x0.125 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999 . All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMSO2G data product contains almost all parameters that are contained in OMSO2 files. For example, in addition to three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the retrieval algorithm, and ancillary parameters, e.g., UV aerosol index, cloud fraction, cloud pressure, geolocation, solar and satellite viewing angles, and quality flags. The OMSO2G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 146 Mbytes.",
"license": "proprietary"
},
- {
- "id": "OMSO2_003",
- "title": "OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 (OMSO2) at GES DISC",
- "catalog": "GES_DISC STAC Catalog",
- "state_date": "2004-10-01",
- "end_date": "",
- "bbox": "-180, -90, 180, 90",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966837-GES_DISC.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966837-GES_DISC.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/OMSO2_003",
- "description": "The Aura Ozone Monitoring Instrument (OMI) level 2 sulphur dioxide (SO2) total column product (OMSO2) has been updated with a principal component analysis (PCA)-based algorithm (v2) with new SO2 Jacobian lookup tables and a priori profiles that significantly improve retrievals for anthropogenic SO2. The data files (or granules) contain different estimates of the vertical column density (VCD) of SO2 depending on the users investigating anthropogenic or volcanic sources. Files also contain quality flags, geolocation and other ancillary information. The lead scientist for the OMSO2 product is Can Li. The OMSO2 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the daylit half of an orbit (~53 minutes). There are approximately 14 orbits per day. The resolution of the data is 13x24 km2 at nadir, with a swath width of 2600 km and 60 pixels per scan line every 2 seconds.",
- "license": "proprietary"
- },
{
"id": "OMSO2_003",
"title": "OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 NRT",
@@ -170390,6 +170377,19 @@
"description": "The Ozone Monitoring Instrument (OMI) was launched aboard the EOS-Aura satellite on July 15, 2004 (1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Space Office (NSO) in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO,NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. The Sulfer Dioxide Product 'OMSO2' from the Aura-OMI is now publicly available from NASA GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMSO2 product contains three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the retrieval algorithm. It also contains quality flags, geolocation and other ancillary information. The shortname for this Level-2 OMI total column SO2 product is OMSO2 and the algorithm leads for this product are NASA/UMBC OMI scientists Drs. Nikolay Krotkov (nickolay.a.krotkov@nasa.gov),Kai Yang(kai.yang@nasa.gov) and Arlin J. Krueger(krueger@umbc.edu). OMSO2 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMSO2 data product is about 21 Mbytes. On-line spatial and parameter subset options are available during data download A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMSO2 Readme Document that includes brief algorithm description and documents that provides known data quality related issues are available from the UMBC OMI site ( http://so2.gsfc.nasa.gov/docs.php ) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://so2.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/. For the full set of Aura products and other atmospheric composition data available from the GES DISC, please see the links below. http://disc.sci.gsfc.nasa.gov/Aura/ http://disc.gsfc.nasa.gov/acdisc/",
"license": "proprietary"
},
+ {
+ "id": "OMSO2_003",
+ "title": "OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 (OMSO2) at GES DISC",
+ "catalog": "GES_DISC STAC Catalog",
+ "state_date": "2004-10-01",
+ "end_date": "",
+ "bbox": "-180, -90, 180, 90",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966837-GES_DISC.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966837-GES_DISC.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/OMSO2_003",
+ "description": "The Aura Ozone Monitoring Instrument (OMI) level 2 sulphur dioxide (SO2) total column product (OMSO2) has been updated with a principal component analysis (PCA)-based algorithm (v2) with new SO2 Jacobian lookup tables and a priori profiles that significantly improve retrievals for anthropogenic SO2. The data files (or granules) contain different estimates of the vertical column density (VCD) of SO2 depending on the users investigating anthropogenic or volcanic sources. Files also contain quality flags, geolocation and other ancillary information. The lead scientist for the OMSO2 product is Can Li. The OMSO2 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the daylit half of an orbit (~53 minutes). There are approximately 14 orbits per day. The resolution of the data is 13x24 km2 at nadir, with a swath width of 2600 km and 60 pixels per scan line every 2 seconds.",
+ "license": "proprietary"
+ },
{
"id": "OMSO2_CPR_003",
"title": "OMI/Aura Level 2 Sulphur Dioxide (SO2) Trace Gas Column Data 1-Orbit Subset and Collocated Swath along CloudSat V003 (OMSO2_CPR) at GES DISC",
@@ -170429,19 +170429,6 @@
"description": "This Level-2G daily global gridded product OMTO3G is based on the pixel level OMI Level-2 Total Ozone Product OMTO3. The OMTO3 product is from the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. The OMTO3G data product is a special Level-2 Global Gridded Product where pixel level data are binned into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved Without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMTO3G data product contains almost all parameters that are contained in the OMTO3. For example, in addition to the total column ozone it also contains UV aerosol index, cloud fraction, cloud pressure, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The OMTO3G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 150 Mbytes.",
"license": "proprietary"
},
- {
- "id": "OMTO3_003",
- "title": "OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT",
- "catalog": "OMINRT STAC Catalog",
- "state_date": "2004-07-15",
- "end_date": "",
- "bbox": "-180, -90, 180, 90",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3_003",
- "description": "The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ .",
- "license": "proprietary"
- },
{
"id": "OMTO3_003",
"title": "OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km V003 (OMTO3) at GES DISC",
@@ -170455,6 +170442,19 @@
"description": "The Aura Ozone Monitoring Instrument (OMI) Level-2 Total Column Ozone Data Product OMTO3 (Version 003) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI provides two Level-2 (OMTO3 and OMDOAO3) total column ozone products at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms. This level-2 global total column ozone product (OMTO3) is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrievals (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3. The algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia. The OMTO3 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is approximately 35 MB.",
"license": "proprietary"
},
+ {
+ "id": "OMTO3_003",
+ "title": "OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT",
+ "catalog": "OMINRT STAC Catalog",
+ "state_date": "2004-07-15",
+ "end_date": "",
+ "bbox": "-180, -90, 180, 90",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/OMINRT/collections/OMTO3_003",
+ "description": "The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ .",
+ "license": "proprietary"
+ },
{
"id": "OMTO3_CPR_003",
"title": "OMI/Aura Level 2 Ozone (O3) Total Column 1-Orbit Subset and Collocated Swath along CloudSat track 200-km wide at 13x24 km2 resolution",
@@ -171677,6 +171677,19 @@
"description": "The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.",
"license": "proprietary"
},
+ {
+ "id": "PACE_OCI_L3B_AVW_NRT_2.0",
+ "title": "PACE OCI Level-3 Global Binned Apparent Visible Wavelength (AVW) - Near Real Time (NRT) Data, version 2.0",
+ "catalog": "OB_CLOUD STAC Catalog",
+ "state_date": "2024-02-25",
+ "end_date": "",
+ "bbox": "-180, -90, 180, 90",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3020922066-OB_CLOUD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3020922066-OB_CLOUD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_OCI_L3B_AVW_NRT_2.0",
+ "description": "The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.",
+ "license": "proprietary"
+ },
{
"id": "PACE_OCI_L3B_CHL_NRT_2.0",
"title": "PACE OCI Level-3 Global Binned Chlorophyll (CHL) - NRT Data, version 2.0",
@@ -172031,7 +172044,7 @@
{
"id": "PASSCAL_ABBA",
"title": "Adirondack Broad Band Array (ABBA)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1995-01-01",
"end_date": "1996-12-31",
"bbox": "-74.5, 43.5, -73.8, 44.4",
@@ -172044,7 +172057,7 @@
{
"id": "PASSCAL_ABBA",
"title": "Adirondack Broad Band Array (ABBA)",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1995-01-01",
"end_date": "1996-12-31",
"bbox": "-74.5, 43.5, -73.8, 44.4",
@@ -172083,7 +172096,7 @@
{
"id": "PASSCAL_KRAFLA",
"title": "1994 Krafla Undershooting Experiment",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-24.55, 62.81, -12.79, 67.01",
@@ -172096,7 +172109,7 @@
{
"id": "PASSCAL_KRAFLA",
"title": "1994 Krafla Undershooting Experiment",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-24.55, 62.81, -12.79, 67.01",
@@ -172109,7 +172122,7 @@
{
"id": "PASSCAL_WABASH",
"title": "A comprehensive geophysical investigation to assess seismic hazards in the coassesment of seismicity in the Wabash Valley",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1995-11-01",
"end_date": "1996-06-30",
"bbox": "-88.1706, 38.2057, -88.1706, 38.2057",
@@ -172122,7 +172135,7 @@
{
"id": "PASSCAL_WABASH",
"title": "A comprehensive geophysical investigation to assess seismic hazards in the coassesment of seismicity in the Wabash Valley",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1995-11-01",
"end_date": "1996-06-30",
"bbox": "-88.1706, 38.2057, -88.1706, 38.2057",
@@ -172590,7 +172603,7 @@
{
"id": "POSTER-2004 Hurricanes_Not Applicable",
"title": "2004 Landfalling Hurricanes Poster",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-08-13",
"end_date": "2004-09-25",
"bbox": "-91, 8, -33, 46.5",
@@ -172603,7 +172616,7 @@
{
"id": "POSTER-2004 Hurricanes_Not Applicable",
"title": "2004 Landfalling Hurricanes Poster",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2004-08-13",
"end_date": "2004-09-25",
"bbox": "-91, 8, -33, 46.5",
@@ -172616,7 +172629,7 @@
{
"id": "POSTER-2005 Atl Hurricanes_Not Applicable",
"title": "2005 Atlantic Hurricanes Poster",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-07-03",
"end_date": "2005-12-08",
"bbox": "-97, 20, -65, 40.5",
@@ -172629,7 +172642,7 @@
{
"id": "POSTER-2005 Atl Hurricanes_Not Applicable",
"title": "2005 Atlantic Hurricanes Poster",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2005-07-03",
"end_date": "2005-12-08",
"bbox": "-97, 20, -65, 40.5",
@@ -173357,7 +173370,7 @@
{
"id": "Permafrost_ActiveLayer_NSlope_1759_1",
"title": "ABoVE: Active Layer Soil Characterization of Permafrost Sites, Northern Alaska, 2018",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-08-22",
"end_date": "2018-08-26",
"bbox": "-149.31, 68.61, -148.56, 69.81",
@@ -173370,7 +173383,7 @@
{
"id": "Permafrost_ActiveLayer_NSlope_1759_1",
"title": "ABoVE: Active Layer Soil Characterization of Permafrost Sites, Northern Alaska, 2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2018-08-22",
"end_date": "2018-08-26",
"bbox": "-149.31, 68.61, -148.56, 69.81",
@@ -173383,7 +173396,7 @@
{
"id": "Permafrost_Thaw_Depth_YK_1598_1",
"title": "ABoVE: Permafrost Measurements and Distribution Across the Y-K Delta, Alaska, 2016",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2009-06-27",
"end_date": "2016-07-17",
"bbox": "-165.69, 61.17, -165.03, 61.29",
@@ -173396,7 +173409,7 @@
{
"id": "Permafrost_Thaw_Depth_YK_1598_1",
"title": "ABoVE: Permafrost Measurements and Distribution Across the Y-K Delta, Alaska, 2016",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2009-06-27",
"end_date": "2016-07-17",
"bbox": "-165.69, 61.17, -165.03, 61.29",
@@ -173461,7 +173474,7 @@
{
"id": "Photos_ThermokarstLakes_AK_1845_1",
"title": "ABoVE: Aerial Photographs of Frozen Lakes near Fairbanks, Alaska, October 2014",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-147.95, 64.86, -147.76, 64.94",
@@ -173474,7 +173487,7 @@
{
"id": "Photos_ThermokarstLakes_AK_1845_1",
"title": "ABoVE: Aerial Photographs of Frozen Lakes near Fairbanks, Alaska, October 2014",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-10-08",
"end_date": "2014-10-08",
"bbox": "-147.95, 64.86, -147.76, 64.94",
@@ -173734,7 +173747,7 @@
{
"id": "PostFire_Tree_Regeneration_1955_1.1",
"title": "ABoVE: Synthesis of Post-Fire Regeneration Across Boreal North America",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1989-01-01",
"end_date": "2018-12-31",
"bbox": "-152.2, 49.12, -71.01, 66.96",
@@ -173747,7 +173760,7 @@
{
"id": "PostFire_Tree_Regeneration_1955_1.1",
"title": "ABoVE: Synthesis of Post-Fire Regeneration Across Boreal North America",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1989-01-01",
"end_date": "2018-12-31",
"bbox": "-152.2, 49.12, -71.01, 66.96",
@@ -174033,7 +174046,7 @@
{
"id": "Profile_based_PBL_heights_1706_1.1",
"title": "ACT-America: Profile-based Planetary Boundary Layer Heights, Eastern USA",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2016-07-18",
"end_date": "2019-07-26",
"bbox": "-106.36, 28.65, -73.13, 49.49",
@@ -174046,7 +174059,7 @@
{
"id": "Profile_based_PBL_heights_1706_1.1",
"title": "ACT-America: Profile-based Planetary Boundary Layer Heights, Eastern USA",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-07-18",
"end_date": "2019-07-26",
"bbox": "-106.36, 28.65, -73.13, 49.49",
@@ -174982,7 +174995,7 @@
{
"id": "RSFDCE_KLIM4",
"title": "Absolute Minimum of Air Temperature. Year By Year Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1881-01-01",
"end_date": "1965-12-31",
"bbox": "25, 23.21, -175, 71",
@@ -174995,7 +175008,7 @@
{
"id": "RSFDCE_KLIM4",
"title": "Absolute Minimum of Air Temperature. Year By Year Data",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1881-01-01",
"end_date": "1965-12-31",
"bbox": "25, 23.21, -175, 71",
@@ -175073,7 +175086,7 @@
{
"id": "Radial_Growth_PRI_1781_1",
"title": "ABoVE: Photochemical Reflectance and Tree Growth, Brooks Range, Alaska, 2018-2019",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-05-01",
"end_date": "2019-09-13",
"bbox": "-149.76, 67.97, -149.72, 68.02",
@@ -175086,7 +175099,7 @@
{
"id": "Radial_Growth_PRI_1781_1",
"title": "ABoVE: Photochemical Reflectance and Tree Growth, Brooks Range, Alaska, 2018-2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2018-05-01",
"end_date": "2019-09-13",
"bbox": "-149.76, 67.97, -149.72, 68.02",
@@ -175307,7 +175320,7 @@
{
"id": "RiSCC_Outcomes_Bibliography_1",
"title": "A bibliography containing references to the outcomes of the RiSCC project from the Antarctic and subantarctic regions",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1994-01-01",
"end_date": "2006-12-31",
"bbox": "-180, -70, 180, -50",
@@ -175320,7 +175333,7 @@
{
"id": "RiSCC_Outcomes_Bibliography_1",
"title": "A bibliography containing references to the outcomes of the RiSCC project from the Antarctic and subantarctic regions",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1994-01-01",
"end_date": "2006-12-31",
"bbox": "-180, -70, 180, -50",
@@ -175333,7 +175346,7 @@
{
"id": "RiSCC_Research_Support_Bibliography_1",
"title": "A bibliography containing references to the research support of the RiSCC project from the Antarctic and subantarctic regions",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1875-01-01",
"end_date": "2004-12-31",
"bbox": "-180, -70, 180, -50",
@@ -175346,7 +175359,7 @@
{
"id": "RiSCC_Research_Support_Bibliography_1",
"title": "A bibliography containing references to the research support of the RiSCC project from the Antarctic and subantarctic regions",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1875-01-01",
"end_date": "2004-12-31",
"bbox": "-180, -70, 180, -50",
@@ -175359,7 +175372,7 @@
{
"id": "River_Ice_Breakup_Freezeup_1697_1",
"title": "ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1972-11-04",
"end_date": "2016-11-30",
"bbox": "-160.07, 62.9, -142.99, 66.36",
@@ -175372,7 +175385,7 @@
{
"id": "River_Ice_Breakup_Freezeup_1697_1",
"title": "ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1972-11-04",
"end_date": "2016-11-30",
"bbox": "-160.07, 62.9, -142.99, 66.36",
@@ -176841,7 +176854,7 @@
{
"id": "SAR_Methane_Ebullition_AK_1790_1",
"title": "ABoVE: SAR-based Methane Ebullition Flux from Lakes, Five Regions, Alaska, 2007-2010",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2007-11-13",
"end_date": "2010-11-11",
"bbox": "-165.17, 64.44, -147.37, 71.35",
@@ -176854,7 +176867,7 @@
{
"id": "SAR_Methane_Ebullition_AK_1790_1",
"title": "ABoVE: SAR-based Methane Ebullition Flux from Lakes, Five Regions, Alaska, 2007-2010",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-11-13",
"end_date": "2010-11-11",
"bbox": "-165.17, 64.44, -147.37, 71.35",
@@ -178050,7 +178063,7 @@
{
"id": "SEAGLIDER_GUAM_2019_V1",
"title": "Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020)",
- "catalog": "POCLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-10-03",
"end_date": "2020-01-15",
"bbox": "143.63035, 13.39476, 144.613, 14.71229",
@@ -178063,7 +178076,7 @@
{
"id": "SEAGLIDER_GUAM_2019_V1",
"title": "Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "POCLOUD STAC Catalog",
"state_date": "2019-10-03",
"end_date": "2020-01-15",
"bbox": "143.63035, 13.39476, 144.613, 14.71229",
@@ -179038,7 +179051,7 @@
{
"id": "SIPEX_II_AUV_1",
"title": "3-D mapping of sea ice draft with an autonomous underwater vehicle",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2012-09-28",
"end_date": "2012-10-13",
"bbox": "115, -65, 125, -60",
@@ -179051,7 +179064,7 @@
{
"id": "SIPEX_II_AUV_1",
"title": "3-D mapping of sea ice draft with an autonomous underwater vehicle",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2012-09-28",
"end_date": "2012-10-13",
"bbox": "115, -65, 125, -60",
@@ -179623,7 +179636,7 @@
{
"id": "SIZEX-89-SAR",
"title": "Airborne X- and C-band SAR Images of Sea Ice in the Barents Sea",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1989-02-15",
"end_date": "1989-02-27",
"bbox": "15, 74, 25, 77",
@@ -179636,7 +179649,7 @@
{
"id": "SIZEX-89-SAR",
"title": "Airborne X- and C-band SAR Images of Sea Ice in the Barents Sea",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1989-02-15",
"end_date": "1989-02-27",
"bbox": "15, 74, 25, 77",
@@ -180195,7 +180208,7 @@
{
"id": "SMHI_IPY_ACEX-2004-Seismic",
"title": "ACEX 2004 Seismic",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2004-08-08",
"end_date": "2004-09-13",
"bbox": "139.0632, 87.917, 140.31, 87.977",
@@ -180208,7 +180221,7 @@
{
"id": "SMHI_IPY_ACEX-2004-Seismic",
"title": "ACEX 2004 Seismic",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-08-08",
"end_date": "2004-09-13",
"bbox": "139.0632, 87.917, 140.31, 87.977",
@@ -184056,7 +184069,7 @@
{
"id": "SOE_greenhouse_gas_1",
"title": "Air sampling for greenhouse gas concentrations and associated species",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1984-11-01",
"end_date": "",
"bbox": "62, -90, 159, -41",
@@ -184069,7 +184082,7 @@
{
"id": "SOE_greenhouse_gas_1",
"title": "Air sampling for greenhouse gas concentrations and associated species",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1984-11-01",
"end_date": "",
"bbox": "62, -90, 159, -41",
@@ -185109,26 +185122,26 @@
{
"id": "SPL1AP_002",
"title": "SMAP L1A Radiometer Time-Ordered Parsed Telemetry V002",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -86.4, 180, 86.4",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000001801-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000001801-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL1AP_002",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661641-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661641-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL1AP_002",
"description": "Each Level-1A (L1A) granule incorporates all radiometer data downlinked from the Soil Moisture Active Passive (SMAP) spacecraft for one specific half orbit. The data are scaled instrument counts of the following:
- The first four raw moments of the fullband channel for both vertical and horizontal polarizations
- The complex cross-correlations of the fullband channel
- The 16 subband channels for both vertical and horizontal polarizations
",
"license": "proprietary"
},
{
"id": "SPL1AP_002",
"title": "SMAP L1A Radiometer Time-Ordered Parsed Telemetry V002",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -86.4, 180, 86.4",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661641-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661641-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL1AP_002",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000001801-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000001801-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL1AP_002",
"description": "Each Level-1A (L1A) granule incorporates all radiometer data downlinked from the Soil Moisture Active Passive (SMAP) spacecraft for one specific half orbit. The data are scaled instrument counts of the following:
- The first four raw moments of the fullband channel for both vertical and horizontal polarizations
- The complex cross-correlations of the fullband channel
- The 16 subband channels for both vertical and horizontal polarizations
",
"license": "proprietary"
},
@@ -185330,26 +185343,26 @@
{
"id": "SPL1BTB_006",
"title": "SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V006",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -86.4, 180, 86.4",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661904-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661904-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL1BTB_006",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463679-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463679-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL1BTB_006",
"description": "This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed.",
"license": "proprietary"
},
{
"id": "SPL1BTB_006",
"title": "SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V006",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -86.4, 180, 86.4",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463679-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463679-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL1BTB_006",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661904-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938661904-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL1BTB_006",
"description": "This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed.",
"license": "proprietary"
},
@@ -185512,26 +185525,26 @@
{
"id": "SPL1CTB_E_004",
"title": "SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures V004",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663435-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663435-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL1CTB_E_004",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463717-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463717-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL1CTB_E_004",
"description": "This enhanced Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract enhanced information from SMAP antenna temperatures before they are converted to brightness temperatures. The resulting brightness temperatures are posted to an Earth-fixed, 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal.",
"license": "proprietary"
},
{
"id": "SPL1CTB_E_004",
"title": "SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures V004",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463717-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463717-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL1CTB_E_004",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663435-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663435-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL1CTB_E_004",
"description": "This enhanced Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract enhanced information from SMAP antenna temperatures before they are converted to brightness temperatures. The resulting brightness temperatures are posted to an Earth-fixed, 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal.",
"license": "proprietary"
},
@@ -185707,78 +185720,78 @@
{
"id": "SPL2SMA_003",
"title": "SMAP L2 Radar Half-Orbit 3 km EASE-Grid Soil Moisture V003",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-04-13",
"end_date": "2015-07-07",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303826-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303826-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL2SMA_003",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2812935277-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2812935277-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL2SMA_003",
"description": "This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) active radar during 6:00 a.m. descending half-orbit passes, as well as ancillary data such as surface temperature and vegetation water content. Input backscatter data used to derive soil moisture are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).",
"license": "proprietary"
},
{
"id": "SPL2SMA_003",
"title": "SMAP L2 Radar Half-Orbit 3 km EASE-Grid Soil Moisture V003",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-04-13",
"end_date": "2015-07-07",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2812935277-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2812935277-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL2SMA_003",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303826-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303826-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL2SMA_003",
"description": "This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) active radar during 6:00 a.m. descending half-orbit passes, as well as ancillary data such as surface temperature and vegetation water content. Input backscatter data used to derive soil moisture are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).",
"license": "proprietary"
},
{
"id": "SPL2SMP_009",
"title": "SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V009",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL2SMP_009",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663609-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663609-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL2SMP_009",
"description": "This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) [and made available as the SPL1CTB product], and the gridded brightness temperatures are then used to derive gridded soil moisture data.",
"license": "proprietary"
},
{
"id": "SPL2SMP_009",
"title": "SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V009",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663609-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663609-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL2SMP_009",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL2SMP_009",
"description": "This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) [and made available as the SPL1CTB product], and the gridded brightness temperatures are then used to derive gridded soil moisture data.",
"license": "proprietary"
},
{
"id": "SPL2SMP_E_006",
"title": "SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V006",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 90",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL2SMP_E_006",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663676-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663676-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL2SMP_E_006",
"description": "This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product].",
"license": "proprietary"
},
{
"id": "SPL2SMP_E_006",
"title": "SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V006",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 90",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663676-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938663676-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL2SMP_E_006",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL2SMP_E_006",
"description": "This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product].",
"license": "proprietary"
},
@@ -185850,52 +185863,52 @@
{
"id": "SPL3FTP_E_004",
"title": "SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State V004",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664439-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664439-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL3FTP_E_004",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463920-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463920-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL3FTP_E_004",
"description": "This enhanced Level-3 (L3) product provides a daily composite of global and Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP enhanced Level-1C brightness temperatures (SPL1CTB_E). Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures. The data are then posted to two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal.",
"license": "proprietary"
},
{
"id": "SPL3FTP_E_004",
"title": "SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State V004",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463920-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463920-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL3FTP_E_004",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664439-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664439-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL3FTP_E_004",
"description": "This enhanced Level-3 (L3) product provides a daily composite of global and Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP enhanced Level-1C brightness temperatures (SPL1CTB_E). Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures. The data are then posted to two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal.",
"license": "proprietary"
},
{
"id": "SPL3SMAP_003",
"title": "SMAP L3 Radar/Radiometer Global Daily 9 km EASE-Grid Soil Moisture V003",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-04-13",
"end_date": "2015-07-07",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2872767144-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2872767144-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL3SMAP_003",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303847-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303847-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL3SMAP_003",
"description": "This Level-3 (L3) soil moisture product provides a daily composite of global land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radar and radiometer. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).",
"license": "proprietary"
},
{
"id": "SPL3SMAP_003",
"title": "SMAP L3 Radar/Radiometer Global Daily 9 km EASE-Grid Soil Moisture V003",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-04-13",
"end_date": "2015-07-07",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303847-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236303847-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL3SMAP_003",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2872767144-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2872767144-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL3SMAP_003",
"description": "This Level-3 (L3) soil moisture product provides a daily composite of global land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radar and radiometer. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).",
"license": "proprietary"
},
@@ -185928,26 +185941,26 @@
{
"id": "SPL3SMP_009",
"title": "SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture V009",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664585-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664585-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL3SMP_009",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463935-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463935-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL3SMP_009",
"description": "This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band soil moisture data are resampled to a global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).",
"license": "proprietary"
},
{
"id": "SPL3SMP_009",
"title": "SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture V009",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463935-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776463935-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL3SMP_009",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664585-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938664585-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL3SMP_009",
"description": "This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band soil moisture data are resampled to a global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0).",
"license": "proprietary"
},
@@ -186006,78 +186019,78 @@
{
"id": "SPL4SMAU_007",
"title": "SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update V007",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665508-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665508-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL4SMAU_007",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2537927247-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2537927247-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL4SMAU_007",
"description": "SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: - SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D)
- SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3)
- SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG).
For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.",
"license": "proprietary"
},
{
"id": "SPL4SMAU_007",
"title": "SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update V007",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2537927247-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2537927247-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL4SMAU_007",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665508-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665508-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL4SMAU_007",
"description": "SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: - SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D)
- SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3)
- SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG).
For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.",
"license": "proprietary"
},
{
"id": "SPL4SMGP_007",
"title": "SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V007",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2531308461-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2531308461-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL4SMGP_007",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665761-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665761-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL4SMGP_007",
"description": "SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.",
"license": "proprietary"
},
{
"id": "SPL4SMGP_007",
"title": "SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V007",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665761-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938665761-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL4SMGP_007",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2531308461-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2531308461-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL4SMGP_007",
"description": "SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.",
"license": "proprietary"
},
{
"id": "SPL4SMLM_007",
"title": "SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants V007",
- "catalog": "NSIDC_ECS STAC Catalog",
+ "catalog": "NSIDC_CPRD STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2537926833-NSIDC_ECS.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2537926833-NSIDC_ECS.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL4SMLM_007",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938666109-NSIDC_CPRD.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938666109-NSIDC_CPRD.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL4SMLM_007",
"description": "SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.",
"license": "proprietary"
},
{
"id": "SPL4SMLM_007",
"title": "SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants V007",
- "catalog": "NSIDC_CPRD STAC Catalog",
+ "catalog": "NSIDC_ECS STAC Catalog",
"state_date": "2015-03-31",
"end_date": "",
"bbox": "-180, -85.044, 180, 85.044",
- "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2938666109-NSIDC_CPRD.umm_json",
- "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2938666109-NSIDC_CPRD.html",
- "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/SPL4SMLM_007",
+ "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2537926833-NSIDC_ECS.umm_json",
+ "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2537926833-NSIDC_ECS.html",
+ "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections/SPL4SMLM_007",
"description": "SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection.",
"license": "proprietary"
},
@@ -187007,7 +187020,7 @@
{
"id": "SSEC-AMRC-AIRCRAFT",
"title": "Aircraft meteorological reports over Antarctica",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-04-04",
"end_date": "2015-08-31",
"bbox": "-180, -90, 180, 0",
@@ -187020,7 +187033,7 @@
{
"id": "SSEC-AMRC-AIRCRAFT",
"title": "Aircraft meteorological reports over Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2004-04-04",
"end_date": "2015-08-31",
"bbox": "-180, -90, 180, 0",
@@ -189477,7 +189490,7 @@
{
"id": "Scambos_PLR1441432",
"title": "A Low-power, Quick-install Polar Observation System ('AMIGOS-II') for Monitoring Climate-ice-ocean Interactions",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-06-01",
"end_date": "2015-05-31",
"bbox": "-180, -90, 180, 90",
@@ -189490,7 +189503,7 @@
{
"id": "Scambos_PLR1441432",
"title": "A Low-power, Quick-install Polar Observation System ('AMIGOS-II') for Monitoring Climate-ice-ocean Interactions",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2014-06-01",
"end_date": "2015-05-31",
"bbox": "-180, -90, 180, 90",
@@ -190283,7 +190296,7 @@
{
"id": "Seasonality_Tundra_Vegetation_1606_1",
"title": "ABoVE: Climate Drivers of Pan-Arctic Tundra Vegetation Productivity, 1982-2015",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1982-01-01",
"end_date": "2015-12-31",
"bbox": "-180, 70, 180, 90",
@@ -190296,7 +190309,7 @@
{
"id": "Seasonality_Tundra_Vegetation_1606_1",
"title": "ABoVE: Climate Drivers of Pan-Arctic Tundra Vegetation Productivity, 1982-2015",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1982-01-01",
"end_date": "2015-12-31",
"bbox": "-180, 70, 180, 90",
@@ -190556,7 +190569,7 @@
{
"id": "SnowMeltDuration_PMicrowave_1843_1.1",
"title": "ABoVE: Passive Microwave-derived Annual Snow Melt Duration Date Maps, 1988-2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1988-02-09",
"end_date": "2018-07-20",
"bbox": "-180, 51.6, -107.83, 72.41",
@@ -190569,7 +190582,7 @@
{
"id": "SnowMeltDuration_PMicrowave_1843_1.1",
"title": "ABoVE: Passive Microwave-derived Annual Snow Melt Duration Date Maps, 1988-2018",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1988-02-09",
"end_date": "2018-07-20",
"bbox": "-180, 51.6, -107.83, 72.41",
@@ -190647,7 +190660,7 @@
{
"id": "Snowpack_Dall_Sheep_Track_1583_1",
"title": "ABoVE: Dall Sheep Track Sinking Depths, Snow Depth, Hardness, and Density, 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2017-03-19",
"end_date": "2017-03-22",
"bbox": "-143.06, 62.26, -143.01, 62.28",
@@ -190660,7 +190673,7 @@
{
"id": "Snowpack_Dall_Sheep_Track_1583_1",
"title": "ABoVE: Dall Sheep Track Sinking Depths, Snow Depth, Hardness, and Density, 2017",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-03-19",
"end_date": "2017-03-22",
"bbox": "-143.06, 62.26, -143.01, 62.28",
@@ -190712,7 +190725,7 @@
{
"id": "Soil_ActiveLayer_Properties_AK_2315_1",
"title": "ABoVE: Active Layer Soil Characteristics at Selected Sites Across Alaska",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2016-08-09",
"end_date": "2018-07-07",
"bbox": "-149.53, 63.88, -146.56, 68.56",
@@ -190725,7 +190738,7 @@
{
"id": "Soil_ActiveLayer_Properties_AK_2315_1",
"title": "ABoVE: Active Layer Soil Characteristics at Selected Sites Across Alaska",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-08-09",
"end_date": "2018-07-07",
"bbox": "-149.53, 63.88, -146.56, 68.56",
@@ -190803,7 +190816,7 @@
{
"id": "Soil_Temperature_Profiles_AK_1767_1",
"title": "ABoVE: Soil Temperature Profiles, USArray Seismic Stations, AK and Canada, 2016-2019",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-06-25",
"end_date": "2019-08-22",
"bbox": "-163.18, 63.89, -134.34, 69.92",
@@ -190816,7 +190829,7 @@
{
"id": "Soil_Temperature_Profiles_AK_1767_1",
"title": "ABoVE: Soil Temperature Profiles, USArray Seismic Stations, AK and Canada, 2016-2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2016-06-25",
"end_date": "2019-08-22",
"bbox": "-163.18, 63.89, -134.34, 69.92",
@@ -191882,7 +191895,7 @@
{
"id": "TEMR_RSFCE",
"title": "Air Temperature Time Series",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1883-01-01",
"end_date": "1987-12-31",
"bbox": "25, 23.21, -175, 71",
@@ -191895,7 +191908,7 @@
{
"id": "TEMR_RSFCE",
"title": "Air Temperature Time Series",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1883-01-01",
"end_date": "1987-12-31",
"bbox": "25, 23.21, -175, 71",
@@ -199734,7 +199747,7 @@
{
"id": "Tundra_Greeness_Temp_Trends_1893_1",
"title": "ABoVE: Landsat Tundra Greenness and Summer Air Temperatures, Arctic Tundra, 1985-2016",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1985-07-01",
"end_date": "2016-08-31",
"bbox": "-180, 31.49, 180, 90",
@@ -199747,7 +199760,7 @@
{
"id": "Tundra_Greeness_Temp_Trends_1893_1",
"title": "ABoVE: Landsat Tundra Greenness and Summer Air Temperatures, Arctic Tundra, 1985-2016",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1985-07-01",
"end_date": "2016-08-31",
"bbox": "-180, 31.49, 180, 90",
@@ -199773,7 +199786,7 @@
{
"id": "Turbid9_0",
"title": "2004 Measurements made in the Chesapeake Bay",
- "catalog": "OB_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-10-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -199786,7 +199799,7 @@
{
"id": "Turbid9_0",
"title": "2004 Measurements made in the Chesapeake Bay",
- "catalog": "ALL STAC Catalog",
+ "catalog": "OB_DAAC STAC Catalog",
"state_date": "2004-10-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -200618,7 +200631,7 @@
{
"id": "UKASSEL_GLOBAL_IRRIGATED_AREA",
"title": "A Digital Global Map of Irrigated Areas",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1995-01-01",
"end_date": "1995-12-31",
"bbox": "-180, -90, 180, 90",
@@ -200631,7 +200644,7 @@
{
"id": "UKASSEL_GLOBAL_IRRIGATED_AREA",
"title": "A Digital Global Map of Irrigated Areas",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1995-01-01",
"end_date": "1995-12-31",
"bbox": "-180, -90, 180, 90",
@@ -200644,7 +200657,7 @@
{
"id": "UM0405_26_aerosol_optical",
"title": "Aerosol optical thickness - UM0405_26_aerosol_optical",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-12-31",
"end_date": "2005-01-25",
"bbox": "18, -68, 115, -32",
@@ -200657,7 +200670,7 @@
{
"id": "UM0405_26_aerosol_optical",
"title": "Aerosol optical thickness - UM0405_26_aerosol_optical",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2004-12-31",
"end_date": "2005-01-25",
"bbox": "18, -68, 115, -32",
@@ -200670,7 +200683,7 @@
{
"id": "UM0506_26_aerosol_optical",
"title": "Aerosol optical thickness",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2006-01-03",
"end_date": "2006-01-30",
"bbox": "18, -68, 115, -32",
@@ -200683,7 +200696,7 @@
{
"id": "UM0506_26_aerosol_optical",
"title": "Aerosol optical thickness",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2006-01-03",
"end_date": "2006-01-30",
"bbox": "18, -68, 115, -32",
@@ -200722,7 +200735,7 @@
{
"id": "UM0809_33_nano",
"title": "Abundance and composition of nano, picoplankton, microzooplankton",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2009-01-12",
"end_date": "2009-01-25",
"bbox": "38, -70, 75, -60",
@@ -200735,7 +200748,7 @@
{
"id": "UM0809_33_nano",
"title": "Abundance and composition of nano, picoplankton, microzooplankton",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2009-01-12",
"end_date": "2009-01-25",
"bbox": "38, -70, 75, -60",
@@ -200917,7 +200930,7 @@
{
"id": "USAP-1043471",
"title": "A Study of Atmospheric Dust in the WAIS Divide Ice Core Based on Sr-Nd-Pb-He Isotopes",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2011-08-01",
"end_date": "2015-07-31",
"bbox": "-112.5, -79.5, -112.086, -79.468",
@@ -200930,7 +200943,7 @@
{
"id": "USAP-1043471",
"title": "A Study of Atmospheric Dust in the WAIS Divide Ice Core Based on Sr-Nd-Pb-He Isotopes",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-08-01",
"end_date": "2015-07-31",
"bbox": "-112.5, -79.5, -112.086, -79.468",
@@ -201203,7 +201216,7 @@
{
"id": "USAP-1543498_1",
"title": "A Full Lifecycle Approach to Understanding Ad\u00e9lie Penguin Response to Changing Pack Ice Conditions in the Ross Sea",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-06-01",
"end_date": "",
"bbox": "165, -78, -150, -60",
@@ -201216,7 +201229,7 @@
{
"id": "USAP-1543498_1",
"title": "A Full Lifecycle Approach to Understanding Ad\u00e9lie Penguin Response to Changing Pack Ice Conditions in the Ross Sea",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2016-06-01",
"end_date": "",
"bbox": "165, -78, -150, -60",
@@ -201229,7 +201242,7 @@
{
"id": "USAP-1544526_1",
"title": "Activity, Preservation and Fossilization of Cryptoendolithic Microorganisms in Antarctica",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-09-01",
"end_date": "2017-08-31",
"bbox": "160, -77.8, 163.7, -76.5",
@@ -201242,7 +201255,7 @@
{
"id": "USAP-1544526_1",
"title": "Activity, Preservation and Fossilization of Cryptoendolithic Microorganisms in Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2016-09-01",
"end_date": "2017-08-31",
"bbox": "160, -77.8, 163.7, -76.5",
@@ -201268,7 +201281,7 @@
{
"id": "USAP-1643722_1",
"title": "A High Resolution Atmospheric Methane Record from the South Pole Ice Core",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2017-02-01",
"end_date": "2019-01-31",
"bbox": "180, -90, 180, -90",
@@ -201281,7 +201294,7 @@
{
"id": "USAP-1643722_1",
"title": "A High Resolution Atmospheric Methane Record from the South Pole Ice Core",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-02-01",
"end_date": "2019-01-31",
"bbox": "180, -90, 180, -90",
@@ -201346,7 +201359,7 @@
{
"id": "USAP-1644234_1",
"title": "A Test of Global and Antarctic Models for Cosmogenic-nuclide Production Rates using High-precision Dating of 40Ar/39Ar Lava Flows from Mount Erebus",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-07-15",
"end_date": "2022-06-30",
"bbox": "166.17, -77.7, 167.75, -77.3",
@@ -201359,7 +201372,7 @@
{
"id": "USAP-1644234_1",
"title": "A Test of Global and Antarctic Models for Cosmogenic-nuclide Production Rates using High-precision Dating of 40Ar/39Ar Lava Flows from Mount Erebus",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2017-07-15",
"end_date": "2022-06-30",
"bbox": "166.17, -77.7, 167.75, -77.3",
@@ -201372,7 +201385,7 @@
{
"id": "USAP-1656344_1",
"title": "A Preliminary Assessment of the Influence of Ice Cover on Microbial Carbon and Energy Acquisition during the Antarctic Winter-spring Seasonal Transition",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-08-01",
"end_date": "2018-07-31",
"bbox": "-64.1, -65, -63.9, -64.75",
@@ -201385,7 +201398,7 @@
{
"id": "USAP-1656344_1",
"title": "A Preliminary Assessment of the Influence of Ice Cover on Microbial Carbon and Energy Acquisition during the Antarctic Winter-spring Seasonal Transition",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2016-08-01",
"end_date": "2018-07-31",
"bbox": "-64.1, -65, -63.9, -64.75",
@@ -201398,7 +201411,7 @@
{
"id": "USAP-1744755_1",
"title": "A mechanistic study of bio-physical interaction and air-sea carbon transfer in the Southern Ocean",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-05-01",
"end_date": "2022-04-30",
"bbox": "-80, -70, -30, -45",
@@ -201411,7 +201424,7 @@
{
"id": "USAP-1744755_1",
"title": "A mechanistic study of bio-physical interaction and air-sea carbon transfer in the Southern Ocean",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2018-05-01",
"end_date": "2022-04-30",
"bbox": "-80, -70, -30, -45",
@@ -201788,7 +201801,7 @@
{
"id": "USAP-2130663_1",
"title": "2021 Antarctic Subsea Cable Workshop: High-Speed Connectivity Needs to Advance US Antarctic Science",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2021-06-01",
"end_date": "2023-05-31",
"bbox": "-180, -90, 180, -60",
@@ -201801,7 +201814,7 @@
{
"id": "USAP-2130663_1",
"title": "2021 Antarctic Subsea Cable Workshop: High-Speed Connectivity Needs to Advance US Antarctic Science",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "2021-06-01",
"end_date": "2023-05-31",
"bbox": "-180, -90, 180, -60",
@@ -201918,7 +201931,7 @@
{
"id": "USAP-9615281_1",
"title": "Air-Ground Study of Tectonics at the Boundary Between the Eastern Ross Embayment and Western Marie Byrd Land, Antarctica: Basement Geology and Structure",
- "catalog": "AMD_USAPDC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1997-08-15",
"end_date": "2002-07-31",
"bbox": "-170, -84, -135, -76",
@@ -201931,7 +201944,7 @@
{
"id": "USAP-9615281_1",
"title": "Air-Ground Study of Tectonics at the Boundary Between the Eastern Ross Embayment and Western Marie Byrd Land, Antarctica: Basement Geology and Structure",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AMD_USAPDC STAC Catalog",
"state_date": "1997-08-15",
"end_date": "2002-07-31",
"bbox": "-170, -84, -135, -76",
@@ -201957,7 +201970,7 @@
{
"id": "USARC_AERIAL_PHOTOS",
"title": "Aerial Photography of Antarctica",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, -62.83",
@@ -201970,7 +201983,7 @@
{
"id": "USARC_AERIAL_PHOTOS",
"title": "Aerial Photography of Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, -62.83",
@@ -201983,7 +201996,7 @@
{
"id": "USArray_Ground_Temperature_1680_1.1",
"title": "ABoVE: Soil Temperature Profiles, USArray Seismic Stations, 2016-2021",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2016-05-13",
"end_date": "2021-07-08",
"bbox": "-165.35, 59.25, -141.59, 71",
@@ -201996,7 +202009,7 @@
{
"id": "USArray_Ground_Temperature_1680_1.1",
"title": "ABoVE: Soil Temperature Profiles, USArray Seismic Stations, 2016-2021",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2016-05-13",
"end_date": "2021-07-08",
"bbox": "-165.35, 59.25, -141.59, 71",
@@ -202139,7 +202152,7 @@
{
"id": "USGS-DDS-3",
"title": "A Geologic Map of the Sea Floor in Western Massachusetts Bay, Constructed from Digital Sidescan-Sonar Images, Photography, and Sediment Samples",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-71.5, 42, -70, 43",
@@ -202152,7 +202165,7 @@
{
"id": "USGS-DDS-3",
"title": "A Geologic Map of the Sea Floor in Western Massachusetts Bay, Constructed from Digital Sidescan-Sonar Images, Photography, and Sediment Samples",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-71.5, 42, -70, 43",
@@ -202217,7 +202230,7 @@
{
"id": "USGS-DDS_30_P-10_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Joaquin Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-121.388916, 34.890034, -118.58517, 37.83907",
@@ -202230,7 +202243,7 @@
{
"id": "USGS-DDS_30_P-10_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Joaquin Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-121.388916, 34.890034, -118.58517, 37.83907",
@@ -202243,7 +202256,7 @@
{
"id": "USGS-DDS_30_P10_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the San Joaquin Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-121.388916, 34.890034, -118.58517, 37.83907",
@@ -202256,7 +202269,7 @@
{
"id": "USGS-DDS_30_P10_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the San Joaquin Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-121.388916, 34.890034, -118.58517, 37.83907",
@@ -202321,7 +202334,7 @@
{
"id": "USGS_ALASKA_RADIOCARBON",
"title": "Alaska Radiocarbon Data Base; USGS, Menlo Park",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1951-01-01",
"end_date": "",
"bbox": "-179, 50, -140, 72",
@@ -202334,7 +202347,7 @@
{
"id": "USGS_ALASKA_RADIOCARBON",
"title": "Alaska Radiocarbon Data Base; USGS, Menlo Park",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1951-01-01",
"end_date": "",
"bbox": "-179, 50, -140, 72",
@@ -202620,7 +202633,7 @@
{
"id": "USGS_DDS_P12_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Santa Maria Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-121.977486, 34.488464, -119.44189, 36.40565",
@@ -202633,7 +202646,7 @@
{
"id": "USGS_DDS_P12_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Santa Maria Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-121.977486, 34.488464, -119.44189, 36.40565",
@@ -202646,7 +202659,7 @@
{
"id": "USGS_DDS_P12_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Santa Maria Basin Province - USGS_DDS_P12_conventional",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-121.977486, 34.488464, -119.44189, 36.40565",
@@ -202659,7 +202672,7 @@
{
"id": "USGS_DDS_P12_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Santa Maria Basin Province - USGS_DDS_P12_conventional",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-121.977486, 34.488464, -119.44189, 36.40565",
@@ -202672,7 +202685,7 @@
{
"id": "USGS_DDS_P13_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Ventura Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-120.58227, 33.84158, -117.37425, 34.824276",
@@ -202685,7 +202698,7 @@
{
"id": "USGS_DDS_P13_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Ventura Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-120.58227, 33.84158, -117.37425, 34.824276",
@@ -202750,7 +202763,7 @@
{
"id": "USGS_DDS_P14_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Los Angeles Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-119.63631, 32.7535, -117.52315, 34.17464",
@@ -202763,7 +202776,7 @@
{
"id": "USGS_DDS_P14_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Los Angeles Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-119.63631, 32.7535, -117.52315, 34.17464",
@@ -202802,7 +202815,7 @@
{
"id": "USGS_DDS_P16_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Salton Trough Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-116.66911, 32.634293, -114.74501, 34.02059",
@@ -202815,7 +202828,7 @@
{
"id": "USGS_DDS_P16_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Salton Trough Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-116.66911, 32.634293, -114.74501, 34.02059",
@@ -202828,7 +202841,7 @@
{
"id": "USGS_DDS_P17_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Idaho - Snake River Downwarp Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-117.24303, 41.99332, -111.04548, 49.00115",
@@ -202841,7 +202854,7 @@
{
"id": "USGS_DDS_P17_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Idaho - Snake River Downwarp Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-117.24303, 41.99332, -111.04548, 49.00115",
@@ -202880,7 +202893,7 @@
{
"id": "USGS_DDS_P18_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Western Great Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-122.29004, 32.717037, -114.13121, 44.563953",
@@ -202893,7 +202906,7 @@
{
"id": "USGS_DDS_P18_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Western Great Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-122.29004, 32.717037, -114.13121, 44.563953",
@@ -202932,7 +202945,7 @@
{
"id": "USGS_DDS_P19_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Eastern Great Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-117.02622, 35.002083, -111.170425, 43.022377",
@@ -202945,7 +202958,7 @@
{
"id": "USGS_DDS_P19_cells",
"title": "1995 National Oil and Gas Assessment 1/4-Mile Cells within the Eastern Great Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1990-12-01",
"end_date": "1990-12-01",
"bbox": "-117.02622, 35.002083, -111.170425, 43.022377",
@@ -202958,7 +202971,7 @@
{
"id": "USGS_DDS_P19_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Eastern Great Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-117.02622, 35.002083, -111.170425, 43.022377",
@@ -202971,7 +202984,7 @@
{
"id": "USGS_DDS_P19_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Eastern Great Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-117.02622, 35.002083, -111.170425, 43.022377",
@@ -203010,7 +203023,7 @@
{
"id": "USGS_DDS_P20_continuous",
"title": "1995 National Oil and Gas Assessment Continuous-Type Plays within the Uinta - Piceance Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-111.486916, 38.14689, -105.87804, 40.85869",
@@ -203023,7 +203036,7 @@
{
"id": "USGS_DDS_P20_continuous",
"title": "1995 National Oil and Gas Assessment Continuous-Type Plays within the Uinta - Piceance Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-111.486916, 38.14689, -105.87804, 40.85869",
@@ -203036,7 +203049,7 @@
{
"id": "USGS_DDS_P20_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Uinta - Piceance Basin Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-111.486916, 38.14689, -105.87804, 40.85869",
@@ -203049,7 +203062,7 @@
{
"id": "USGS_DDS_P20_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Uinta - Piceance Basin Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-111.486916, 38.14689, -105.87804, 40.85869",
@@ -203127,7 +203140,7 @@
{
"id": "USGS_DS-845_PierScoutDatabase_1.0",
"title": "A pier-scour database: 2,427 field and laboratory measurements of pier scour",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "19.6, 16.916668, -52.62, 83.1",
@@ -203140,7 +203153,7 @@
{
"id": "USGS_DS-845_PierScoutDatabase_1.0",
"title": "A pier-scour database: 2,427 field and laboratory measurements of pier scour",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "19.6, 16.916668, -52.62, 83.1",
@@ -203283,7 +203296,7 @@
{
"id": "USGS_DS_2006_224",
"title": "Aeromagnetic Survey of Taylor Mountains Area in Southwest Alaska, A Website for the Distribution of Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "2004-04-17",
"end_date": "2004-05-31",
"bbox": "-160, 60, -156, 61",
@@ -203296,7 +203309,7 @@
{
"id": "USGS_DS_2006_224",
"title": "Aeromagnetic Survey of Taylor Mountains Area in Southwest Alaska, A Website for the Distribution of Data",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-04-17",
"end_date": "2004-05-31",
"bbox": "-160, 60, -156, 61",
@@ -204687,7 +204700,7 @@
{
"id": "USGS_NPS_AcadiaParkBoundary_Final",
"title": "Acadia National Park Vegetation Mapping Project - Park Boundary",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-10-01",
"end_date": "2003-10-01",
"bbox": "-68.944374, 43.99941, -68.02303, 44.48051",
@@ -204700,7 +204713,7 @@
{
"id": "USGS_NPS_AcadiaParkBoundary_Final",
"title": "Acadia National Park Vegetation Mapping Project - Park Boundary",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "2003-10-01",
"end_date": "2003-10-01",
"bbox": "-68.944374, 43.99941, -68.02303, 44.48051",
@@ -204713,7 +204726,7 @@
{
"id": "USGS_NPS_AcadiaSpatialVeg_Final",
"title": "Acadia National Park Vegetation Mapping Project - Spatial Vegetation Data",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1997-05-27",
"end_date": "1997-05-28",
"bbox": "-69, 43.99574, -67.99682, 44.50385",
@@ -204726,7 +204739,7 @@
{
"id": "USGS_NPS_AcadiaSpatialVeg_Final",
"title": "Acadia National Park Vegetation Mapping Project - Spatial Vegetation Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1997-05-27",
"end_date": "1997-05-28",
"bbox": "-69, 43.99574, -67.99682, 44.50385",
@@ -206221,7 +206234,7 @@
{
"id": "USGS_OFR_2003_247_1.0",
"title": "A Digital Geological Map Database For the State of Oklahoma",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-103, 33, -94, 37",
@@ -206234,7 +206247,7 @@
{
"id": "USGS_OFR_2003_247_1.0",
"title": "A Digital Geological Map Database For the State of Oklahoma",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-103, 33, -94, 37",
@@ -206468,7 +206481,7 @@
{
"id": "USGS_OFR_2004_1058",
"title": "2002 Volcanic Activity in Alaska and Kamchatka: Summary of Events and Response of the Alaska Volcano Observatory",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "2002-01-01",
"end_date": "",
"bbox": "-168, 46, -126, 76",
@@ -206481,7 +206494,7 @@
{
"id": "USGS_OFR_2004_1058",
"title": "2002 Volcanic Activity in Alaska and Kamchatka: Summary of Events and Response of the Alaska Volcano Observatory",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-01-01",
"end_date": "",
"bbox": "-168, 46, -126, 76",
@@ -206520,7 +206533,7 @@
{
"id": "USGS_OFR_2004_1069",
"title": "A 30-Year Record of Surface Mass Balance (1966-95) and Motion and Surface Altitude (1975-95) at Wolverine Glacier, Alaska",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1966-04-01",
"end_date": "1995-12-31",
"bbox": "-156, 57, -144, 66",
@@ -206533,7 +206546,7 @@
{
"id": "USGS_OFR_2004_1069",
"title": "A 30-Year Record of Surface Mass Balance (1966-95) and Motion and Surface Altitude (1975-95) at Wolverine Glacier, Alaska",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1966-04-01",
"end_date": "1995-12-31",
"bbox": "-156, 57, -144, 66",
@@ -208444,7 +208457,7 @@
{
"id": "USGS_OFR_Acid_Deposition",
"title": "Acid Deposition Sensitivity of the Southern Appalachian Assessment Area",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-87, 31, -77, 39",
@@ -208457,7 +208470,7 @@
{
"id": "USGS_OFR_Acid_Deposition",
"title": "Acid Deposition Sensitivity of the Southern Appalachian Assessment Area",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-87, 31, -77, 39",
@@ -208509,7 +208522,7 @@
{
"id": "USGS_P-11_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Central Coastal Province",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-123.80987, 34.66294, -118.997696, 39.082233",
@@ -208522,7 +208535,7 @@
{
"id": "USGS_P-11_conventional",
"title": "1995 National Oil and Gas Assessment Conventional Plays within the Central Coastal Province",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "1996-12-31",
"bbox": "-123.80987, 34.66294, -118.997696, 39.082233",
@@ -208691,7 +208704,7 @@
{
"id": "USGS_SESC_SturgeonBiblio_3",
"title": "A bibliography of all known publications & reports on the Gulf Sturgeon, Acipenser oxyrinchus desotoi.",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -208704,7 +208717,7 @@
{
"id": "USGS_SESC_SturgeonBiblio_3",
"title": "A bibliography of all known publications & reports on the Gulf Sturgeon, Acipenser oxyrinchus desotoi.",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -208769,7 +208782,7 @@
{
"id": "USGS_SOFIA_ASR_04",
"title": "A retrospective and critical review of aquifer and storage (ASR) sites and conceptual framework of the Upper Floridian aquifer in south Florida",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1999-10-01",
"end_date": "2004-09-30",
"bbox": "-82.55795, 24.441917, -79.84407, 27.586416",
@@ -208782,7 +208795,7 @@
{
"id": "USGS_SOFIA_ASR_04",
"title": "A retrospective and critical review of aquifer and storage (ASR) sites and conceptual framework of the Upper Floridian aquifer in south Florida",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-10-01",
"end_date": "2004-09-30",
"bbox": "-82.55795, 24.441917, -79.84407, 27.586416",
@@ -208899,7 +208912,7 @@
{
"id": "USGS_SOFIA_Eco_hist_db_2008_present_2",
"title": "2008 - Present Ecosystem History of South Florida's Estuaries Database version 2",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2008-03-16",
"end_date": "2012-09-30",
"bbox": "-81.83, 24.75, -80, 26.5",
@@ -208912,7 +208925,7 @@
{
"id": "USGS_SOFIA_Eco_hist_db_2008_present_2",
"title": "2008 - Present Ecosystem History of South Florida's Estuaries Database version 2",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "2008-03-16",
"end_date": "2012-09-30",
"bbox": "-81.83, 24.75, -80, 26.5",
@@ -209224,7 +209237,7 @@
{
"id": "USGS_SOFIA_aerial-photos",
"title": "Aerial Photos of the 1940s",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1940-02-14",
"end_date": "1940-08-21",
"bbox": "-81.9, 24.41, -79.98, 26.22",
@@ -209237,7 +209250,7 @@
{
"id": "USGS_SOFIA_aerial-photos",
"title": "Aerial Photos of the 1940s",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1940-02-14",
"end_date": "1940-08-21",
"bbox": "-81.9, 24.41, -79.98, 26.22",
@@ -209276,7 +209289,7 @@
{
"id": "USGS_SOFIA_atlss_prog",
"title": "Across Trophic Level System Simulation (ATLSS) Program",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1996-01-01",
"end_date": "",
"bbox": "-81.30333, 24.696152, -80.26212, 25.847113",
@@ -209289,7 +209302,7 @@
{
"id": "USGS_SOFIA_atlss_prog",
"title": "Across Trophic Level System Simulation (ATLSS) Program",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1996-01-01",
"end_date": "",
"bbox": "-81.30333, 24.696152, -80.26212, 25.847113",
@@ -209510,7 +209523,7 @@
{
"id": "USGS_SOFIA_coupled_sw-gw_model",
"title": "A Coupled Surface Water and Ground-Water Model to Simulate Past, Present, and Future Hydrologic Conditions in DOI Managed Lands",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1995-01-01",
"end_date": "2009-09-30",
"bbox": "-81.56, 25.02, -80, 25.75",
@@ -209523,7 +209536,7 @@
{
"id": "USGS_SOFIA_coupled_sw-gw_model",
"title": "A Coupled Surface Water and Ground-Water Model to Simulate Past, Present, and Future Hydrologic Conditions in DOI Managed Lands",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1995-01-01",
"end_date": "2009-09-30",
"bbox": "-81.56, 25.02, -80, 25.75",
@@ -209653,7 +209666,7 @@
{
"id": "USGS_SOFIA_eco_hist_db1995-2007_version 7",
"title": "1995 - 2007 Ecosystem History of South Florida's Estuaries Database version 7",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1994-09-27",
"end_date": "2007-04-03",
"bbox": "-81.83, 24.75, -80, 26.5",
@@ -209666,7 +209679,7 @@
{
"id": "USGS_SOFIA_eco_hist_db1995-2007_version 7",
"title": "1995 - 2007 Ecosystem History of South Florida's Estuaries Database version 7",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1994-09-27",
"end_date": "2007-04-03",
"bbox": "-81.83, 24.75, -80, 26.5",
@@ -211434,7 +211447,7 @@
{
"id": "USGS_cont1992",
"title": "1992 Water-Table Contours of the Mojave River Ground-Water Basin, San Bernardino County, California",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-117.652695, 34.364513, -116.55357, 35.081955",
@@ -211447,7 +211460,7 @@
{
"id": "USGS_cont1992",
"title": "1992 Water-Table Contours of the Mojave River Ground-Water Basin, San Bernardino County, California",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-117.652695, 34.364513, -116.55357, 35.081955",
@@ -211460,7 +211473,7 @@
{
"id": "USGS_cont1994",
"title": "1994 Water-Table Contours of the Morongo Ground-Water Basin, San Bernardino County, California",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-117.07194, 34.095333, -115.98976, 34.64026",
@@ -211473,7 +211486,7 @@
{
"id": "USGS_cont1994",
"title": "1994 Water-Table Contours of the Morongo Ground-Water Basin, San Bernardino County, California",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-117.07194, 34.095333, -115.98976, 34.64026",
@@ -212344,7 +212357,7 @@
{
"id": "UTC_1990countyboundaries",
"title": "1990 County Boundaries of the United States",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1972-01-01",
"end_date": "1990-12-31",
"bbox": "-177.1, 13.71, -61.48, 76.63",
@@ -212357,7 +212370,7 @@
{
"id": "UTC_1990countyboundaries",
"title": "1990 County Boundaries of the United States",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1972-01-01",
"end_date": "1990-12-31",
"bbox": "-177.1, 13.71, -61.48, 76.63",
@@ -216426,7 +216439,7 @@
{
"id": "VMS_Genomics_1",
"title": "2010/11 VMS Geonomics sampling - data collected from the VMS (Voyage Marine Science) voyage of the Aurora Australis",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2011-01-04",
"end_date": "2011-02-06",
"bbox": "140, -67, 150, -42",
@@ -216439,7 +216452,7 @@
{
"id": "VMS_Genomics_1",
"title": "2010/11 VMS Geonomics sampling - data collected from the VMS (Voyage Marine Science) voyage of the Aurora Australis",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-01-04",
"end_date": "2011-02-06",
"bbox": "140, -67, 150, -42",
@@ -219949,7 +219962,7 @@
{
"id": "WISPMAWSON04-05_1",
"title": "A GIS dataset of Wilson's storm petrel nests mapped in the Mawson region during the 2004-2005 season",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2004-12-10",
"end_date": "2005-04-25",
"bbox": "62.18384, -67.68587, 63.40759, -67.47282",
@@ -219962,7 +219975,7 @@
{
"id": "WISPMAWSON04-05_1",
"title": "A GIS dataset of Wilson's storm petrel nests mapped in the Mawson region during the 2004-2005 season",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-12-10",
"end_date": "2005-04-25",
"bbox": "62.18384, -67.68587, 63.40759, -67.47282",
@@ -220274,7 +220287,7 @@
{
"id": "WYGISC_HYDRO24K",
"title": "1:24,000-scale Hydrography for ortions Wyoming, various sources",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1967-01-01",
"end_date": "1971-12-31",
"bbox": "-111, 41, -104, 45",
@@ -220287,7 +220300,7 @@
{
"id": "WYGISC_HYDRO24K",
"title": "1:24,000-scale Hydrography for ortions Wyoming, various sources",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1967-01-01",
"end_date": "1971-12-31",
"bbox": "-111, 41, -104, 45",
@@ -220300,7 +220313,7 @@
{
"id": "WYGISC_LANDUSE",
"title": "Agricultural Land Use of Wyoming",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1980-01-01",
"end_date": "1982-12-31",
"bbox": "-111.09, 40.95, -103.88, 45.107",
@@ -220313,7 +220326,7 @@
{
"id": "WYGISC_LANDUSE",
"title": "Agricultural Land Use of Wyoming",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1980-01-01",
"end_date": "1982-12-31",
"bbox": "-111.09, 40.95, -103.88, 45.107",
@@ -220482,7 +220495,7 @@
{
"id": "WhiteSpruce_Leaf_Traits_Alaska_2124_1",
"title": "ABoVE: White Spruce Photosynthetic and Leaf Traits, Alaska and New York, 2017",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-06-19",
"end_date": "2017-07-20",
"bbox": "-149.75, 41.4, -74.02, 67.99",
@@ -220495,7 +220508,7 @@
{
"id": "WhiteSpruce_Leaf_Traits_Alaska_2124_1",
"title": "ABoVE: White Spruce Photosynthetic and Leaf Traits, Alaska and New York, 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2017-06-19",
"end_date": "2017-07-20",
"bbox": "-149.75, 41.4, -74.02, 67.99",
@@ -220508,7 +220521,7 @@
{
"id": "Wildfire_Effects_Spruce_Field_1595_1",
"title": "ABoVE: Characterization of Burned and Unburned Spruce Forest Sites, Tanana, AK, 2017",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-07-26",
"end_date": "2017-07-28",
"bbox": "-152.42, 65.1, -151.95, 65.23",
@@ -220521,7 +220534,7 @@
{
"id": "Wildfire_Effects_Spruce_Field_1595_1",
"title": "ABoVE: Characterization of Burned and Unburned Spruce Forest Sites, Tanana, AK, 2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2017-07-26",
"end_date": "2017-07-28",
"bbox": "-152.42, 65.1, -151.95, 65.23",
@@ -220547,7 +220560,7 @@
{
"id": "Wildfires_2014_NWT_Canada_1307_1",
"title": "ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1997-07-07",
"end_date": "2015-07-15",
"bbox": "-121.6, 60.33, -110.68, 64.25",
@@ -220560,7 +220573,7 @@
{
"id": "Wildfires_2014_NWT_Canada_1307_1",
"title": "ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1997-07-07",
"end_date": "2015-07-15",
"bbox": "-121.6, 60.33, -110.68, 64.25",
@@ -220625,7 +220638,7 @@
{
"id": "Wildfires_NWT_Canada_2018_1703_1",
"title": "ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2018",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-08-12",
"end_date": "2018-08-22",
"bbox": "-117.43, 60.45, -113.42, 62.57",
@@ -220638,7 +220651,7 @@
{
"id": "Wildfires_NWT_Canada_2018_1703_1",
"title": "ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2018-08-12",
"end_date": "2018-08-22",
"bbox": "-117.43, 60.45, -113.42, 62.57",
@@ -220651,7 +220664,7 @@
{
"id": "Wildfires_NWT_Canada_2019_1900_1",
"title": "ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2019",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-08-16",
"end_date": "2019-09-05",
"bbox": "-117.43, 60.92, -113.02, 62.57",
@@ -220664,7 +220677,7 @@
{
"id": "Wildfires_NWT_Canada_2019_1900_1",
"title": "ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2019",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2018-08-16",
"end_date": "2019-09-05",
"bbox": "-117.43, 60.92, -113.02, 62.57",
@@ -220703,7 +220716,7 @@
{
"id": "Wolves_Denning_Pups_Climate_1846_1",
"title": "ABoVE: Wolf Denning Phenology and Reproductive Success, Alaska and Canada, 2000-2017",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2000-03-29",
"end_date": "2017-08-31",
"bbox": "-154.58, 52.97, -112.97, 67.84",
@@ -220716,7 +220729,7 @@
{
"id": "Wolves_Denning_Pups_Climate_1846_1",
"title": "ABoVE: Wolf Denning Phenology and Reproductive Success, Alaska and Canada, 2000-2017",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2000-03-29",
"end_date": "2017-08-31",
"bbox": "-154.58, 52.97, -112.97, 67.84",
@@ -220807,7 +220820,7 @@
{
"id": "XAERDT_L2_ABI_G16_1",
"title": "ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "ALL STAC Catalog",
+ "catalog": "LAADS STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2023-01-02",
"bbox": "-180, -90, 180, 90",
@@ -220820,7 +220833,7 @@
{
"id": "XAERDT_L2_ABI_G16_1",
"title": "ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "LAADS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2023-01-02",
"bbox": "-180, -90, 180, 90",
@@ -220833,7 +220846,7 @@
{
"id": "XAERDT_L2_ABI_G17_1",
"title": "ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "LAADS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2023-01-02",
"bbox": "-180, -90, 180, 90",
@@ -220846,7 +220859,7 @@
{
"id": "XAERDT_L2_ABI_G17_1",
"title": "ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "ALL STAC Catalog",
+ "catalog": "LAADS STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2023-01-02",
"bbox": "-180, -90, 180, 90",
@@ -220859,7 +220872,7 @@
{
"id": "XAERDT_L2_AHI_H08_1",
"title": "AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "ALL STAC Catalog",
+ "catalog": "LAADS STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2022-12-31",
"bbox": "-180, -90, 180, 90",
@@ -220872,7 +220885,7 @@
{
"id": "XAERDT_L2_AHI_H08_1",
"title": "AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "LAADS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2022-12-31",
"bbox": "-180, -90, 180, 90",
@@ -220885,7 +220898,7 @@
{
"id": "XAERDT_L2_AHI_H09_1",
"title": "AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "ALL STAC Catalog",
+ "catalog": "LAADS STAC Catalog",
"state_date": "2022-12-13",
"end_date": "2022-12-31",
"bbox": "-180, -90, 180, 90",
@@ -220898,7 +220911,7 @@
{
"id": "XAERDT_L2_AHI_H09_1",
"title": "AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km",
- "catalog": "LAADS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2022-12-13",
"end_date": "2022-12-31",
"bbox": "-180, -90, 180, 90",
@@ -220976,7 +220989,7 @@
{
"id": "YKDelta_EnvChange_InfoExchange_1894_1",
"title": "Alaska's Changing YK Delta: Knowledge Exchange between Elders and Geoscientists, 2018",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "2018-11-14",
"end_date": "2018-11-16",
"bbox": "-166.55, 59.58, -159.48, 63.43",
@@ -220989,7 +221002,7 @@
{
"id": "YKDelta_EnvChange_InfoExchange_1894_1",
"title": "Alaska's Changing YK Delta: Knowledge Exchange between Elders and Geoscientists, 2018",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2018-11-14",
"end_date": "2018-11-16",
"bbox": "-166.55, 59.58, -159.48, 63.43",
@@ -221015,7 +221028,7 @@
{
"id": "ZZZ302",
"title": "Alabama Remote Sensing Archive Multispectral Imagery of Alabama from Landsat and Skylab",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1972-01-01",
"end_date": "1984-01-01",
"bbox": "-92, 24, -80, 35",
@@ -221028,7 +221041,7 @@
{
"id": "ZZZ302",
"title": "Alabama Remote Sensing Archive Multispectral Imagery of Alabama from Landsat and Skylab",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1972-01-01",
"end_date": "1984-01-01",
"bbox": "-92, 24, -80, 35",
@@ -221431,7 +221444,7 @@
{
"id": "accessibility-of-the-swiss-forest-for-economic-wood-extraction_1.0",
"title": "Accessibility of the Swiss forest for economic wood extraction (2021)",
- "catalog": "ENVIDAT STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2023-01-01",
"end_date": "2023-01-01",
"bbox": "5.95587, 45.81802, 10.49203, 47.80838",
@@ -221444,7 +221457,7 @@
{
"id": "accessibility-of-the-swiss-forest-for-economic-wood-extraction_1.0",
"title": "Accessibility of the Swiss forest for economic wood extraction (2021)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ENVIDAT STAC Catalog",
"state_date": "2023-01-01",
"end_date": "2023-01-01",
"bbox": "5.95587, 45.81802, 10.49203, 47.80838",
@@ -221457,7 +221470,7 @@
{
"id": "accum-measurements-domec-traverse-1982_1",
"title": "Accumulation Measurements from Pioneerskaya to Dome C, 1982-84",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1982-01-01",
"end_date": "1984-12-31",
"bbox": "124.5, -78.5, 93, -67",
@@ -221470,7 +221483,7 @@
{
"id": "accum-measurements-domec-traverse-1982_1",
"title": "Accumulation Measurements from Pioneerskaya to Dome C, 1982-84",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1982-01-01",
"end_date": "1984-12-31",
"bbox": "124.5, -78.5, 93, -67",
@@ -221522,7 +221535,7 @@
{
"id": "aces1am_1",
"title": "ACES Aircraft and Mechanical Data",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221535,7 +221548,7 @@
{
"id": "aces1am_1",
"title": "ACES Aircraft and Mechanical Data",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221574,7 +221587,7 @@
{
"id": "aces1efm_1",
"title": "ACES ELECTRIC FIELD MILL V1",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221587,7 +221600,7 @@
{
"id": "aces1efm_1",
"title": "ACES ELECTRIC FIELD MILL V1",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221626,7 +221639,7 @@
{
"id": "aces1time_1",
"title": "ACES TIMING DATA",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221639,7 +221652,7 @@
{
"id": "aces1time_1",
"title": "ACES TIMING DATA",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221652,7 +221665,7 @@
{
"id": "aces1trig_1",
"title": "ACES TRIGGERED DATA",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221665,7 +221678,7 @@
{
"id": "aces1trig_1",
"title": "ACES TRIGGERED DATA",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2002-07-10",
"end_date": "2002-08-30",
"bbox": "-85, 23, -81, 26",
@@ -221704,7 +221717,7 @@
{
"id": "acoustic_doppler_current_profiler_data_-_2010",
"title": "Acoustic Doppler Current Profiler Data - 2010",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2010-08-21",
"end_date": "2010-09-17",
"bbox": "-156, 70, -154, 72",
@@ -221717,7 +221730,7 @@
{
"id": "acoustic_doppler_current_profiler_data_-_2010",
"title": "Acoustic Doppler Current Profiler Data - 2010",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-08-21",
"end_date": "2010-09-17",
"bbox": "-156, 70, -154, 72",
@@ -221730,7 +221743,7 @@
{
"id": "acoustic_doppler_current_profiler_data_-_2011",
"title": "Acoustic Doppler Current Profiler Data - 2011",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-08-22",
"end_date": "2011-09-13",
"bbox": "-156, 70, -154, 72",
@@ -221743,7 +221756,7 @@
{
"id": "acoustic_doppler_current_profiler_data_-_2011",
"title": "Acoustic Doppler Current Profiler Data - 2011",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2011-08-22",
"end_date": "2011-09-13",
"bbox": "-156, 70, -154, 72",
@@ -221782,7 +221795,7 @@
{
"id": "active_layer_arcss_grid_atqasuk_alaska_2011",
"title": "Active Layer ARCSS grid Atqasuk, Alaska 2011",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-06-17",
"end_date": "2011-08-12",
"bbox": "-157, 70, -156, 71",
@@ -221795,7 +221808,7 @@
{
"id": "active_layer_arcss_grid_atqasuk_alaska_2011",
"title": "Active Layer ARCSS grid Atqasuk, Alaska 2011",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2011-06-17",
"end_date": "2011-08-12",
"bbox": "-157, 70, -156, 71",
@@ -221834,7 +221847,7 @@
{
"id": "active_layer_arcss_grid_barrow_alaska_2010",
"title": "Active Layer ARCSS grid Barrow, Alaska 2010",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2010-06-30",
"end_date": "2010-08-11",
"bbox": "-156.6, 71, -156.5, 71.5",
@@ -221847,7 +221860,7 @@
{
"id": "active_layer_arcss_grid_barrow_alaska_2010",
"title": "Active Layer ARCSS grid Barrow, Alaska 2010",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2010-06-30",
"end_date": "2010-08-11",
"bbox": "-156.6, 71, -156.5, 71.5",
@@ -221886,7 +221899,7 @@
{
"id": "active_layer_arcss_grid_barrow_alaska_2012",
"title": "Active Layer ARCSS grid Barrow, Alaska 2012",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2012-06-09",
"end_date": "2012-08-18",
"bbox": "-156.6, 71, -156.5, 71.5",
@@ -221899,7 +221912,7 @@
{
"id": "active_layer_arcss_grid_barrow_alaska_2012",
"title": "Active Layer ARCSS grid Barrow, Alaska 2012",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2012-06-09",
"end_date": "2012-08-18",
"bbox": "-156.6, 71, -156.5, 71.5",
@@ -221964,7 +221977,7 @@
{
"id": "active_layer_nims_grid_barrow_alaska_2011",
"title": "Active Layer NIMS grid Barrow, Alaska 2011",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-06-14",
"end_date": "2011-08-09",
"bbox": "-156.6, 71, -156.5, 71.5",
@@ -221977,7 +221990,7 @@
{
"id": "active_layer_nims_grid_barrow_alaska_2011",
"title": "Active Layer NIMS grid Barrow, Alaska 2011",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2011-06-14",
"end_date": "2011-08-09",
"bbox": "-156.6, 71, -156.5, 71.5",
@@ -222081,7 +222094,7 @@
{
"id": "adpe-aat-census_1",
"title": "Adelie penguin census from records from 1931 to 2007 AAT region",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1931-02-13",
"end_date": "2006-12-08",
"bbox": "38.2, -69.6, 89.5, -65.8",
@@ -222094,7 +222107,7 @@
{
"id": "adpe-aat-census_1",
"title": "Adelie penguin census from records from 1931 to 2007 AAT region",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1931-02-13",
"end_date": "2006-12-08",
"bbox": "38.2, -69.6, 89.5, -65.8",
@@ -222224,7 +222237,7 @@
{
"id": "aerial_photo_sea_ice_ARISE_1",
"title": "Aerial photographs of sea ice flown by the Australian Antarctic Division on the ARISE voyage in 2003",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2003-09-10",
"end_date": "2003-10-31",
"bbox": "109.1, -66.7, 118.85, -64.03",
@@ -222237,7 +222250,7 @@
{
"id": "aerial_photo_sea_ice_ARISE_1",
"title": "Aerial photographs of sea ice flown by the Australian Antarctic Division on the ARISE voyage in 2003",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-09-10",
"end_date": "2003-10-31",
"bbox": "109.1, -66.7, 118.85, -64.03",
@@ -222250,7 +222263,7 @@
{
"id": "aerial_photo_sea_ice_ISPOL_1",
"title": "Aerial photographs of sea ice flown by the Australian Antarctic Division on the ISPOL voyage in 2004",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2004-11-06",
"end_date": "2005-01-19",
"bbox": "-58.2, -69.67, -55.2, -67.57",
@@ -222263,7 +222276,7 @@
{
"id": "aerial_photo_sea_ice_ISPOL_1",
"title": "Aerial photographs of sea ice flown by the Australian Antarctic Division on the ISPOL voyage in 2004",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-11-06",
"end_date": "2005-01-19",
"bbox": "-58.2, -69.67, -55.2, -67.57",
@@ -222276,7 +222289,7 @@
{
"id": "aerial_photo_sea_ice_SIPEX_1",
"title": "Aerial photographs of sea ice flown by the Australian Antarctic Division on the SIPEX voyage in 2007",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2007-08-29",
"end_date": "2007-10-16",
"bbox": "109.1, -66.7, 118.85, -64.03",
@@ -222289,7 +222302,7 @@
{
"id": "aerial_photo_sea_ice_SIPEX_1",
"title": "Aerial photographs of sea ice flown by the Australian Antarctic Division on the SIPEX voyage in 2007",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-08-29",
"end_date": "2007-10-16",
"bbox": "109.1, -66.7, 118.85, -64.03",
@@ -222315,7 +222328,7 @@
{
"id": "aerial_photographs_from_columbia_glacier_1976-2010",
"title": "Aerial Photographs from Columbia Glacier, 1976-2010",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1976-07-24",
"end_date": "2011-06-15",
"bbox": "-146.895, 61.22, -146.895, 61.22",
@@ -222328,7 +222341,7 @@
{
"id": "aerial_photographs_from_columbia_glacier_1976-2010",
"title": "Aerial Photographs from Columbia Glacier, 1976-2010",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1976-07-24",
"end_date": "2011-06-15",
"bbox": "-146.895, 61.22, -146.895, 61.22",
@@ -222367,7 +222380,7 @@
{
"id": "aerial_surveys_vestfold_2017-18_1",
"title": "Aerial surveys of Davis station and an area of the Vestfold Hills to the north-east of the station 2017/18",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2017-11-19",
"end_date": "2018-01-31",
"bbox": "77.8923, -68.6067, 78.2235, -68.4809",
@@ -222380,7 +222393,7 @@
{
"id": "aerial_surveys_vestfold_2017-18_1",
"title": "Aerial surveys of Davis station and an area of the Vestfold Hills to the north-east of the station 2017/18",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-11-19",
"end_date": "2018-01-31",
"bbox": "77.8923, -68.6067, 78.2235, -68.4809",
@@ -222393,7 +222406,7 @@
{
"id": "aerosol-data-davos-wolfgang_1.0",
"title": "Aerosol Data Davos Wolfgang",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ENVIDAT STAC Catalog",
"state_date": "2020-01-01",
"end_date": "2020-01-01",
"bbox": "9.853594, 46.835577, 9.853594, 46.835577",
@@ -222406,7 +222419,7 @@
{
"id": "aerosol-data-davos-wolfgang_1.0",
"title": "Aerosol Data Davos Wolfgang",
- "catalog": "ENVIDAT STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2020-01-01",
"end_date": "2020-01-01",
"bbox": "9.853594, 46.835577, 9.853594, 46.835577",
@@ -222419,7 +222432,7 @@
{
"id": "aerosol-data-weissfluhjoch_1.0",
"title": "Aerosol Data Weissfluhjoch",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ENVIDAT STAC Catalog",
"state_date": "2020-01-01",
"end_date": "2020-01-01",
"bbox": "9.806475, 46.832964, 9.806475, 46.832964",
@@ -222432,7 +222445,7 @@
{
"id": "aerosol-data-weissfluhjoch_1.0",
"title": "Aerosol Data Weissfluhjoch",
- "catalog": "ENVIDAT STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2020-01-01",
"end_date": "2020-01-01",
"bbox": "9.806475, 46.832964, 9.806475, 46.832964",
@@ -222744,7 +222757,7 @@
{
"id": "air_temperature_observations_in_the_arctic_1979-2004",
"title": "Air Temperature Observations in the Arctic 1979-2004",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1979-01-01",
"end_date": "2005-12-01",
"bbox": "-180, 14.5, 180, 90",
@@ -222757,7 +222770,7 @@
{
"id": "air_temperature_observations_in_the_arctic_1979-2004",
"title": "Air Temperature Observations in the Arctic 1979-2004",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1979-01-01",
"end_date": "2005-12-01",
"bbox": "-180, 14.5, 180, 90",
@@ -222900,7 +222913,7 @@
{
"id": "albedo_line_snow_depths",
"title": "Albedo Line Snow Depths",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2009-04-27",
"end_date": "2009-04-28",
"bbox": "-157, 71, -156, 72",
@@ -222913,7 +222926,7 @@
{
"id": "albedo_line_snow_depths",
"title": "Albedo Line Snow Depths",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2009-04-27",
"end_date": "2009-04-28",
"bbox": "-157, 71, -156, 72",
@@ -223316,7 +223329,7 @@
{
"id": "amsua15sp_1",
"title": "ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "1998-08-03",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -223329,7 +223342,7 @@
{
"id": "amsua15sp_1",
"title": "ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1998-08-03",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -223368,7 +223381,7 @@
{
"id": "amsua17sp_1",
"title": "ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-17",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-07-21",
"end_date": "2003-12-13",
"bbox": "-180, -89.575, 180, 89.629",
@@ -223381,7 +223394,7 @@
{
"id": "amsua17sp_1",
"title": "ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-17",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2002-07-21",
"end_date": "2003-12-13",
"bbox": "-180, -89.575, 180, 89.629",
@@ -223511,7 +223524,7 @@
{
"id": "apr3cpex_1",
"title": "Airborne Precipitation Radar 3rd Generation (APR-3) CPEX",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2017-05-27",
"end_date": "2017-06-24",
"bbox": "-96.0262, 16.8091, -69.2994, 28.9042",
@@ -223524,7 +223537,7 @@
{
"id": "apr3cpex_1",
"title": "Airborne Precipitation Radar 3rd Generation (APR-3) CPEX",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-05-27",
"end_date": "2017-06-24",
"bbox": "-96.0262, 16.8091, -69.2994, 28.9042",
@@ -223537,7 +223550,7 @@
{
"id": "apr3cpexaw_1",
"title": "Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2021-08-20",
"end_date": "2021-09-04",
"bbox": "-80.7804, 11.8615, -45.6417, 34.046",
@@ -223550,7 +223563,7 @@
{
"id": "apr3cpexaw_1",
"title": "Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2021-08-20",
"end_date": "2021-09-04",
"bbox": "-80.7804, 11.8615, -45.6417, 34.046",
@@ -223628,7 +223641,7 @@
{
"id": "asas",
"title": "Advanced Solid-state Array Spectroradiometer (ASAS)",
- "catalog": "USGS_LTA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1988-06-26",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -223641,7 +223654,7 @@
{
"id": "asas",
"title": "Advanced Solid-state Array Spectroradiometer (ASAS)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "USGS_LTA STAC Catalog",
"state_date": "1988-06-26",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -223771,7 +223784,7 @@
{
"id": "aster_1",
"title": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster) satellite image data held by the Australian Antarctic Data Centre",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2000-10-08",
"end_date": "",
"bbox": "-180, -90, 180, -53",
@@ -223784,7 +223797,7 @@
{
"id": "aster_1",
"title": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster) satellite image data held by the Australian Antarctic Data Centre",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2000-10-08",
"end_date": "",
"bbox": "-180, -90, 180, -53",
@@ -224395,7 +224408,7 @@
{
"id": "avapsimpacts_1",
"title": "Advanced Vertical Atmospheric Profiling System Dropsondes (AVAPS) IMPACTS",
- "catalog": "ALL STAC Catalog",
+ "catalog": "GHRC_DAAC STAC Catalog",
"state_date": "2020-01-12",
"end_date": "2023-02-28",
"bbox": "-77.815, 33.54, -65.44, 44.17",
@@ -224408,7 +224421,7 @@
{
"id": "avapsimpacts_1",
"title": "Advanced Vertical Atmospheric Profiling System Dropsondes (AVAPS) IMPACTS",
- "catalog": "GHRC_DAAC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2020-01-12",
"end_date": "2023-02-28",
"bbox": "-77.815, 33.54, -65.44, 44.17",
@@ -224837,7 +224850,7 @@
{
"id": "bech_nest_locations_1",
"title": "Adelie Penguin nest locations on Bechervaise Island",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2000-02-01",
"end_date": "2000-02-22",
"bbox": "62.8084, -67.5879, 62.8152, -67.5863",
@@ -224850,7 +224863,7 @@
{
"id": "bech_nest_locations_1",
"title": "Adelie Penguin nest locations on Bechervaise Island",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2000-02-01",
"end_date": "2000-02-22",
"bbox": "62.8084, -67.5879, 62.8152, -67.5863",
@@ -225513,7 +225526,7 @@
{
"id": "bromwich_0337948_1",
"title": "A 45-Y Hindcast of Antarctic Surface Mass Balance Using Polar MM5",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1979-01-01",
"end_date": "2002-08-31",
"bbox": "-180, -90, 180, -60",
@@ -225526,7 +225539,7 @@
{
"id": "bromwich_0337948_1",
"title": "A 45-Y Hindcast of Antarctic Surface Mass Balance Using Polar MM5",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1979-01-01",
"end_date": "2002-08-31",
"bbox": "-180, -90, 180, -60",
@@ -225747,7 +225760,7 @@
{
"id": "c2d1361c3fcbc6c7b60b35791f7bbc45bf8079dc",
"title": "3 year daily average solar exposure map Mali 3Km GRAS January 2008-2011",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-15, 8, 5, 28",
@@ -225760,7 +225773,7 @@
{
"id": "c2d1361c3fcbc6c7b60b35791f7bbc45bf8079dc",
"title": "3 year daily average solar exposure map Mali 3Km GRAS January 2008-2011",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-15, 8, 5, 28",
@@ -226436,7 +226449,7 @@
{
"id": "capeden_sat_ikonos_1",
"title": "A georeferenced high resolution satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast acquired on 26, 31 January 2001",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2001-01-26",
"end_date": "2001-01-31",
"bbox": "142.5153, -67.0697, 143.03, -66.9478",
@@ -226449,7 +226462,7 @@
{
"id": "capeden_sat_ikonos_1",
"title": "A georeferenced high resolution satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast acquired on 26, 31 January 2001",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2001-01-26",
"end_date": "2001-01-31",
"bbox": "142.5153, -67.0697, 143.03, -66.9478",
@@ -226475,7 +226488,7 @@
{
"id": "casey_alk_clones_1",
"title": "Alkane mono-oxygenase genes from marine sediment near Casey",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2001-12-01",
"end_date": "2001-12-25",
"bbox": "110.3, -66.35, 110.35, -66.3",
@@ -226488,7 +226501,7 @@
{
"id": "casey_alk_clones_1",
"title": "Alkane mono-oxygenase genes from marine sediment near Casey",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2001-12-01",
"end_date": "2001-12-25",
"bbox": "110.3, -66.35, 110.35, -66.3",
@@ -227047,7 +227060,7 @@
{
"id": "climate_pressure_1",
"title": "ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air pressure",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1901-01-01",
"end_date": "1998-12-31",
"bbox": "-180, -80, 180, -17",
@@ -227060,7 +227073,7 @@
{
"id": "climate_pressure_1",
"title": "ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air pressure",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1901-01-01",
"end_date": "1998-12-31",
"bbox": "-180, -80, 180, -17",
@@ -228555,7 +228568,7 @@
{
"id": "doi:10.25921/sta3-3b95_Not Applicable",
"title": "2014-2015 Untrawlable Habitat Strategic Initiative (UHSI) Video and Still Imagery Data Collection",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-09-08",
"end_date": "2015-05-08",
"bbox": "-84.4, 27.7, -83.4, 29.7",
@@ -228568,7 +228581,7 @@
{
"id": "doi:10.25921/sta3-3b95_Not Applicable",
"title": "2014-2015 Untrawlable Habitat Strategic Initiative (UHSI) Video and Still Imagery Data Collection",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2014-09-08",
"end_date": "2015-05-08",
"bbox": "-84.4, 27.7, -83.4, 29.7",
@@ -229114,7 +229127,7 @@
{
"id": "ecousm1",
"title": "A comparative study on floral ecology between Malaysia and Antarctica",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "110.32, -66.28, 110.32, -66.28",
@@ -229127,7 +229140,7 @@
{
"id": "ecousm1",
"title": "A comparative study on floral ecology between Malaysia and Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "110.32, -66.28, 110.32, -66.28",
@@ -229712,7 +229725,7 @@
{
"id": "envidat-lwf-34_2019-03-06",
"title": "10-HS Pfynwald",
- "catalog": "ENVIDAT STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2019-01-01",
"bbox": "7.61211, 46.30279, 7.61211, 46.30279",
@@ -229725,7 +229738,7 @@
{
"id": "envidat-lwf-34_2019-03-06",
"title": "10-HS Pfynwald",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ENVIDAT STAC Catalog",
"state_date": "2019-01-01",
"end_date": "2019-01-01",
"bbox": "7.61211, 46.30279, 7.61211, 46.30279",
@@ -231090,7 +231103,7 @@
{
"id": "fife_AF_dtrnd_nae_3_1",
"title": "Aircraft Flux-Detrended: NRCC (FIFE)",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1987-06-26",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231103,7 +231116,7 @@
{
"id": "fife_AF_dtrnd_nae_3_1",
"title": "Aircraft Flux-Detrended: NRCC (FIFE)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1987-06-26",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231116,7 +231129,7 @@
{
"id": "fife_AF_dtrnd_ncar_5_1",
"title": "Aircraft Flux-Detrended: Univ. Col. (FIFE)",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1987-05-26",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231129,7 +231142,7 @@
{
"id": "fife_AF_dtrnd_ncar_5_1",
"title": "Aircraft Flux-Detrended: Univ. Col. (FIFE)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1987-05-26",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231194,7 +231207,7 @@
{
"id": "fife_AF_filtr_ncar_8_1",
"title": "Aircraft Flux-Filtered: Univ. Col. (FIFE)",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1987-05-26",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231207,7 +231220,7 @@
{
"id": "fife_AF_filtr_ncar_8_1",
"title": "Aircraft Flux-Filtered: Univ. Col. (FIFE)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1987-05-26",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231298,7 +231311,7 @@
{
"id": "fife_AF_raw_wyo_10_1",
"title": "Aircraft Flux-Raw: U of Wy. (FIFE)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1987-08-11",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231311,7 +231324,7 @@
{
"id": "fife_AF_raw_wyo_10_1",
"title": "Aircraft Flux-Raw: U of Wy. (FIFE)",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1987-08-11",
"end_date": "1989-10-31",
"bbox": "-102, 37, -95, 40",
@@ -231649,7 +231662,7 @@
{
"id": "fife_hydrology_strm_15m_1_1",
"title": "15 Minute Stream Flow Data: USGS (FIFE)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1984-12-25",
"end_date": "1988-03-04",
"bbox": "-96.6, 39.1, -96.6, 39.1",
@@ -231662,7 +231675,7 @@
{
"id": "fife_hydrology_strm_15m_1_1",
"title": "15 Minute Stream Flow Data: USGS (FIFE)",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1984-12-25",
"end_date": "1988-03-04",
"bbox": "-96.6, 39.1, -96.6, 39.1",
@@ -232221,7 +232234,7 @@
{
"id": "fife_sur_met_rain_30m_2_1",
"title": "30 Minute Rainfall Data (FIFE)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "ORNL_CLOUD STAC Catalog",
"state_date": "1987-05-29",
"end_date": "1987-10-26",
"bbox": "-96.6, 39.08, -96.55, 39.11",
@@ -232234,7 +232247,7 @@
{
"id": "fife_sur_met_rain_30m_2_1",
"title": "30 Minute Rainfall Data (FIFE)",
- "catalog": "ORNL_CLOUD STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1987-05-29",
"end_date": "1987-10-26",
"bbox": "-96.6, 39.08, -96.55, 39.11",
@@ -232650,7 +232663,7 @@
{
"id": "foraging_trip_duration_BI_1",
"title": "Adelie penguin foraging trip duration, Bechervaise Island, Mawson",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1991-10-01",
"end_date": "2005-02-01",
"bbox": "62.8055, -67.5916, 62.825, -67.5861",
@@ -232663,7 +232676,7 @@
{
"id": "foraging_trip_duration_BI_1",
"title": "Adelie penguin foraging trip duration, Bechervaise Island, Mawson",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1991-10-01",
"end_date": "2005-02-01",
"bbox": "62.8055, -67.5916, 62.825, -67.5861",
@@ -237044,7 +237057,7 @@
{
"id": "geodata_2217",
"title": "Agricultural Area Certified Organic",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-01-01",
"end_date": "2008-12-31",
"bbox": "-180, -90, 180, -60.5033",
@@ -237057,7 +237070,7 @@
{
"id": "geodata_2217",
"title": "Agricultural Area Certified Organic",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "2003-01-01",
"end_date": "2008-12-31",
"bbox": "-180, -90, 180, -60.5033",
@@ -238760,7 +238773,7 @@
{
"id": "gov.noaa.ncdc:C01598_Beta4",
"title": "Adaptive Ecosystem Climatology Beta 4 Model and Satellite Climatology",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1980-01-01",
"end_date": "2012-12-31",
"bbox": "-98, 18.091, -77.36, 30.73",
@@ -238773,7 +238786,7 @@
{
"id": "gov.noaa.ncdc:C01598_Beta4",
"title": "Adaptive Ecosystem Climatology Beta 4 Model and Satellite Climatology",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1980-01-01",
"end_date": "2012-12-31",
"bbox": "-98, 18.091, -77.36, 30.73",
@@ -238994,7 +239007,7 @@
{
"id": "gov.noaa.nodc:0000015_Not Applicable",
"title": "Alkalinity, dissolved oxygen, nutrients, pH, phosphate, salinity, silicate, and temperature collected by bottle from multiple cruises in the Southern Oceans from 1/15/1958 - 3/2/1990 (NCEI Accession 0000015)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1958-01-15",
"end_date": "1990-03-02",
"bbox": "6.05, -70.233333, -47.033333, -26.05",
@@ -239007,7 +239020,7 @@
{
"id": "gov.noaa.nodc:0000015_Not Applicable",
"title": "Alkalinity, dissolved oxygen, nutrients, pH, phosphate, salinity, silicate, and temperature collected by bottle from multiple cruises in the Southern Oceans from 1/15/1958 - 3/2/1990 (NCEI Accession 0000015)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1958-01-15",
"end_date": "1990-03-02",
"bbox": "6.05, -70.233333, -47.033333, -26.05",
@@ -239033,7 +239046,7 @@
{
"id": "gov.noaa.nodc:0000029_Not Applicable",
"title": "1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1990-09-26",
"end_date": "1995-05-26",
"bbox": "-124.041667, 0.766667, -16.25, 46.263167",
@@ -239046,7 +239059,7 @@
{
"id": "gov.noaa.nodc:0000029_Not Applicable",
"title": "1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-09-26",
"end_date": "1995-05-26",
"bbox": "-124.041667, 0.766667, -16.25, 46.263167",
@@ -239085,7 +239098,7 @@
{
"id": "gov.noaa.nodc:0000052_Not Applicable",
"title": "1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1988-03-01",
"end_date": "1988-06-28",
"bbox": "-149.4083, 59.9117, -149.3583, 60.02",
@@ -239098,7 +239111,7 @@
{
"id": "gov.noaa.nodc:0000052_Not Applicable",
"title": "1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1988-03-01",
"end_date": "1988-06-28",
"bbox": "-149.4083, 59.9117, -149.3583, 60.02",
@@ -239475,7 +239488,7 @@
{
"id": "gov.noaa.nodc:0000599_Not Applicable",
"title": "Aids to Navigation (ATONS) GIS data from the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas as of 1999-10-21 (NCEI Accession 0000599)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-01-01",
"end_date": "1999-10-21",
"bbox": "-98.320706, 17.398031, -61.876841, 32.288483",
@@ -239488,7 +239501,7 @@
{
"id": "gov.noaa.nodc:0000599_Not Applicable",
"title": "Aids to Navigation (ATONS) GIS data from the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas as of 1999-10-21 (NCEI Accession 0000599)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1999-01-01",
"end_date": "1999-10-21",
"bbox": "-98.320706, 17.398031, -61.876841, 32.288483",
@@ -239592,7 +239605,7 @@
{
"id": "gov.noaa.nodc:0000794_Not Applicable",
"title": "A survey of selected coral and fish assemblages near the Waianae Ocean Outfall, Oahu, Hawaii, 1990-1999 (NCEI Accession 0000794)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1990-10-01",
"end_date": "1999-08-31",
"bbox": "-158.28, 21.41, -158.26, 21.43",
@@ -239605,7 +239618,7 @@
{
"id": "gov.noaa.nodc:0000794_Not Applicable",
"title": "A survey of selected coral and fish assemblages near the Waianae Ocean Outfall, Oahu, Hawaii, 1990-1999 (NCEI Accession 0000794)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1990-10-01",
"end_date": "1999-08-31",
"bbox": "-158.28, 21.41, -158.26, 21.43",
@@ -239670,7 +239683,7 @@
{
"id": "gov.noaa.nodc:0000879_Not Applicable",
"title": "Abundance data acquired in support of invasive species distribution studies at ten macroalgal ecology and taxonomic assessment sites in Hawaii during 2001 (NCEI Accession 0000879)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2001-01-26",
"end_date": "2001-05-18",
"bbox": "-158.14, 19.27, -155.05, 21.37",
@@ -239683,7 +239696,7 @@
{
"id": "gov.noaa.nodc:0000879_Not Applicable",
"title": "Abundance data acquired in support of invasive species distribution studies at ten macroalgal ecology and taxonomic assessment sites in Hawaii during 2001 (NCEI Accession 0000879)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2001-01-26",
"end_date": "2001-05-18",
"bbox": "-158.14, 19.27, -155.05, 21.37",
@@ -239930,7 +239943,7 @@
{
"id": "gov.noaa.nodc:0001746_Not Applicable",
"title": "ALINE time series (NCEI Accession 0001746)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1989-01-01",
"end_date": "2001-01-01",
"bbox": "141, 37, 150, 44",
@@ -239943,7 +239956,7 @@
{
"id": "gov.noaa.nodc:0001746_Not Applicable",
"title": "ALINE time series (NCEI Accession 0001746)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1989-01-01",
"end_date": "2001-01-01",
"bbox": "141, 37, 150, 44",
@@ -239969,7 +239982,7 @@
{
"id": "gov.noaa.nodc:0001941_Not Applicable",
"title": "Aerial surveys of bowhead and beluga whales along with incidental sighting of other marine mammals in the Bering, Beaufort and Chukchi Seas for the Bowhead Whale Aerial Survey Project (BWASP), 1979 - 2004 (NCEI Accession 0001941)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1979-04-01",
"end_date": "2004-10-18",
"bbox": "-174.01, 57.72, -125.25, 76.14",
@@ -239982,7 +239995,7 @@
{
"id": "gov.noaa.nodc:0001941_Not Applicable",
"title": "Aerial surveys of bowhead and beluga whales along with incidental sighting of other marine mammals in the Bering, Beaufort and Chukchi Seas for the Bowhead Whale Aerial Survey Project (BWASP), 1979 - 2004 (NCEI Accession 0001941)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1979-04-01",
"end_date": "2004-10-18",
"bbox": "-174.01, 57.72, -125.25, 76.14",
@@ -239995,7 +240008,7 @@
{
"id": "gov.noaa.nodc:0002013_Not Applicable",
"title": "A mesoscale hydrographic survey off Northwest Africa to examine the horizontal mixing by eddies, March - April 2003 (NCEI Accession 0002013)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-03-26",
"end_date": "2003-04-16",
"bbox": "-31.5, 6.6, -25, 11",
@@ -240008,7 +240021,7 @@
{
"id": "gov.noaa.nodc:0002013_Not Applicable",
"title": "A mesoscale hydrographic survey off Northwest Africa to examine the horizontal mixing by eddies, March - April 2003 (NCEI Accession 0002013)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2003-03-26",
"end_date": "2003-04-16",
"bbox": "-31.5, 6.6, -25, 11",
@@ -240047,7 +240060,7 @@
{
"id": "gov.noaa.nodc:0002192_Not Applicable",
"title": "A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico from 1999 to 2002 (NCEI Accession 0002192)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1999-09-01",
"end_date": "2002-08-25",
"bbox": "-96.01, 23.49, -85.47, 29.38",
@@ -240060,7 +240073,7 @@
{
"id": "gov.noaa.nodc:0002192_Not Applicable",
"title": "A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico from 1999 to 2002 (NCEI Accession 0002192)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-09-01",
"end_date": "2002-08-25",
"bbox": "-96.01, 23.49, -85.47, 29.38",
@@ -240099,7 +240112,7 @@
{
"id": "gov.noaa.nodc:0002196_Not Applicable",
"title": "Acoustic doppler current meter data collected in support of the Minerals Management Service-supported Deep Water Program in the the Gulf of Mexico, 1999 - 2003 (NCEI Accession 0002196)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-09-01",
"end_date": "2003-08-01",
"bbox": "-96, 23.47, -85.47, 29.33",
@@ -240112,7 +240125,7 @@
{
"id": "gov.noaa.nodc:0002196_Not Applicable",
"title": "Acoustic doppler current meter data collected in support of the Minerals Management Service-supported Deep Water Program in the the Gulf of Mexico, 1999 - 2003 (NCEI Accession 0002196)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1999-09-01",
"end_date": "2003-08-01",
"bbox": "-96, 23.47, -85.47, 29.33",
@@ -240177,7 +240190,7 @@
{
"id": "gov.noaa.nodc:0002295_Not Applicable",
"title": "A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002295)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1999-09-01",
"end_date": "2002-08-20",
"bbox": "-92.01, 23.79, -85.49, 25.49",
@@ -240190,7 +240203,7 @@
{
"id": "gov.noaa.nodc:0002295_Not Applicable",
"title": "A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002295)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-09-01",
"end_date": "2002-08-20",
"bbox": "-92.01, 23.79, -85.49, 25.49",
@@ -240255,7 +240268,7 @@
{
"id": "gov.noaa.nodc:0002650_Not Applicable",
"title": "A survey of the marine biota of the island of Lanai, Hawaii, to determine the presence and impact of marine non-indigenous and cryptogenic species, February - March 2005 (NCEI Accession 0002650)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2005-02-28",
"end_date": "2005-03-04",
"bbox": "-157.05, 20.73, -156.88, 20.92",
@@ -240268,7 +240281,7 @@
{
"id": "gov.noaa.nodc:0002650_Not Applicable",
"title": "A survey of the marine biota of the island of Lanai, Hawaii, to determine the presence and impact of marine non-indigenous and cryptogenic species, February - March 2005 (NCEI Accession 0002650)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-02-28",
"end_date": "2005-03-04",
"bbox": "-157.05, 20.73, -156.88, 20.92",
@@ -240424,7 +240437,7 @@
{
"id": "gov.noaa.nodc:0046934_Not Applicable",
"title": "Acropora Spatial Survey Data of the Upper Florida Keys National Marine Sanctuary, 2005 - 2007 (NCEI Accession 0046934)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2005-01-01",
"end_date": "2007-12-31",
"bbox": "-81.41079, 24.54466, -80.19632, 25.29129",
@@ -240437,7 +240450,7 @@
{
"id": "gov.noaa.nodc:0046934_Not Applicable",
"title": "Acropora Spatial Survey Data of the Upper Florida Keys National Marine Sanctuary, 2005 - 2007 (NCEI Accession 0046934)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-01-01",
"end_date": "2007-12-31",
"bbox": "-81.41079, 24.54466, -80.19632, 25.29129",
@@ -240541,7 +240554,7 @@
{
"id": "gov.noaa.nodc:0061208_Not Applicable",
"title": "Algal, coral, and other data collected by ROV and scuba diver videography from M.V. FLING and M.V. SPREE for Post-Hurricane Assessment of Sensitive Habitats of the Flower Garden Banks Vicinity project from November 13, 2005 to June 23, 2007 (NCEI Accession 0061208)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-11-13",
"end_date": "2007-05-23",
"bbox": "-93.58, 27.85, -92.45, 28.3",
@@ -240554,7 +240567,7 @@
{
"id": "gov.noaa.nodc:0061208_Not Applicable",
"title": "Algal, coral, and other data collected by ROV and scuba diver videography from M.V. FLING and M.V. SPREE for Post-Hurricane Assessment of Sensitive Habitats of the Flower Garden Banks Vicinity project from November 13, 2005 to June 23, 2007 (NCEI Accession 0061208)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2005-11-13",
"end_date": "2007-05-23",
"bbox": "-93.58, 27.85, -92.45, 28.3",
@@ -242504,7 +242517,7 @@
{
"id": "gov.noaa.nodc:0125597_Not Applicable",
"title": "Acoustic travel time, bottom pressure, and near bottom current velocities from inverted echo sounders in the Atlantic Ocean from 2004-09-27 to 2016-02-25 (NCEI Accession 0125597)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-09-27",
"end_date": "2016-02-25",
"bbox": "-76.84, 26.491, -72.004, 26.516",
@@ -242517,7 +242530,7 @@
{
"id": "gov.noaa.nodc:0125597_Not Applicable",
"title": "Acoustic travel time, bottom pressure, and near bottom current velocities from inverted echo sounders in the Atlantic Ocean from 2004-09-27 to 2016-02-25 (NCEI Accession 0125597)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2004-09-27",
"end_date": "2016-02-25",
"bbox": "-76.84, 26.491, -72.004, 26.516",
@@ -242595,7 +242608,7 @@
{
"id": "gov.noaa.nodc:0130929_Not Applicable",
"title": "AFSC/REFM: Isolation by distance (IBD) Alaskan fish stock structure modeling (NCEI Accession 0130929)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1980-01-01",
"end_date": "2012-01-01",
"bbox": "170, 50, -160, 62",
@@ -242608,7 +242621,7 @@
{
"id": "gov.noaa.nodc:0130929_Not Applicable",
"title": "AFSC/REFM: Isolation by distance (IBD) Alaskan fish stock structure modeling (NCEI Accession 0130929)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1980-01-01",
"end_date": "2012-01-01",
"bbox": "170, 50, -160, 62",
@@ -242699,7 +242712,7 @@
{
"id": "gov.noaa.nodc:0138863_Not Applicable",
"title": "Acoustics short-term passive monitoring using sonobuoys in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-01 to 2015-09-28 (NCEI Accession 0138863)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2007-08-01",
"end_date": "2015-09-28",
"bbox": "-177.5925, 53.52167, -141.62497, 72.86938",
@@ -242712,7 +242725,7 @@
{
"id": "gov.noaa.nodc:0138863_Not Applicable",
"title": "Acoustics short-term passive monitoring using sonobuoys in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-01 to 2015-09-28 (NCEI Accession 0138863)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-08-01",
"end_date": "2015-09-28",
"bbox": "-177.5925, 53.52167, -141.62497, 72.86938",
@@ -242751,7 +242764,7 @@
{
"id": "gov.noaa.nodc:0143303_Not Applicable",
"title": "Acoustics long-term passive monitoring using moored autonomous recorders in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-15 to 2015-04-30 (NCEI Accession 0143303)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2007-08-15",
"end_date": "2015-04-30",
"bbox": "171.7, 53.63, -0.78, 78.837",
@@ -242764,7 +242777,7 @@
{
"id": "gov.noaa.nodc:0143303_Not Applicable",
"title": "Acoustics long-term passive monitoring using moored autonomous recorders in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-15 to 2015-04-30 (NCEI Accession 0143303)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2007-08-15",
"end_date": "2015-04-30",
"bbox": "171.7, 53.63, -0.78, 78.837",
@@ -242855,7 +242868,7 @@
{
"id": "gov.noaa.nodc:0148759_Not Applicable",
"title": "AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Helheim Glacier Ice Front from 2009-08-11 to 2016-02-20 (NCEI Accession 0148759)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2009-08-11",
"end_date": "2016-02-20",
"bbox": "-38.146, 66.329, -38.146, 66.329",
@@ -242868,7 +242881,7 @@
{
"id": "gov.noaa.nodc:0148759_Not Applicable",
"title": "AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Helheim Glacier Ice Front from 2009-08-11 to 2016-02-20 (NCEI Accession 0148759)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2009-08-11",
"end_date": "2016-02-20",
"bbox": "-38.146, 66.329, -38.146, 66.329",
@@ -242959,7 +242972,7 @@
{
"id": "gov.noaa.nodc:0156424_Not Applicable",
"title": "Absolute Geostrophic Velocity Inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156424)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1950-01-01",
"end_date": "1996-12-31",
"bbox": "-180, 58, 180, 90",
@@ -242972,7 +242985,7 @@
{
"id": "gov.noaa.nodc:0156424_Not Applicable",
"title": "Absolute Geostrophic Velocity Inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156424)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1950-01-01",
"end_date": "1996-12-31",
"bbox": "-180, 58, 180, 90",
@@ -243102,7 +243115,7 @@
{
"id": "gov.noaa.nodc:0157074_Not Applicable",
"title": "ACOUSTIC TRAVEL TIME collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) from March 1995 to March 1997 (NCEI Accession 0157074)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1995-03-20",
"end_date": "1997-03-28",
"bbox": "143.63333, -52.08133, 143.805, -47.99867",
@@ -243115,7 +243128,7 @@
{
"id": "gov.noaa.nodc:0157074_Not Applicable",
"title": "ACOUSTIC TRAVEL TIME collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) from March 1995 to March 1997 (NCEI Accession 0157074)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1995-03-20",
"end_date": "1997-03-28",
"bbox": "143.63333, -52.08133, 143.805, -47.99867",
@@ -243219,7 +243232,7 @@
{
"id": "gov.noaa.nodc:0161311_Not Applicable",
"title": "A Comprehensive Inventory of Alabama Coastal Zone Wetland Habitats (Swamps, Marshes, Submersed Grassbeds) from 1980 to 1982 (NCEI Accession 0161311)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1979-01-01",
"end_date": "1982-12-31",
"bbox": "-88.431, 30.2129, -87.328, 31.0701",
@@ -243232,7 +243245,7 @@
{
"id": "gov.noaa.nodc:0161311_Not Applicable",
"title": "A Comprehensive Inventory of Alabama Coastal Zone Wetland Habitats (Swamps, Marshes, Submersed Grassbeds) from 1980 to 1982 (NCEI Accession 0161311)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1979-01-01",
"end_date": "1982-12-31",
"bbox": "-88.431, 30.2129, -87.328, 31.0701",
@@ -243895,7 +243908,7 @@
{
"id": "gov.noaa.nodc:0172043_Not Applicable",
"title": "ADCP, CTD, and continuous data from the Multiple Instrument Data Acquisition System (MIDAS) collected in the Southeast of the Mississippi River Delta aboard the R/V Pelican from 2012-11-28 to 2012-12-19 (NCEI Accession 0172043)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2012-11-28",
"end_date": "2012-12-19",
"bbox": "-94.0863, 25.7961, -87.2228, 28.9733",
@@ -243908,7 +243921,7 @@
{
"id": "gov.noaa.nodc:0172043_Not Applicable",
"title": "ADCP, CTD, and continuous data from the Multiple Instrument Data Acquisition System (MIDAS) collected in the Southeast of the Mississippi River Delta aboard the R/V Pelican from 2012-11-28 to 2012-12-19 (NCEI Accession 0172043)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2012-11-28",
"end_date": "2012-12-19",
"bbox": "-94.0863, 25.7961, -87.2228, 28.9733",
@@ -243921,7 +243934,7 @@
{
"id": "gov.noaa.nodc:0172377_Not Applicable",
"title": "Abundance and biomass of parrotfishes (Labridae, Scarinae) in St.Croix, U.S. Virgin Islands 2015 to 2016 (NCEI Accession 0172377)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2015-07-21",
"end_date": "2016-08-05",
"bbox": "-64.9199, 17.63764, -64.47889, 17.82709",
@@ -243934,7 +243947,7 @@
{
"id": "gov.noaa.nodc:0172377_Not Applicable",
"title": "Abundance and biomass of parrotfishes (Labridae, Scarinae) in St.Croix, U.S. Virgin Islands 2015 to 2016 (NCEI Accession 0172377)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2015-07-21",
"end_date": "2016-08-05",
"bbox": "-64.9199, 17.63764, -64.47889, 17.82709",
@@ -244012,7 +244025,7 @@
{
"id": "gov.noaa.nodc:0175745_Not Applicable",
"title": "Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2011-07-07 to 2016-10-29 (NCEI Accession 0175745)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2011-07-07",
"end_date": "2016-10-29",
"bbox": "-51.5, -34.503, -44.5, -34.5",
@@ -244025,7 +244038,7 @@
{
"id": "gov.noaa.nodc:0175745_Not Applicable",
"title": "Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2011-07-07 to 2016-10-29 (NCEI Accession 0175745)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2011-07-07",
"end_date": "2016-10-29",
"bbox": "-51.5, -34.503, -44.5, -34.5",
@@ -244038,7 +244051,7 @@
{
"id": "gov.noaa.nodc:0175783_Not Applicable",
"title": "Agulhas Current transport derived from satellite altimetry observations in Indian Ocean from 1992-10-14 to 2016-12-28 (NCEI Accession 0175783)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1992-10-14",
"end_date": "2016-12-28",
"bbox": "27, -40, 30, -34",
@@ -244051,7 +244064,7 @@
{
"id": "gov.noaa.nodc:0175783_Not Applicable",
"title": "Agulhas Current transport derived from satellite altimetry observations in Indian Ocean from 1992-10-14 to 2016-12-28 (NCEI Accession 0175783)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1992-10-14",
"end_date": "2016-12-28",
"bbox": "27, -40, 30, -34",
@@ -244155,7 +244168,7 @@
{
"id": "gov.noaa.nodc:0186561_Not Applicable",
"title": "2003 Marine Fisheries Initiative (MARFIN) Gulf of Mexico and South Atlantic angler survey (NCEI Accession 0186561)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-01-01",
"end_date": "2003-12-31",
"bbox": "-98, 25, -80, 31",
@@ -244168,7 +244181,7 @@
{
"id": "gov.noaa.nodc:0186561_Not Applicable",
"title": "2003 Marine Fisheries Initiative (MARFIN) Gulf of Mexico and South Atlantic angler survey (NCEI Accession 0186561)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2003-01-01",
"end_date": "2003-12-31",
"bbox": "-98, 25, -80, 31",
@@ -244194,7 +244207,7 @@
{
"id": "gov.noaa.nodc:0194300_Not Applicable",
"title": "ADCP, CTD, water and sediment chemistry, and underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24 (NCEI Accession 0194300)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2012-04-11",
"end_date": "2012-04-24",
"bbox": "-90.5895, 27.2111, -87.42629, 30.35717",
@@ -244207,7 +244220,7 @@
{
"id": "gov.noaa.nodc:0194300_Not Applicable",
"title": "ADCP, CTD, water and sediment chemistry, and underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24 (NCEI Accession 0194300)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2012-04-11",
"end_date": "2012-04-24",
"bbox": "-90.5895, 27.2111, -87.42629, 30.35717",
@@ -244480,7 +244493,7 @@
{
"id": "gov.noaa.nodc:0210577_Not Applicable",
"title": "Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from 2014-07-15 to 2018-11-11 (NCEI Accession 0210577)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2014-07-15",
"end_date": "2018-11-11",
"bbox": "-162, 11, -50, 43",
@@ -244493,7 +244506,7 @@
{
"id": "gov.noaa.nodc:0210577_Not Applicable",
"title": "Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from 2014-07-15 to 2018-11-11 (NCEI Accession 0210577)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2014-07-15",
"end_date": "2018-11-11",
"bbox": "-162, 11, -50, 43",
@@ -244558,7 +244571,7 @@
{
"id": "gov.noaa.nodc:0221188_Not Applicable",
"title": "3-dimensional current velocity and other parameters taken by ADCP from the offshore supply ship Gerry Bordelon in Gulf of Mexico on 2017-09-24 (NCEI Accession 0221188)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2017-09-24",
"end_date": "2017-09-24",
"bbox": "-88.974, 28.932, -88.965, 28.944",
@@ -244571,7 +244584,7 @@
{
"id": "gov.noaa.nodc:0221188_Not Applicable",
"title": "3-dimensional current velocity and other parameters taken by ADCP from the offshore supply ship Gerry Bordelon in Gulf of Mexico on 2017-09-24 (NCEI Accession 0221188)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "2017-09-24",
"end_date": "2017-09-24",
"bbox": "-88.974, 28.932, -88.965, 28.944",
@@ -244805,7 +244818,7 @@
{
"id": "gov.noaa.nodc:7000422_Not Applicable",
"title": "AIR PRESSURE and Other Data from GOSNOLD From NW Atlantic (limit-40 W) from 1969-10-28 to 1969-10-29 (NCEI Accession 7000422)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1969-10-28",
"end_date": "1969-10-29",
"bbox": "-72, 39, -71, 40",
@@ -244818,7 +244831,7 @@
{
"id": "gov.noaa.nodc:7000422_Not Applicable",
"title": "AIR PRESSURE and Other Data from GOSNOLD From NW Atlantic (limit-40 W) from 1969-10-28 to 1969-10-29 (NCEI Accession 7000422)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1969-10-28",
"end_date": "1969-10-29",
"bbox": "-72, 39, -71, 40",
@@ -244831,7 +244844,7 @@
{
"id": "gov.noaa.nodc:7000981_Not Applicable",
"title": "A summary of seawater chemistry analysis of stations in North Atlantic Ocean from 1970-06-20 to 1970-07-03 (NCEI Accession 7000981)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1970-06-01",
"end_date": "1970-07-01",
"bbox": "-29.33, 50.01, -14.2, 55.56",
@@ -244844,7 +244857,7 @@
{
"id": "gov.noaa.nodc:7000981_Not Applicable",
"title": "A summary of seawater chemistry analysis of stations in North Atlantic Ocean from 1970-06-20 to 1970-07-03 (NCEI Accession 7000981)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-06-01",
"end_date": "1970-07-01",
"bbox": "-29.33, 50.01, -14.2, 55.56",
@@ -244961,7 +244974,7 @@
{
"id": "gov.noaa.nodc:7200320_Not Applicable",
"title": "AIR PRESSURE and Other Data from UNKNOWN PLATFORMS and Other Platforms from 1955-03-01 to 1970-08-13 (NCEI Accession 7200320)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1955-03-01",
"end_date": "1970-08-13",
"bbox": "-71.9, 29.4, 8.8, 65.6",
@@ -244974,7 +244987,7 @@
{
"id": "gov.noaa.nodc:7200320_Not Applicable",
"title": "AIR PRESSURE and Other Data from UNKNOWN PLATFORMS and Other Platforms from 1955-03-01 to 1970-08-13 (NCEI Accession 7200320)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1955-03-01",
"end_date": "1970-08-13",
"bbox": "-71.9, 29.4, 8.8, 65.6",
@@ -245299,7 +245312,7 @@
{
"id": "gov.noaa.nodc:7601613_Not Applicable",
"title": "AIR PRESSURE and Other Data from TIDE STATIONS From North American Coastline-North and Others from 1972-01-01 to 1974-06-30 (NCEI Accession 7601613)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1972-01-01",
"end_date": "1974-06-30",
"bbox": "-77, 37, -76, 39",
@@ -245312,7 +245325,7 @@
{
"id": "gov.noaa.nodc:7601613_Not Applicable",
"title": "AIR PRESSURE and Other Data from TIDE STATIONS From North American Coastline-North and Others from 1972-01-01 to 1974-06-30 (NCEI Accession 7601613)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1972-01-01",
"end_date": "1974-06-30",
"bbox": "-77, 37, -76, 39",
@@ -249004,7 +249017,7 @@
{
"id": "gov.noaa.nodc:9600025_Not Applicable",
"title": "AIR PRESSURE and Other Data from SHI YAN 3 From Antarctic and Others from 1992-11-09 to 1993-02-24 (NCEI Accession 9600025)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1992-11-09",
"end_date": "1993-02-24",
"bbox": "158, -2, 158, -2",
@@ -249017,7 +249030,7 @@
{
"id": "gov.noaa.nodc:9600025_Not Applicable",
"title": "AIR PRESSURE and Other Data from SHI YAN 3 From Antarctic and Others from 1992-11-09 to 1993-02-24 (NCEI Accession 9600025)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1992-11-09",
"end_date": "1993-02-24",
"bbox": "158, -2, 158, -2",
@@ -249446,7 +249459,7 @@
{
"id": "gov.noaa.nodc:9800197_Not Applicable",
"title": "Algal species and other data collected using photographs in the southern coast of the island of Ofu from 1992-09-08 to 1992-09-11 (NCEI Accession 9800197)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1992-09-08",
"end_date": "1992-09-11",
"bbox": "-169.7, -14.2, -169.7, -14.2",
@@ -249459,7 +249472,7 @@
{
"id": "gov.noaa.nodc:9800197_Not Applicable",
"title": "Algal species and other data collected using photographs in the southern coast of the island of Ofu from 1992-09-08 to 1992-09-11 (NCEI Accession 9800197)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1992-09-08",
"end_date": "1992-09-11",
"bbox": "-169.7, -14.2, -169.7, -14.2",
@@ -249524,7 +249537,7 @@
{
"id": "gov.noaa.nodc:9900022_Not Applicable",
"title": "AIR PRESSURE and Other Data from FIXED PLATFORM and Other Platforms from 1998-08-01 to 1998-12-31 (NCEI Accession 9900022)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1998-08-01",
"end_date": "1998-12-31",
"bbox": "-124.1, 44.6, -124, 44.8",
@@ -249537,7 +249550,7 @@
{
"id": "gov.noaa.nodc:9900022_Not Applicable",
"title": "AIR PRESSURE and Other Data from FIXED PLATFORM and Other Platforms from 1998-08-01 to 1998-12-31 (NCEI Accession 9900022)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1998-08-01",
"end_date": "1998-12-31",
"bbox": "-124.1, 44.6, -124, 44.8",
@@ -249550,7 +249563,7 @@
{
"id": "gov.noaa.nodc:9900054_Not Applicable",
"title": "Algal species and other data collected using photographs in the South Pacific Ocean from 1992-01-02 to 1992-12-31 (NCEI Accession 9900054)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1992-01-02",
"end_date": "1992-12-31",
"bbox": "-170.8, -14.4, -170.6, -14.3",
@@ -249563,7 +249576,7 @@
{
"id": "gov.noaa.nodc:9900054_Not Applicable",
"title": "Algal species and other data collected using photographs in the South Pacific Ocean from 1992-01-02 to 1992-12-31 (NCEI Accession 9900054)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1992-01-02",
"end_date": "1992-12-31",
"bbox": "-170.8, -14.4, -170.6, -14.3",
@@ -249576,7 +249589,7 @@
{
"id": "gov.noaa.nodc:9900094_Not Applicable",
"title": "AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-01-01 to 1999-04-29 (NCEI Accession 9900094)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "NOAA_NCEI STAC Catalog",
"state_date": "1999-01-01",
"end_date": "1999-04-29",
"bbox": "-124, 44.6, -124, 44.6",
@@ -249589,7 +249602,7 @@
{
"id": "gov.noaa.nodc:9900094_Not Applicable",
"title": "AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-01-01 to 1999-04-29 (NCEI Accession 9900094)",
- "catalog": "NOAA_NCEI STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-01-01",
"end_date": "1999-04-29",
"bbox": "-124, 44.6, -124, 44.6",
@@ -255296,7 +255309,7 @@
{
"id": "heard_dem_terrasar_1",
"title": "A Digital Elevation Model of Heard Island derived from TerraSAR satellite imagery",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2009-10-31",
"end_date": "2009-11-14",
"bbox": "73.185, -53.266, 74.02, -52.931",
@@ -255309,7 +255322,7 @@
{
"id": "heard_dem_terrasar_1",
"title": "A Digital Elevation Model of Heard Island derived from TerraSAR satellite imagery",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2009-10-31",
"end_date": "2009-11-14",
"bbox": "73.185, -53.266, 74.02, -52.931",
@@ -256427,7 +256440,7 @@
{
"id": "insects_subsaharanAfrica",
"title": "A Checklist of the Insects of Subsaharan Africa",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2000-01-01",
"end_date": "",
"bbox": "13.68, -35.9, 33.98, -21.27",
@@ -256440,7 +256453,7 @@
{
"id": "insects_subsaharanAfrica",
"title": "A Checklist of the Insects of Subsaharan Africa",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2000-01-01",
"end_date": "",
"bbox": "13.68, -35.9, 33.98, -21.27",
@@ -257883,7 +257896,7 @@
{
"id": "law_dome_700yr_ion_chem_2",
"title": "700 Years of Ice Core Major Ion Chemistry Data from Law Dome, Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1988-01-01",
"end_date": "2000-03-06",
"bbox": "112.8, -66.76, 112.86, -66.7",
@@ -257896,7 +257909,7 @@
{
"id": "law_dome_700yr_ion_chem_2",
"title": "700 Years of Ice Core Major Ion Chemistry Data from Law Dome, Antarctica",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1988-01-01",
"end_date": "2000-03-06",
"bbox": "112.8, -66.76, 112.86, -66.7",
@@ -258039,7 +258052,7 @@
{
"id": "lawdome_1979_field_data_1",
"title": "Accumulation, Air Temperature, Barometric Pressure and Magnetic Readings from Law Dome and Wilkes Land, 1979",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1979-01-01",
"end_date": "1979-12-31",
"bbox": "110, -68, 115, -65",
@@ -258052,7 +258065,7 @@
{
"id": "lawdome_1979_field_data_1",
"title": "Accumulation, Air Temperature, Barometric Pressure and Magnetic Readings from Law Dome and Wilkes Land, 1979",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1979-01-01",
"end_date": "1979-12-31",
"bbox": "110, -68, 115, -65",
@@ -259651,7 +259664,7 @@
{
"id": "macquarie_taspaws_grid_1",
"title": "A grid system used by the Parks and Wildlife Service, Tasmania, for Macquarie Island, 1974 to June 2001",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1974-01-01",
"end_date": "2001-06-02",
"bbox": "158.7322, -54.8011, 158.9781, -54.4714",
@@ -259664,7 +259677,7 @@
{
"id": "macquarie_taspaws_grid_1",
"title": "A grid system used by the Parks and Wildlife Service, Tasmania, for Macquarie Island, 1974 to June 2001",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1974-01-01",
"end_date": "2001-06-02",
"bbox": "158.7322, -54.8011, 158.9781, -54.4714",
@@ -260067,7 +260080,7 @@
{
"id": "mbs_wilhelm_msa_hooh_1",
"title": "15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1984-01-01",
"end_date": "1998-12-31",
"bbox": "86.082, -69.13, 86.084, -69.12",
@@ -260080,7 +260093,7 @@
{
"id": "mbs_wilhelm_msa_hooh_1",
"title": "15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS)",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1984-01-01",
"end_date": "1998-12-31",
"bbox": "86.082, -69.13, 86.084, -69.12",
@@ -260093,7 +260106,7 @@
{
"id": "mcdonald_dem_may2012_1",
"title": "A Digital Elevation Model of McDonald Island derived from GeoEye-1 stereo imagery captured 19 May 2012",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2012-05-19",
"end_date": "2012-05-19",
"bbox": "72.533, -53.067, 72.74, -53.003",
@@ -260106,7 +260119,7 @@
{
"id": "mcdonald_dem_may2012_1",
"title": "A Digital Elevation Model of McDonald Island derived from GeoEye-1 stereo imagery captured 19 May 2012",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2012-05-19",
"end_date": "2012-05-19",
"bbox": "72.533, -53.067, 72.74, -53.003",
@@ -260145,7 +260158,7 @@
{
"id": "medical_bibliography_1",
"title": "A bibliography of polar medicine related articles",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1947-01-01",
"end_date": "2007-06-06",
"bbox": "60, -90, 160, -42",
@@ -260158,7 +260171,7 @@
{
"id": "medical_bibliography_1",
"title": "A bibliography of polar medicine related articles",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1947-01-01",
"end_date": "2007-06-06",
"bbox": "60, -90, 160, -42",
@@ -260184,7 +260197,7 @@
{
"id": "mendocino_mathison_peak_nff_sr",
"title": "Airborne laser swath mapping (ALSM) data of the San Andreas fault",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2003-02-05",
"end_date": "2003-02-11",
"bbox": "-123.81387, 39.31092, -123.720085, 39.333496",
@@ -260197,7 +260210,7 @@
{
"id": "mendocino_mathison_peak_nff_sr",
"title": "Airborne laser swath mapping (ALSM) data of the San Andreas fault",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2003-02-05",
"end_date": "2003-02-11",
"bbox": "-123.81387, 39.31092, -123.720085, 39.333496",
@@ -262030,7 +262043,7 @@
{
"id": "nwrc_amphibianslowermiss",
"title": "A Multi-scale Habitat Evaluation of Amphibians in the Lower Mississippi River Alluvial Valley",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1999-09-05",
"end_date": "1999-12-05",
"bbox": "-91.95, 31.15, -91.25, 32.4333",
@@ -262043,7 +262056,7 @@
{
"id": "nwrc_amphibianslowermiss",
"title": "A Multi-scale Habitat Evaluation of Amphibians in the Lower Mississippi River Alluvial Valley",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1999-09-05",
"end_date": "1999-12-05",
"bbox": "-91.95, 31.15, -91.25, 32.4333",
@@ -262069,7 +262082,7 @@
{
"id": "obrienbay_bathy_dem_1",
"title": "A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1997-03-31",
"end_date": "1997-03-31",
"bbox": "110.516, -66.297, 110.54, -66.293",
@@ -262082,7 +262095,7 @@
{
"id": "obrienbay_bathy_dem_1",
"title": "A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1997-03-31",
"end_date": "1997-03-31",
"bbox": "110.516, -66.297, 110.54, -66.293",
@@ -262290,7 +262303,7 @@
{
"id": "oxygen-isotopes-plateau-1984_1",
"title": "7 year oxygen isotope results from samples taken on Antarctic Plateau traverse, 1984",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1978-01-01",
"end_date": "1984-12-31",
"bbox": "100, -75, 130, -65",
@@ -262303,7 +262316,7 @@
{
"id": "oxygen-isotopes-plateau-1984_1",
"title": "7 year oxygen isotope results from samples taken on Antarctic Plateau traverse, 1984",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1978-01-01",
"end_date": "1984-12-31",
"bbox": "100, -75, 130, -65",
@@ -263876,7 +263889,7 @@
{
"id": "robinson_adelie_colonies_1",
"title": "Adelie penguin colonies in the Robinson Group, Antarctica: surveys conducted during 2005/06 and 2006/07",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2005-09-30",
"end_date": "2007-03-31",
"bbox": "63.233334, -67.51667, 63.85, -67.36667",
@@ -263889,7 +263902,7 @@
{
"id": "robinson_adelie_colonies_1",
"title": "Adelie penguin colonies in the Robinson Group, Antarctica: surveys conducted during 2005/06 and 2006/07",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-09-30",
"end_date": "2007-03-31",
"bbox": "63.233334, -67.51667, 63.85, -67.36667",
@@ -265280,7 +265293,7 @@
{
"id": "scarmarbin_1647",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Tanaidacea.",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265293,7 +265306,7 @@
{
"id": "scarmarbin_1647",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Tanaidacea.",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265306,7 +265319,7 @@
{
"id": "scarmarbin_1648",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Cumacea.",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265319,7 +265332,7 @@
{
"id": "scarmarbin_1648",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Cumacea.",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265384,7 +265397,7 @@
{
"id": "scarmarbin_1716",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 - scarmarbin_1716",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1979-12-27",
"end_date": "1980-02-07",
"bbox": "-180, -90, 180, 90",
@@ -265397,7 +265410,7 @@
{
"id": "scarmarbin_1716",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 - scarmarbin_1716",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1979-12-27",
"end_date": "1980-02-07",
"bbox": "-180, -90, 180, 90",
@@ -265462,7 +265475,7 @@
{
"id": "scarmarbin_1807",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1994).",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265475,7 +265488,7 @@
{
"id": "scarmarbin_1807",
"title": "Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1994).",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265514,7 +265527,7 @@
{
"id": "scarmarbin_987",
"title": "A Biotic Database of Indo-Pacific Marine Mollusks (Southern Ocean Collection)",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265527,7 +265540,7 @@
{
"id": "scarmarbin_987",
"title": "A Biotic Database of Indo-Pacific Marine Mollusks (Southern Ocean Collection)",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265540,7 +265553,7 @@
{
"id": "scarmarbin_ABBED",
"title": "Admiralty Bay Benthos Biodiversity Database [SCAR-MarBIN]",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "1906-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -265553,7 +265566,7 @@
{
"id": "scarmarbin_ABBED",
"title": "Admiralty Bay Benthos Biodiversity Database [SCAR-MarBIN]",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1906-01-01",
"end_date": "",
"bbox": "-180, -90, 180, 90",
@@ -266008,7 +266021,7 @@
{
"id": "simrad_SO",
"title": "Acoustic responses to water column features, Antarctic, Aug-Sept 2002, GLOBEC.",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2002-08-03",
"end_date": "2002-09-15",
"bbox": "-75.5, -68.75, -69.5, -65.75",
@@ -266021,7 +266034,7 @@
{
"id": "simrad_SO",
"title": "Acoustic responses to water column features, Antarctic, Aug-Sept 2002, GLOBEC.",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2002-08-03",
"end_date": "2002-09-15",
"bbox": "-75.5, -68.75, -69.5, -65.75",
@@ -271585,7 +271598,7 @@
{
"id": "usgs_nps_agatefossilbedsspatial",
"title": "Agate Fossil Beds National Monument Spatial Vegetation Data: Cover Type/Association Level of the National Vegetation Classification System",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1995-07-29",
"end_date": "1995-07-29",
"bbox": "-103.8, 42.40833, -103.7, 42.44167",
@@ -271598,7 +271611,7 @@
{
"id": "usgs_nps_agatefossilbedsspatial",
"title": "Agate Fossil Beds National Monument Spatial Vegetation Data: Cover Type/Association Level of the National Vegetation Classification System",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1995-07-29",
"end_date": "1995-07-29",
"bbox": "-103.8, 42.40833, -103.7, 42.44167",
@@ -271832,7 +271845,7 @@
{
"id": "usgs_npwrc_graywolves_Version 30APR2001",
"title": "Accuracy and Precision of Estimating Age of Gray Wolves by Tooth Wear",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-168, 43.5, -75, 55",
@@ -271845,7 +271858,7 @@
{
"id": "usgs_npwrc_graywolves_Version 30APR2001",
"title": "Accuracy and Precision of Estimating Age of Gray Wolves by Tooth Wear",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-168, 43.5, -75, 55",
@@ -271871,7 +271884,7 @@
{
"id": "usgs_npwrc_manitobaspiders_Version 16JUL97",
"title": "A Checklist of Manitoba Spiders (Araneae) with Notes on Geographic Relationships",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-145.27, 37.3, -48.11, 87.61",
@@ -271884,7 +271897,7 @@
{
"id": "usgs_npwrc_manitobaspiders_Version 16JUL97",
"title": "A Checklist of Manitoba Spiders (Araneae) with Notes on Geographic Relationships",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-145.27, 37.3, -48.11, 87.61",
@@ -272027,7 +272040,7 @@
{
"id": "usgsbrdnpwrcb00000013_Version 30SEP2002",
"title": "A Bibliography of Fisheries Biology in North and South Dakota",
- "catalog": "CEOS_EXTRA STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-104, 43, -96, 49",
@@ -272040,7 +272053,7 @@
{
"id": "usgsbrdnpwrcb00000013_Version 30SEP2002",
"title": "A Bibliography of Fisheries Biology in North and South Dakota",
- "catalog": "ALL STAC Catalog",
+ "catalog": "CEOS_EXTRA STAC Catalog",
"state_date": "1970-01-01",
"end_date": "",
"bbox": "-104, 43, -96, 49",
@@ -272599,7 +272612,7 @@
{
"id": "waddington_0352584",
"title": "A Unique Opportunity for In-Situ Measurement of Seasonally-Varying Firn Densification at Summit, Greenland",
- "catalog": "SCIOPS STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2004-01-01",
"end_date": "2009-01-01",
"bbox": "-38.6, 72.5, -38.4, 72.7",
@@ -272612,7 +272625,7 @@
{
"id": "waddington_0352584",
"title": "A Unique Opportunity for In-Situ Measurement of Seasonally-Varying Firn Densification at Summit, Greenland",
- "catalog": "ALL STAC Catalog",
+ "catalog": "SCIOPS STAC Catalog",
"state_date": "2004-01-01",
"end_date": "2009-01-01",
"bbox": "-38.6, 72.5, -38.4, 72.7",
@@ -272833,7 +272846,7 @@
{
"id": "whitney_dem_1",
"title": "A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "2005-01-01",
"end_date": "2007-05-01",
"bbox": "110.522, -66.255, 110.544, -66.248",
@@ -272846,7 +272859,7 @@
{
"id": "whitney_dem_1",
"title": "A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "2005-01-01",
"end_date": "2007-05-01",
"bbox": "110.522, -66.255, 110.544, -66.248",
@@ -272924,7 +272937,7 @@
{
"id": "winston_bathy_1",
"title": "A bathymetric survey of Winston Lagoon",
- "catalog": "ALL STAC Catalog",
+ "catalog": "AU_AADC STAC Catalog",
"state_date": "1987-01-09",
"end_date": "1987-01-14",
"bbox": "73.23557, -53.20274, 73.83911, -52.95006",
@@ -272937,7 +272950,7 @@
{
"id": "winston_bathy_1",
"title": "A bathymetric survey of Winston Lagoon",
- "catalog": "AU_AADC STAC Catalog",
+ "catalog": "ALL STAC Catalog",
"state_date": "1987-01-09",
"end_date": "1987-01-14",
"bbox": "73.23557, -53.20274, 73.83911, -52.95006",
diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv
index 1b7df0f82b..8b05ec28bb 100644
--- a/nasa_cmr_catalog.tsv
+++ b/nasa_cmr_catalog.tsv
@@ -8904,14 +8904,14 @@ KOPRI-KPDC-00000585_1 Soil moisture and temperature data collected from climate
KOPRI-KPDC-00000586_1 Permafrost core samples in Council, Alaska, USA in 2014 AMD_KOPRI STAC Catalog 2015-12-21 2015-12-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244301145-AMD_KOPRI.umm_json Nine permafrost core samples were collected in Council, Alaska. Three sampling sites were determined by soil resistivity test, and three replicates were collected in each site. Soil core was about 1.1 – 1.5 m in length. Soil microbial community and physical and chemical properties will be analyzed. To investigate the differences of microbial community structure and soil physical and chemical properties 1) between active and permafrost layers and 2) among soils showing different resistivity. proprietary
KOPRI-KPDC-00000587_1 Eddy covariance data of Alaska permafrost site in 2014 AMD_KOPRI STAC Catalog 2014-04-01 2014-11-01 -163.705333, 64.843333, -163.705333, 64.843333 https://cmr.earthdata.nasa.gov/search/concepts/C2244295657-AMD_KOPRI.umm_json Turbulent fluxes of momentum, heat, water vapor, and CO2 had been measured during summertime in 2014 at Council, Alaska. Eddy covariance system, consisting of 3-D sonic anemometer and open-path CO2/H2O gas analyzer was used for the measurement. Data were recorded with CR3000 logger with sampling rate of 10 Hz. To monitor and understand energy/water/green-house-gas flux over permafrost region proprietary
KOPRI-KPDC-00000588_1 Methane flux data of Alaska permafrost site in 2014 AMD_KOPRI STAC Catalog 2014-07-10 2014-07-23 -163.705333, 64.843333, -163.705333, 64.843333 https://cmr.earthdata.nasa.gov/search/concepts/C2244295661-AMD_KOPRI.umm_json High-frequency methane concentration was measured in July 2014 at Council, Alaska. Along with atmospheric turbulence data from 3-D sonic anemometer, methane flux was obtained at 30-minute interval. To monitor and understand methane flux over permafrost region proprietary
-KOPRI-KPDC-00000589_1 Air temperature and humidity in Cambridge Bay, Canada in 2012 AMD_KOPRI STAC Catalog 2012-07-11 2013-08-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295675-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation) To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
KOPRI-KPDC-00000589_1 Air temperature and humidity in Cambridge Bay, Canada in 2012 ALL STAC Catalog 2012-07-11 2013-08-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295675-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation) To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
+KOPRI-KPDC-00000589_1 Air temperature and humidity in Cambridge Bay, Canada in 2012 AMD_KOPRI STAC Catalog 2012-07-11 2013-08-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295675-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation) To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
KOPRI-KPDC-00000590_1 Soil samples after one year of climate manipulation AMD_KOPRI STAC Catalog 2013-07-31 2013-08-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295694-AMD_KOPRI.umm_json Soil samples from climate manipulation plots after one year of warming and increasing precipitation To determine the effects of climate change on soil properties and microbial diversity proprietary
KOPRI-KPDC-00000591_1 Soil samples after three years of climate manipulation AMD_KOPRI STAC Catalog 2015-07-29 2015-08-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295728-AMD_KOPRI.umm_json Soil samples from climate manipulation plots after three years of warming and increasing precipitation To determine the effects of climate change on soil properties and microbial structure and function proprietary
-KOPRI-KPDC-00000592_1 Air temperature and humidity in Cambridge Bay, Canada in 2013 AMD_KOPRI STAC Catalog 2013-08-01 2014-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295766-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation in 2013 To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
KOPRI-KPDC-00000592_1 Air temperature and humidity in Cambridge Bay, Canada in 2013 ALL STAC Catalog 2013-08-01 2014-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295766-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation in 2013 To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
-KOPRI-KPDC-00000593_1 Air temperature and humidity in Cambridge Bay, Canada in 2014 AMD_KOPRI STAC Catalog 2014-06-01 2015-08-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296042-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation) in 2014 To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
+KOPRI-KPDC-00000592_1 Air temperature and humidity in Cambridge Bay, Canada in 2013 AMD_KOPRI STAC Catalog 2013-08-01 2014-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295766-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation in 2013 To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
KOPRI-KPDC-00000593_1 Air temperature and humidity in Cambridge Bay, Canada in 2014 ALL STAC Catalog 2014-06-01 2015-08-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296042-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation) in 2014 To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
+KOPRI-KPDC-00000593_1 Air temperature and humidity in Cambridge Bay, Canada in 2014 AMD_KOPRI STAC Catalog 2014-06-01 2015-08-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296042-AMD_KOPRI.umm_json Air temperature and humidity at 25 cm above the surface from the climate manipulation plots (increasing temperature and precipitation) in 2014 To monitor the changes in micro-climate properties in air by increasing temperature and precipitation proprietary
KOPRI-KPDC-00000594_1 Soil moisture and temperature data collected from climate manipulation plots in Cambridge Bay, Canada in 2013 AMD_KOPRI STAC Catalog 2013-08-01 2014-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296351-AMD_KOPRI.umm_json Soil volumetric moisture content and temperature for 5 cm depth from climate manipulation (combination of warming and precipitation) plots in 2013 To monitor the changes in micro-climate properties in soil by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00000595_1 Soil moisture and temperature data collected from climate manipulation plots in Cambridge Bay, Canada in 2014 AMD_KOPRI STAC Catalog 2014-06-01 2015-08-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296625-AMD_KOPRI.umm_json Soil moisture and temperature data collected from climate manipulation plots in Cambridge Bay, Canada in 2014 proprietary
KOPRI-KPDC-00000596_1 Fossil specimens of Northern Victoria Land, 2014-2015 season AMD_KOPRI STAC Catalog 2015-12-30 2015-12-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296805-AMD_KOPRI.umm_json This entry is for the fossil specimens of Northern Victoria Land (NVL), Antarctica collected in 2014-15 austral summer season. The collection includes trilobites of the Lower Paleozoic Bowers Supergroup and plant fossils of the Beacon Supergroup. Information from the fossils will be helpful for understanding geological processes and paleoenvironments of the Northern Victoria Land. proprietary
@@ -8938,12 +8938,12 @@ KOPRI-KPDC-00000616_1 Benthos image data from transect line, coastal of Jang Bog
KOPRI-KPDC-00000617_1 Black Carbon data at Jang Bogo station, 2015 AMD_KOPRI STAC Catalog 2015-02-14 164.228333, -74.623333, 164.228333, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244298913-AMD_KOPRI.umm_json The aethalometer is used to measure atmospheric black carbon concentration every 5 minute over Jang Bogo station. Monitoring of Black Carbon concentration over Jang Bogo station proprietary
KOPRI-KPDC-00000618_1 Soil and Fresh/Sea water samples from Barton Peninsular collected in 2015-2016 AMD_KOPRI STAC Catalog 2016-01-18 2016-02-21 -58.80624, -62.24449, -58.69884, -62.20679 https://cmr.earthdata.nasa.gov/search/concepts/C2244299282-AMD_KOPRI.umm_json Analysis of microbial community structure and diversity in soil and fresh/sea water samples from Barton Peninsular in Antarctica Investigation to the terrestrial biodiversity in Barton Peninsular for the monitoring by environment change proprietary
KOPRI-KPDC-00000619_1 Environmental data about King George Islands collected in 2016 AMD_KOPRI STAC Catalog 2015-01-31 2015-02-21 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244299653-AMD_KOPRI.umm_json Microclimate data from King George Islands collected in 2016. Investigate relationship between biota proprietary
-KOPRI-KPDC-00000620_1 2015-2016 JBS_micro-climate data_HOBO_soil temp.,PAR,air temp.,relative humidity ALL STAC Catalog 2015-02-09 2015-02-13 164.191389, -74.632806, 164.229972, -74.613 https://cmr.earthdata.nasa.gov/search/concepts/C2244300021-AMD_KOPRI.umm_json Micro-climate data set from The Jang Bogo Station in Terra Nova Bay collected during 1 year, 2015 proprietary
KOPRI-KPDC-00000620_1 2015-2016 JBS_micro-climate data_HOBO_soil temp.,PAR,air temp.,relative humidity AMD_KOPRI STAC Catalog 2015-02-09 2015-02-13 164.191389, -74.632806, 164.229972, -74.613 https://cmr.earthdata.nasa.gov/search/concepts/C2244300021-AMD_KOPRI.umm_json Micro-climate data set from The Jang Bogo Station in Terra Nova Bay collected during 1 year, 2015 proprietary
+KOPRI-KPDC-00000620_1 2015-2016 JBS_micro-climate data_HOBO_soil temp.,PAR,air temp.,relative humidity ALL STAC Catalog 2015-02-09 2015-02-13 164.191389, -74.632806, 164.229972, -74.613 https://cmr.earthdata.nasa.gov/search/concepts/C2244300021-AMD_KOPRI.umm_json Micro-climate data set from The Jang Bogo Station in Terra Nova Bay collected during 1 year, 2015 proprietary
KOPRI-KPDC-00000621_1 Soil and Fresh water samples of the Antarctic Jang Bogo Station from Terra Nova Bay collected in 2016 AMD_KOPRI STAC Catalog 2016-01-07 2016-02-21 164.192056, -74.633361, 164.23725, -74.612056 https://cmr.earthdata.nasa.gov/search/concepts/C2244300323-AMD_KOPRI.umm_json Analysis of microbial community structure and diversity in soil and water samples of the Antarctic Jang Bogo Station from Terra Nova Bay in Antarctica Investigation to the terrestrial biodiversity in Terra Nova Bay for the monitoring by environment change proprietary
KOPRI-KPDC-00000622_1 Sampling activity for identification between biotic (ciliate) and abiotic data from Barton Peninsular in Antarctica during the summer season in 2015/2016. AMD_KOPRI STAC Catalog 2015-12-04 2015-12-18 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300508-AMD_KOPRI.umm_json Identification of ciliate biota and environmental data of habitats from Antarctica (Barton Peninsular) Identification of the relationship between biotic sample and abiotic data proprietary
-KOPRI-KPDC-00000623_1 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2015 AMD_KOPRI STAC Catalog 2015-03-01 2016-02-01 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244300569-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2015 Long term monitoring proprietary
KOPRI-KPDC-00000623_1 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2015 ALL STAC Catalog 2015-03-01 2016-02-01 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244300569-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2015 Long term monitoring proprietary
+KOPRI-KPDC-00000623_1 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2015 AMD_KOPRI STAC Catalog 2015-03-01 2016-02-01 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244300569-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2015 Long term monitoring proprietary
KOPRI-KPDC-00000624_1 Lichen samples from South Shetland Islands collected in 2016 AMD_KOPRI STAC Catalog 2016-02-01 2016-02-21 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300624-AMD_KOPRI.umm_json Lichen samples from Barton Peninsular collected in 2016 Ecophysiological study of lichen proprietary
KOPRI-KPDC-00000625_2 Climate Measurement Around the King Sejong Station, Antarctica in 2016 AMD_KOPRI STAC Catalog 2016-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244305947-AMD_KOPRI.umm_json Meteorological observation was carried out at the King Sejong Station in 2016. Observational elements are composed of wind, air temperature, relative humidity, station level atmospheric pressure, horizontal global solar radiation, longwave radiation, UV radiation, and precipitation. Goals of this observation are 1) to understand meteorological phenomena and 2) to monitor climate change at Antarctic Peninsula. These data are recorded automatically then examined by meteorological expert at the station to be produced as a daily, monthly, and annual report. To understand weather phenomema and to monitor at Antarctic Peninsula proprietary
KOPRI-KPDC-00000626_1 Soil samples of the Antarctic King Sejong Station from Barton Peninsular collected in 2016 AMD_KOPRI STAC Catalog 2016-02-19 2016-02-19 -58.788436, -62.224964, -58.786192, -62.22415 https://cmr.earthdata.nasa.gov/search/concepts/C2244300652-AMD_KOPRI.umm_json Analysis of microbial community structure and diversity in soil samples of the Antarctic King Sejong Station from Barton Peninsular in Antarctica Investigation to the terrestrial biodiversity in Barton peninsular for the monitoring by environment change proprietary
@@ -9026,8 +9026,8 @@ KOPRI-KPDC-00000703_1 Soil physical and chemical properties in Council, Alaska i
KOPRI-KPDC-00000704_1 Soil physical and chemical properties in Cambridge Bay, Canada in 2012 AMD_KOPRI STAC Catalog 2012-06-28 2012-07-14 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244296757-AMD_KOPRI.umm_json Physical and chemical properties of soil which were collected in 2012 (before climate manipulation) were analyzed. Soils from 0-5 and 5-10 cm depths were sampled. To monitor the changes in soil physical and chemical properties by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00000705_1 Soil physical and chemical properties in Cambridge Bay, Canada in 2013 AMD_KOPRI STAC Catalog 2013-07-31 2013-08-09 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244296821-AMD_KOPRI.umm_json Physical and chemical properties of soil which were collected in 2013 after one year of climate manipulation were analyzed. Soils from 0-5 and 5-10 cm depths were sampled. To monitor the changes in soil physical and chemical properties by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00000706_1 Soil physical and chemical properties in Cambridge Bay, Canada in 2015 AMD_KOPRI STAC Catalog 2015-07-30 2015-08-07 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244296843-AMD_KOPRI.umm_json Physical and chemical properties of soil which were collected in 2015 after three years of climate manipulation were analyzed. Soils from organic and mineral layers were sampled. To monitor the changes in soil physical and chemical properties by increasing temperature by open top chambers and increasing precipitation proprietary
-KOPRI-KPDC-00000707_3 3D floorplan for CAD of Jang Bogo Station AMD_KOPRI STAC Catalog 2011-01-01 2011-01-31 164.228817, -74.624017, 164.228817, -74.624017 https://cmr.earthdata.nasa.gov/search/concepts/C2244296823-AMD_KOPRI.umm_json 3D floorplan for CAD of Jang Bogo Station To use for Numerical Weather Prediction Model proprietary
KOPRI-KPDC-00000707_3 3D floorplan for CAD of Jang Bogo Station ALL STAC Catalog 2011-01-01 2011-01-31 164.228817, -74.624017, 164.228817, -74.624017 https://cmr.earthdata.nasa.gov/search/concepts/C2244296823-AMD_KOPRI.umm_json 3D floorplan for CAD of Jang Bogo Station To use for Numerical Weather Prediction Model proprietary
+KOPRI-KPDC-00000707_3 3D floorplan for CAD of Jang Bogo Station AMD_KOPRI STAC Catalog 2011-01-01 2011-01-31 164.228817, -74.624017, 164.228817, -74.624017 https://cmr.earthdata.nasa.gov/search/concepts/C2244296823-AMD_KOPRI.umm_json 3D floorplan for CAD of Jang Bogo Station To use for Numerical Weather Prediction Model proprietary
KOPRI-KPDC-00000708_1 Multiprotein-bridging factor 1c-like gene sequence from an Antarctic moss Polytrichastrum alpinum AMD_KOPRI STAC Catalog 2017-03-03 2017-03-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244297364-AMD_KOPRI.umm_json PaMBF1c (Multiprotein-bridging factor 1c-like) gene considered as an abiotic stimulus related genes from an Antarctic moss Polytrichastrum alpinum Investigation of molecular adaptation mechanism of the Antarcic moss to Antarctic environment proprietary
KOPRI-KPDC-00000709_1 AMIGOS data in the Drygalski Ice Tongue, 2012 AMD_KOPRI STAC Catalog 2012-01-31 2012-12-31 164.294346, -75.412399, 165.17164, -75.348164 https://cmr.earthdata.nasa.gov/search/concepts/C2244295101-AMD_KOPRI.umm_json GPS, camera, and weather (air temperature, humidity, pressure, wind speed, wind direction) measurements from the AMIGOS systems in the Drygalski Ice Tongue Monitoring the movement and environmental change of Drygalski Ice Tongue proprietary
KOPRI-KPDC-00000710_1 Hydro-Carbon Hydrate Accumulations in the Okhotsk Sea III AMD_KOPRI STAC Catalog 2006-05-24 2006-06-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295224-AMD_KOPRI.umm_json We had very remarkable results from the CHAOS-1 (2003) and CHAOS-2 (2005) project; lots of gas flares in the water column, many gas venting structures on the seafloor, gas hydrate samples including massive gas hydrate chunk (about 45 cm thick) near the seafloor, and gas hydrate-related structures in deep sub-bottom depth. These results encourage us to continue and expend the CHAOS project. Since the previous expedition focused on the relatively small area where gas hydrate-related phenomena has been known to be active, the basic aim of the CHAOS-III expedition is to improve understanding on gas hydrate-related phenomena in the Sea of Okhotsk in terms of multidisciplinary areas including geology, chemistry, oceanology and biology. 1. Detection of new gas hydrate-related structures including gas flares and gas venting structures. 2. Definition of the boundaries of the gas hydrate province 3. Mapping of the seafloor expressions related with gas hydrates and gas seepages using side-scan sonar. 4. Recognition of size, shape, and morphology of gas seepages on the seafloor. 5. High-resolution seismic investigation to examine inner structures and the gas hydrate stability condition in gas hydrate-baring sediments in detail. 6. Detection of gas flares in the water column emitted from gas seepages. 7. Study on hydrated water and dissociated gas sample 8. Chemistry of gas, gas hydrate, hydrate-forming fluids and carbonates including isotopic analysis. 9. Determination of methane concentration in the water column. 10. Underway survey to understand distribution of methane and dioxide in surface water and its controlling factor. 11. Detailed investigation of marine sedimentological environment in the gas hydrate area 12. Mechanism of formation-dissociation for gas-hydrates. 13. Interrelation of methane fluxes and mercury 14. Organic geochemical information related to the origin and composition of sedimentary organic matter. 15. Identification of biomarkers of microorganisms associated methane cycle. 16. Understanding of the composition of microbial community in gas hydrate environment proprietary
@@ -9043,10 +9043,10 @@ KOPRI-KPDC-00000719_1 Seawater for dissolved organic carbon AMD_KOPRI STAC Catal
KOPRI-KPDC-00000720_1 Biogeochemical data of seawater and sediment AMD_KOPRI STAC Catalog 2014-10-08 2014-10-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295503-AMD_KOPRI.umm_json Biogeochemical data of seawater and sediment proprietary
KOPRI-KPDC-00000721_1 Lichen samples from South Shetland Islands collected in 2014 AMD_KOPRI STAC Catalog 2014-10-08 2014-10-08 -64.083333, -64.766667, -64.083333, -64.766667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295558-AMD_KOPRI.umm_json Lichen samples from Barton Peninsular collected in 2014. Locality, habitat information for 1286 lichen samples Investigation to diversity, morphology, phylogeography and ecophysiology in lichen proprietary
KOPRI-KPDC-00000722_1 Lichen samples from Punta Arenas in Chile collected in 2014 AMD_KOPRI STAC Catalog 2014-10-08 2014-10-08 -71.416667, -53.6, -71.416667, -53.6 https://cmr.earthdata.nasa.gov/search/concepts/C2244295591-AMD_KOPRI.umm_json Lichen samples from Chile collected in 2014. Locality, habitat information for 165 lichen samples Investigation to diversity, morphology and phylogeography in lichen proprietary
-KOPRI-KPDC-00000723_1 Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2012 AMD_KOPRI STAC Catalog 2014-10-08 2014-10-08 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295614-AMD_KOPRI.umm_json Yearly air temperature data from Barton Peninsular collected in 2012 Long term monitoring proprietary
KOPRI-KPDC-00000723_1 Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2012 ALL STAC Catalog 2014-10-08 2014-10-08 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295614-AMD_KOPRI.umm_json Yearly air temperature data from Barton Peninsular collected in 2012 Long term monitoring proprietary
-KOPRI-KPDC-00000724_1 Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2013 ALL STAC Catalog 2014-10-08 2014-10-08 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295626-AMD_KOPRI.umm_json Yearly air temperauter and relative humidity data from Barton Peninsular collected in 2013 Long term monitoring proprietary
+KOPRI-KPDC-00000723_1 Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2012 AMD_KOPRI STAC Catalog 2014-10-08 2014-10-08 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295614-AMD_KOPRI.umm_json Yearly air temperature data from Barton Peninsular collected in 2012 Long term monitoring proprietary
KOPRI-KPDC-00000724_1 Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2013 AMD_KOPRI STAC Catalog 2014-10-08 2014-10-08 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295626-AMD_KOPRI.umm_json Yearly air temperauter and relative humidity data from Barton Peninsular collected in 2013 Long term monitoring proprietary
+KOPRI-KPDC-00000724_1 Air temperature and relative humidity data from Barton Peninsular in South Shetland Islands collected in 2013 ALL STAC Catalog 2014-10-08 2014-10-08 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295626-AMD_KOPRI.umm_json Yearly air temperauter and relative humidity data from Barton Peninsular collected in 2013 Long term monitoring proprietary
KOPRI-KPDC-00000725_1 Water isotope composition in a GV7 3-m snow pit (2013-2014) AMD_KOPRI STAC Catalog 2014-10-10 2014-10-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295745-AMD_KOPRI.umm_json A 3 m snow pit was collected at GV7 (Antarctica) in the 2013-2014 summer season. Its water isotope composition (dD, d18O) was determined using cavity ringdown spectroscopy (PICARRO). To detect annual (seasonal) layering of snowpack. proprietary
KOPRI-KPDC-00000726_1 NEEM project_ice core AMD_KOPRI STAC Catalog 2014-10-10 2014-10-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244295831-AMD_KOPRI.umm_json We obtained ice cores after participating the North Greenland Eemian Ice Drilling program. We reconstruct the high-resolution ice record of a shift of mineral dust sources in response to climate transition between the Last Glacial Maximum(~25,000 yr BP) and Holocene(8,000 yr BP) by analyzing trace elements including rare earth elements from a Greenland NEEM ice core. proprietary
KOPRI-KPDC-00000727_1 ARA05C BC AMD_KOPRI STAC Catalog 2014-10-10 2014-10-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244296153-AMD_KOPRI.umm_json ARA05C BC proprietary
@@ -9083,26 +9083,26 @@ KOPRI-KPDC-00000756_1 Gravity cores from Antarctic Weddell Sea(JV10-GC01) AMD_KO
KOPRI-KPDC-00000757_1 Physical and chemical properties of soil cores from Council, Alaska in 2016 AMD_KOPRI STAC Catalog 2017-06-01 2017-09-20 -163.7, 64.85, -163.7, 64.85 https://cmr.earthdata.nasa.gov/search/concepts/C2244299727-AMD_KOPRI.umm_json Several soil physical and chemical properties (moisture content, bulk density, C and N content, etc.) were analyzed from soil samples acquired in tussock and inter-tussock areas in August. 2016. To use for the basic information in the laboratory incubation study and to understand the site characteristics proprietary
KOPRI-KPDC-00000758_1 Crystal structure and functional characterization of an isoaspartyl dipeptidase (CpsIadA) from Colwellia psychrerythraea strain 34H AMD_KOPRI STAC Catalog 2017-06-21 2017-06-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244300669-AMD_KOPRI.umm_json Isoaspartyl dipeptidase (IadA) is an enzyme that catalyzes the hydrolysis of an isoaspartyl dipeptide-like moiety, which can be inappropriately formed in proteins, between the β-carboxyl group side chain of Asp and the amino group of the following amino acid. Here, we have determined the structures of an isoaspartyl dipeptidase (CpsIadA) from Colwellia psychrerythraea, both ligand-free and that complexed with β-isoaspartyl lysine, at 1.85-Å and 2.33-Å resolution, respectively. In both structures, CpsIadA formed an octamer with two Zn ions in the active site. A structural comparison with Escherichia coli isoaspartyl dipeptidase (EcoIadA) revealed a major difference in the structure of the active site. For metal ion coordination, CpsIadA has a Glu166 residue in the active site, whereas EcoIadA has a post-translationally carbamylated-lysine 162 residue. Site-directed mutagenesis studies confirmed that the Glu166 residue is critical for CpsIadA enzymatic activity. This residue substitution from lysine to glutamate induces the protrusion of the β12-α8 loop into the active site to compensate for the loss of length of the side chain. In addition, the α3-β9 loop of CpsIadA adopts a different conformation compared to EcoIadA, which induces a change in the structure of the substrate-binding pocket. Despite CpsIadA having a different active-site residue composition and substrate-binding pocket, there is only a slight difference in CpsIadA substrate specificity compared with EcoIadA. Comparative sequence analysis classified IadA-containing bacteria and archaea into two groups based on the active-site residue composition, with Type I IadAs having a glutamate residue and Type II IadAs having a carbamylated-lysine residue. CpsIadA has maximal activity at pH 8±8.5 and 45ÊC, and was completely inactivated at 60ÊC. Despite being isolated from a psychrophilic bacteria, CpsIadA is thermostable probably owing to its octameric structure. This is the first conclusive description of the structure and properties of a Type I IadA. To determine the structures of an isoaspartyl dipeptidase IadA from a psychrophilic bacterium Colwellia psychrerythraea strain 34H (CpsIadA) in both the ligand-free form and that complexed with β-isoaspartyl lysine proprietary
KOPRI-KPDC-00000759_1 X-ray diffraction data of EaEST AMD_KOPRI STAC Catalog 2016-04-03 2016-04-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244300649-AMD_KOPRI.umm_json A novel microbial esterase, EaEST, from a psychrophilic bacterium Exiguobacterium antarcticum B7, was identified and characterized. To our knowledge, this is the first report describing structural analysis and biochemical characterization of an esterase isolated from the genus Exiguobacterium. Crystal structure of EaEST, determined at a resolution of 1.9 Å, showed that the enzyme has a canonical α/β hydrolase fold with an α-helical cap domain and a catalytic triad consisting of Ser96, Asp220, and His248. Interestingly, the active site of the structure of EaEST is occupied by a peracetate molecule, which is the product of perhydrolysis of acetate. This result suggests that EaEST may have perhydrolase activity. The activity assay showed that EaEST has significant perhydrolase and esterase activity with respect to short-chain p-nitrophenyl esters (≤C8), naphthyl derivatives, phenyl acetate, and glyceryl tributyrate. However, the S96A single mutant had low esterase and perhydrolase activity. Moreover, the L30A mutant showed low levels of protein expression and solubility as well as preference for different substrates. On conducting an enantioselectivity analysis using R- and S-methyl-3-hydroxy-2-methylpropionate, a preference for R-enantiomers was observed. Surprisingly, immobilized EaEST was found to not only retain 200% of its initial activity after incubation for 1 h at 80°C, but also retained more than 60% of its initial activity after 20 cycles of reutilization. This research will serve as basis for future engineering of this esterase for biotechnological and industrial applications. Our goal was to identify a novel cold-active esterase from a polar microorganism. We identified and characterized a novel esterase, EaEST, from a psychrophilic bacterium Exiguobacterium antarcticum B7. Further structural and functional analysis indicated that EaEST had dual activity of a perhydrolase and an esterase. It is known that perhydrolysis is a side activity of esterases and it may be useful in industrial and organic synthesis. Moreover, the peracetate-bound EaEST structure reported in our study provides the first snapshot of the peracetate binding mode, and a comparison of the structure of EaEST with that of PfEST (PDB code 3HI4) reveals a comprehensive structural basis for the conformational changes of this enzyme induced by binding of different substrates. proprietary
-KOPRI-KPDC-00000760_1 Air borne Ice radar survey data of Korean route from David glacier, Antarctica in 2016-2017 ALL STAC Catalog 2016-12-28 2017-02-15 153.936483, -75.389942, 159.216086, -75.059956 https://cmr.earthdata.nasa.gov/search/concepts/C2244300682-AMD_KOPRI.umm_json David glacier area ice surface / bed elevation ice surface / bed elevation proprietary
KOPRI-KPDC-00000760_1 Air borne Ice radar survey data of Korean route from David glacier, Antarctica in 2016-2017 AMD_KOPRI STAC Catalog 2016-12-28 2017-02-15 153.936483, -75.389942, 159.216086, -75.059956 https://cmr.earthdata.nasa.gov/search/concepts/C2244300682-AMD_KOPRI.umm_json David glacier area ice surface / bed elevation ice surface / bed elevation proprietary
+KOPRI-KPDC-00000760_1 Air borne Ice radar survey data of Korean route from David glacier, Antarctica in 2016-2017 ALL STAC Catalog 2016-12-28 2017-02-15 153.936483, -75.389942, 159.216086, -75.059956 https://cmr.earthdata.nasa.gov/search/concepts/C2244300682-AMD_KOPRI.umm_json David glacier area ice surface / bed elevation ice surface / bed elevation proprietary
KOPRI-KPDC-00000761_1 Comparison of diversity of ciliate between Barton peninsula in Antarctica and Korea using NGS technique. AMD_KOPRI STAC Catalog 2017-05-04 2017-06-18 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300615-AMD_KOPRI.umm_json Identification of ciliate diversity from Korea and Antarctica (Barton Peninsular) Comparison of both data to know the specific ciliate in Antarctica proprietary
KOPRI-KPDC-00000762_1 Greenland NEEM 2009S1 shallow ice core trace elements concentrations AMD_KOPRI STAC Catalog 2017-09-27 2017-09-27 -51.06, 77.45, -51.06, 77.45 https://cmr.earthdata.nasa.gov/search/concepts/C2244300703-AMD_KOPRI.umm_json The first high resolution records of atmospherc trace metals for 1711~1969 were recovered from Greenland NEEM shallow ice core together with ions records. These records reveal increases in various atmospheric metals since the Industrial Revolution. Also, the comparion between these records and those from other Greenland ice cores represents regional differences in anthropogenic contributions. Researches for changes in atmospheric trace element over Greenland after the Industrial Revolution and contributions from natural/anthropogenic sources proprietary
KOPRI-KPDC-00000763_1 CPS2 AMD_KOPRI STAC Catalog 2013-02-20 2013-02-27 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244300790-AMD_KOPRI.umm_json CPS2 is termed as cell-protection substances 2 capable of protection of the cells and lowering freezing points below melting points. Antarctic freshwater green microalga, Chloromonas sp. was reported to produce and secrete CPS2. CPS2 genes will be utilized to protect the skin and tissue cells by applying any valuable products. proprietary
KOPRI-KPDC-00000764_1 Fatty acid content of polar microalgae and mesophilic Chlamydomonas CC125 using Gas Chromatography AMD_KOPRI STAC Catalog 2017-05-05 2017-06-04 -58.783333, -62.216667, 11.933333, 78.916667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300805-AMD_KOPRI.umm_json Fatty acid content of polar microalgae and mesophilic microalga Comparison and analysis of fatty acid content of both microalagae proprietary
KOPRI-KPDC-00000765_2 Climate Measurement Around the King Sejong Station, Antarctica in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244305675-AMD_KOPRI.umm_json Meteorological observation was carried out at the King Sejong Station in 2017. Observational elements are composed of wind, air temperature, relative humidity, station level atmospheric pressure, solar radiation, longwave radiation, UV radiation, and precipitation. Goals of this observation are 1) to understand meteorological phenomena and 2) to monitor climate change at Antarctic Peninsula. These data are recorded automatically then examined by meteorological expert at the station to be produced as a daily, monthly, and annual report. To understand weather phenomema and to monitor at Antarctic Peninsula proprietary
KOPRI-KPDC-00000766_1 Soil samples of the Antarctic King Sejong Station from Barton Peninsular collected in 2017 AMD_KOPRI STAC Catalog 2017-01-12 2017-01-27 -58.788436, -62.240056, -58.719694, -62.218583 https://cmr.earthdata.nasa.gov/search/concepts/C2244300827-AMD_KOPRI.umm_json Analysis of microbial community structure and diversity in soil samples of the Antarctic King Sejong Station from Barton Peninsular in Antarctica Investigation to the terrestrial biodiversity in Barton peninsular for the monitoring by environment change proprietary
-KOPRI-KPDC-00000767_1 2016-2017 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity AMD_KOPRI STAC Catalog 2016-01-14 2017-01-27 -58.788436, -62.240056, -58.719694, -62.218583 https://cmr.earthdata.nasa.gov/search/concepts/C2244300860-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2016 Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2016 proprietary
KOPRI-KPDC-00000767_1 2016-2017 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity ALL STAC Catalog 2016-01-14 2017-01-27 -58.788436, -62.240056, -58.719694, -62.218583 https://cmr.earthdata.nasa.gov/search/concepts/C2244300860-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2016 Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2016 proprietary
+KOPRI-KPDC-00000767_1 2016-2017 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity AMD_KOPRI STAC Catalog 2016-01-14 2017-01-27 -58.788436, -62.240056, -58.719694, -62.218583 https://cmr.earthdata.nasa.gov/search/concepts/C2244300860-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2016 Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2016 proprietary
KOPRI-KPDC-00000768_1 Rn gas data measured at KSG during 2013.2-2016.11 AMD_KOPRI STAC Catalog 2013-02-01 2016-11-24 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300905-AMD_KOPRI.umm_json Monitoring of Rn gas at KSG, Antarctica Investigation of air mass path moving to the KSG, Antarctica proprietary
KOPRI-KPDC-00000769_1 Simulated Atmospheric Wind at 850 hPa by Boundary Conditions during Last Glacial Maximum AMD_KOPRI STAC Catalog 2017-09-28 2017-09-28 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244301166-AMD_KOPRI.umm_json Atmospheric wind climatology at 850 hPa from the preindustrial simulation, Last Glacial Maximum simulation, LGM-SST simulation, LGM-SEAICE simulation, and LGM-topography simulation. To examine the responses of SH westerly winds to LGM boundary conditions using the state-of-the-art numerical model. To evaluate which boundary conditions are more important in the position and strength of SH westerly winds. proprietary
-KOPRI-KPDC-00000770_1 Aerosol Number Concentration (>10nm) from King Sejong Station collected in 2010-2016. ALL STAC Catalog 2010-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244298407-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 10nm in diameter Monitoring of Aerosol Number Concentration (>10nm) from King Sejong Station. proprietary
KOPRI-KPDC-00000770_1 Aerosol Number Concentration (>10nm) from King Sejong Station collected in 2010-2016. AMD_KOPRI STAC Catalog 2010-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244298407-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 10nm in diameter Monitoring of Aerosol Number Concentration (>10nm) from King Sejong Station. proprietary
+KOPRI-KPDC-00000770_1 Aerosol Number Concentration (>10nm) from King Sejong Station collected in 2010-2016. ALL STAC Catalog 2010-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244298407-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 10nm in diameter Monitoring of Aerosol Number Concentration (>10nm) from King Sejong Station. proprietary
KOPRI-KPDC-00000771_1 Italian Seismic Line 2017 AMD_KOPRI STAC Catalog 2017-02-02 2017-03-01 170.15625, -76.980149, -165.498047, -72.127936 https://cmr.earthdata.nasa.gov/search/concepts/C2244295712-AMD_KOPRI.umm_json Italian Seismic Line 2017, single channel seismic data, were collected during the 2016-2017 austral summer with the RV OGS Explora in the Ross Sea continental margin, Antarctica The major purpose of this survey is to investigate stratigraphy and sedimentary structure of the Ross Sea continental margin, Antarctica proprietary
KOPRI-KPDC-00000772_1 List of marine benthic invertebrate animal species around King Sejong Station (2017) AMD_KOPRI STAC Catalog 2017-09-29 2017-09-29 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295664-AMD_KOPRI.umm_json Survey of marine benthic invertebrate biota by diving around King Sejong Station Diversity of marine benthic invertebrates proprietary
KOPRI-KPDC-00000773_2 Comparison of diversity of ciliate between Jang Bogo Station in Antarctica and Korea using NGS technique (Site261_2014) AMD_KOPRI STAC Catalog 2021-08-02 2021-08-02 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244305169-AMD_KOPRI.umm_json Identification of ciliate diversity from Korea and Antarctica (Jang Bogo Station) Comparison of both data to know the specific ciliate in Antarctica proprietary
KOPRI-KPDC-00000774_1 ANA07C Multi-Channel Seismic Survey Lines AMD_KOPRI STAC Catalog 2017-02-04 2017-02-05 166, -75, 170, -74.5 https://cmr.earthdata.nasa.gov/search/concepts/C2244295683-AMD_KOPRI.umm_json Multi-Channel seismic data were collected during the 2016-2017 ANA07C cruise in the Ross Sea, Antarctic Ocean The major purpose of this survey is to investigate stratography and the structure of sediments across the Terror Rift, Antarctica. proprietary
-KOPRI-KPDC-00000775_1 Aerosol Size Distribution from King Sejong Station collected in 2010-2016. ALL STAC Catalog 2010-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244298745-AMD_KOPRI.umm_json SMPS(Scanning Mobility Particle Sizer) measures the aerosol size distribution from King Sejong Station in 2010-2016. Monitoring of aerosol size distribution from King Sejong Station. proprietary
KOPRI-KPDC-00000775_1 Aerosol Size Distribution from King Sejong Station collected in 2010-2016. AMD_KOPRI STAC Catalog 2010-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244298745-AMD_KOPRI.umm_json SMPS(Scanning Mobility Particle Sizer) measures the aerosol size distribution from King Sejong Station in 2010-2016. Monitoring of aerosol size distribution from King Sejong Station. proprietary
+KOPRI-KPDC-00000775_1 Aerosol Size Distribution from King Sejong Station collected in 2010-2016. ALL STAC Catalog 2010-01-01 2016-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244298745-AMD_KOPRI.umm_json SMPS(Scanning Mobility Particle Sizer) measures the aerosol size distribution from King Sejong Station in 2010-2016. Monitoring of aerosol size distribution from King Sejong Station. proprietary
KOPRI-KPDC-00000776_1 Meterological data at BearPeninsula in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-04-11 -115.56512, -74.1877, -115.56512, -74.1877 https://cmr.earthdata.nasa.gov/search/concepts/C2244300521-AMD_KOPRI.umm_json Meterological observation at BearPeninsula DATA. Continuous meteorological monitoring is required for deep understanding long-term trend of climate change in Antarctic region. Primary climate factors including solar radiation wind speed and direction, air temperature, pressure and relative humidity has been monitored using automatic weather monitoring system at Bear Peninsula. One hourly averaged data are stored at a data logger and an Argos Satellite transmitter is used to transmit daily data. The objectives of this monitoring are to record the past and current climate change through continuous operation of AWS, and to understand characteristics of meteorological phenomena at Bear Peninsula. Monitoring on meteorology at Bear Peninsula. proprietary
KOPRI-KPDC-00000777_2 Fossils from North Greenland (2016) AMD_KOPRI STAC Catalog 2016-07-25 2016-08-12 -42.228333, 82.793333, -42.228333, 82.793333 https://cmr.earthdata.nasa.gov/search/concepts/C2244305474-AMD_KOPRI.umm_json This entry includes the Early Cambrian fossils from Sirius Passet, North Greenland, collected by 2016 KOPRI expedition. The collections include various kinds of marine invertebrates, representing morphology of the early stage of animal evolution. Total of ca. 600 kg of fossils were collected during 2016 expedition. The Early Cambrian fossils will help us understand the rise of the first animals during the Cambrian Explosion. proprietary
KOPRI-KPDC-00000778_1 GV7_S2_dust data AMD_KOPRI STAC Catalog 2017-10-10 2017-10-10 158.85, -70.683333, 158.85, -70.683333 https://cmr.earthdata.nasa.gov/search/concepts/C2244300372-AMD_KOPRI.umm_json GV7_S2_dust data MS4_GV7 S22 dust data proprietary
@@ -9119,8 +9119,8 @@ KOPRI-KPDC-00000788_1 Doppler wind lidar data at DASAN Station in 2017 AMD_KOPRI
KOPRI-KPDC-00000789_2 Ionic species in shallow ice core from GV7 site excavated in 2013-2014 AMD_KOPRI STAC Catalog 2013-12-01 2014-01-10 158.866667, -70.683333, 158.866667, -70.683333 https://cmr.earthdata.nasa.gov/search/concepts/C2244305848-AMD_KOPRI.umm_json Analysis of ionic species in the section of ~15-78m depth of shallow ice core from GV7 site in Antarctica Reconstruction of ionic species to indicate paleo atmospheric environment/climate change of Northern Victoria Land, Antarctica proprietary
KOPRI-KPDC-00000790_3 Ionic species in the firn core sampled at Styx glacier in 2014-15 AMD_KOPRI STAC Catalog 2014-12-10 2015-01-02 163.766667, -73.9, 163.766667, -73.9 https://cmr.earthdata.nasa.gov/search/concepts/C2244307106-AMD_KOPRI.umm_json Analysis of ionic species in the upper section of firn core from Styx glacier in Antarctica Determination of ionic species in the upper section of firn core from Styx glacier in Antarctica proprietary
KOPRI-KPDC-00000791_1 Lichen samples from King George Island collected in 2016 and 2017 AMD_KOPRI STAC Catalog 2016-12-03 2017-02-01 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300628-AMD_KOPRI.umm_json Lichen samples from King George Island collected in 2016 and 2017 Ecophysiological study of lichen proprietary
-KOPRI-KPDC-00000792_3 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2016 ALL STAC Catalog 2016-01-10 2017-02-02 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244301575-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2016 Long term monitoring proprietary
KOPRI-KPDC-00000792_3 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2016 AMD_KOPRI STAC Catalog 2016-01-10 2017-02-02 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244301575-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2016 Long term monitoring proprietary
+KOPRI-KPDC-00000792_3 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2016 ALL STAC Catalog 2016-01-10 2017-02-02 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244301575-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2016 Long term monitoring proprietary
KOPRI-KPDC-00000793_2 Mesospheric temperature, Dasan Station, Arctic, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-10-02 11.932, 78.9233, 11.932, 78.9233 https://cmr.earthdata.nasa.gov/search/concepts/C2244306430-AMD_KOPRI.umm_json Mesospheric temperature and airglow intensity measured from Fourier Transform Spectrometer (FTS) at Dasan Station, Arctic Study of the long-term trend of mesospheric temperature in the northern high latitude proprietary
KOPRI-KPDC-00000794_3 Neutral wind and temperature from FPI, Dasan Station, Arctic, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-03-22 11.9333, 78.9167, 11.9333, 78.9167 https://cmr.earthdata.nasa.gov/search/concepts/C2244306038-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from Fabry-Perot Interferometer (FPI) at Dasan Station, Arctic Study of the atmosphere wave activities in the upper atmosphere in the northern high-latitude proprietary
KOPRI-KPDC-00000795_2 Ionospheric scintillation, Dasan Station, Arctic, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-10-08 11.932, 78.9233, 11.932, 78.9233 https://cmr.earthdata.nasa.gov/search/concepts/C2244307129-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Dasan Station, Arctic Study of the ionospheric irregularity in the northern high latitude proprietary
@@ -9208,8 +9208,8 @@ KOPRI-KPDC-00000875_1 Eddy covariance data at DASAN Station in 2016 AMD_KOPRI ST
KOPRI-KPDC-00000876_1 Eddy covariance data at DASAN Station in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-09-19 11.865833, 78.921944, 11.865833, 78.921944 https://cmr.earthdata.nasa.gov/search/concepts/C2244295705-AMD_KOPRI.umm_json Turbulent fluxes of momentum, heat, water vapor, and CO2 had been measured in 2017 at Ny-Alesund where Arctic DASAN station is located. Eddy covariance system, consisting of 3-D sonic anemometer and open-path CO2/H2O gas analyzer was used for the measurement. Data were recorded on a data logger with sampling rate of 10 Hz. To monitor and understand energy/water/green-house-gas flux at DASAN Station proprietary
KOPRI-KPDC-00000877_1 CCN(Cloud Condensation Nuclei) data at Zeppelin station in January-November, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-11-30 11.888889, 78.906667, 11.888889, 78.906667 https://cmr.earthdata.nasa.gov/search/concepts/C2244295663-AMD_KOPRI.umm_json The CCNC(Cloud Condensation Nuclei Counter) is used to measure atmospheric CCN(Cloud Condensation Nuclei) concentration over Zeppelin station. Monitoring of CCN(Cloud Condensation Nuclei) concentration over Zeppelin station proprietary
KOPRI-KPDC-00000878_1 LED NDVI measured at Council site of Alaska in 2016 AMD_KOPRI STAC Catalog 2017-12-05 2017-12-05 -163.711, 64.844, -163.711, 64.844 https://cmr.earthdata.nasa.gov/search/concepts/C2244301187-AMD_KOPRI.umm_json A vegetation index NDVI was measured during growing season at the Council site, 70-miles northeast from the Nome, Alaska. The sensor was developed by Seoul National University (Prof. Young-Ryul Ryu) and provided for in-situ installation. The sensor is composed of one pair of upward/downward looking LEDs to obtain reflectivity in each bandwidth. We can calculate NDVI (normalized difference vegetation index) using this sensor to monitor vegetation activity. To monitor high-temporal variation of vegetaion activity at permafrost region, west Alaska. proprietary
-KOPRI-KPDC-00000879_1 Air temperature and air humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2017 ALL STAC Catalog 2016-06-19 2017-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300975-AMD_KOPRI.umm_json Micro-climate data (air temperature and humidity for 20 cm height) from climate manipulation (combination of warming and precipitation) plots for 1 year (2016.06~2017.06) were collected. To monitor the changes in micro-climate properties of air by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00000879_1 Air temperature and air humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2017 AMD_KOPRI STAC Catalog 2016-06-19 2017-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300975-AMD_KOPRI.umm_json Micro-climate data (air temperature and humidity for 20 cm height) from climate manipulation (combination of warming and precipitation) plots for 1 year (2016.06~2017.06) were collected. To monitor the changes in micro-climate properties of air by increasing temperature by open top chambers and increasing precipitation proprietary
+KOPRI-KPDC-00000879_1 Air temperature and air humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2017 ALL STAC Catalog 2016-06-19 2017-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300975-AMD_KOPRI.umm_json Micro-climate data (air temperature and humidity for 20 cm height) from climate manipulation (combination of warming and precipitation) plots for 1 year (2016.06~2017.06) were collected. To monitor the changes in micro-climate properties of air by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00000880_1 Soil moisture and soil temperature data collected from climate manipulation plots in Cambridge Bay, Canada in 2017 AMD_KOPRI STAC Catalog 2016-06-19 2017-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300926-AMD_KOPRI.umm_json Micro-climate data (soil volumetric content and temperature for 5 cm depth) from climate manipulation (combination of warming and precipitation) plots for 1 year (2016.06~2017.06) were collected. To monitor the changes in micro-climate properties in soil by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00000881_1 CO2 auto-chamber data of Council site in 2017 AMD_KOPRI STAC Catalog 2016-09-22 2017-09-13 -163.705333, 64.843333, -163.705333, 64.843333 https://cmr.earthdata.nasa.gov/search/concepts/C2244301146-AMD_KOPRI.umm_json CO2 fluxes at dominant vegetation types were measured using custom-made auto-chamber system during summertime in 2017 at Council site, Alaska. Auto-chamber system was consisted of a gas-analyzer (LI-840) connected with 15-chambers, which are controlled by electronic board with 225-second opening for each chamber. As a result, whole-chamber cycle is completed in a hour. CO2 data is recorded every 10-second by CR1000 logger. Also, soil temperature and moisture at 5-cm depth at each chamber were recorded at 10-min interval. To monitor and understand CO2 flux of dominant vegetation types of Alaska permafrost site. proprietary
KOPRI-KPDC-00000882_1 Upper air observation data at Jang Bogo Station in 2016 AMD_KOPRI STAC Catalog 2016-02-01 2016-12-21 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244300540-AMD_KOPRI.umm_json Regular upper air observation is made once a day at 00 UTC from February to November by using auto and manual lauch of radio sondes. Data of pressure, temperature, relative humidity, wind speed and wind direction are sampled and recorded every two-second. The minimum observation height is over 20 km. Monitoring of changes in meteorological variables with altitude over Jang Bogo station proprietary
@@ -9278,8 +9278,8 @@ KOPRI-KPDC-00000944_1 Moderate Resolution Imaging Spectroradiometer in Arctic (M
KOPRI-KPDC-00000945_1 Moderate Resolution Imaging Spectroradiometer in Antarctic (MODIS) / Aqua, 2015 AMD_KOPRI STAC Catalog 2015-01-01 2015-12-31 180, -90, -180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2244297229-AMD_KOPRI.umm_json MODIS is a 36-band spectroradiometer measuring visible and infrared radiation and obtaining data in Antarctic. The first MODIS instrument was launched on board the Terra satellite in December 1999, and the second was launched on Aqua in May 2002. Derive products ranging from vegetation, land surface cover, and ocean chlorophyll fluorescence to cloud and aerosol properties, fire occurrence, snow cover on the land, and sea ice cover on the oceans. proprietary
KOPRI-KPDC-00000946_1 Advanced TIROS Operational Vertical Sounder (ATOVS) around the Jang Bogo Station, 2015-2016 ALL STAC Catalog 2015-03-01 2016-02-15 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244297301-AMD_KOPRI.umm_json The Advanced TIROS Operational Vertical Sounder (ATOVS) consists of High Resolution Infrared Radiation Sounder (HIRS), the Advanced Microwave Sounding Unit-A (AMSU-A) and AMSU-B for retrieving temperature, humidity and ozone sounding in all weather conditions. The data were obtained around the Jang Bogo Station in Antarctic. To derive products including cloud, ozone, surface elevation, surface pressure, temperature around the Jang Bogo Station. proprietary
KOPRI-KPDC-00000946_1 Advanced TIROS Operational Vertical Sounder (ATOVS) around the Jang Bogo Station, 2015-2016 AMD_KOPRI STAC Catalog 2015-03-01 2016-02-15 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244297301-AMD_KOPRI.umm_json The Advanced TIROS Operational Vertical Sounder (ATOVS) consists of High Resolution Infrared Radiation Sounder (HIRS), the Advanced Microwave Sounding Unit-A (AMSU-A) and AMSU-B for retrieving temperature, humidity and ozone sounding in all weather conditions. The data were obtained around the Jang Bogo Station in Antarctic. To derive products including cloud, ozone, surface elevation, surface pressure, temperature around the Jang Bogo Station. proprietary
-KOPRI-KPDC-00000947_1 Advanced Very High Resolution Radiometer (AVHRR) around the Jang Bogo Station, 2015-2016 AMD_KOPRI STAC Catalog 2015-03-03 2016-02-15 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244297622-AMD_KOPRI.umm_json The AVHRR is a six channel scanning radiometer providing three solar channels in the visible-near infrared region and three thermal infrared channels and obtained data around the Jang Bogo Station in Antarctic. To derive products including cloud cover, surface temperature, land-water boundaries, snow and ice detection around the Jang Bogo Station. proprietary
KOPRI-KPDC-00000947_1 Advanced Very High Resolution Radiometer (AVHRR) around the Jang Bogo Station, 2015-2016 ALL STAC Catalog 2015-03-03 2016-02-15 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244297622-AMD_KOPRI.umm_json The AVHRR is a six channel scanning radiometer providing three solar channels in the visible-near infrared region and three thermal infrared channels and obtained data around the Jang Bogo Station in Antarctic. To derive products including cloud cover, surface temperature, land-water boundaries, snow and ice detection around the Jang Bogo Station. proprietary
+KOPRI-KPDC-00000947_1 Advanced Very High Resolution Radiometer (AVHRR) around the Jang Bogo Station, 2015-2016 AMD_KOPRI STAC Catalog 2015-03-03 2016-02-15 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244297622-AMD_KOPRI.umm_json The AVHRR is a six channel scanning radiometer providing three solar channels in the visible-near infrared region and three thermal infrared channels and obtained data around the Jang Bogo Station in Antarctic. To derive products including cloud cover, surface temperature, land-water boundaries, snow and ice detection around the Jang Bogo Station. proprietary
KOPRI-KPDC-00000948_1 Moderate Resolution Imaging Spectroradiometer (MODIS) around the Jang Bogo Station, 2015-2016 AMD_KOPRI STAC Catalog 2015-03-30 2016-02-03 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244297939-AMD_KOPRI.umm_json MODIS is a 36-band spectroradiometer measuring visible and infrared radiation and obtaining data around the Jang Bogo Station in Antarctic. To derive products including vegetation, land surface cover, and ocean chlorophyll fluorescence to cloud and aerosol properties, fire occurrence, snow cover on the land, and sea ice cover on the oceans around the Jang Bogo Station. proprietary
KOPRI-KPDC-00000949_1 Medium Resolution Spectral Imager (MERSI) around the Jang Bogo Station, 2015-2016 AMD_KOPRI STAC Catalog 2015-10-31 2015-11-09 164.233333, -74.616667, 164.233333, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244298276-AMD_KOPRI.umm_json MERSI is a scanner carried aboard the third FengYun (FY-3) series of meteorological satellites launched by China and obtained data around the Jang Bogo Station in Antarctic. To derive products including cloud, vegetation, snow and ice, ocean color around the Jang Bogo Station. proprietary
KOPRI-KPDC-00000952_1 Moderate Resolution Imaging Spectroradiometer in the Arctic (MODIS) / Aqua, 2012 AMD_KOPRI STAC Catalog 2012-01-01 2012-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2244298621-AMD_KOPRI.umm_json MODIS is a 36-band spectroradiometer measuring visible and infrared radiation and obtaining data in Arctic. The first MODIS instrument was launched on board the Aqua satellite in May 2002. Derive products ranging from vegetation, land surface cover, and ocean chlorophyll fluorescence to cloud and aerosol properties, fire occurrence, snow cover on the land, and sea ice cover on the oceans. proprietary
@@ -9329,8 +9329,8 @@ KOPRI-KPDC-00000995_1 Sea Ice from SW of James Ross Island AMD_KOPRI STAC Catalo
KOPRI-KPDC-00000996_1 Sea Ice from W of James Ross Island AMD_KOPRI STAC Catalog 2018-04-20 -58.543322, -64.147707, -58.543322, -64.147707 https://cmr.earthdata.nasa.gov/search/concepts/C2244299635-AMD_KOPRI.umm_json 2018 W of James Ross Island Sea Ice, Antarctic Climate change observation proprietary
KOPRI-KPDC-00000997_1 Identification of growth rate of Antarctic terrestrial ciliates based on temperature around King Sejong Station (2017/18) AMD_KOPRI STAC Catalog 2017-12-06 2018-01-24 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244300273-AMD_KOPRI.umm_json Identification of growth rate of ciliates from Barton Peninsular, South Shetland Islands in Antarctica To show the growth rate of ciliates based on temperature in Antarctica proprietary
KOPRI-KPDC-00000998_2 ANA08C Marine Magnetic Data AMD_KOPRI STAC Catalog 2018-03-13 164.4, -75.5, 165.9, -75.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244301255-AMD_KOPRI.umm_json Marine magnetic data were collected during the ANA08C Expedition in the 2017-2018 austral summer in the Ross Sea, Antarctica proprietary
-KOPRI-KPDC-00000999_2 2018 Multibeam bathymetry data in the Ross Sea, Antarctica AMD_KOPRI STAC Catalog 2018-03-13 164.4, -75.5, 165.9, -75.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244301265-AMD_KOPRI.umm_json Multibeam bathymetry data were collected during the ANA08C Expedition in the Ross Sea, Antarctica proprietary
KOPRI-KPDC-00000999_2 2018 Multibeam bathymetry data in the Ross Sea, Antarctica ALL STAC Catalog 2018-03-13 164.4, -75.5, 165.9, -75.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244301265-AMD_KOPRI.umm_json Multibeam bathymetry data were collected during the ANA08C Expedition in the Ross Sea, Antarctica proprietary
+KOPRI-KPDC-00000999_2 2018 Multibeam bathymetry data in the Ross Sea, Antarctica AMD_KOPRI STAC Catalog 2018-03-13 164.4, -75.5, 165.9, -75.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244301265-AMD_KOPRI.umm_json Multibeam bathymetry data were collected during the ANA08C Expedition in the Ross Sea, Antarctica proprietary
KOPRI-KPDC-00001000_2 Sub-bottom profile data in the Ross Sea, Antarctica AMD_KOPRI STAC Catalog 2018-03-13 164.4, -75.5, 165.9, -75.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244301275-AMD_KOPRI.umm_json Sub-bottom profile (SBP) data were collected during the ANA08C Expedition in the Ross Sea, Antarctica proprietary
KOPRI-KPDC-00001001_1 De novo transcriptome assembly of the moss Sanionia uncinata in response to relative water content reduction in the Antarctic natural habitat AMD_KOPRI STAC Catalog 2016-03-21 -58.771667, -62.220278, -58.771667, -62.220278 https://cmr.earthdata.nasa.gov/search/concepts/C2244300607-AMD_KOPRI.umm_json Despite the importance, the molecular responses of S. uncinata related to the decrease in water availability in the long-term future have not yet been identified. To explain physiological and molecular change induced by dehydration, we performed de novo transcriptome assembly. Using the short-read assembly program, 32,100 unigenes were assembled with an N50 of 1,296 bp. proprietary
KOPRI-KPDC-00001002_1 EGRIP SP TE AMD_KOPRI STAC Catalog 2018-06-01 2018-06-30 -35.9915, 75.6268, -35.9915, 75.6268 https://cmr.earthdata.nasa.gov/search/concepts/C2244300642-AMD_KOPRI.umm_json Greenland EastGRIP 2017 snow pit trace metals Investigation of seasonal changes in atmospheric trace metals over northeastern Greenland proprietary
@@ -9434,21 +9434,21 @@ KOPRI-KPDC-00001098_2 Marine algal diversity and subtidal distribution in Maxwel
KOPRI-KPDC-00001099_5 Neutral wind and temperature from Meteor Radar, King Sejong Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 -58.7885, -62.2245, -58.7885, -62.2245 https://cmr.earthdata.nasa.gov/search/concepts/C2244307224-AMD_KOPRI.umm_json Neutral wind (80 – 100 km) and temperature (~90 km) measured from Meteor Radar (MR) at King Sejong Station, Antarctica Study of the atmosphere wave activities in the mesosphere and lower-thermosphere (MLT) over the southern high-latitude proprietary
KOPRI-KPDC-00001100_3 Ionospheric scintillation, King Sejong Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 -58.7885, -62.2245, -58.7885, -62.2245 https://cmr.earthdata.nasa.gov/search/concepts/C2244306086-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at King Sejong Station (KSS), Antarctica Study of the ionospheric irregularity in the southern high latitude proprietary
KOPRI-KPDC-00001101_5 Neutral wind and temperature from FPI, King Sejong Station, Antarctica, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-12-31 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244307207-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from Fabry-Perot Interferometer (FPI) at KSS station, Antarctica Study of the atmosphere wave activities in the upper atmosphere in the southern high-latitude proprietary
-KOPRI-KPDC-00001102_3 All-Sky airglow image, King Sejong Station, Antarctica, 2017 ALL STAC Catalog 2017-01-01 2017-10-01 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244307078-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high-latitude proprietary
KOPRI-KPDC-00001102_3 All-Sky airglow image, King Sejong Station, Antarctica, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-10-01 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244307078-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high-latitude proprietary
+KOPRI-KPDC-00001102_3 All-Sky airglow image, King Sejong Station, Antarctica, 2017 ALL STAC Catalog 2017-01-01 2017-10-01 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244307078-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high-latitude proprietary
KOPRI-KPDC-00001103_3 All-Sky airglow image, King Sejong Station, Antarctica, 2018 ALL STAC Catalog 2018-01-01 2018-10-01 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244306042-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001103_3 All-Sky airglow image, King Sejong Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244306042-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001104_3 Electron density and plasma drift, Jang Bogo Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-02 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306739-AMD_KOPRI.umm_json Electron density profile, plasma drift velocity, and ionospheric tilt information measured from VIPIR (ionosonde) at Jang Bogo Station, Antarctica Study of the ionospheric characteristics in the southern high latitude proprietary
KOPRI-KPDC-00001105_4 Neutral wind and temperature from FPI, Jang Bogo Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-03-06 2018-10-01 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306027-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from Fabry-Perot Interferometer (FPI) at Jang Bogo Station (JBS), Antarctica Study of the atmosphere wave activities in the upper atmosphere in the southern high-latitude proprietary
KOPRI-KPDC-00001106_3 Neutron count, Jang Bogo Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-09-30 164.14, -74.6202, 164.2273, -74.37 https://cmr.earthdata.nasa.gov/search/concepts/C2244306728-AMD_KOPRI.umm_json Cosmic ray origin neutron count measured from neutron monitor at Jang Bogo Station, Antarctica Study of the variation of neutron count in the southern high latitude proprietary
KOPRI-KPDC-00001107_4 Ionospheric scintillation, Jang Bogo Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306588-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Jang Bogo Station, Antarctica Study of the ionospheric irregularity in the southern high latitude proprietary
-KOPRI-KPDC-00001108_4 All-sky aurora (proton) image at Jang Bogo Station, Antarctica, 2018 ALL STAC Catalog 2018-01-01 2018-12-31 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306540-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at Jang Bogo Station, Antarctica Study of the aurora characteristics in the southern high latitude proprietary
KOPRI-KPDC-00001108_4 All-sky aurora (proton) image at Jang Bogo Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-12-31 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306540-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at Jang Bogo Station, Antarctica Study of the aurora characteristics in the southern high latitude proprietary
+KOPRI-KPDC-00001108_4 All-sky aurora (proton) image at Jang Bogo Station, Antarctica, 2018 ALL STAC Catalog 2018-01-01 2018-12-31 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306540-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at Jang Bogo Station, Antarctica Study of the aurora characteristics in the southern high latitude proprietary
KOPRI-KPDC-00001109_4 Geomagnetic field, Jang Bogo Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-09-30 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306279-AMD_KOPRI.umm_json Variation of geomagnetic field measured from search-coil magnetometer (SCM) at Jang Bogo Station, antarctica Study of the activity of ultra low frequency (ULF) wave in the southern high latitude proprietary
KOPRI-KPDC-00001110_4 Neutral wind and temperature from FPI, Dasan Station, Arctic, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-03-22 11.836, 78.938, 11.836, 78.938 https://cmr.earthdata.nasa.gov/search/concepts/C2244307214-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from Febry-Perot interferometer (FPI) at Dasan station, Arctic Study of the atmosphere wave activities in the upper atmosphere in the southern/northern high-latitude proprietary
KOPRI-KPDC-00001111_4 Ionospheric scintillation, Dasan Station, Arctic, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-08 11.932, 78.9233, 11.932, 78.9233 https://cmr.earthdata.nasa.gov/search/concepts/C2244306245-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Dasan Station, Arctica Study of the ionospheric irregularity in the northern high latitude proprietary
-KOPRI-KPDC-00001112_4 All-sky aurora (proton) image, Longyearbyen, Norway, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-02-28 16.040746, 78.147909, 16.040746, 78.147909 https://cmr.earthdata.nasa.gov/search/concepts/C2244306694-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at Kjell Henriksen Observatory (KHO), Longyearbyen, Norway Study of the aurora (proton) characteristics in the northern high latitude proprietary
KOPRI-KPDC-00001112_4 All-sky aurora (proton) image, Longyearbyen, Norway, 2018 ALL STAC Catalog 2018-01-01 2018-02-28 16.040746, 78.147909, 16.040746, 78.147909 https://cmr.earthdata.nasa.gov/search/concepts/C2244306694-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at Kjell Henriksen Observatory (KHO), Longyearbyen, Norway Study of the aurora (proton) characteristics in the northern high latitude proprietary
+KOPRI-KPDC-00001112_4 All-sky aurora (proton) image, Longyearbyen, Norway, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-02-28 16.040746, 78.147909, 16.040746, 78.147909 https://cmr.earthdata.nasa.gov/search/concepts/C2244306694-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at Kjell Henriksen Observatory (KHO), Longyearbyen, Norway Study of the aurora (proton) characteristics in the northern high latitude proprietary
KOPRI-KPDC-00001113_3 Mesospheric temperature, Kiruna, Sweden, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 21.03, 67.872, 21.03, 67.872 https://cmr.earthdata.nasa.gov/search/concepts/C2244306621-AMD_KOPRI.umm_json Mesospheric temperature and airglow intensity measured from Fourier Transform Spectrometer (FTS) at Kiruna, Sweden Study of the long-term trend of mesospheric temperature in the northern high latitude proprietary
KOPRI-KPDC-00001114_4 Neutral wind and temperature from FPI, Kiruna, Sweden, 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 21.03, 67.872, 21.03, 67.872 https://cmr.earthdata.nasa.gov/search/concepts/C2244307306-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from Fabry-Perot Interferometer (FPI) at Kiruna, Sweden Study of the atmosphere wave activities in the upper atmosphere in the northern high-latitude proprietary
KOPRI-KPDC-00001115_2 Ionospheric total electron content monitoring system over Kiruna, Sweden at 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-10-01 21.03, 67.53, 21.03, 67.53 https://cmr.earthdata.nasa.gov/search/concepts/C2244305498-AMD_KOPRI.umm_json Total electron content in the ionosphere over Kiruna, Sweden Study of the statistical characteristics of ionosphere in northern high latitude proprietary
@@ -9466,8 +9466,8 @@ KOPRI-KPDC-00001125_4 NanoSMPS particle number concentration in 2017 AMD_KOPRI S
KOPRI-KPDC-00001126_5 NanoSMPS particle number concentration in 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-12-31 11.894, 78.908, 11.894, 78.908 https://cmr.earthdata.nasa.gov/search/concepts/C2244301557-AMD_KOPRI.umm_json The nano-SMPS (nano-Scanning Mobility Particle Sizer) involving Classifier (3080, TSI), nano-DMA (Differential Mobility Analyzer) (3081, TSI, USA), and UCPC (Ultra-Condensation Particle Counter) (3776, TSI, USA) is an important instrument to measure nano-size aerosols (3 to 60 nm). From Oct 2016 to Feb 2020, the nano-SMPS has been operating successfully at Zeppelin Mt, Ny-Alesund in Norway. Based-on the size distribution with particle number concentration in range of 3-60 nm of nanoSMPS, we will invest time-variation of the new particle formation, Climatological circle, and so on in Arctic region. proprietary
KOPRI-KPDC-00001127_3 NanoSMPS particle number concentration in 2016 AMD_KOPRI STAC Catalog 2016-10-01 2016-12-31 11.894, 78.908, 11.894, 78.908 https://cmr.earthdata.nasa.gov/search/concepts/C2244301534-AMD_KOPRI.umm_json The nano-SMPS (nano-Scanning Mobility Particle Sizer) involving Classifier (3080, TSI), nano-DMA (Differential Mobility Analyzer) (3081, TSI, USA), and UCPC (Ultra-Condensation Particle Counter) (3776, TSI, USA) is an important instrument to measure nano-size aerosols (3 to 60 nm). From Oct 2016 to Feb 2020, the nano-SMPS has been operating successfully at Zeppelin Mt, Ny-Alesund in Norway. Based-on the size distribution with particle number concentration in range of 3-60 nm of nanoSMPS, we will invest time-variation of the new particle formation, Climatological circle, and so on in Arctic region. proprietary
KOPRI-KPDC-00001128_1 Soil moisture and soil temperature data collected from climate manipulation plots in Cambridge Bay, Canada in 2018 AMD_KOPRI STAC Catalog 2017-06-19 2018-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300912-AMD_KOPRI.umm_json Micro-climate data (soil volumetric content and temperature for 5 cm depth) from climate manipulation (combination of warming and precipitation) plots for 1 year (2017.06 ~ 2018. 06) were collected. To monitor the changes in micro-climate properties in soil by increasing temperature by open top chambers and increasing precipitation proprietary
-KOPRI-KPDC-00001129_1 Air temperature and humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2018 AMD_KOPRI STAC Catalog 2017-06-19 2018-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300871-AMD_KOPRI.umm_json Micro-climate data (air temperature and humidity for 20 cm height) from climate manipulation (combination of warming and precipitation) plots for 1 year (2017.06~2018.06) were collected To monitor the changes in micro-climate properties of air by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00001129_1 Air temperature and humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2018 ALL STAC Catalog 2017-06-19 2018-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300871-AMD_KOPRI.umm_json Micro-climate data (air temperature and humidity for 20 cm height) from climate manipulation (combination of warming and precipitation) plots for 1 year (2017.06~2018.06) were collected To monitor the changes in micro-climate properties of air by increasing temperature by open top chambers and increasing precipitation proprietary
+KOPRI-KPDC-00001129_1 Air temperature and humidity data collected from climate manipulation plots in Cambridge Bay, Canada in 2018 AMD_KOPRI STAC Catalog 2017-06-19 2018-06-18 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300871-AMD_KOPRI.umm_json Micro-climate data (air temperature and humidity for 20 cm height) from climate manipulation (combination of warming and precipitation) plots for 1 year (2017.06~2018.06) were collected To monitor the changes in micro-climate properties of air by increasing temperature by open top chambers and increasing precipitation proprietary
KOPRI-KPDC-00001130_1 Atmospheric DMS mixing ratio measured from Storhofdi, Iceland in 2017-2018. AMD_KOPRI STAC Catalog 2017-04-04 2018-08-18 -20.29, 63.4, -20.29, 63.4 https://cmr.earthdata.nasa.gov/search/concepts/C2244300807-AMD_KOPRI.umm_json Custum-made DMS analyzer was installed at the Storhofdi observatory, Iceland, and monitored the atmospheric DMS mixing ratio in 2017-208. Analyzing in-situ DMs mixing ratio Storhofdi, Iceland. proprietary
KOPRI-KPDC-00001131_1 NDVI data collected from climate manipulation plots in Cambridge Bay, Canada in 2018 AMD_KOPRI STAC Catalog 2018-07-04 2018-09-05 -105.133333, 69.1, -105.133333, 69.1 https://cmr.earthdata.nasa.gov/search/concepts/C2244300832-AMD_KOPRI.umm_json NDVI(Normalized Difference Vegetation Index) from climate manipulation (increasing snow cover) plot for 2 months (2018.7.4 ~ 9.5) were collected proprietary
KOPRI-KPDC-00001132_1 Eddy covariance data of Canada permafrost site in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-12-31 -105.058917, 69.13025, -105.058917, 69.13025 https://cmr.earthdata.nasa.gov/search/concepts/C2244301100-AMD_KOPRI.umm_json Turbulent fluxes of momentum, heat, water vapor, CO2 had been measured during summertime in 2017 at Cambridge bay, Canada. Eddy covariance system, consisting of 3-D sonic anemometer, open-path CO2/H2O gas analyzer and open-path CH4 gas analyzer was used for the measurement. Data were recorded with CR3000 logger with sampling rate of 10 Hz. To monitor and understand energy/water/green-house-gas flux over permafrost region proprietary
@@ -9495,8 +9495,8 @@ KOPRI-KPDC-00001153_2 Profile of Meteorological data at the Jang Bogo Station, A
KOPRI-KPDC-00001154_2 Data for observation and prediction to model responses of Antarctic hairgrass AMD_KOPRI STAC Catalog 2017-01-01 2018-12-31 -58.771667, -62.220278, -58.771667, -62.220278 https://cmr.earthdata.nasa.gov/search/concepts/C2244303875-AMD_KOPRI.umm_json In order to model the distribution and physiological response of Antarctic hairgrass, we obtained 2,127 data points (Po, average 118.7) of distributions and physiological response observations in the vicinity of Sejong Station, King George Island, Antarctica in 2017. In addition, we obtained 2,127 data points for this species. With these data, the prediction accuracy of the model acquired in 2018 was 83.3%. proprietary
KOPRI-KPDC-00001155_2 Data for observation and prediction to model responses of Antarctic pearlwort AMD_KOPRI STAC Catalog 2016-01-01 2017-12-31 -58.771667, -62.220278, -58.771667, -62.220278 https://cmr.earthdata.nasa.gov/search/concepts/C2244303548-AMD_KOPRI.umm_json In order to model the distribution and physiological response of Antarctic pearlwort, we obtained 1,150 data points (Po, average 96.7) of distributions and physiological response observations in the vicinity of Sejong Station, King George Island, Antarctica in 2016. In addition, we obtained 1,150 data points for this species. With these data, the prediction accuracy of the model acquired in 2017 was 78.84%. proprietary
KOPRI-KPDC-00001156_4 Neutral wind and temperature from FPI, King Sejong Station, Antarctica, 2018 AMD_KOPRI STAC Catalog 2018-03-01 2018-10-31 -58.7766, -62.2206, -58.7766, -62.2206 https://cmr.earthdata.nasa.gov/search/concepts/C2244306106-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from Fabry-Perot Interferometer (FPI) at KSS station, Antarctica Study of the atmosphere wave activities in the upper atmosphere in the southern high-latitude proprietary
-KOPRI-KPDC-00001157_3 All-Sky airglow image, Jang Bogo Station, Antarctica, 2017 ALL STAC Catalog 2017-01-01 2017-10-01 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306682-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at Jang Bogo Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001157_3 All-Sky airglow image, Jang Bogo Station, Antarctica, 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-10-01 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306682-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at Jang Bogo Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
+KOPRI-KPDC-00001157_3 All-Sky airglow image, Jang Bogo Station, Antarctica, 2017 ALL STAC Catalog 2017-01-01 2017-10-01 164.2273, -74.6202, 164.2273, -74.6202 https://cmr.earthdata.nasa.gov/search/concepts/C2244306682-AMD_KOPRI.umm_json Airglow (OI 557.7nm, OI 630.0nm, Na 589.7nm, OH Meinel band) image measured from all-sky camera at Jang Bogo Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001158_1 Upper O3 observation data at Jang Bogo Station in 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-09-30 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244297194-AMD_KOPRI.umm_json Regular upper O3 observation is made once a week from SEP to NOV, and a month except for the preceding period. O3 is sampled and recorded every a second. Monitoring of changes in meteorological variables (O3) with altitude over Jang Bogo station. proprietary
KOPRI-KPDC-00001159_1 O3 observation data using BREWER at Jang Bogo Station in 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-09-30 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244299602-AMD_KOPRI.umm_json The Brewer Ozone spectroscopy (BREWER) accurately measures the amount of light from a certain wavelength (286.5 nm to 363 nm) that absorbs ozone and is a total of ozone. Monitoring of changes in meteorological variables (O3) at Jang Bogo station. proprietary
KOPRI-KPDC-00001160_2 Upper air observation data at Jang Bogo Station during YOPP-SH(Year of Polar Prediction-Southern Hemisphere) in 2018/19 AMD_KOPRI STAC Catalog 2018-11-16 2019-02-11 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244296754-AMD_KOPRI.umm_json Upper air observation is made once a day at 1800UTC during YOPP-SH (from 16 NOV. 2018 and 11 FEB 2019) by using auto and manual lauch of radio sondes. Data of pressure, temperature, relative humidity, wind speed and wind direction are sampled and recorded every a second. The minimum observation height is over 20 km. Monitoring of changes in meteorological variables with altitude over Jang Bogo station proprietary
@@ -9554,8 +9554,8 @@ KOPRI-KPDC-00001216_3 Cloud Condensation Nuclei concentration at King Sejong Sta
KOPRI-KPDC-00001217_3 Cloud Condensation Nuclei concentration at King Sejong Station collected in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244302084-AMD_KOPRI.umm_json Cloud Condensation Nuclei Counter(CCNC) measures the number of aerosol CCN Monitoring of Aerosol CCN from King Sejong Station. proprietary
KOPRI-KPDC-00001218_3 Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2018 AMD_KOPRI STAC Catalog 2018-01-01 2018-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244301229-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 2.5 and 10nm in diameter Monitoring of Aerosol Number Concentration (>2.5 and 10nm) at King Sejong Station. proprietary
KOPRI-KPDC-00001218_3 Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2018 ALL STAC Catalog 2018-01-01 2018-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244301229-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 2.5 and 10nm in diameter Monitoring of Aerosol Number Concentration (>2.5 and 10nm) at King Sejong Station. proprietary
-KOPRI-KPDC-00001219_3 Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244301244-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 2.5 and 10nm in diameter Monitoring of Aerosol Number Concentration (>2.5 and 10nm) at King Sejong Station. proprietary
KOPRI-KPDC-00001219_3 Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2017 ALL STAC Catalog 2017-01-01 2017-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244301244-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 2.5 and 10nm in diameter Monitoring of Aerosol Number Concentration (>2.5 and 10nm) at King Sejong Station. proprietary
+KOPRI-KPDC-00001219_3 Aerosol Number Concentration (> 2.5 and 10nm) from King Sejong Station collected in 2017 AMD_KOPRI STAC Catalog 2017-01-01 2017-12-31 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244301244-AMD_KOPRI.umm_json Condensation particle counter measures the number of aerosol condensation particles of > 2.5 and 10nm in diameter Monitoring of Aerosol Number Concentration (>2.5 and 10nm) at King Sejong Station. proprietary
KOPRI-KPDC-00001220_2 Aerosol Size Distribution from King Sejong Station collected in 2019. AMD_KOPRI STAC Catalog 2019-01-01 2019-06-30 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244305477-AMD_KOPRI.umm_json SMPS(Scanning Mobility Particle Sizer) measures the aerosol size distribution from King Sejong Station in 2010-2016. Monitoring of aerosol size distribution from King Sejong Station. proprietary
KOPRI-KPDC-00001220_2 Aerosol Size Distribution from King Sejong Station collected in 2019. ALL STAC Catalog 2019-01-01 2019-06-30 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244305477-AMD_KOPRI.umm_json SMPS(Scanning Mobility Particle Sizer) measures the aerosol size distribution from King Sejong Station in 2010-2016. Monitoring of aerosol size distribution from King Sejong Station. proprietary
KOPRI-KPDC-00001221_3 KPDC MAXDOAS For Halogen gases at KSJ 2018-2019 AMD_KOPRI STAC Catalog 2018-12-09 2019-06-12 -58.78, -62.22, -58.78, -62.22 https://cmr.earthdata.nasa.gov/search/concepts/C2244306023-AMD_KOPRI.umm_json Spectrum intensity for gaseous halogen compounds measured at King Sejong Station in 2018-2019 (from 9 Dec 2018 to 12 June 2019) by using Multi-Axis Differential Optic Absorption Spectroscopy (Max-DOAS) Monitoring of atmospheric halogen compounds at King Sejong Station. proprietary
@@ -9597,8 +9597,8 @@ KOPRI-KPDC-00001261_1 Phytoplankton abundance in the Sea water of the Kongsfjord
KOPRI-KPDC-00001262_4 Ionospheric scintillation, Kiruna Sweden, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-09-30 21.06242, 67.87654, 21.06242, 67.87654 https://cmr.earthdata.nasa.gov/search/concepts/C2244306224-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Kiruna, Sweden Study of the ionospheric irregularity in the northern high latitude proprietary
KOPRI-KPDC-00001263_3 Neutral wind and temperature, Kiruna Sweden, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-04-15 21.06242, 67.87654, 21.06242, 67.87654 https://cmr.earthdata.nasa.gov/search/concepts/C2244306088-AMD_KOPRI.umm_json Horizontal neutral wind around 250km measured from Fabry-Perot Interferometer (FPI) at Esrange Space Center, Kiruna, Sweden Study of the atmosphere wave activities in the upper atmosphere in the northern high-latitude proprietary
KOPRI-KPDC-00001264_4 Mesospheric temperature, Kiruna Sweden, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-04-15 21.06242, 67.87654, 21.06242, 67.87654 https://cmr.earthdata.nasa.gov/search/concepts/C2244306165-AMD_KOPRI.umm_json Mesospheric temperature and airglow intensity measured from Fourier Transform Spectrometer (FTS) at Kiruna, Study of the long-term trend of mesospheric temperature in the northern high latitude proprietary
-KOPRI-KPDC-00001265_3 All-sky aurora (proton) image, KHO Longyearbyen, 2019 ALL STAC Catalog 2019-01-01 2019-04-15 16.03412, 78.15174, 16.03412, 78.15174 https://cmr.earthdata.nasa.gov/search/concepts/C2244305996-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at KHO, Longyearbyen Study of the aurora characteristics in thenorthern high latitude proprietary
KOPRI-KPDC-00001265_3 All-sky aurora (proton) image, KHO Longyearbyen, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-04-15 16.03412, 78.15174, 16.03412, 78.15174 https://cmr.earthdata.nasa.gov/search/concepts/C2244305996-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at KHO, Longyearbyen Study of the aurora characteristics in thenorthern high latitude proprietary
+KOPRI-KPDC-00001265_3 All-sky aurora (proton) image, KHO Longyearbyen, 2019 ALL STAC Catalog 2019-01-01 2019-04-15 16.03412, 78.15174, 16.03412, 78.15174 https://cmr.earthdata.nasa.gov/search/concepts/C2244305996-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at KHO, Longyearbyen Study of the aurora characteristics in thenorthern high latitude proprietary
KOPRI-KPDC-00001266_4 Ionospheric scintillation, Dasan Station, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-12-31 11.9342, 78.9272, 11.9342, 78.9272 https://cmr.earthdata.nasa.gov/search/concepts/C2244306538-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Dasan station, Arctic Study of the ionospheric irregularity in the northern high latitude proprietary
KOPRI-KPDC-00001267_3 Neutral wind and temperature, Dasan Station, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-04-15 11.9333, 78.9167, 11.9333, 78.9167 https://cmr.earthdata.nasa.gov/search/concepts/C2244306103-AMD_KOPRI.umm_json Horizontal neutral wind around 250km measured from Fabry-Perot Interferometer (FPI) at Dasan station, Arctic region Study of the atmosphere wave activities in the upper atmosphere in the northern high-latitude proprietary
KOPRI-KPDC-00001268_2 The measurement of geomagnetic field at Jang Bogo Station, Antarctica at 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-09-30 164.14, -74.37, 164.14, -74.37 https://cmr.earthdata.nasa.gov/search/concepts/C2244301263-AMD_KOPRI.umm_json The value of geomagnetic field intensity observed at Jang Bogo Station, Antarctica To investigate the interaction between ionosphere and geomagnetic disturbances proprietary
@@ -9608,8 +9608,8 @@ KOPRI-KPDC-00001271_2 Ionospheric total electron content monitoring system over
KOPRI-KPDC-00001272_2 Neutron Monitor installed at Jang Bogo Station, Antarctica at 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-09-30 164.14, -74.37, 164.14, -74.37 https://cmr.earthdata.nasa.gov/search/concepts/C2244301215-AMD_KOPRI.umm_json The Neutron Monitor observes the neutron flux incoming from space to earth's atmosphere over JBS, Antarctica. To study the variation of neutron flux with the strength of solar activity and the relationship between neutron flux and atmospheric constituents. proprietary
KOPRI-KPDC-00001273_2 Neutral wind data from FPI installed at Jang Bogo Station, Antarctica at 2019 AMD_KOPRI STAC Catalog 2019-03-11 2019-09-30 164.14, -74.37, 164.14, -74.37 https://cmr.earthdata.nasa.gov/search/concepts/C2244301235-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, 250km measured from FPI instrument at JBS station, Antarctica Study of the atmospheric wave activities in MLT and thermosphere regions over the southern high-latitude proprietary
KOPRI-KPDC-00001274_2 Plasma density and drift velocity in ionoephre over Jang Bogo Station, Antarctica at 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-09-30 164.14, -74.37, 164.14, -74.37 https://cmr.earthdata.nasa.gov/search/concepts/C2244305912-AMD_KOPRI.umm_json Ionospheric plasma density and drift velocity measured from VIPIR at JBS station, Antarctica Comprehensive study of ionosphere on plasma-neutral interaction over the southern high-latitude proprietary
-KOPRI-KPDC-00001275_3 All-sky airglow image, King Sejong Station, 2019 ALL STAC Catalog 2019-03-11 2019-09-30 -58.78804, -62.22268, -58.78804, -62.22268 https://cmr.earthdata.nasa.gov/search/concepts/C2244306051-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001275_3 All-sky airglow image, King Sejong Station, 2019 AMD_KOPRI STAC Catalog 2019-03-11 2019-09-30 -58.78804, -62.22268, -58.78804, -62.22268 https://cmr.earthdata.nasa.gov/search/concepts/C2244306051-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
+KOPRI-KPDC-00001275_3 All-sky airglow image, King Sejong Station, 2019 ALL STAC Catalog 2019-03-11 2019-09-30 -58.78804, -62.22268, -58.78804, -62.22268 https://cmr.earthdata.nasa.gov/search/concepts/C2244306051-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001276_3 Neutral wind and temperature, King Sejong Station, 2019 AMD_KOPRI STAC Catalog 2019-03-11 2019-09-30 -58.78804, -62.22268, -58.78804, -62.22268 https://cmr.earthdata.nasa.gov/search/concepts/C2244306024-AMD_KOPRI.umm_json Horizontal neutral wind around 87km, 97km, and 250km measured from Fabry-Perot Interferometer (FPI) at King Sejong Station Study of the atmosphere wave activities in the upper atmosphere in the southern high-latitude proprietary
KOPRI-KPDC-00001277_3 Ionospheric scintillation, King Sejong Station, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-09-30 -58.78804, -62.22268, -58.78804, -62.22268 https://cmr.earthdata.nasa.gov/search/concepts/C2244306035-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at King Sejong Station Study of the ionospheric irregularity in the southern high latitude proprietary
KOPRI-KPDC-00001278_4 Neutral wind and temperature (MR), King Sejong Station, 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-09-30 -58.78462, -62.2238, -58.78462, -62.2238 https://cmr.earthdata.nasa.gov/search/concepts/C2244306123-AMD_KOPRI.umm_json Neutral wind (80 – 100 km) and temperature (~90 km) measured from Meteor Radar (MR) at King Sejong Station, Antarctica Study of the atmosphere wave activities in the mesosphere and lower-thermosphere (MLT) over the southern high-latitude proprietary
@@ -9758,8 +9758,8 @@ KOPRI-KPDC-00001418_1 Eddy covariance data at DASAN Station in 2019 AMD_KOPRI ST
KOPRI-KPDC-00001420_2 Marine heat flow in Chukchi Plateau and East Siberian shelf areas on Arctic ocean 2019 AMD_KOPRI STAC Catalog 2019-09-01 2019-09-17 165.5, 72.9, -162.5, 77.2 https://cmr.earthdata.nasa.gov/search/concepts/C2244307184-AMD_KOPRI.umm_json Heat flow measurements in Chukchi Plateau and East Siberian shelf areas on Arctic ocean Investigation to the thermal structure in Chukchi Plateau and East Siberian shelf areas on Arctic ocean proprietary
KOPRI-KPDC-00001421_1 Hydrocasting observation of conductivity, temperature, and depth (CTD) AMD_KOPRI STAC Catalog 2019-08-30 2019-09-20 165.640667, 73.456833, -169.736, 77.132 https://cmr.earthdata.nasa.gov/search/concepts/C2244304657-AMD_KOPRI.umm_json Warming the Arctic surface ocean due to influx of warm Pacific water not only leads to the declining of the sea ice extent but also triggers melting gas hydrate stored in the Arctic Sea floor of the continental shelf areas. Methane (CH4) is the most abundant hydrocarbon in the atmosphere, where it plays a much more effective role as the greenhouse gas than carbon dioxide (CO2). To understand the behavior of gas hydrate in the sediment and to estimate the CH4 fluxes from the sediment through the water column to the atmosphere, we obtained data on water temperature, salinity, density and fluorescence in the water column. proprietary
KOPRI-KPDC-00001422_2 Surface observation of CH4 in the atmosphere and ocean AMD_KOPRI STAC Catalog 2019-08-30 2019-09-20 165.640667, 64.49025, -156.825778, 77.132 https://cmr.earthdata.nasa.gov/search/concepts/C2244305666-AMD_KOPRI.umm_json Warming the Arctic surface ocean due to influx of warm Pacific water not only leads to the declining of the sea ice extent but also triggers melting gas hydrate stored in the Arctic Sea floor of the continental shelf areas. Methane (CH4) is the most abundant hydrocarbon in the atmosphere, where it plays a much more effective role as the greenhouse gas than carbon dioxide (CO2). We study to estimate the CH4 fluxes on the interface of air and seawater. The CH4 in the ambient air and the surface water were quantitatively measured along the ship track. proprietary
-KOPRI-KPDC-00001423_2 2019 Arctic Araon Cruise (ARA10C) sediment cores (multiple, gravity, and box cores) AMD_KOPRI STAC Catalog 2019-08-29 2019-09-20 167.676767, 73.69587, 179.98125, 77.132017 https://cmr.earthdata.nasa.gov/search/concepts/C2244305039-AMD_KOPRI.umm_json Sediment cores during ARA10C were collected for various scientific research including methane cycle, sedimentology, paleontology, microbiology, organic geochemistry, etc. proprietary
KOPRI-KPDC-00001423_2 2019 Arctic Araon Cruise (ARA10C) sediment cores (multiple, gravity, and box cores) ALL STAC Catalog 2019-08-29 2019-09-20 167.676767, 73.69587, 179.98125, 77.132017 https://cmr.earthdata.nasa.gov/search/concepts/C2244305039-AMD_KOPRI.umm_json Sediment cores during ARA10C were collected for various scientific research including methane cycle, sedimentology, paleontology, microbiology, organic geochemistry, etc. proprietary
+KOPRI-KPDC-00001423_2 2019 Arctic Araon Cruise (ARA10C) sediment cores (multiple, gravity, and box cores) AMD_KOPRI STAC Catalog 2019-08-29 2019-09-20 167.676767, 73.69587, 179.98125, 77.132017 https://cmr.earthdata.nasa.gov/search/concepts/C2244305039-AMD_KOPRI.umm_json Sediment cores during ARA10C were collected for various scientific research including methane cycle, sedimentology, paleontology, microbiology, organic geochemistry, etc. proprietary
KOPRI-KPDC-00001424_1 Manganese nodule samples in the East siberian shelf (2019 ARA10C cruise) AMD_KOPRI STAC Catalog 2019-08-29 2019-11-20 176.338742, 74.921332, 179.055023, 75.799365 https://cmr.earthdata.nasa.gov/search/concepts/C2244305407-AMD_KOPRI.umm_json We collected the manganese nodule by dredge to study the distribution of manganese nodule in the East siberian sea, Arctic Ocean. proprietary
KOPRI-KPDC-00001425_1 Ship-borne radiosonde observation data over the Arctic Ocean in the 2016 Araon summer expedition(ARA07B,ARA07C) AMD_KOPRI STAC Catalog 2016-08-06 2016-09-08 179.619, 66.819, 179.024, 78.547 https://cmr.earthdata.nasa.gov/search/concepts/C2244301446-AMD_KOPRI.umm_json The radiosonde balloon sounding observations were performed from 6 August 2016 to 8 September 2016 to obtain the Arctic Ocean high-resolution atmospheric vertical profiles along the IBRV Araon cruise track at four times daily intervals(00,06,12, and 18UTC). The data include vertical profiles of temperature, humidity, pressure, wind speed, and wind direction up to about 30km. The data have been used for the data assimilation of the KOPRI Arctic weather forecast system. proprietary
KOPRI-KPDC-00001426_1 Ship-borne radiosonde observation data over the Arctic Ocean in the 2017 Araon summer expedition(ARA08B,ARA08C) AMD_KOPRI STAC Catalog 2017-08-07 2017-09-13 179.183, 65.174, 179.086, 77.991 https://cmr.earthdata.nasa.gov/search/concepts/C2244301491-AMD_KOPRI.umm_json The radiosonde balloon sounding observations were performed from 7 August 2017 to 13 September 2017 to obtain the Arctic Ocean high-resolution atmospheric vertical profiles along the IBRV Araon cruise track at four times daily intervals(00,06,12, and 18UTC). The data include vertical profiles of temperature, humidity, pressure, wind speed, and wind direction up to about 30km. The data have been used for the data assimilation of the KOPRI Arctic weather forecast system. proprietary
@@ -9832,8 +9832,8 @@ KOPRI-KPDC-00001494_2 Ionospheric scintillation, King Sejong Station, 2020 AMD_K
KOPRI-KPDC-00001495_3 Metamorphic pressure (P)-temperature (T) condition of the Dessent Ridge amphibolite from the Mountaineer Range, northern Victoria Land, Antarctica AMD_KOPRI STAC Catalog 2020-05-01 2020-08-31 166.575833, -73.391667, 166.575833, -73.391667 https://cmr.earthdata.nasa.gov/search/concepts/C2244306301-AMD_KOPRI.umm_json The metamorphic P-T condition of the Dessent Ridge (Mountaineer Range) amphibolite (SB171119-3B) was calculated in order to investigate the history of tectonic evolution in northern Victoria Land, Antarctica. proprietary
KOPRI-KPDC-00001496_3 SHRIMP U-Pb age data for the Mt. Murchison migmatitic gneiss (four samples) from the Mountaineer Range, northern Victoria Land, Antarctica AMD_KOPRI STAC Catalog 2020-05-01 2020-08-31 166.432778, -73.407778, 166.432778, -73.407778 https://cmr.earthdata.nasa.gov/search/concepts/C2244306320-AMD_KOPRI.umm_json The SHRIMP U-Pb age of the Mt. Murchison (Mountaineer Range) gneiss was measured in order to examine the history of tectonic evolution in northern Victoria Land, Antarctica. The metamorphic and detrital ages of the migmatitic gneiss SB171122-3 (four different parts) were obtained. proprietary
KOPRI-KPDC-00001497_2 Lichen samples from King George Island collected in 2020 AMD_KOPRI STAC Catalog 2020-01-10 2020-01-19 -58.766667, -62.216667, -58.766667, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244306335-AMD_KOPRI.umm_json Lichen samples from King George Island collected in 2020 Ecophysiological study of lichen proprietary
-KOPRI-KPDC-00001498_2 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2019 AMD_KOPRI STAC Catalog 2019-01-19 2020-01-26 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244306346-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2019 Long term monitoring proprietary
KOPRI-KPDC-00001498_2 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2019 ALL STAC Catalog 2019-01-19 2020-01-26 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244306346-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2019 Long term monitoring proprietary
+KOPRI-KPDC-00001498_2 Air temperature, air humidity, PAR, substrate temperature, and substrate humidity data from Barton Peninsular in King George Island collected in 2019 AMD_KOPRI STAC Catalog 2019-01-19 2020-01-26 -58.789338, -62.240538, -58.721474, -62.220364 https://cmr.earthdata.nasa.gov/search/concepts/C2244306346-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in King George Island collected during 1 year, 2019 Long term monitoring proprietary
KOPRI-KPDC-00001501_2 Temporal variation of marine phytoplankton in the surface water of the Antarctic Jang Bogo Station in Terra Nova Bay, January 2020- September 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-09-30 164.2, -74.616667, 164.2, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244303668-AMD_KOPRI.umm_json As a research on the ecology of phytoplankton in the coastal waters of the Jang Bogo Station in Antarctica, the community of phytoplankton and the temporal influences of environmental factors. The temporal influences of environmental factors on marine phytoplankton community were investigated in the Jang Bogo Station in Antarctica. Investigation of marine phytoplankton biomass in the coastal waters around the Jang Bogo Station in Antarctica for the monitoring by environmental change in the surface sea water conducted. proprietary
KOPRI-KPDC-00001502_4 Soil physicochemical data from Barton and Weaver peninsula in King George Island at 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-01-31 -58.8, -62.233333, -58.766664, -62.2 https://cmr.earthdata.nasa.gov/search/concepts/C2244301429-AMD_KOPRI.umm_json Physicochemical data (pH, EC, TC, TIC, TN and soil texture) of glacier foreland soil samples obtained from Barton and Weaver Peninsula in King George Island at 2019 proprietary
KOPRI-KPDC-00001503_4 Fungal NGS data from Barton and Weaver peninsula in King George Island at 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-01-31 -58.8, -62.233333, -58.766664, -62.2 https://cmr.earthdata.nasa.gov/search/concepts/C2244301480-AMD_KOPRI.umm_json These data were obtained to examine fungal community structure and reveal the correlation between soil physicochemical factors and soil fungal composition in glacial foreland of the Antarctic. proprietary
@@ -9842,14 +9842,14 @@ KOPRI-KPDC-00001505_5 All-sky airglow image, King Sejong Station, 2020 ALL STAC
KOPRI-KPDC-00001505_5 All-sky airglow image, King Sejong Station, 2020 AMD_KOPRI STAC Catalog 2020-02-18 2020-09-23 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244307204-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001506_6 Ionospheric scintillation, Kiruna Sweden, 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-10-20 21.03, 67.53, 21.03, 67.53 https://cmr.earthdata.nasa.gov/search/concepts/C2244307220-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Kiruna, Sweden Study of the ionospheric irregularity in the northern high latitude proprietary
KOPRI-KPDC-00001507_6 Ionospheric scintillation, Dasan Station, 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-12-31 11.9342, 78.9272, 11.9342, 78.9272 https://cmr.earthdata.nasa.gov/search/concepts/C2244306380-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Dasan station, Arctic Study of the ionospheric irregularity in the northern high latitude proprietary
-KOPRI-KPDC-00001508_4 All-sky aurora (proton) image, KHO Longyearbyen, 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-10-19 16.12, 78.48, 16.12, 78.48 https://cmr.earthdata.nasa.gov/search/concepts/C2244307127-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at KHO, Longyearbyen Study of the aurora characteristics in thenorthern high latitude proprietary
KOPRI-KPDC-00001508_4 All-sky aurora (proton) image, KHO Longyearbyen, 2020 ALL STAC Catalog 2020-01-01 2020-10-19 16.12, 78.48, 16.12, 78.48 https://cmr.earthdata.nasa.gov/search/concepts/C2244307127-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at KHO, Longyearbyen Study of the aurora characteristics in thenorthern high latitude proprietary
+KOPRI-KPDC-00001508_4 All-sky aurora (proton) image, KHO Longyearbyen, 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-10-19 16.12, 78.48, 16.12, 78.48 https://cmr.earthdata.nasa.gov/search/concepts/C2244307127-AMD_KOPRI.umm_json Aurora (proton) image measured from all-sky camera at KHO, Longyearbyen Study of the aurora characteristics in thenorthern high latitude proprietary
KOPRI-KPDC-00001509_1 2019-2020 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity AMD_KOPRI STAC Catalog 2019-01-19 2020-01-26 -58.788436, -62.240056, -58.719694, -62.218583 https://cmr.earthdata.nasa.gov/search/concepts/C2244301374-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2019 proprietary
KOPRI-KPDC-00001509_1 2019-2020 Barton Peninsular micro-climate data_HOBO soil temp., PAR, air temp., relative humidity ALL STAC Catalog 2019-01-19 2020-01-26 -58.788436, -62.240056, -58.719694, -62.218583 https://cmr.earthdata.nasa.gov/search/concepts/C2244301374-AMD_KOPRI.umm_json Micro-climate data set from Barton Peninsular in Antarctica collected during 1 year, 2019 proprietary
KOPRI-KPDC-00001510_2 Snow cover map of the Barton Peninsula, King George Island, Antarctica AMD_KOPRI STAC Catalog 1986-01-28 2020-01-19 -58.747839, -62.229025, -58.747839, -62.229025 https://cmr.earthdata.nasa.gov/search/concepts/C2244306359-AMD_KOPRI.umm_json Snow cover on the Barton Peninsula, Antarctica extracted from time-series Landsat satellite data proprietary
KOPRI-KPDC-00001511_3 Bacterial NGS data from Barton and Weaver peninsula in King George Island at 2019 AMD_KOPRI STAC Catalog 2019-01-01 2019-01-31 -58.8, -62.233333, -58.766664, -62.2 https://cmr.earthdata.nasa.gov/search/concepts/C2244306368-AMD_KOPRI.umm_json These data were obtained to examine bacterial community structure and reveal the correlation between soil physicochemical factors and soil bacterial composition in glacial foreland of the Antarctic. proprietary
-KOPRI-KPDC-00001512_2 2019/20 season Korean Route Traverse based GPS GIS data ALL STAC Catalog 2019-11-07 2020-01-18 149.040453, -77.04815, 164.228789, -74.62405 https://cmr.earthdata.nasa.gov/search/concepts/C2244306379-AMD_KOPRI.umm_json GOAL ○ Development of Korean route and infrastructure such as research camp to approach the Antarctic inland ○ Establishment of support system for the Antarctic inland researches RESEARCH CONTENTS ○ A safe and reliable route expedition to the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland researches ○ Construction of logistic camps at the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland researches proprietary
KOPRI-KPDC-00001512_2 2019/20 season Korean Route Traverse based GPS GIS data AMD_KOPRI STAC Catalog 2019-11-07 2020-01-18 149.040453, -77.04815, 164.228789, -74.62405 https://cmr.earthdata.nasa.gov/search/concepts/C2244306379-AMD_KOPRI.umm_json GOAL ○ Development of Korean route and infrastructure such as research camp to approach the Antarctic inland ○ Establishment of support system for the Antarctic inland researches RESEARCH CONTENTS ○ A safe and reliable route expedition to the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland researches ○ Construction of logistic camps at the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland researches proprietary
+KOPRI-KPDC-00001512_2 2019/20 season Korean Route Traverse based GPS GIS data ALL STAC Catalog 2019-11-07 2020-01-18 149.040453, -77.04815, 164.228789, -74.62405 https://cmr.earthdata.nasa.gov/search/concepts/C2244306379-AMD_KOPRI.umm_json GOAL ○ Development of Korean route and infrastructure such as research camp to approach the Antarctic inland ○ Establishment of support system for the Antarctic inland researches RESEARCH CONTENTS ○ A safe and reliable route expedition to the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland researches ○ Construction of logistic camps at the sites of the Subglacial Lake and Deep Ice Core drilling for Antarctic inland researches proprietary
KOPRI-KPDC-00001513_2 Soil physical and chemical data from Alaska permafrost soil AMD_KOPRI STAC Catalog 2016-10-01 2018-11-30 -163.711, 64.8443, -163.711, 64.8443 https://cmr.earthdata.nasa.gov/search/concepts/C2244306469-AMD_KOPRI.umm_json - Various soil physical and chemical properties are interacting with environment and soil microorganisms. proprietary
KOPRI-KPDC-00001514_3 Continuous monitoring of pCO2 and its relevant parameters in the coast of the Jang Bogo Station, Antarctica, in 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-10-28 164.2, -74.616667, 164.2, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244307332-AMD_KOPRI.umm_json In order to conduct long-term monitoring of the acidification of the coastal waters around Antarctica, ocean pCO2 and its relevant physical, chemical, biological parameters start monitoring in 2020. These include atmospheric CO2 concentration, ocean pCO2, seawater temperature, salinity, dissolved oxygen, pH, chlorophyll-a, CDOM, and, turbidity. proprietary
KOPRI-KPDC-00001515_2 Continuous monitoring of nutrients in the coast of the Jang Bogo Station, Antarctica AMD_KOPRI STAC Catalog 2020-01-01 2020-10-28 164.2, -74.616667, 164.2, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244301504-AMD_KOPRI.umm_json In order to conduct long-term monitoring of the acidification of the coastal waters around Antarctica, nutrients were measured using a QuAAtro auto analyzer (Seal Analytical, Germany) in 2020. proprietary
@@ -9872,8 +9872,8 @@ KOPRI-KPDC-00001531_2 Neutral wind data from FPI installed at Jang Bogo Station,
KOPRI-KPDC-00001532_2 The measurement of geomagnetic field at Jang Bogo Station, Antarctica at 2020 AMD_KOPRI STAC Catalog 2019-10-01 2020-10-31 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244307086-AMD_KOPRI.umm_json The value of geomagnetic field intensity observed at Jang Bogo Station, Antarctica To investigate the interaction between ionosphere and geomagnetic disturbances proprietary
KOPRI-KPDC-00001533_2 The measurement of geomagnetic field at King Sejong Station, Antarctica at 2020 AMD_KOPRI STAC Catalog 2019-10-01 2020-10-31 -58.783333, -62.216667, -58.783333, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244307126-AMD_KOPRI.umm_json The value of geomagnetic field intensity observed at KSS, Antarctica To investigate the interaction between ionosphere and geomagnetic disturbances proprietary
KOPRI-KPDC-00001534_2 Ionospheric total electron content monitoring system over Jang Bogo Station, Antarctica at 2020 AMD_KOPRI STAC Catalog 2019-10-01 2020-10-31 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244307158-AMD_KOPRI.umm_json Total electron content in the ionosphere at JBS station, Antarctica Study of the statistical characteristics of ionosphere in southern high latitude proprietary
-KOPRI-KPDC-00001535_2 2019/20 season Korean Route Traverse heavy machine fuel consumption in Antarctica AMD_KOPRI STAC Catalog 2019-11-07 2020-12-18 149.0976, -77.04815, 164.228789, -74.62405 https://cmr.earthdata.nasa.gov/search/concepts/C2244307169-AMD_KOPRI.umm_json For recording heavy machine operation and fuel consumption during 2019/20 Korean Route Traverse period. Data consist of eight sheets(six Pisten Bullys and two Challenger) proprietary
KOPRI-KPDC-00001535_2 2019/20 season Korean Route Traverse heavy machine fuel consumption in Antarctica ALL STAC Catalog 2019-11-07 2020-12-18 149.0976, -77.04815, 164.228789, -74.62405 https://cmr.earthdata.nasa.gov/search/concepts/C2244307169-AMD_KOPRI.umm_json For recording heavy machine operation and fuel consumption during 2019/20 Korean Route Traverse period. Data consist of eight sheets(six Pisten Bullys and two Challenger) proprietary
+KOPRI-KPDC-00001535_2 2019/20 season Korean Route Traverse heavy machine fuel consumption in Antarctica AMD_KOPRI STAC Catalog 2019-11-07 2020-12-18 149.0976, -77.04815, 164.228789, -74.62405 https://cmr.earthdata.nasa.gov/search/concepts/C2244307169-AMD_KOPRI.umm_json For recording heavy machine operation and fuel consumption during 2019/20 Korean Route Traverse period. Data consist of eight sheets(six Pisten Bullys and two Challenger) proprietary
KOPRI-KPDC-00001536_2 Neutron Monitor installed at Jang Bogo Station, Antarctica at 2020 AMD_KOPRI STAC Catalog 2019-10-01 2020-10-31 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244307178-AMD_KOPRI.umm_json The Neutron Monitor observes the neutron flux incoming from space to earth's atmosphere over JBS, Antarctica. To study the variation of neutron flux with the strength of solar activity and the relationship between neutron flux and atmospheric constituents. proprietary
KOPRI-KPDC-00001537_3 Biogeochemical data from David glacier AMD_KOPRI STAC Catalog 2019-11-01 2020-10-30 155.784167, -75.709783, 155.784167, -75.709783 https://cmr.earthdata.nasa.gov/search/concepts/C2244307187-AMD_KOPRI.umm_json Environmental evaluation proprietary
KOPRI-KPDC-00001538_1 Underwater logger data in the coast of the Jang Bogo Station, Antarctica AMD_KOPRI STAC Catalog 2017-02-10 2019-11-09 164.242639, -74.627472, 164.242639, -74.627472 https://cmr.earthdata.nasa.gov/search/concepts/C2244301567-AMD_KOPRI.umm_json To monitor ocean environment data (Temperature, Salinity, Chlorophyll a) of ocean water on the coast of the Jang Bogo Station, Antarctica. proprietary
@@ -9896,8 +9896,8 @@ KOPRI-KPDC-00001560_4 Phocid seal tissue samples AMD_KOPRI STAC Catalog 2019-12-
KOPRI-KPDC-00001561_2 Extract Library (2020) AMD_KOPRI STAC Catalog 2020-01-01 2020-12-31 9.986558, 77.563883, 18.280906, 78.644719 https://cmr.earthdata.nasa.gov/search/concepts/C2244306061-AMD_KOPRI.umm_json List of extracts derived from Arctic plants were made. Many extracts can be used in natural product research to provide samples for finding bioactive substances. proprietary
KOPRI-KPDC-00001562_2 The photosynthetic efficiency of antarctic plants with the environmental changes AMD_KOPRI STAC Catalog 2020-01-05 2020-01-24 -58, -62, -58, -62 https://cmr.earthdata.nasa.gov/search/concepts/C2244306078-AMD_KOPRI.umm_json To prospect the community responses of Antarctic Peninsular vegetations with the environmental changes, the photosynthetic efficiency of the representative plant species was measured under the different environmental conditions. proprietary
KOPRI-KPDC-00001563_1 Chlorophyll-a concentration from the Amundsen Sea, Antarctica, 2020 AMD_KOPRI STAC Catalog 2020-01-16 2020-02-16 -145, -74.6, -112, -72.5 https://cmr.earthdata.nasa.gov/search/concepts/C2244302216-AMD_KOPRI.umm_json The phytoplantkon biomass (chl-a) was investigated in the Amundsen Sea, Antarctica from January to February 2020. This data includes investigator and locality for chlorophyll-a concentration. The investigation of chlorophyll-a concentration in the Amundsen Sea, Antarctica 2020. proprietary
-KOPRI-KPDC-00001564_4 2016-8 KOPRI North Greenland Sirius Passet collection (modified) ALL STAC Catalog 2016-07-20 2018-07-19 -42.228333, 82.793333, -42.228333, 82.793333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306091-AMD_KOPRI.umm_json This entry includes the Early Cambrian fossils from Sirius Passet, North Greenland, collected by 2016-2018 KOPRI expedition. The collections include various kinds of marine invertebrates, representing morphology of the early stage of animal evolution. Total of ca. 2000 kg of fossils were collected during 2016-2018 expedition. The Early Cambrian fossils will help us understand the rise of the first animals during the Cambrian Explosion. proprietary
KOPRI-KPDC-00001564_4 2016-8 KOPRI North Greenland Sirius Passet collection (modified) AMD_KOPRI STAC Catalog 2016-07-20 2018-07-19 -42.228333, 82.793333, -42.228333, 82.793333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306091-AMD_KOPRI.umm_json This entry includes the Early Cambrian fossils from Sirius Passet, North Greenland, collected by 2016-2018 KOPRI expedition. The collections include various kinds of marine invertebrates, representing morphology of the early stage of animal evolution. Total of ca. 2000 kg of fossils were collected during 2016-2018 expedition. The Early Cambrian fossils will help us understand the rise of the first animals during the Cambrian Explosion. proprietary
+KOPRI-KPDC-00001564_4 2016-8 KOPRI North Greenland Sirius Passet collection (modified) ALL STAC Catalog 2016-07-20 2018-07-19 -42.228333, 82.793333, -42.228333, 82.793333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306091-AMD_KOPRI.umm_json This entry includes the Early Cambrian fossils from Sirius Passet, North Greenland, collected by 2016-2018 KOPRI expedition. The collections include various kinds of marine invertebrates, representing morphology of the early stage of animal evolution. Total of ca. 2000 kg of fossils were collected during 2016-2018 expedition. The Early Cambrian fossils will help us understand the rise of the first animals during the Cambrian Explosion. proprietary
KOPRI-KPDC-00001565_2 Pondwater sampling from Weaver Peninsula in Antarctica AMD_KOPRI STAC Catalog 2019-12-30 2019-12-30 -58.796361, -62.210889, -58.796361, -62.210889 https://cmr.earthdata.nasa.gov/search/concepts/C2244306104-AMD_KOPRI.umm_json We collected pondwater sample from Weaver Peninsula in Antarctica to investigate the chemical reactions in ice. proprietary
KOPRI-KPDC-00001566_2 Fresh snow sampling from Weaver Peninsula in Antarctica AMD_KOPRI STAC Catalog 2019-12-30 2019-12-30 -58.796361, -62.210889, -58.796361, -62.210889 https://cmr.earthdata.nasa.gov/search/concepts/C2244306125-AMD_KOPRI.umm_json We collected fresh snow sample from Weaver Peninsula in Antarctica to investigate the chemical reactions in ice. proprietary
KOPRI-KPDC-00001567_1 Excitation-emission matrixes(EEM) of Antarctic seawaters(10 of 10) measured using a fluorescence spectrometer(2019-12-19) AMD_KOPRI STAC Catalog 2019-12-19 2019-12-20 169.747342, -57.297208, 169.747342, -57.297208 https://cmr.earthdata.nasa.gov/search/concepts/C2244302260-AMD_KOPRI.umm_json Abstract : Excitation-emission matrixes (EEM) of Antarctic seawater samples measured using a fluorescence spectrometer Purpose : Understanding optical properties of organic matters in seawater to predict their sources proprietary
@@ -9956,8 +9956,8 @@ KOPRI-KPDC-00001628_3 Weather forecasts over the Arctic region AMD_KOPRI STAC Ca
KOPRI-KPDC-00001629_1 Foraging trips of Chinstrap penguin and Gentoo penguin breeding at Narebski Point from 2006 to 2019 AMD_KOPRI STAC Catalog 2006-12-17 2020-01-02 -58.766667, -62.233333, -58.766667, -62.233333 https://cmr.earthdata.nasa.gov/search/concepts/C2244301271-AMD_KOPRI.umm_json This dataset is the foraging trips of the chick-guarding period penguin obtained by attaching a GPS logger and a time depth recorder device to Chinstrap penguin and Gentoo penguin at Narebski Point from December 2006 to January 2020. In sheet1 and sheet2, the coordinates are recorded in the foraging dive. Separate sheet2 has metadata and parameters of tested penguin. proprietary
KOPRI-KPDC-00001630_1 Foraging trips of Adélie penguin breeding at Inexpressible Island on December 2018 AMD_KOPRI STAC Catalog 2018-12-15 2018-12-17 163.65, -74.9, 163.65, -74.9 https://cmr.earthdata.nasa.gov/search/concepts/C2244301300-AMD_KOPRI.umm_json This dataset is the foraging trips of the chick-guarding period penguin obtained by attaching a GPS logger and a time depth recorder device to Adélie penguin at Inexpressible Island on December 2018. In sheet1, the coordinates are recorded in the foraging dive. Separate sheet2 has metadata and parameters of tested penguin. proprietary
KOPRI-KPDC-00001631_2 Foraging trips of Adélie penguin breeding at Adélie Cove on December 2018 AMD_KOPRI STAC Catalog 2018-12-31 2019-01-02 164, -74.75, 164, -74.75 https://cmr.earthdata.nasa.gov/search/concepts/C2244306008-AMD_KOPRI.umm_json This dataset is the foraging trips of the chick-guarding period penguin obtained by attaching a GPS logger and a time depth recorder device to Adélie penguin at Adélie Cove from December 2018 to January 2019. In sheet1, the coordinates are recorded in the foraging dive. Separate sheet2 has metadata and parameters of tested penguin. proprietary
-KOPRI-KPDC-00001632_1 A study on the distribution characteristics of stable oxygen isotope in the Amundsen Sea in 2011 ALL STAC Catalog 2010-12-20 2011-01-20 -145, -74.6, -112, -72.5 https://cmr.earthdata.nasa.gov/search/concepts/C2244301322-AMD_KOPRI.umm_json To investigate the controls that affect inorganic carbon in the water column of the Amundsen Sea, hydrographic survey using IBRV Araon was carried out from December 20, 2010 to January 22, 2011. Oxygen-18 isotopes were analyzed at 21 stations. proprietary
KOPRI-KPDC-00001632_1 A study on the distribution characteristics of stable oxygen isotope in the Amundsen Sea in 2011 AMD_KOPRI STAC Catalog 2010-12-20 2011-01-20 -145, -74.6, -112, -72.5 https://cmr.earthdata.nasa.gov/search/concepts/C2244301322-AMD_KOPRI.umm_json To investigate the controls that affect inorganic carbon in the water column of the Amundsen Sea, hydrographic survey using IBRV Araon was carried out from December 20, 2010 to January 22, 2011. Oxygen-18 isotopes were analyzed at 21 stations. proprietary
+KOPRI-KPDC-00001632_1 A study on the distribution characteristics of stable oxygen isotope in the Amundsen Sea in 2011 ALL STAC Catalog 2010-12-20 2011-01-20 -145, -74.6, -112, -72.5 https://cmr.earthdata.nasa.gov/search/concepts/C2244301322-AMD_KOPRI.umm_json To investigate the controls that affect inorganic carbon in the water column of the Amundsen Sea, hydrographic survey using IBRV Araon was carried out from December 20, 2010 to January 22, 2011. Oxygen-18 isotopes were analyzed at 21 stations. proprietary
KOPRI-KPDC-00001633_1 Observed CTD data and dissolved noble gases along the Dotson Trough, Amundsen Sea, Antarctica in 2011 AMD_KOPRI STAC Catalog 2010-12-26 2011-01-02 -117.6895, -74.2067, -112.4962, -72.4145 https://cmr.earthdata.nasa.gov/search/concepts/C2244301379-AMD_KOPRI.umm_json This dataset is dissolved noble gases obtained during ANA01C cruise. The dataset also contain potential temperature, salinity and dissolved oxygen obtained by CTD rosette system. The dataset constituted 5 station along the Dotson Trough, Amundsen Sea. proprietary
KOPRI-KPDC-00001634_2 Lowered Acoustic Doppler Current Profiler (LADCP) data - August 2016, western Arctic Ocean (4 CTD stations) AMD_KOPRI STAC Catalog 2016-08-08 2016-08-27 -175.895, 76.575, -164.155, 77.864 https://cmr.earthdata.nasa.gov/search/concepts/C2244306113-AMD_KOPRI.umm_json The data are the Lowered Acoustic Doppler Current Profiler (LADCP) data obtained from R/V Icebreaker ARAON in August 2016. The dataset contains LADCP data from surface to 100 m depth (5-m interval) at 4 CTD stations (Sts. 23, 24, 29, and 30) aiming at measuring instantaneous current profiles. proprietary
KOPRI-KPDC-00001635_2 Meteorological data at the Jang Bogo Station, Antarctica in 2020 AMD_KOPRI STAC Catalog 2020-01-01 2020-12-31 164.228333, -74.623333, 164.228333, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306204-AMD_KOPRI.umm_json Meteorological observation was carried out at the Jang Bogo Station in 2020. Observational elements are composed of wind, air temperature, relative humidity, station level atmospheric pressure, visibility, snow depth, cloud height, and precipitation. Goals of this observation are 1) to understand meteorological phenomena and 2) to monitor climate change at Antarctica. These data are recorded automatically then examined by meteorological expert at the station to be produced as a daily, monthly, and annual report. To understand weather phenomena and to monitor climate variation at Jang Bogo Station, Antarctica proprietary
@@ -9995,8 +9995,8 @@ KOPRI-KPDC-00001666_2 Wind data on ARAON DaDis for Antarctic cruise, 2020/2021 A
KOPRI-KPDC-00001667_2 Upper O3 observation data at Jang Bogo Station in 2019 AMD_KOPRI STAC Catalog 2019-01-17 2019-11-28 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244306388-AMD_KOPRI.umm_json Regular upper O3 observation is made once a week from SEP to NOV, and a month except for the preceding period. O3 is sampled and recorded every a second. Monitoring of changes in meteorological variables (O3) with altitude over Jang Bogo station. proprietary
KOPRI-KPDC-00001668_2 Upper O3 observation data at Jang Bogo Station in 2020 AMD_KOPRI STAC Catalog 2020-01-16 2020-12-17 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244306563-AMD_KOPRI.umm_json Regular upper O3 observation is made once a week from SEP to NOV, and a month except for the preceding period. O3 is sampled and recorded every a second. Monitoring of changes in meteorological variables (O3) with altitude over Jang Bogo station. proprietary
KOPRI-KPDC-00001669_2 Upper O3 observation data at Jang Bogo Station in 2021 AMD_KOPRI STAC Catalog 2021-01-02 2021-06-10 164.232072, -74.623811, 164.232072, -74.623811 https://cmr.earthdata.nasa.gov/search/concepts/C2244306666-AMD_KOPRI.umm_json Regular upper O3 observation is made once a week from SEP to NOV, and a month except for the preceding period. O3 is sampled and recorded every a second. Monitoring of changes in meteorological variables (O3) with altitude over Jang Bogo station. proprietary
-KOPRI-KPDC-00001671_3 2018&19 Multibeam data of Terra Nova Bay (around Jang Bogo station) AMD_KOPRI STAC Catalog 2019-02-14 2019-02-15 163.984928, -74.73604, 164.57053, -74.610485 https://cmr.earthdata.nasa.gov/search/concepts/C2244306725-AMD_KOPRI.umm_json The necessity of supplying charts for securing the safety required for navigation and berthing of small ships for research activities and support around the Jang Bogo station increased. Accordingly, in the 2018&19 season, the bathymetry survey was conducted in Terra Noval Bay using the IBRV Araon / Multibeam equipment is EM122 of Kongsberg proprietary
KOPRI-KPDC-00001671_3 2018&19 Multibeam data of Terra Nova Bay (around Jang Bogo station) ALL STAC Catalog 2019-02-14 2019-02-15 163.984928, -74.73604, 164.57053, -74.610485 https://cmr.earthdata.nasa.gov/search/concepts/C2244306725-AMD_KOPRI.umm_json The necessity of supplying charts for securing the safety required for navigation and berthing of small ships for research activities and support around the Jang Bogo station increased. Accordingly, in the 2018&19 season, the bathymetry survey was conducted in Terra Noval Bay using the IBRV Araon / Multibeam equipment is EM122 of Kongsberg proprietary
+KOPRI-KPDC-00001671_3 2018&19 Multibeam data of Terra Nova Bay (around Jang Bogo station) AMD_KOPRI STAC Catalog 2019-02-14 2019-02-15 163.984928, -74.73604, 164.57053, -74.610485 https://cmr.earthdata.nasa.gov/search/concepts/C2244306725-AMD_KOPRI.umm_json The necessity of supplying charts for securing the safety required for navigation and berthing of small ships for research activities and support around the Jang Bogo station increased. Accordingly, in the 2018&19 season, the bathymetry survey was conducted in Terra Noval Bay using the IBRV Araon / Multibeam equipment is EM122 of Kongsberg proprietary
KOPRI-KPDC-00001672_3 2016&17 Multibeam data of Terra Nova Bay (around Jang Bogo station) ALL STAC Catalog 2017-01-29 2017-02-06 163.984928, -74.73604, 164.57053, -74.610485 https://cmr.earthdata.nasa.gov/search/concepts/C2244306756-AMD_KOPRI.umm_json The necessity of supplying charts for securing the safety required for navigation and berthing of small ships for research activities and support around the Jang Bogo station increased. Accordingly, in the 2016&17 season, the bathymetry survey was conducted in Terra Noval Bay using the IBRV Araon / Multibeam equipment is EM122 of Kongsberg proprietary
KOPRI-KPDC-00001672_3 2016&17 Multibeam data of Terra Nova Bay (around Jang Bogo station) AMD_KOPRI STAC Catalog 2017-01-29 2017-02-06 163.984928, -74.73604, 164.57053, -74.610485 https://cmr.earthdata.nasa.gov/search/concepts/C2244306756-AMD_KOPRI.umm_json The necessity of supplying charts for securing the safety required for navigation and berthing of small ships for research activities and support around the Jang Bogo station increased. Accordingly, in the 2016&17 season, the bathymetry survey was conducted in Terra Noval Bay using the IBRV Araon / Multibeam equipment is EM122 of Kongsberg proprietary
KOPRI-KPDC-00001673_2 Multibeam data, Australian-Antarctic Ridge (AAR) and the Pacific-Antarctic Ridge (PAR), 2020/21 season AMD_KOPRI STAC Catalog 2020-11-28 2020-11-29 -179.79775, -66.58295, -176.64499, -64.11792 https://cmr.earthdata.nasa.gov/search/concepts/C2244306908-AMD_KOPRI.umm_json During 2020/2021 summer season, due to sea ice, we obtained high resolution bathymetric data and marine magnetic data for only one short spreading-segment in “large-scaled spreading and fracture zones (or leaky transform faults)” located between the Australian-Antarctic Ridge (AAR) and the Pacific-Antarctic Ridge (PAR). It is expected that it will be able to contribute to the investigations for the tectonic evolution of the Antarctica related to the Australian-Pacific-Antarctic plates and the evolution of the Zealandia-Antarctic mantle, through the bathymetric and magnetic data that will be accumulated in the future. proprietary
@@ -10134,8 +10134,8 @@ KOPRI-KPDC-00001813_2 Neutral wind and temperature, King Sejong Station, 2021 AM
KOPRI-KPDC-00001814_2 Ionospheric scintillation, King Sejong Station, 2021 AMD_KOPRI STAC Catalog 2021-01-01 2021-09-28 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244306818-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at King Sejong Station Study of the ionospheric irregularity in the southern high latitude proprietary
KOPRI-KPDC-00001815_2 Ionospheric scintillation, Kiruna Sweden, 2021 AMD_KOPRI STAC Catalog 2021-01-01 2021-09-29 21.03, 67.53, 21.03, 67.53 https://cmr.earthdata.nasa.gov/search/concepts/C2244306982-AMD_KOPRI.umm_json Amplitude and phase scintillations of GPS signal measured from scintillation monitor at Kiruna, Sweden Study of the ionospheric irregularity in the northern high latitude proprietary
KOPRI-KPDC-00001816_3 Geomagnetic field, King Sejong Station, 2021 AMD_KOPRI STAC Catalog 2021-01-01 2021-09-29 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244306742-AMD_KOPRI.umm_json Variation of geomagnetic field measured from search-coil magnetometer at King Sejong Station. Study of the activity of ultra low frequency (ULF) wave in the southern high latitude. proprietary
-KOPRI-KPDC-00001817_2 All-sky airglow image, King Sejong Station, 2021 ALL STAC Catalog 2021-02-01 2021-08-31 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244306764-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001817_2 All-sky airglow image, King Sejong Station, 2021 AMD_KOPRI STAC Catalog 2021-02-01 2021-08-31 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244306764-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
+KOPRI-KPDC-00001817_2 All-sky airglow image, King Sejong Station, 2021 ALL STAC Catalog 2021-02-01 2021-08-31 -58.47, -62.13, -58.47, -62.13 https://cmr.earthdata.nasa.gov/search/concepts/C2244306764-AMD_KOPRI.umm_json Airglow(OI 557.7nm, OI 630.0nm, and OH Meinel band) image measured from all-sky camera at King Sejong Station, Antarctica Study of the atmospheric wave activities in the southern high latitude proprietary
KOPRI-KPDC-00001818_2 Neutral wind and temperature, Kiruna Sweden, 2021 AMD_KOPRI STAC Catalog 2021-01-01 2021-04-20 21.03, 67.53, 21.03, 67.53 https://cmr.earthdata.nasa.gov/search/concepts/C2244306754-AMD_KOPRI.umm_json Horizontal neutral wind around 250km measured from Fabry-Perot Interferometer (FPI) at Esrange Space Center, Kiruna, Sweden Study of the atmosphere wave activities in the upper atmosphere in the northern high-latitude proprietary
KOPRI-KPDC-00001819_2 Metagenomic Analysis of Bacterial Communities AMD_KOPRI STAC Catalog 2021-03-30 2021-10-01 -58.767778, -62.219722, -58.767778, -62.219722 https://cmr.earthdata.nasa.gov/search/concepts/C2244306737-AMD_KOPRI.umm_json Metagenomic Analysis of Bacterial Communities in Colobanthus quitensis in KGI, Antarctic Peninsula proprietary
KOPRI-KPDC-00001820_2 Metagenomic Analysis of Fungal Communities AMD_KOPRI STAC Catalog 2021-03-30 2021-10-01 -58.767778, -62.219722, -58.767778, -62.219722 https://cmr.earthdata.nasa.gov/search/concepts/C2244306749-AMD_KOPRI.umm_json Metagenomic Analysis of Fungal Communities in Colobanthus quitensis in KGI, Antarctic Peninsula proprietary
@@ -10167,8 +10167,8 @@ KOPRI-KPDC-00001846_2 Major ionic species measured at ice core from Tourmaline P
KOPRI-KPDC-00001847_2 Trace elements in GV7 snow pit AMD_KOPRI STAC Catalog 2013-12-22 2013-12-24 158.863583, -70.688083, 158.863583, -70.688083 https://cmr.earthdata.nasa.gov/search/concepts/C2244305965-AMD_KOPRI.umm_json Trace elements in GV7 snow pit investigation of climate change mechanism by observation and simulation of polar climate for the past and present proprietary
KOPRI-KPDC-00001848_2 Trace elements in Hercules Neve snow pit AMD_KOPRI STAC Catalog 2015-12-16 2015-12-16 165.410756, -73.052936, 165.410756, -73.052936 https://cmr.earthdata.nasa.gov/search/concepts/C2244305998-AMD_KOPRI.umm_json Trace elements in Hercules Neve snow pit investigation of climate change mechanism by observation and simulation of polar climate for the past and present proprietary
KOPRI-KPDC-00001850_3 Continuous monitoring of pCO2 and its relevant parameters in the coast of the Jang Bogo Station, Antarctica, in 2021 AMD_KOPRI STAC Catalog 2021-01-01 2021-06-30 164.2, -74.616667, 164.2, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244307445-AMD_KOPRI.umm_json In order to conduct long-term monitoring of the acidification of the coastal waters around Antarctica, ocean pCO2 and its relevant physical, chemical, biological parameters start monitoring in 2020. These include atmospheric CO2 concentration, ocean pCO2, seawater temperature, salinity, dissolved oxygen, pH, chlorophyll-a, CDOM, and, turbidity. proprietary
-KOPRI-KPDC-00001851_2 All-sky aurora (electron) image, Jang Bogo Station, 2021 ALL STAC Catalog 2021-03-01 2021-09-30 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306019-AMD_KOPRI.umm_json Aurora (electron) image measured from all-sky camera at Jang Bogo Station. Study of the aurora characterisitcs in the southern high latitude. proprietary
KOPRI-KPDC-00001851_2 All-sky aurora (electron) image, Jang Bogo Station, 2021 AMD_KOPRI STAC Catalog 2021-03-01 2021-09-30 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306019-AMD_KOPRI.umm_json Aurora (electron) image measured from all-sky camera at Jang Bogo Station. Study of the aurora characterisitcs in the southern high latitude. proprietary
+KOPRI-KPDC-00001851_2 All-sky aurora (electron) image, Jang Bogo Station, 2021 ALL STAC Catalog 2021-03-01 2021-09-30 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306019-AMD_KOPRI.umm_json Aurora (electron) image measured from all-sky camera at Jang Bogo Station. Study of the aurora characterisitcs in the southern high latitude. proprietary
KOPRI-KPDC-00001852_2 Neutral wind and temperature, Jang Bogo Station, 2021 AMD_KOPRI STAC Catalog 2021-03-01 2021-09-30 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306033-AMD_KOPRI.umm_json Horizontal neutral wind around 250km measured from Fabry-Perot Interferometer (FPI) Jang Bogo Station, Antarctica Study of the atmospheric wave activities in the upper atmosphere in the southern high-latitude. proprietary
KOPRI-KPDC-00001853_2 Electron density, plasma drift, Jang Bogo Station, 2021 AMD_KOPRI STAC Catalog 2020-11-01 2021-09-30 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306043-AMD_KOPRI.umm_json Electron density profile, plasma drift velocity, and ionospheric tile information measured from VIPIR (ionosonde) at Jang Bogo Station. Study of the ionospheric characteristics in the southern high latitude. proprietary
KOPRI-KPDC-00001854_2 Neutron count, Jang Bogo Station, 2021 AMD_KOPRI STAC Catalog 2020-11-01 2021-09-30 164.2, -74.623333, 164.2, -74.623333 https://cmr.earthdata.nasa.gov/search/concepts/C2244306067-AMD_KOPRI.umm_json Cosmic ray origin neutron count from space measured from neutron monitor at Jang Bogo Station, Antarctica. Study of the variation of neutron count in the southern high latitude. proprietary
@@ -10213,8 +10213,8 @@ KOPRI-KPDC-00001899_1 Tidal data at King Sejong Station AMD_KOPRI STAC Catalog 2
KOPRI-KPDC-00001900_1 Geochemical, isotope, and grain size data of GC05-DP02 AMD_KOPRI STAC Catalog 2005-12-01 2005-12-31 -62.639765, -61.04516, -62.639765, -61.04516 https://cmr.earthdata.nasa.gov/search/concepts/C2244306353-AMD_KOPRI.umm_json Magnetic susceptibility, total organic carbon, total nitrogen, C/N ratio, biogenic opal, CaCO3, nitrogen isotope of acid treated samples, grain size analysis data of GC05-DP02 covering the last 600 kyrs. proprietary
KOPRI-KPDC-00001902_1 Time series of volume backscattering strength in the Arctic Ocean AMD_KOPRI STAC Catalog 2018-09-01 2019-05-31 -177.069017, 75.777983, -177.069017, 75.777983 https://cmr.earthdata.nasa.gov/search/concepts/C2244306041-AMD_KOPRI.umm_json Data were collected and processed to monitor the vertical dynamics of zooplankton and micro nekton in the Arctic Ocean. proprietary
KOPRI-KPDC-00001904_1 Lipid biomarkers (HBIs, sterols) from surface sediments in the Western Arctic AMD_KOPRI STAC Catalog 2020-05-01 2020-12-31 174.001, 73.228, 174, 78 https://cmr.earthdata.nasa.gov/search/concepts/C2244306081-AMD_KOPRI.umm_json To establish a reconstruction technique for past sea ice changes based on pure domestic technology. Acquisition of lipid biomarkers (HBIs, sterols) from surface sediments in the Western Arctic. proprietary
-KOPRI-KPDC-00001905_1 2015 ARA06C-01JPC: Lipid biomarkers (HBIs, sterols) from core sediments ALL STAC Catalog 2021-01-01 2021-12-31 -166.428882, 73.620361, -166.428882, 73.620361 https://cmr.earthdata.nasa.gov/search/concepts/C2244306092-AMD_KOPRI.umm_json To identify past sea ice changes based on lipid biomarkers of a sediment core (ARA06C-01JPC) covering the Holocene in the Western Arctic. proprietary
KOPRI-KPDC-00001905_1 2015 ARA06C-01JPC: Lipid biomarkers (HBIs, sterols) from core sediments AMD_KOPRI STAC Catalog 2021-01-01 2021-12-31 -166.428882, 73.620361, -166.428882, 73.620361 https://cmr.earthdata.nasa.gov/search/concepts/C2244306092-AMD_KOPRI.umm_json To identify past sea ice changes based on lipid biomarkers of a sediment core (ARA06C-01JPC) covering the Holocene in the Western Arctic. proprietary
+KOPRI-KPDC-00001905_1 2015 ARA06C-01JPC: Lipid biomarkers (HBIs, sterols) from core sediments ALL STAC Catalog 2021-01-01 2021-12-31 -166.428882, 73.620361, -166.428882, 73.620361 https://cmr.earthdata.nasa.gov/search/concepts/C2244306092-AMD_KOPRI.umm_json To identify past sea ice changes based on lipid biomarkers of a sediment core (ARA06C-01JPC) covering the Holocene in the Western Arctic. proprietary
KOPRI-KPDC-00001906_1 Temporal variation of phytoplankton in the surface water of Marian Cove, King George Island, Antarctica, September 2021 - December 2021 AMD_KOPRI STAC Catalog 2021-09-01 2021-12-31 -58.783333, -62.216667, -58.783333, -62.216667 https://cmr.earthdata.nasa.gov/search/concepts/C2244306105-AMD_KOPRI.umm_json As a research on the ecology of phytoplankton in the coastal waters of the King Sejong Station in Antarctica, the community of phytoplankton and the temporal influences of environmental factors were investigated in the Marian Cove, Maxwell Bay of King George Island in Antarctica. Investigation to marine phytoplankton biomass in the coastal waters around the King Sejong Station in Antarctica for the monitoring by environment change of surface sea water conducted. proprietary
KOPRI-KPDC-00001907_1 Temporal variation of marine phytoplankton in the surface water of the Antarctic Jang Bogo Station in Terra Nova Bay, July 2021 - December 2021 AMD_KOPRI STAC Catalog 2021-07-01 2021-12-31 164.2, -74.616667, 164.2, -74.616667 https://cmr.earthdata.nasa.gov/search/concepts/C2244306127-AMD_KOPRI.umm_json As a research on the ecology of phytoplankton in the coastal waters of the Jang Bogo Station in Antarctica, the community of phytoplankton and the temporal influences of environmental factors. The temporal influences of environmental factors on marine phytoplankton community were investigated in the Jang Bogo Station in Antarctica. Investigation of marine phytoplankton biomass in the coastal waters around the Jang Bogo Station in Antarctica for the monitoring by environmental change in the surface sea water conducted. proprietary
KOPRI-KPDC-00001908_1 Stable isotope ratios of carbon and nitrogen from penguin and its diets in the Ross Sea region, 2018-2019 AMD_KOPRI STAC Catalog 2018-10-31 2019-04-16 170.619, -74.5462, 175.8171, -72.0951 https://cmr.earthdata.nasa.gov/search/concepts/C2244306177-AMD_KOPRI.umm_json Antarctic krill and ice krill samples were collected in the western Ross Sea during the ARAON cruise in 2018-2019 (ANA09B). Chick carcasses of Adelie and Emperor penguins were collected at Cape Hallett, Inexpressible Island, Cape Washington, and Coulman Island. Pretreated samples were used for carbon stable isotope analysis, and untreated samples were used for nitrogen stable isotope. The stable isotope ratios of carbon and nitrogen were determined using an isotope ratio mass spectrometer coupled with and elemental analyzer (EA-IRMS). proprietary
@@ -10273,8 +10273,8 @@ L1B_Wind_Products_3.0 Aeolus preliminary HLOS (horizontal line-of-sight) wind ob
L1B_Wind_Products_3.0 Aeolus preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers ALL STAC Catalog 2020-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689596-ESA.umm_json The Level 1B wind product of the Aeolus mission contains the preliminary HLOS (horizontal line-of-sight) wind observations for Rayleigh and Mie receivers, which are generated in Near Real Time. Standard atmospheric correction (Rayleigh channel), receiver response and bias correction is applied. The product is generated within 3 hours after data acquisition. proprietary
L2B_Wind_Products_3.0 Aeolus Scientific L2B Rayleigh/Mie wind product ESA STAC Catalog 2020-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689544-ESA.umm_json The Level 2B wind product of the Aeolus mission is a geo-located consolidated HLOS (horizontal line-of-sight) wind observation with actual atmospheric correction applied to Rayleigh channel. The product is generated by within 3 hours after data acquisition. proprietary
L2B_Wind_Products_3.0 Aeolus Scientific L2B Rayleigh/Mie wind product ALL STAC Catalog 2020-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689544-ESA.umm_json The Level 2B wind product of the Aeolus mission is a geo-located consolidated HLOS (horizontal line-of-sight) wind observation with actual atmospheric correction applied to Rayleigh channel. The product is generated by within 3 hours after data acquisition. proprietary
-L2C_Wind_products_5.0 Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing ALL STAC Catalog 2020-07-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2619280864-ESA.umm_json The Level 2C wind product of the Aeolus mission provides ECMWF analysis horizontal wind vectors at the geolocations of assimilated L2B HLOS wind components. The L2C can therefore be described as an Aeolus-assisted horizontal wind vector product. The L2C is a distinct product, however the L2C and L2B share a common Earth Explorer file template, with the L2C being a superset of the L2B. The L2C consists of extra datasets appended to the L2B product with information which are relevant to the data assimilation of the L2B winds. proprietary
L2C_Wind_products_5.0 Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing ESA STAC Catalog 2020-07-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2619280864-ESA.umm_json The Level 2C wind product of the Aeolus mission provides ECMWF analysis horizontal wind vectors at the geolocations of assimilated L2B HLOS wind components. The L2C can therefore be described as an Aeolus-assisted horizontal wind vector product. The L2C is a distinct product, however the L2C and L2B share a common Earth Explorer file template, with the L2C being a superset of the L2B. The L2C consists of extra datasets appended to the L2B product with information which are relevant to the data assimilation of the L2B winds. proprietary
+L2C_Wind_products_5.0 Aeolus Level 2C assisted wind fields resulting from NWP Numerical Weather Prediction assimilation processing ALL STAC Catalog 2020-07-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2619280864-ESA.umm_json The Level 2C wind product of the Aeolus mission provides ECMWF analysis horizontal wind vectors at the geolocations of assimilated L2B HLOS wind components. The L2C can therefore be described as an Aeolus-assisted horizontal wind vector product. The L2C is a distinct product, however the L2C and L2B share a common Earth Explorer file template, with the L2C being a superset of the L2B. The L2C consists of extra datasets appended to the L2B product with information which are relevant to the data assimilation of the L2B winds. proprietary
L2SW_Open_3.0 SMOS NRT L2 Swath Wind Speed ESA STAC Catalog 2018-05-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689620-ESA.umm_json SMOS retrieved surface wind speed gridded maps (with a spatial sampling of 1/4 x 1/4 degrees) are available in NetCDF format. Each product contains parts of ascending and descending orbits and it is generated by Ifremer, starting from the SMOS L1B data products, in Near Real Time i.e. within 4 to 6 hours from sensing time. Before using this dataset, please check the read-me-first note available in the Resources section below. proprietary
L3SW_Open_4.0 SMOS L3 Daily Wind Speed ESA STAC Catalog 2018-05-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689536-ESA.umm_json SMOS L3WS products are daily composite maps of the collected SMOS L2 swath wind products for a specific day, provided with the same grid than the Level 2 wind data (SMOS L2WS NRT) but separated into ascending and descending passes. This product is available the day after sensing from Ifremer, in NetCDF format. Before using this dataset, please check the read-me-first note available in the Resources section below. proprietary
L3S_LEO_AM-STAR-v2.80_2.80 GHRSST NOAA/STAR ACSPO v2.80 0.02 degree L3S Dataset from mid-Morning LEO Satellites (GDS v2) POCLOUD STAC Catalog 2006-12-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2050135480-POCLOUD.umm_json NOAA STAR produces two lines of gridded 0.02 degree super-collated L3S LEO sub-skin Sea Surface Temperature (SST) datasets, one from the NOAA afternoon JPSS (L3S_LEO_PM) satellites and the other from the EUMETSAT mid-morning Metop (L3S_LEO_AM) satellites. The L3S_LEO_AM is derived from three Low Earth Orbiting (LEO) Metop-FG satellites: Metop-A, -B and -C . The Metop-FG satellite program was jointly established by the European Space Agency (ESA) and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The US National Oceanic and Atmospheric Administration (NOAA) under the joint NOAA/EUMETSAT Initial Joint Polar System Agreement, has contributed three Advanced Very High Resolution Radiometer (AVHRR) sensors capable of collecting and transmitting data in the Full Resolution Area Coverage (FRAC; 1km/nadir) format. The L3S_LEO_AM dataset is produced by aggregating three L3U datasets from MetOp-FG satellites (MetOp-A, -B and -C; all hosted in PO.DAAC) and covers from Dec 2006-present. The L3S_LEO_AM SST dataset is reported in two files per 24-hour interval, daytime and nighttime (nominal Metop local equator crossing times around 09:30/21:30, respectively), in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). The Near Real Time (NRT) L3S-LEO data are archived at PO.DAAC with approximately 6 hours latency, and then replaced by the Re-ANalysis (RAN) files about 2 months later, with identical file names. The dataset is validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014), and monitored in another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010). The L3S SST imagery and local coverage are continuously evaluated, and checked for consistency with other Level 2, 3 and 4 datasets in the ACSPO Regional Monitor for SST (ARMS) system. NOAA plans to include data from other mid-morning platforms and sensors, such as MetOp-SG METImage and Terra MODIS, into L3S_LEO_AM. More information about the dataset can be found under the Documentation and Citation tabs. proprietary
@@ -10292,8 +10292,8 @@ LADSII_hydrographic_survey_1 Hydrographic survey LADSII by the RAN Australian Hy
LAI_Africa_2325_1 MODIS-derived Aggregate, Woody and Herbaceous Leaf Area Index for Africa, 2002-2022 ORNL_CLOUD STAC Catalog 2002-07-05 2022-07-29 -21.28, -40.02, 63.86, 20.02 https://cmr.earthdata.nasa.gov/search/concepts/C2954717391-ORNL_CLOUD.umm_json This dataset provides leaf area index (LAI) estimates for Sub-Saharan Africa for woody, herbaceous, and aggregate vegetation types. The estimates were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4 and the native MODIS LAI product (MCD15A2H Version 6.1), which provides LAI measurements every 8 days at 500-m pixel size. Data from the MCD15A2H product were processed further to generate three layers including: a smoothed and gap filled LAI layer referred to as aggregate leaf area index and two additional layers processed to separate woody LAI (tree and shrubs) and herbaceous LAI (grass and forbs). The data include 31 MODIS 10-degree tiles and cover 2002 to 2022. The data are provided in NetCDF format. proprietary
LAI_Canada_816_1 Leaf Area Index Maps at 30-m Resolution, Selected Sites, Canada ORNL_CLOUD STAC Catalog 2000-01-01 2001-12-31 -135.05, 44.23, -65, 63.14 https://cmr.earthdata.nasa.gov/search/concepts/C2737900059-ORNL_CLOUD.umm_json This data set provides local LAI maps for the selected measured sites in Canada. These derived maps may also be useful for validating other LAI maps over these same sites given that the areas are protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The data set may also be useful for monitoring changes in the land surface.The Leaf Area Index (LAI) maps are at 30-m resolution for the selected sites. LAI is defined here as half the total (all-sided) live foliage area per unit horizontal projected ground surface area. Overstory LAI corresponds to all tree foliage except for treeless areas where it corresponds to total foliage. The algorithms were developed from ground measurements and Landsat TM and ETM+ images (Fernandes et. al., 2003). A mask was developed using the Landsat ETM+/TM5 image and available land cover map to identify only those areas with land cover belonging to the sample land cover classes and with Landsat ETM+/TM5 spectral reflectance values that fell within the convex hull of the spectral reflectance values over the plots. LAI was mapped within the masked region using the Landsat ETM+/TM5 image and the developed transfer function. The final LAI map was scaled by a factor of 20 (offset 0). The LAI maps are in Tagged Image File Format (TIFF). proprietary
LAI_VALERI_Canada_829_1 Leaf Area Index Maps at 30-m Resolution, VALERI Site, Larose, Canada ORNL_CLOUD STAC Catalog 2003-05-08 2003-08-19 -75.24, 45.37, -75.2, 45.39 https://cmr.earthdata.nasa.gov/search/concepts/C2737900380-ORNL_CLOUD.umm_json This data set provide local LAI maps for the Larose (Ontario) site in Canada. These derived maps may also be useful for validating other LAI maps over this same site given that the area is protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The dataset may also be useful for monitoring changes in the land surface. A complete description of producing the maps for the Larose site and the ground measurement campaign is provided in the companion document Larose2003FTReport.pdf. proprietary
-LAI_Woody_Plants_1231_1 A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011 ALL STAC Catalog 1932-01-01 2011-12-31 -164.78, -54.2, 175.62, 78.42 https://cmr.earthdata.nasa.gov/search/concepts/C2784385653-ORNL_CLOUD.umm_json This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources. proprietary
LAI_Woody_Plants_1231_1 A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011 ORNL_CLOUD STAC Catalog 1932-01-01 2011-12-31 -164.78, -54.2, 175.62, 78.42 https://cmr.earthdata.nasa.gov/search/concepts/C2784385653-ORNL_CLOUD.umm_json This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources. proprietary
+LAI_Woody_Plants_1231_1 A Global Database of Field-observed Leaf Area Index in Woody Plant Species, 1932-2011 ALL STAC Catalog 1932-01-01 2011-12-31 -164.78, -54.2, 175.62, 78.42 https://cmr.earthdata.nasa.gov/search/concepts/C2784385653-ORNL_CLOUD.umm_json This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources. proprietary
LAI_surfaces_747_1 BigFoot Leaf Area Index Surfaces for North and South American Sites, 2000-2003 ORNL_CLOUD STAC Catalog 2000-01-01 2003-12-31 -156.61, -2.86, -54.96, 71.27 https://cmr.earthdata.nasa.gov/search/concepts/C2751481204-ORNL_CLOUD.umm_json The BigFoot project gathered leaf area index (LAI) data for nine EOS Land Validation Sites located from Alaska to Brazil from 2000 to 2003. Each site is representative of one or two distinct biomes, including the Arctic tundra; boreal evergreen needleleaf forest; temperate cropland, grassland, evergreen needleleaf forest, and deciduous broadleaf forest; desert grassland and shrubland; and tropical evergreen broadleaf forest. LAI was measured at plots within each site for at least two years using standard direct and optical methods at each site. BigFoot was funded by NASA's Terrestrial Ecology Program. proprietary
LAMONT_ATL_0 Lamont-Doherty Earth Observatory measurements from the South Atlantic Ocean (ATL) OB_DAAC STAC Catalog 2015-09-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360421-OB_DAAC.umm_json Measurements from the South Atlantic Ocean (ATL) made by researchers at Columbia Universitys Lamont-Doherty Earth Observatory (LDEO). proprietary
LAMONT_GOM_0 Lamont-Doherty Earth Observatory measurements from the Gulf of Mexico (GOM) OB_DAAC STAC Catalog 2010-08-22 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360423-OB_DAAC.umm_json Measurements from the Gulf of Mexico (GOM) made by researchers at Columbia University's Lamont-Doherty Earth Observatory (LDEO). proprietary
@@ -10417,8 +10417,8 @@ LEOLSTCMG30_002 Low Earth Orbit Land Surface Temperature Monthly Global Gridded
LEO_0 Long-term Ecosystem Observatory (LEO) oceanographic and meteorological data collection system OB_DAAC STAC Catalog 2001-07-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360429-OB_DAAC.umm_json Measurements from the LEO station off the Atlantic Coast of New Jersey in 2001. proprietary
LEVEL_1C__3_5.0 Proba-V 1Km, 333m, and 100m products ESA STAC Catalog 2013-11-28 -180, -56, 180, 75 https://cmr.earthdata.nasa.gov/search/concepts/C1965336924-ESA.umm_json The Proba-V VEGETATION Raw products (Level 1C/P) and synthesis products (Level 3, S1 = daily, S5 = 5 days, S10 = decade) ensure coverage of all significant landmasses worldwide with, in the case of a 10-day synthesis product, a minimum effect of cloud cover, resulting from selection of cloud-free acquisitions during the 10-day period. It ensures a daily coverage between Lat. 35°N and 75°N, and between 35°S and 56°S, and a full coverage every two days at equator. The VEGETATION instrument is pre-programmed with an indefinite repeated sequence of acquisitions. This nominal acquisition scenario allows a continuous series of identical products to be generated, aiming to map land cover and vegetation growth across the entire planet every two days.Products overview • Projection: Plate carrée projection • Spectral bands: All 4 + NDVI • Format: HDF5 & GeoTiFF The Proba-V VEGETATION Level 3 synthesis products are divided into so called granules, each measuring 10 degrees x 10 degrees, each granule being delivered as a single file. Level 3 products are: - Syntesys S1, with resolution 100m (TOA, TOC and TOC NDVI reflectance), 333m (TOA and TOC reflectance) and 1km (TOA and TOC reflectance) - Syntesys S5, with resolution 100m (TOA, TOC and TOC NDVI reflectance) - Syntesys S10, with resolution 333m (TOC and TOC NDVI reflectance) and 1km (TOC and TOC NDVI reflectance) proprietary
LF_Bibliography_1 Bibliography of papers relevant to longline fishing. AU_AADC STAC Catalog 1972-01-01 -180, -80, 180, 85 https://cmr.earthdata.nasa.gov/search/concepts/C1214313596-AU_AADC.umm_json The bibliography covers a wealth of published, 'grey', and unpublished literature addressing the effects of longline fishing on seabird mortality. The scope is global, but with a special emphasis on the Southern Ocean. Information on longline methodology is included and attention is given to materials that cover the various mitigation methods in use, tested or proposed. Further, information on the relevant aspects of the ecology of affected seabird species is covered, especially that dealing with mortality levels, at-sea distributions and population and conservation biology. Data sources covered include the scientific literature, popular publications, newspaper articles, videos, brochures, maps and posters, as well as government, NGO and IGO reports. proprietary
-LGB_10m_traverse_1 10 m firn temperature data: LGB traverses 1990-95 ALL STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313574-AU_AADC.umm_json The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. Ten metre depth (10 m) firn temperatures, as a proxy indicator of annual mean surface temperature at a site, were recorded approximately every 30 km along the 2014 km main traverse route from LGB00 (68.6543 S, 61.1201 E) near Mawson Station, to LGB72 (69.9209 S, 76.4933 E) near Davis Station. 10 m depth firn temperatures were recorded manually in field notebooks and the data transferred to spreadsheet files (MS Excel). Summary data (30 km spatial resolution) can be obtained from CRC Research Note No.09 'Surface Mass Balance and Snow Surface Properties from the Lambert Glacier Basin Traverses 1990-94'. This work was completed as part of ASAC projects 3 and 2216. Some of this data have been stored in a very old format. The majority of files have been updated to current formats, but some files (kaleidograph files in particular) were not able to be modified due to a lack of appropriate software. However, these files are simply figures, and can be regenerated from the raw data (also provided). The fields in this dataset are: Latitutde Longitude Height Cane Distance Elevation Density Mass Accumulation Year Delta Oxygen-18 Grain Size Ice Crusts Depth Hoar proprietary
LGB_10m_traverse_1 10 m firn temperature data: LGB traverses 1990-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313574-AU_AADC.umm_json The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. Ten metre depth (10 m) firn temperatures, as a proxy indicator of annual mean surface temperature at a site, were recorded approximately every 30 km along the 2014 km main traverse route from LGB00 (68.6543 S, 61.1201 E) near Mawson Station, to LGB72 (69.9209 S, 76.4933 E) near Davis Station. 10 m depth firn temperatures were recorded manually in field notebooks and the data transferred to spreadsheet files (MS Excel). Summary data (30 km spatial resolution) can be obtained from CRC Research Note No.09 'Surface Mass Balance and Snow Surface Properties from the Lambert Glacier Basin Traverses 1990-94'. This work was completed as part of ASAC projects 3 and 2216. Some of this data have been stored in a very old format. The majority of files have been updated to current formats, but some files (kaleidograph files in particular) were not able to be modified due to a lack of appropriate software. However, these files are simply figures, and can be regenerated from the raw data (also provided). The fields in this dataset are: Latitutde Longitude Height Cane Distance Elevation Density Mass Accumulation Year Delta Oxygen-18 Grain Size Ice Crusts Depth Hoar proprietary
+LGB_10m_traverse_1 10 m firn temperature data: LGB traverses 1990-95 ALL STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313574-AU_AADC.umm_json The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. Ten metre depth (10 m) firn temperatures, as a proxy indicator of annual mean surface temperature at a site, were recorded approximately every 30 km along the 2014 km main traverse route from LGB00 (68.6543 S, 61.1201 E) near Mawson Station, to LGB72 (69.9209 S, 76.4933 E) near Davis Station. 10 m depth firn temperatures were recorded manually in field notebooks and the data transferred to spreadsheet files (MS Excel). Summary data (30 km spatial resolution) can be obtained from CRC Research Note No.09 'Surface Mass Balance and Snow Surface Properties from the Lambert Glacier Basin Traverses 1990-94'. This work was completed as part of ASAC projects 3 and 2216. Some of this data have been stored in a very old format. The majority of files have been updated to current formats, but some files (kaleidograph files in particular) were not able to be modified due to a lack of appropriate software. However, these files are simply figures, and can be regenerated from the raw data (also provided). The fields in this dataset are: Latitutde Longitude Height Cane Distance Elevation Density Mass Accumulation Year Delta Oxygen-18 Grain Size Ice Crusts Depth Hoar proprietary
LGB_Del_traverse_1 Delta Oxygen-18 isotope data: LGB traverses 1989-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313576-AU_AADC.umm_json The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. Several shallow depth ice cores (15-60 m) were drilled at selected sites along 2014 km of the main traverse track from LGB00 (68.6543 S, 61.1201 E) near Mawson Station to LGB72 (69.9209 S,76.4933 E) near Davis Station, and at selected sites along a western traverse line from LGB00 toward Enderby Land. Surface cores (2 m) were collected at 30 km intervals along the entire route from LGB00-LGB72. Ice cores have been kept in cool storage at a local cold room storage facility. Isotope data from the cores have been saved in various spreadsheet files (mainly MS Excel). Initial summary data can be obtained from CRC Research Note No.09 'Surface mass balance and snow surface properties from the Lambert Glacier Basin Traverses 1990-94'. This work was completed as part of ASAC projects 3 and 2216. Some of this data have been stored in a very old format. The majority of files have been updated to current formats, but some files (kaleidograph files in particular) were not able to be modified due to a lack of appropriate software. However, these files are simply figures, and can be regenerated from the raw data (also provided). The fields in this dataset are: Latitutde Longitude Height Cane Distance Elevation Density Mass Accumulation Year Delta Oxygen-18 Grain Size Ice Crusts Depth Hoar proprietary
LGB_Gra_traverse_1 Earth gravity field for ice thickness data: LGB traverses 1989-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313598-AU_AADC.umm_json The Lambert Glacier Basin (LGB) series of five oversnow traverses were conducted from 1989-95. LaCoste and Romberg gravity meters were used to record measurements of the Earth's gravity field approximately every 2 km along the 2014 km main traverse route from LGB00 (68.6543 S, 61.1201 E) near Mawson Station, to LGB72 (69.9209 S, 76.4933 E) near Davis Station. Gravity readings were also obtained at 5 km intervals along a 516 km upper western offset track (50 km parallel upslope from main route) from LGBUW485 (68.6458 S, 60.0272 E) to LGBUW000 (72.6508 S, 55.9275 E). Raw data were stored as meter readings in field notebooks, transferred manually to spreadsheet files (MS Excel). Processed data were stored in spreadsheet files (MS Excel). The data available at the url below are stored in various formats. Summary data (2 km spatial resolution) can be obtained from CRC Research Note No.27 'Ice Thicknesses and Surface and Bedrock Elevations from the Lambert Glacier Basin Traverses 1990-95'. Documents providing archive details of the logbooks are available for download from the provided URL. This work was completed as part of ASAC projects 3 and 2216. Logbook(s): - Gravity Meter Log 89/90 - LGBT Gravity #2 1992-93 - Glaciology Gravity Readings LGBT 1990-91 proprietary
LGB_Ht_traverse_1 Ice sheet surface elevation data: LGB traverses 1989-95 AU_AADC STAC Catalog 1989-11-01 1995-02-28 54, -77, 78, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214313577-AU_AADC.umm_json The ANARE Lambert Glacier Basin (LGB) series of oversnow traverses were conducted during the period 1989-95. Field operations were carried out along the proximity of the 2500 m elevation contour around the interior basin between Mawson and Davis stations. The main traverse route covered some 2014 km of track from LGB00 at 68.6543 S, 61.1201 E, and LGB72 at 69.9209 S, 76.4933 E. An offset route (50 km upslope) parallels the main traverse track around the western half of the basin. Raw data were stored in binary files containing pressure, temperature, navigational position and a variety of other parameters at an approximately 10 m spacing associated with each 2 km long section of track. Processed data were stored as 2 km averaged ice sheet surface elevation spreadsheet files (MS Excel). The data available at the url below are stored in various formats. Summary data (2 km spatial average) can be obtained from CRC Research Note No. 27 'Ice Thicknesses and Surface and Bedrock Elevations from the Lambert Glacier Basin Traverses 1989-95'. This work was completed as part of ASAC projects 3 and 2216. proprietary
@@ -10526,8 +10526,8 @@ Lab96_0 Labrador Sea measurements in 1996 OB_DAAC STAC Catalog 1996-10-20 -180,
LakeBathymetry_Model_NSlope_AK_2243_1 Lake Bathymetry Maps derived from Landsat and Random Forest Modeling, North Slope, AK ORNL_CLOUD STAC Catalog 2016-07-01 2018-08-31 -177.47, 56.09, -128.2, 77.26 https://cmr.earthdata.nasa.gov/search/concepts/C2837050574-ORNL_CLOUD.umm_json This dataset provides lake bathymetry maps derived from Landsat surface reflectance products for a portion of the North Slope area of Alaska. A random forest regression algorithm was used to generate depths for each point identified as being part of a lake, creating depth prediction files for each Landsat scene available for the study period: 2016-07-01 to 2018-08-31. These products are fitted to the ABoVE standard projection and reference grid to make them easily scalable and geometrically compatible with other products in the ABoVE study domain. The data are provided in cloud-optimized GeoTIFF (COG) format. proprietary
LakeSuperior_0 University of Rhode Island measurements in Lake Superior OB_DAAC STAC Catalog 2013-05-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360420-OB_DAAC.umm_json Measurements made in Lake Superior by researchers at the University of Rhode Island. proprietary
Lake_MI_2012_WaterQual_0 Water quality monitoring program in Lake Michigan and Green Bay OB_DAAC STAC Catalog 2012-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360419-OB_DAAC.umm_json Measurements taken in Lake Michigan and Green Bay in 2012 as part of a water quality monitoring program. proprietary
-Lake_Wetland_Classes_UAVSAR_1883_1 ABoVE: Lake and Wetland Classification from L-band SAR, Alaska and Canada, 2017-2019 ALL STAC Catalog 2017-01-01 2019-09-19 -149.16, 53.71, -107.86, 67.91 https://cmr.earthdata.nasa.gov/search/concepts/C2192619280-ORNL_CLOUD.umm_json This dataset contains a high-resolution land cover classification focused on water and wetland vegetation classes over three NASA ABoVE Campaign regions: Yukon Flats, Alaska, USA; the Peace-Athabasca Delta, Alberta; and the Canadian Shield, Northwest Territories (NWT), Canada. The product was derived from L-band synthetic aperture radar (SAR) acquisitions from the airborne NASA UAVSAR instrument in 2017-2019. The classification was trained and validated from field visits, UAV images, satellite imagery as well as other ABoVE datasets. Classifications in all regions are provided as both preliminary 13-class versions and final, simplified 5-class versions. Training and test data used for the classifier are also included as well as characteristics of lakes in the study area. This land cover classification was developed to support a project focusing on potential methane emissions from the shallow near-shore, or littoral, regions of lakes. The emergent aquatic vegetation classes can be used as a proxy for these littoral zones. Wetland vegetation classifications are provided as gridded raster files with an approximately 5-meter spatial resolution and aligned with the original UAVSAR footprints. Composite mosaics that aggregate these UAVSAR scenes by region and day of acquisition, if applicable, are also provided. Classifications in all regions are provided as both preliminary 13-class versions and final 5-class versions. proprietary
Lake_Wetland_Classes_UAVSAR_1883_1 ABoVE: Lake and Wetland Classification from L-band SAR, Alaska and Canada, 2017-2019 ORNL_CLOUD STAC Catalog 2017-01-01 2019-09-19 -149.16, 53.71, -107.86, 67.91 https://cmr.earthdata.nasa.gov/search/concepts/C2192619280-ORNL_CLOUD.umm_json This dataset contains a high-resolution land cover classification focused on water and wetland vegetation classes over three NASA ABoVE Campaign regions: Yukon Flats, Alaska, USA; the Peace-Athabasca Delta, Alberta; and the Canadian Shield, Northwest Territories (NWT), Canada. The product was derived from L-band synthetic aperture radar (SAR) acquisitions from the airborne NASA UAVSAR instrument in 2017-2019. The classification was trained and validated from field visits, UAV images, satellite imagery as well as other ABoVE datasets. Classifications in all regions are provided as both preliminary 13-class versions and final, simplified 5-class versions. Training and test data used for the classifier are also included as well as characteristics of lakes in the study area. This land cover classification was developed to support a project focusing on potential methane emissions from the shallow near-shore, or littoral, regions of lakes. The emergent aquatic vegetation classes can be used as a proxy for these littoral zones. Wetland vegetation classifications are provided as gridded raster files with an approximately 5-meter spatial resolution and aligned with the original UAVSAR footprints. Composite mosaics that aggregate these UAVSAR scenes by region and day of acquisition, if applicable, are also provided. Classifications in all regions are provided as both preliminary 13-class versions and final 5-class versions. proprietary
+Lake_Wetland_Classes_UAVSAR_1883_1 ABoVE: Lake and Wetland Classification from L-band SAR, Alaska and Canada, 2017-2019 ALL STAC Catalog 2017-01-01 2019-09-19 -149.16, 53.71, -107.86, 67.91 https://cmr.earthdata.nasa.gov/search/concepts/C2192619280-ORNL_CLOUD.umm_json This dataset contains a high-resolution land cover classification focused on water and wetland vegetation classes over three NASA ABoVE Campaign regions: Yukon Flats, Alaska, USA; the Peace-Athabasca Delta, Alberta; and the Canadian Shield, Northwest Territories (NWT), Canada. The product was derived from L-band synthetic aperture radar (SAR) acquisitions from the airborne NASA UAVSAR instrument in 2017-2019. The classification was trained and validated from field visits, UAV images, satellite imagery as well as other ABoVE datasets. Classifications in all regions are provided as both preliminary 13-class versions and final, simplified 5-class versions. Training and test data used for the classifier are also included as well as characteristics of lakes in the study area. This land cover classification was developed to support a project focusing on potential methane emissions from the shallow near-shore, or littoral, regions of lakes. The emergent aquatic vegetation classes can be used as a proxy for these littoral zones. Wetland vegetation classifications are provided as gridded raster files with an approximately 5-meter spatial resolution and aligned with the original UAVSAR footprints. Composite mosaics that aggregate these UAVSAR scenes by region and day of acquisition, if applicable, are also provided. Classifications in all regions are provided as both preliminary 13-class versions and final 5-class versions. proprietary
LandCoverNet Africa_1 LandCoverNet Africa MLHUB STAC Catalog 2020-01-01 2023-01-01 -15.9378605, -31.6878376, 46.873921, 31.3398255 https://cmr.earthdata.nasa.gov/search/concepts/C2781412437-MLHUB.umm_json LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Africa contains data across Africa, which accounts for ~1/5 of the global dataset. Each pixel is identified as one of the seven land cover classes based on its annual time series. These classes are water, natural bare ground, artificial bare ground, woody vegetation, cultivated vegetation, (semi) natural vegetation, and permanent snow/ice.
There are a total of 1980 image chips of 256 x 256 pixels in LandCoverNet Africa V1.0 spanning 66 tiles. Each image chip contains temporal observations from the following satellite products with an annual class label, all stored in raster format (GeoTIFF files): * Sentinel-1 ground range distance (GRD) with radiometric calibration and orthorectification at 10m spatial resolution * Sentinel-2 surface reflectance product (L2A) at 10m spatial resolution * Landsat-8 surface reflectance product from Collection 2 Level-2
Radiant Earth Foundation designed and generated this dataset with a grant from [Schmidt Futures](https://schmidtfutures.com/) with additional support from [NASA ACCESS](https://earthdata.nasa.gov/esds/competitive-programs/access/radiant-mlhub), [Microsoft AI for Earth](https://www.microsoft.com/en-us/ai/ai-for-earth) and in kind technology support from [Sinergise](https://www.sinergise.com/). proprietary
LandCoverNet Asia_1 LandCoverNet Asia MLHUB STAC Catalog 2020-01-01 2023-01-01 33.0205908, -7.3097478, 160.7091112, 58.6174213 https://cmr.earthdata.nasa.gov/search/concepts/C2781412195-MLHUB.umm_json LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Asia contains data across Asia, which accounts for ~31% of the global dataset. Each pixel is identified as one of the seven land cover classes based on its annual time series. These classes are water, natural bare ground, artificial bare ground, woody vegetation, cultivated vegetation, (semi) natural vegetation, and permanent snow/ice.
There are a total of 2753 image chips of 256 x 256 pixels in LandCoverNet South America V1.0 spanning 92 tiles. Each image chip contains temporal observations from the following satellite products with an annual class label, all stored in raster format (GeoTIFF files):
* Sentinel-1 ground range distance (GRD) with radiometric calibration and orthorectification at 10m spatial resolution
* Sentinel-2 surface reflectance product (L2A) at 10m spatial resolution
* Landsat-8 surface reflectance product from Collection 2 Level-2
Radiant Earth Foundation designed and generated this dataset with a grant from [Schmidt Futures](https://schmidtfutures.com/) with additional support from [NASA ACCESS](https://earthdata.nasa.gov/esds/competitive-programs/access/radiant-mlhub), [Microsoft AI for Earth](https://www.microsoft.com/en-us/ai/ai-for-earth) and in kind technology support from [Sinergise](https://www.sinergise.com/). proprietary
LandCoverNet Australia_1 LandCoverNet Australia MLHUB STAC Catalog 2020-01-01 2023-01-01 123.0069917, -46.1160741, 172.3714334, -14.4766436 https://cmr.earthdata.nasa.gov/search/concepts/C2781412728-MLHUB.umm_json LandCoverNet is a global annual land cover classification training dataset with labels for the multi-spectral satellite imagery from Sentinel-1, Sentinel-2 and Landsat-8 missions in 2018. LandCoverNet Australia contains data across Australia, which accounts for ~7% of the global dataset. Each pixel is identified as one of the seven land cover classes based on its annual time series. These classes are water, natural bare ground, artificial bare ground, woody vegetation, cultivated vegetation, (semi) natural vegetation, and permanent snow/ice.
There are a total of 600 image chips of 256 x 256 pixels in LandCoverNet Australia V1.0 spanning 20 tiles. Each image chip contains temporal observations from the following satellite products with an annual class label, all stored in raster format (GeoTIFF files):
* Sentinel-1 ground range distance (GRD) with radiometric calibration and orthorectification at 10m spatial resolution
* Sentinel-2 surface reflectance product (L2A) at 10m spatial resolution
* Landsat-8 surface reflectance product from Collection 2 Level-2
Radiant Earth Foundation designed and generated this dataset with a grant from [Schmidt Futures](https://schmidtfutures.com/) with additional support from [NASA ACCESS](https://earthdata.nasa.gov/esds/competitive-programs/access/radiant-mlhub), [Microsoft AI for Earth](https://www.microsoft.com/en-us/ai/ai-for-earth) and in kind technology support from [Sinergise](https://www.sinergise.com/). proprietary
@@ -10555,8 +10555,8 @@ Leaf_Carbon_Nutrients_1106_1 A Global Database of Carbon and Nutrient Concentrat
Leaf_Carbon_Nutrients_1106_1 A Global Database of Carbon and Nutrient Concentrations of Green and Senesced Leaves ORNL_CLOUD STAC Catalog 1970-01-01 2009-12-31 -159.7, -50, 176.9, 68.5 https://cmr.earthdata.nasa.gov/search/concepts/C2784383820-ORNL_CLOUD.umm_json This data set provides carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations in green and senesced leaves. Vegetation characteristics reported include species growth habit, leaf area, mass, and mass loss with senescence. The data were compiled from 86 selected studies in 31 countries, and resulted in approximately 1,000 data points for both green and senesced leaves from woody and non-woody vegetation as described in Vergutz et al (2012). The studies were conducted from 1970-2009. There are two comma-delimited data files with this data set. proprietary
Leaf_Photosynthesis_Traits_1224_1 A Global Data Set of Leaf Photosynthetic Rates, Leaf N and P, and Specific Leaf Area ORNL_CLOUD STAC Catalog 1993-01-01 2010-12-31 -122.4, -43.2, 176.13, 58.42 https://cmr.earthdata.nasa.gov/search/concepts/C2784384781-ORNL_CLOUD.umm_json This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file. proprietary
Leaf_Photosynthesis_Traits_1224_1 A Global Data Set of Leaf Photosynthetic Rates, Leaf N and P, and Specific Leaf Area ALL STAC Catalog 1993-01-01 2010-12-31 -122.4, -43.2, 176.13, 58.42 https://cmr.earthdata.nasa.gov/search/concepts/C2784384781-ORNL_CLOUD.umm_json This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file. proprietary
-Level_2A_aerosol_cloud_optical_products_3.0 Aeolus L2A Aerosol/Cloud optical product ESA STAC Catalog 2021-05-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2207498185-ESA.umm_json The Level 2A aerosol/cloud optical products of the Aeolus mission include geo-located consolidated backscatter and extinction profiles, backscatter-to-extinction coefficient, LIDAR ratio, scene classification, heterogeneity index and attenuated backscatter signals. Resolution - Horizontal resolution of L2A optical properties at observation scale (~87 km); Exceptions are group properties (horizontal accumulation of measurements from ~3 km to ~87 km) and attenuated backscatters (~3 km); Note: the resolution of "groups" in the L2A can only go down to 5 measurements at the moment, i.e. ~15 km horizontal resolution. This could be configured to go to 1 measurement - Vertical resolution 250-2000 m (Defined by Range Bin Settings https://earth.esa.int/eogateway/instruments/aladin/overview-of-the-main-wind-rbs-changes). proprietary
Level_2A_aerosol_cloud_optical_products_3.0 Aeolus L2A Aerosol/Cloud optical product ALL STAC Catalog 2021-05-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2207498185-ESA.umm_json The Level 2A aerosol/cloud optical products of the Aeolus mission include geo-located consolidated backscatter and extinction profiles, backscatter-to-extinction coefficient, LIDAR ratio, scene classification, heterogeneity index and attenuated backscatter signals. Resolution - Horizontal resolution of L2A optical properties at observation scale (~87 km); Exceptions are group properties (horizontal accumulation of measurements from ~3 km to ~87 km) and attenuated backscatters (~3 km); Note: the resolution of "groups" in the L2A can only go down to 5 measurements at the moment, i.e. ~15 km horizontal resolution. This could be configured to go to 1 measurement - Vertical resolution 250-2000 m (Defined by Range Bin Settings https://earth.esa.int/eogateway/instruments/aladin/overview-of-the-main-wind-rbs-changes). proprietary
+Level_2A_aerosol_cloud_optical_products_3.0 Aeolus L2A Aerosol/Cloud optical product ESA STAC Catalog 2021-05-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2207498185-ESA.umm_json The Level 2A aerosol/cloud optical products of the Aeolus mission include geo-located consolidated backscatter and extinction profiles, backscatter-to-extinction coefficient, LIDAR ratio, scene classification, heterogeneity index and attenuated backscatter signals. Resolution - Horizontal resolution of L2A optical properties at observation scale (~87 km); Exceptions are group properties (horizontal accumulation of measurements from ~3 km to ~87 km) and attenuated backscatters (~3 km); Note: the resolution of "groups" in the L2A can only go down to 5 measurements at the moment, i.e. ~15 km horizontal resolution. This could be configured to go to 1 measurement - Vertical resolution 250-2000 m (Defined by Range Bin Settings https://earth.esa.int/eogateway/instruments/aladin/overview-of-the-main-wind-rbs-changes). proprietary
LiDAR_Forest_Inventory_Brazil_1644_1 LiDAR Surveys over Selected Forest Research Sites, Brazilian Amazon, 2008-2018 ORNL_CLOUD STAC Catalog 2008-01-01 2018-12-31 -68.3, -26.7, -39.06, -1.58 https://cmr.earthdata.nasa.gov/search/concepts/C2398128915-ORNL_CLOUD.umm_json This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time. proprietary
LiDAR_Tundra_Forest_AK_1782_1 ABoVE: Terrestrial Lidar Scanning Forest-Tundra Ecotone, Brooks Range, Alaska, 2016 ALL STAC Catalog 2016-06-14 2016-06-25 -149.76, 67.97, -149.71, 68.02 https://cmr.earthdata.nasa.gov/search/concepts/C2143401877-ORNL_CLOUD.umm_json This dataset provides terrestrial lidar scanning (TLS) point cloud data collected at 10 research plots along the forest-tundra ecotone (FTE) in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. Data were collected in mid-June 2016. Data were acquired for each plot from multiple scan positions with a Leica ScanStation C10 green wavelength laser instrument. After processing the point spacing is < 1 cm. TLS enables resolution of 3-dimensional landscape features that can be used to derive ecologically important metrics of canopy structure and surface topography at high spatial resolution. proprietary
LiDAR_Tundra_Forest_AK_1782_1 ABoVE: Terrestrial Lidar Scanning Forest-Tundra Ecotone, Brooks Range, Alaska, 2016 ORNL_CLOUD STAC Catalog 2016-06-14 2016-06-25 -149.76, 67.97, -149.71, 68.02 https://cmr.earthdata.nasa.gov/search/concepts/C2143401877-ORNL_CLOUD.umm_json This dataset provides terrestrial lidar scanning (TLS) point cloud data collected at 10 research plots along the forest-tundra ecotone (FTE) in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. Data were collected in mid-June 2016. Data were acquired for each plot from multiple scan positions with a Leica ScanStation C10 green wavelength laser instrument. After processing the point spacing is < 1 cm. TLS enables resolution of 3-dimensional landscape features that can be used to derive ecologically important metrics of canopy structure and surface topography at high spatial resolution. proprietary
@@ -10987,8 +10987,8 @@ MESSR_MOS-1_L2_Data_NA MESSR/MOS-1 L2 Data JAXA STAC Catalog 1987-02-24 1995-11-
MESSR_MOS-1b_L2_Data_NA MESSR/MOS-1b L2 Data JAXA STAC Catalog 1990-03-09 1996-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2698133853-JAXA.umm_json MESSR/MOS-1b L2 Data is obtained from the MESSR sensor onboard MOS-1b, Japan's first marine observation satellite, and produced by the National Space Development Agency of Japan:NASDA. MOS-1b which has the same functions as MOS-1 is Sun-synchronous sub-recurrent Orbit satellite launched on February 7, 1990 as a link in a global satellite observation system for more effective natural resource utilization and for environmental protection. The MESSR is multi-spectral radiometers and has swath of 100 km. This dataset includes radiometric and geometric corrected applied raw data.Map projction is UTM, SOM, PS. The provided format is CEOS. The spatial resolution is 50 m. proprietary
MFLL_CO2_Weighting_Functions_1891_1 ACT-America: L2 Weighting Functions for Airborne Lidar Column-avg CO2, Eastern USA ORNL_CLOUD STAC Catalog 2016-05-27 2018-05-20 -106.05, 27.23, -71.91, 49.11 https://cmr.earthdata.nasa.gov/search/concepts/C2704977536-ORNL_CLOUD.umm_json This dataset provides vertical weighting function coefficients of the Level 2 (L2) remotely sensed column-average carbon dioxide (CO2) concentrations measured during airborne campaigns in Summer 2016, Winter 2017, Fall 2017, and Spring 2018 conducted over central and eastern regions of the U.S. for the Atmospheric Carbon and Transport (ACT-America) project. Column-average CO2 concentrations were measured at a 0.1-second frequency during flights of the C-130 Hercules aircraft at altitudes up to 8 km with a Multi-functional Fiber Laser Lidar (MFLL; Harris Corporation). The MFLL is a set of Continuous-Wave (CW) lidar instruments consisting of an intensity-modulated multi-frequency single-beam synchronous-detection Laser Absorption Spectrometer (LAS) operating at 1571 nm for measuring the column amount of CO2 number density and range between the aircraft and the surface or to cloud tops, and surface reflectance and a Pseudo-random Noise (PN) altimeter at 1596 nm for measuring the path length from the aircraft to the scattering surface and/or cloud tops. The MFLL was onboard all ACT-America seasonal campaigns, except Summer 2019. The MFLL-measured column-averaged CO2 values have certain distinct vertical weights on CO2 profiles depending on the meteorological conditions and the wavelengths used at the measurement time and location. This product includes the instrument location at the time of measurement in geographic coordinates and altitude, along with a vector of weighting function values representing conditions along the nadir direction. proprietary
MFLL_CO2_Weighting_Functions_1891_1 ACT-America: L2 Weighting Functions for Airborne Lidar Column-avg CO2, Eastern USA ALL STAC Catalog 2016-05-27 2018-05-20 -106.05, 27.23, -71.91, 49.11 https://cmr.earthdata.nasa.gov/search/concepts/C2704977536-ORNL_CLOUD.umm_json This dataset provides vertical weighting function coefficients of the Level 2 (L2) remotely sensed column-average carbon dioxide (CO2) concentrations measured during airborne campaigns in Summer 2016, Winter 2017, Fall 2017, and Spring 2018 conducted over central and eastern regions of the U.S. for the Atmospheric Carbon and Transport (ACT-America) project. Column-average CO2 concentrations were measured at a 0.1-second frequency during flights of the C-130 Hercules aircraft at altitudes up to 8 km with a Multi-functional Fiber Laser Lidar (MFLL; Harris Corporation). The MFLL is a set of Continuous-Wave (CW) lidar instruments consisting of an intensity-modulated multi-frequency single-beam synchronous-detection Laser Absorption Spectrometer (LAS) operating at 1571 nm for measuring the column amount of CO2 number density and range between the aircraft and the surface or to cloud tops, and surface reflectance and a Pseudo-random Noise (PN) altimeter at 1596 nm for measuring the path length from the aircraft to the scattering surface and/or cloud tops. The MFLL was onboard all ACT-America seasonal campaigns, except Summer 2019. The MFLL-measured column-averaged CO2 values have certain distinct vertical weights on CO2 profiles depending on the meteorological conditions and the wavelengths used at the measurement time and location. This product includes the instrument location at the time of measurement in geographic coordinates and altitude, along with a vector of weighting function values representing conditions along the nadir direction. proprietary
-MFLL_XCO2_Range_10Hz_1892_1 ACT-America: L2 Remotely Sensed Column-avg CO2 by Airborne Lidar, Lite, Eastern USA ORNL_CLOUD STAC Catalog 2016-05-27 2018-05-20 -106.05, 27.23, -71.91, 49.11 https://cmr.earthdata.nasa.gov/search/concepts/C2704971204-ORNL_CLOUD.umm_json This dataset provides a direct subset (i.e., the Lite version) of the Level 2 (L2) remotely sensed column-average carbon dioxide (CO2) concentrations measured during airborne campaigns in Summer 2016, Winter 2017, Fall 2017, and Spring 2018 conducted over central and eastern regions of the U.S. for the Atmospheric Carbon and Transport (ACT-America) project. Column-average CO2 concentrations were measured at a 0.1-second frequency during flights of the C-130 Hercules aircraft at altitudes up to 8 km with a Multi-functional Fiber Laser Lidar (MFLL; Harris Corporation). The MFLL is a set of Continuous-Wave (CW) lidar instruments consisting of an intensity-modulated multi-frequency single-beam synchronous-detection Laser Absorption Spectrometer (LAS) operating at 1571 nm for measuring the column amount of CO2 number density and range between the aircraft and the surface or to cloud tops, and surface reflectance and a Pseudo-random Noise (PN) altimeter at 1596 nm for measuring the path length from the aircraft to the scattering surface and/or cloud tops. The MFLL was onboard all ACT-America seasonal campaigns, except Summer 2019. Complete aircraft flight information, interpolated to the 0.1-second column CO2 reporting frequency, is included, but not limited to, latitude, longitude, altitude, and attitude. proprietary
MFLL_XCO2_Range_10Hz_1892_1 ACT-America: L2 Remotely Sensed Column-avg CO2 by Airborne Lidar, Lite, Eastern USA ALL STAC Catalog 2016-05-27 2018-05-20 -106.05, 27.23, -71.91, 49.11 https://cmr.earthdata.nasa.gov/search/concepts/C2704971204-ORNL_CLOUD.umm_json This dataset provides a direct subset (i.e., the Lite version) of the Level 2 (L2) remotely sensed column-average carbon dioxide (CO2) concentrations measured during airborne campaigns in Summer 2016, Winter 2017, Fall 2017, and Spring 2018 conducted over central and eastern regions of the U.S. for the Atmospheric Carbon and Transport (ACT-America) project. Column-average CO2 concentrations were measured at a 0.1-second frequency during flights of the C-130 Hercules aircraft at altitudes up to 8 km with a Multi-functional Fiber Laser Lidar (MFLL; Harris Corporation). The MFLL is a set of Continuous-Wave (CW) lidar instruments consisting of an intensity-modulated multi-frequency single-beam synchronous-detection Laser Absorption Spectrometer (LAS) operating at 1571 nm for measuring the column amount of CO2 number density and range between the aircraft and the surface or to cloud tops, and surface reflectance and a Pseudo-random Noise (PN) altimeter at 1596 nm for measuring the path length from the aircraft to the scattering surface and/or cloud tops. The MFLL was onboard all ACT-America seasonal campaigns, except Summer 2019. Complete aircraft flight information, interpolated to the 0.1-second column CO2 reporting frequency, is included, but not limited to, latitude, longitude, altitude, and attitude. proprietary
+MFLL_XCO2_Range_10Hz_1892_1 ACT-America: L2 Remotely Sensed Column-avg CO2 by Airborne Lidar, Lite, Eastern USA ORNL_CLOUD STAC Catalog 2016-05-27 2018-05-20 -106.05, 27.23, -71.91, 49.11 https://cmr.earthdata.nasa.gov/search/concepts/C2704971204-ORNL_CLOUD.umm_json This dataset provides a direct subset (i.e., the Lite version) of the Level 2 (L2) remotely sensed column-average carbon dioxide (CO2) concentrations measured during airborne campaigns in Summer 2016, Winter 2017, Fall 2017, and Spring 2018 conducted over central and eastern regions of the U.S. for the Atmospheric Carbon and Transport (ACT-America) project. Column-average CO2 concentrations were measured at a 0.1-second frequency during flights of the C-130 Hercules aircraft at altitudes up to 8 km with a Multi-functional Fiber Laser Lidar (MFLL; Harris Corporation). The MFLL is a set of Continuous-Wave (CW) lidar instruments consisting of an intensity-modulated multi-frequency single-beam synchronous-detection Laser Absorption Spectrometer (LAS) operating at 1571 nm for measuring the column amount of CO2 number density and range between the aircraft and the surface or to cloud tops, and surface reflectance and a Pseudo-random Noise (PN) altimeter at 1596 nm for measuring the path length from the aircraft to the scattering surface and/or cloud tops. The MFLL was onboard all ACT-America seasonal campaigns, except Summer 2019. Complete aircraft flight information, interpolated to the 0.1-second column CO2 reporting frequency, is included, but not limited to, latitude, longitude, altitude, and attitude. proprietary
MI03_resp_nutrients_GC1_1 GC-FID analysis of soil respirometery experiment. Soil from Macquarie Island, sampled in 2003. AU_AADC STAC Catalog 2003-01-01 2003-12-31 158.76892, -54.78406, 158.96667, -54.47802 https://cmr.earthdata.nasa.gov/search/concepts/C1214313661-AU_AADC.umm_json Field samples were collected from the Main Power House at Macquarie Island - coordinates.... The soil sample used for the respirometer trial was made up as a composite of 8 cores, namely: MPH1, MPH3, MPH4, MPH5, MPH7, MPH8 and MPH9. Each core was analysed for petroleum hydrocarbons (PHCs) at 0.05 m intervals. Intervals containing between 2500 and 5000 mg/kg PHC were then combined into a bulked sample used in the respirometer test. The sample was homogenised by placing all the soil (4.5 kg) into a large mixing bowl and stirring with a flat stirrer. The respirometer experiment was conducted by Jim Walworth and Andrew Pond at the University of Arizona. The objective was to optimise the nutrient status for microbial degradation of PHC's. The respirometer used was an N-Con closed system, with 24 flasks. There were 5 treatments and a control, each run in quadriplate. The control was unammended while treatments were 125, 250, 375, 500, and 625 mg nitrogen/kg of soil (on a dry soil weight basis). See: Sheet 'Sample details' for sample barcode, user ID and sample mass summary. Sheet 'GC-FID Data', cells A1-A18 = sample ID, GC injection file and processing notes Sheet 'GC-FID Data', Rows 10 and 11 contain TPH estimates and estimated standard uncertainty for the TPH value Sheet 'GC-FID Data', cells A21-A125 = compounds or GC elution windows measured Sheet 'GC-FID Data', cells B21-B56 = compound [CAS numbers] Sheet 'GC-FID Data', cells C21-AL125 = GC-FID area responses Sheet 'GC-FID Data', cells C128-AL232 = Estimated standard uncertainties for all GC-FID area responses (from blank drifts,local signal/noise etc) Chemical analysis details........Sample Extraction A 0.5mL volume of internal standard solution containing a mixture of compounds (cyclo-octane at c.1000mg/L, d8-naphthalene at 100mg/L, p-terphenyl at 100 mg/L and 1-bromoeicosane at 1000mg/L) dissolved in hexane, was pipetted onto the soil with a calibrated positive displacement pipette. This was followed by the addition of 10mL of hexane and 10mL of water. The vials were then tumbled end over end (50rpm) overnight and centrifuged at 1500 rpm. 1.8mL of the clear hexane layer was transferred by Pasteur pipette into a 2mL vial for Gas Chromatography Flame Ionisation Detector (GC-FID) analysis Chemical analysis details........GC-FID parameters The download file also includes a paper produced from this data. This work was completed as part of ASAC project 1163 (ASAC_1163). proprietary
MI08_soil_properties_1 Characteristics of soil collected on Macquarie Island in 2008. AU_AADC STAC Catalog 2008-01-01 2008-01-31 158.93, -54.51, 158.94, -54.49 https://cmr.earthdata.nasa.gov/search/concepts/C1214313645-AU_AADC.umm_json Samples were collected on Macquarie Island from three sites: the main powerhouse, the fuel farm and a reference site on the isthmus by the Bioremediation Project team in January 2008. Soil characteristics including conductivity, pH, total petroleum hydrocarbons, total carbon, nitrate, nitrite, ammonium, fluoride, bromide, chloride, sulphate and phosphate were measured. The data consists of two files, the rtf file contains the methods used and the csv file contains the soil characteristics. Samples are identified by a barcode which is the barcode number assigned by the Bioremediation Project Sample Tracking Database. This work was carried out as part of AAS project 1163. proprietary
MI1AC_2 MISR Level 1A Calibration Data V002 LARC STAC Catalog 1999-12-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031451-LARC.umm_json MI1AC_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 1A Calibration data in DN. The data numbers have been commuted from 12-bit to 16-bit, byte-aligned half-word version 2. The MISR instrument consists of nine push-broom cameras that measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four forward, and four aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. proprietary
@@ -11000,8 +11000,8 @@ MI1B2T_003 MISR Level 1B2 Terrain Data V003 LARC STAC Catalog 1999-12-19 -180,
MI1B2T_004 MISR Level 1B2 Terrain Data V004 LARC STAC Catalog 1999-12-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2794373806-LARC.umm_json MI1B2T_004 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 1B2 Terrain Data Version 4 product. It contains Terrain-projected Top-of-Atmosphere (TOA) Radiance, resampled at the surface and topographically corrected, as well as geometrically corrected by PGE22. Data collection for this product is ongoing. MISR itself is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the effects of sunlight on Earth, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. proprietary
MI1B2_ELLIPSOID_NRT_001 MISR Near Real Time (NRT) Level 1B2 Ellipsoid Data V001 LARC STAC Catalog 2021-08-08 2022-10-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000100-LARC.umm_json This file contains Ellipsoid-projected TOA Radiance,resampled at the surface and topographically corrected, as well as geometrically corrected by PGE22. It is used for MISR Near Real Time processing, and is derived from session-based Level 0 input files. proprietary
MI1B2_TERRAIN_NRT_001 MISR Near Real Time (NRT) Level 1B2 Terrain Data V001 LARC STAC Catalog 2021-10-11 2022-10-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-LARC.umm_json This file contains Terrain-projected TOA Radiance,resampled at the surface and topographically corrected, as well as geometrically corrected by PGE22. It is used for MISR Near Real Time processing, and is derived from session-based Level 0 input files. proprietary
-MI2010_11_Alien-plant-survey_JDS_1 Alien plant survey Macquarie Island 2010_11 AU_AADC STAC Catalog 2010-10-13 2011-01-31 158.8, -54.7, 158.9, -54.6 https://cmr.earthdata.nasa.gov/search/concepts/C1214313682-AU_AADC.umm_json "The data are location and abundance data of alien plants found during a systematic survey of Macquarie Island. It relates to three species Poa annua, Cerastium fontanum and Stellaria media. It is essentially a repeat of the Copson 1977 survey. This work has been completed as part of ASAC (AAS) project 2904, ""Aliens in Antarctica"" (ASAC_2904)." proprietary
MI2010_11_Alien-plant-survey_JDS_1 Alien plant survey Macquarie Island 2010_11 ALL STAC Catalog 2010-10-13 2011-01-31 158.8, -54.7, 158.9, -54.6 https://cmr.earthdata.nasa.gov/search/concepts/C1214313682-AU_AADC.umm_json "The data are location and abundance data of alien plants found during a systematic survey of Macquarie Island. It relates to three species Poa annua, Cerastium fontanum and Stellaria media. It is essentially a repeat of the Copson 1977 survey. This work has been completed as part of ASAC (AAS) project 2904, ""Aliens in Antarctica"" (ASAC_2904)." proprietary
+MI2010_11_Alien-plant-survey_JDS_1 Alien plant survey Macquarie Island 2010_11 AU_AADC STAC Catalog 2010-10-13 2011-01-31 158.8, -54.7, 158.9, -54.6 https://cmr.earthdata.nasa.gov/search/concepts/C1214313682-AU_AADC.umm_json "The data are location and abundance data of alien plants found during a systematic survey of Macquarie Island. It relates to three species Poa annua, Cerastium fontanum and Stellaria media. It is essentially a repeat of the Copson 1977 survey. This work has been completed as part of ASAC (AAS) project 2904, ""Aliens in Antarctica"" (ASAC_2904)." proprietary
MI2AS_AEROSOL_NRT_001 MISR Near Real Time (NRT) Level 2 Aerosol parameters V001 LARC STAC Catalog 2021-08-08 2022-10-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2079023474-LARC.umm_json This is the Level 2 Aerosol Product. It contains Aerosol optical depth and particle type, with associated atmospheric data. It is used for MISR Near Real Time processing, and is derived from session-based Level 1 input files. proprietary
MI2TC_CMV_BFR_NRT_001 MISR Near Real Time (NRT) Level 2 Cloud Motion Vector parameters in BUFR format V001 LARC STAC Catalog 2022-03-05 2022-10-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000120-LARC.umm_json This is the MISR Level 2 Cloud Motion Vector Product containing height-resolved cloud motion vectors with associated data in BUFR format. It is used for MISR Near Real Time processing, and is derived from session-based Level 0 input files. proprietary
MI2TC_CMV_HDF_NRT_001 MISR Near Real Time (NRT) Level 2 Cloud Motion Vector parameters V001 LARC STAC Catalog 2021-10-11 2022-10-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000101-LARC.umm_json This is the MISR Level 2 Cloud Motion Vector Product containing height-resolved cloud motion vectors with associated data. It is used for MISR Near Real Time processing, and is derived from session-based Level 0 input files. proprietary
@@ -11133,8 +11133,8 @@ MITgcm_LLC4320_Pre-SWOT_JPL_L4_Yongala_v1.0_1.0 Yongala Pre-SWOT Level-4 Hourly
MI_Azorella_PA_201011_update_1 Macquarie Island Azorella presence/absence data. From island wide plant survey 2010-11 AU_AADC STAC Catalog 2010-10-01 2011-03-31 158.7983, -54.7726, 158.9439, -54.4918 https://cmr.earthdata.nasa.gov/search/concepts/C1532636007-AU_AADC.umm_json This data set contains point location data for the presence or absence of Azorella macquariensis on Macquarie Island. The data were collected during an island wide alien plant survey during the 2010-11 season. This dataset was updated on 2016-08-10 and a new dataset DOI created. proprietary
MI_Azorella_dieback_5x5m_1 Macquarie Is. Azorella dieback 5m x 5m quadrats 2008-2012 AU_AADC STAC Catalog 2008-11-01 2011-12-10 158.77, -54.78, 158.95, -54.48 https://cmr.earthdata.nasa.gov/search/concepts/C1214313644-AU_AADC.umm_json This data set comprises data on Azorella macquariensis dieback from four summer seasons at a range of sites across Macquarie Island: 2008-09, 2009-10, 2010-11, 2011-12. Data on the proportion of healthy and dead or dying Azorella was collected from a 5 x 5m quadrat at each site. In some years data on the health of moss in the quadrats is also provided. The file is in the form of an Excel workbook with a separate worksheet for each year. In addition there are photographs of the sites spanning up to 4 years 2008-09 to - 2011 -12. Most photographic suites contain a North West and a South East site photographs and most are within 5- 10 m of the GPS point for the site. The site codes identify the 5 x 5m quadrats. proprietary
MI_Orchids_1976-2009_1 Biology and population studies of two endemic orchid species on sub-Antarctic Macquarie Island AU_AADC STAC Catalog 1976-01-01 2009-01-01 158.75793, -54.78643, 158.96118, -54.47483 https://cmr.earthdata.nasa.gov/search/concepts/C2102891822-AU_AADC.umm_json Two endemic orchid species, Nematoceras dienemum and N. sulcatum, are known from sub-Antarctic Macquarie Island. Several additional orchid populations on the island are reported and cleistogamy is documented in N. dienemum for the first time. The known population sizes, habitats and locations for both orchid species are documented here, and new information on their biology and population ecology is provided. These data are available from the biodiversity database. There are 20 observations in the data collection. proprietary
-MI_alk_clones_1 Alkane mono-oxygenase clone library from Macquarie Island soil AU_AADC STAC Catalog 2008-01-01 2008-03-30 158.93, -54.491, 158.931, -54.49 https://cmr.earthdata.nasa.gov/search/concepts/C1214311195-AU_AADC.umm_json This dataset consists of 81 DNA sequences of the alkane mono-oxygenase gene. The sequence data are in FASTA format which can be opened with any word-processing or sequence analysis software. The clone library was created using the primers described by Kloos et al. (2006, Journal Microbiological Methods 66:486-496) F: AAYACNGCNCAYGARCTNGGNCAYAA and R:GCRTGRTGRTCNGARTGNCGYTG. The library was created from a soil sample collected at the Main Powerhouse on Macquarie Island and is Human Impacts Sample Tracking Database barcode number:52774. These data were collected as part of AAS project 2672 - Pathways of alkane biodegradation in antarctic and subantarctic soils and sediments. proprietary
MI_alk_clones_1 Alkane mono-oxygenase clone library from Macquarie Island soil ALL STAC Catalog 2008-01-01 2008-03-30 158.93, -54.491, 158.931, -54.49 https://cmr.earthdata.nasa.gov/search/concepts/C1214311195-AU_AADC.umm_json This dataset consists of 81 DNA sequences of the alkane mono-oxygenase gene. The sequence data are in FASTA format which can be opened with any word-processing or sequence analysis software. The clone library was created using the primers described by Kloos et al. (2006, Journal Microbiological Methods 66:486-496) F: AAYACNGCNCAYGARCTNGGNCAYAA and R:GCRTGRTGRTCNGARTGNCGYTG. The library was created from a soil sample collected at the Main Powerhouse on Macquarie Island and is Human Impacts Sample Tracking Database barcode number:52774. These data were collected as part of AAS project 2672 - Pathways of alkane biodegradation in antarctic and subantarctic soils and sediments. proprietary
+MI_alk_clones_1 Alkane mono-oxygenase clone library from Macquarie Island soil AU_AADC STAC Catalog 2008-01-01 2008-03-30 158.93, -54.491, 158.931, -54.49 https://cmr.earthdata.nasa.gov/search/concepts/C1214311195-AU_AADC.umm_json This dataset consists of 81 DNA sequences of the alkane mono-oxygenase gene. The sequence data are in FASTA format which can be opened with any word-processing or sequence analysis software. The clone library was created using the primers described by Kloos et al. (2006, Journal Microbiological Methods 66:486-496) F: AAYACNGCNCAYGARCTNGGNCAYAA and R:GCRTGRTGRTCNGARTGNCGYTG. The library was created from a soil sample collected at the Main Powerhouse on Macquarie Island and is Human Impacts Sample Tracking Database barcode number:52774. These data were collected as part of AAS project 2672 - Pathways of alkane biodegradation in antarctic and subantarctic soils and sediments. proprietary
MI_microcosm2006_microbial_data_1 Microbial data from the Macquarie Island Respirometry Experiment 2006 AU_AADC STAC Catalog 2006-09-10 2006-12-24 158.85, -54.64, 158.87, -54.6 https://cmr.earthdata.nasa.gov/search/concepts/C1214311213-AU_AADC.umm_json A microcosm experiment utilising a respirometry system and 14C-labelled hexadecane was initiated to investigate the effects of differing oxygen regimes on hydrocarbon degradation in soil from sub-Antarctic Macquarie Island. Measurements of oxygen consumed, carbon dioxide produced, total petroleum hydrocarbon degradation and nitrate and ammonium concentrations were made. The microbial community structure at the start of the experiment and after 4, 8 and 12 weeks incubation was explored using terminal restriction fragment length polymorphism and real-time PCR quantification of alkane mono-oxygenase, napthalene dioxygenase, nitrous oxide reductase and ribosomal polymerase sub-unitB. The data described here are the microbial community data only. The download file contains an excel spreadsheet. The first sheet provides further information about the dataset. This work was part of AAS projects 2672 and 1163. proprietary
MIvegmap_1 Macquarie Island Vegetation and Drainage Structure Data Set AU_AADC STAC Catalog 1979-01-01 1997-09-01 158.7761, -54.7772, 158.9508, -54.4853 https://cmr.earthdata.nasa.gov/search/concepts/C1214313649-AU_AADC.umm_json The data for this map were collected as part of two ASAC projects - 488 and 956, of which Patricia Selkirk was the chief investigator. Macquarie Island (54 degrees S 159 degrees E) is a subantarctic island (c. 35km by 3 to 5km) approximately equidistant between Tasmania, New Zealand and Antarctica in the Southern Ocean. The vegetation is herbaceous, lacking shrubs and trees. Vegetation and drainage are mapped at a scale of 1:25 000 from field observations, satellite imagery and limited oblique and aerial photography. The categories adopted for mapping vegetation are based on attributes of foliage height and percentage foliage cover of the ground surface (vegetation structure), not on species distribution (floristics). The distribution of vegetation categories is strongly correlated with aspect, topography and rock type. Mires, streams and lakes form an intricate drainage pattern that is strongly influenced by the geology of this tectonically active emergent crest of the submarine Macquarie Ridge at the boundary of the Pacific and Australian plates. The drainage pattern of the whole island is represented in a map with substantially greater accuracy than in any previous map. proprietary
ML1OA_004 MLS/Aura L1 Orbit/Attitude and Tangent Point Geolocation Data V004 (ML1OA) at GES DISC GES_DISC STAC Catalog 2004-08-01 -180, -82, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1265737437-GES_DISC.umm_json ML1OA is the EOS Aura Microwave Limb Sounder (MLS) product containing the level 1 orbit attitude and tangent point geolocation data. The data version is 4.2. Data coverage is from August 8, 2004 to current. Spatial coverage is near-global (-82 degrees to +82 degrees latitude), and files contain a full days worth of data (15 orbits). Users of the ML1OA data product should read the 'A Short Guide to the Use and Interpretation of v4.2x Level 1 Data' document for additional information. The data are stored in the version 5 Hierarchical Data Format, or HDF-5. Each file contains orbital and attitude information written as HDF-5 dataset objects (n-dimensional arrays), along with file attributes and metadata. proprietary
@@ -11413,8 +11413,8 @@ MODCSR_8_6.1 MODIS/Terra Clear Sky Radiance 8-Day Composite Daily L3 Global 25km
MODCSR_B_6.1 MODIS/Terra 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands LAADS STAC Catalog 2000-02-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1444171490-LAADS.umm_json The MODIS/Terra 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands (MODCSR_B) product consists of 1-degree zonal mean clear-sky biases (observed minus calculated radiance differences) and associated statistics for bands 31 and 33-36 for each calendar day from the previous eight-day period. Zonal means (5-zone moving averages) are created from the eight-day, 25-km radiance differences for daytime land, nighttime land, and ocean data separately. Day and night land data are combined south of -60 degrees latitude due to poor clear-sky sampling and the difficulty of discriminating between clear and cloudy conditions in this region. The zonal mean biases are utilized to correct clear-sky radiance calculations in the cloud top pressure (CO2 slicing) algorithm. The files are in Hierarchical Data Format (HDF). proprietary
MODFNSS_6.1 MODIS/Terra Atmosphere FluxNet Subsetting Product LAADS STAC Catalog 2000-02-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1444310549-LAADS.umm_json The MODIS/Terra Atmosphere FluxNet Subsetting Product (MODFNSS) consists of MODIS Atmosphere and Ancillary Products subsets that are generated over a global network of micrometeorological flux measurement (FLUXNET) sites. The process of generating cutouts for these sites involves locating and identifying a subset of sites taken from a global FLUXNET that are within the spatial coverage of a 5 minute Level 2 MODIS granule and extracting 0.5 x 0.5 degree cutouts. The MODFNSS data set consists of subsets for around 400 sites out of the total flux tower sites around the globe. There is one file per site with around 55 Science Data Sets (SDS) such as at-aperture radiances for 36 discrete MODIS bands, Cloud Mask, and Water Vapor, etc. proprietary
MODGRNLD_1 Multilayer Greenland Ice Surface Temperature, Surface Albedo, and Water Vapor from MODIS V001 NSIDC_ECS STAC Catalog 2000-03-01 2021-08-31 -94, 58, 12, 84 https://cmr.earthdata.nasa.gov/search/concepts/C1597320047-NSIDC_ECS.umm_json This multilayer data set includes standard MODIS Collection 6.1 ice surface temperature (IST) and derived melt map, as well as MODIS Collection 6.0 albedo and water vapor for Greenland, at a spatial resolution of 0.78 km. These fields enable the relationship between IST and surface melt to be evaluated by researchers studying surface changes on the Greenland ice sheet. Water vapor is included to assist with evaluating the accuracy of the IST data and the model output. Also included is an ice mask and a basins mask for delineating drainage basins in Greenland. Surface temperature is a fundamental input for dynamical ice sheet models because it is a component of the ice sheet radiation budget and mass balance. Surface temperature also influences ice sheet processes, such as surface melt. This data set may be used as a resource for model-validation studies such as comparing MERRA-2 surface temperature with MODIS IST, and for comparing MODIS IST, albedo and water vapor with products from sensors on other satellites such as VIIRS and AIRS The temporal coverage for this data set spans 1 March 2000 through 31 December 2019, with the exception of the IST data, which has been extended through 31 Aug 2021. proprietary
-MODISA_L1_1 Aqua MODIS Level-1 Data OB_DAAC STAC Catalog 2002-07-04 -180, 90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1570116979-OB_DAAC.umm_json MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. proprietary
MODISA_L1_1 Aqua MODIS Level-1A Data, version 1 OB_CLOUD STAC Catalog 2002-07-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3380708963-OB_CLOUD.umm_json MODIS (or Moderate-Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. proprietary
+MODISA_L1_1 Aqua MODIS Level-1 Data OB_DAAC STAC Catalog 2002-07-04 -180, 90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1570116979-OB_DAAC.umm_json MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. proprietary
MODISA_L1_GEO_1 Aqua MODIS Geolocation Product Data, version 1 OB_DAAC STAC Catalog 2002-07-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2526537408-OB_DAAC.umm_json MODIS (or Moderate-Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. proprietary
MODISA_L2_IOP_2022.0 Aqua MODIS Level-2 Regional Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-07-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3380708974-OB_CLOUD.umm_json MODIS (or Moderate-Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment. proprietary
MODISA_L2_IOP_NRT_2022.0 Aqua MODIS Level-2 Regional Inherent Optical Properties (IOP) - Near Real-time (NRT) Data, version 2022.0 OB_CLOUD STAC Catalog 2002-07-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3380708971-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
@@ -11823,48 +11823,48 @@ Macquarie_Tide_Gauges_2 Macquarie Island Tide Gauge Data 1993-2007 AU_AADC STAC
MagMix_0 MagMix project OB_DAAC STAC Catalog 2008-05-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360470-OB_DAAC.umm_json Estuarine and coastal systems play important roles in society, serving as port facilities, productive fisheries and rookeries, and scenic recreational areas. However, these same values to society mean that these areas can be significantly affected by human activities. Inputs of nutrients, organic matter, and trace metals are among these impacts. The MagMix project seeks to understand the transport and cycling of nutrients and trace elements and relate that to biogeochemical and optical properties in river-dominated coastal systems. The area of study is the outflow region of the Mississippi and Atchafalaya rivers in the northern Gulf of Mexico. The Mississippi River carries high concentrations of plant nutrients derived from fertilizer use on farms in the heartland of the US. These excess nutrients stimulate plant growth in the surface waters of the Louisiana Shelf. These plants, in turn, sink to the bottom waters of the shelf where they serve as food for respiring organisms. The input of this excess food then stimulates an excess of respiration thereby depleting the shelf bottom waters of oxygen during the summer. These oxygen-depleted (or hypoxic) waters then become a dead zone avoided by animals. The overall goal of this research project is to better understand the mixing processes and their relationship to optical and biogeochemical properties as the waters of the Mississippi River and the Atchafalaya River enter the Gulf of Mexico. proprietary
Main_Melt_Onset_Dates_1841_1.1 ABoVE: Passive Microwave-derived Annual Snowpack Main Melt Onset Date Maps, 1988-2018 ORNL_CLOUD STAC Catalog 1988-02-09 2018-02-10 -180, 51.61, -107.83, 72.41 https://cmr.earthdata.nasa.gov/search/concepts/C2143401742-ORNL_CLOUD.umm_json This dataset provides the annual date of snowpack seasonal beginning melt (i.e., main melt onset date, MMOD) across northwest Canada; Alaska, U.S.; and parts of far eastern Russia at 6.25 km resolution for the period 1988-2018. MMOD was derived from the daily 19V (K-band) and 37V (Ka-band) GHz bands from the Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR). The PMW MMOD dataset was validated using the transition date from Freeze Degree Days (FDD) to Thaw Degree Days (TDD) from in situ air temperature observations from 31 SNOw TELemetry network (SNOTEL) observations, and compared to the established Freeze-Thaw ESDR (FT-ESDR) spring onset date. The resulting MMOD data record is suitable for documenting the spatial-temporal impacts of MMOD variability in ecosystem services, wildlife movements, and hydrologic processes across the ABoVE domain. The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies. proprietary
Main_Melt_Onset_Dates_1841_1.1 ABoVE: Passive Microwave-derived Annual Snowpack Main Melt Onset Date Maps, 1988-2018 ALL STAC Catalog 1988-02-09 2018-02-10 -180, 51.61, -107.83, 72.41 https://cmr.earthdata.nasa.gov/search/concepts/C2143401742-ORNL_CLOUD.umm_json This dataset provides the annual date of snowpack seasonal beginning melt (i.e., main melt onset date, MMOD) across northwest Canada; Alaska, U.S.; and parts of far eastern Russia at 6.25 km resolution for the period 1988-2018. MMOD was derived from the daily 19V (K-band) and 37V (Ka-band) GHz bands from the Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR). The PMW MMOD dataset was validated using the transition date from Freeze Degree Days (FDD) to Thaw Degree Days (TDD) from in situ air temperature observations from 31 SNOw TELemetry network (SNOTEL) observations, and compared to the established Freeze-Thaw ESDR (FT-ESDR) spring onset date. The resulting MMOD data record is suitable for documenting the spatial-temporal impacts of MMOD variability in ecosystem services, wildlife movements, and hydrologic processes across the ABoVE domain. The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies. proprietary
-MaineInvasives A Historical Record of Sponges, Bryozoa and Ascidians on the Coast of Maine: 1843-1980 (Bigelow Laboratory for Ocean Sciences) SCIOPS STAC Catalog 1843-01-01 1980-12-31 -70.7, 42.6, -66.9, 45.2 https://cmr.earthdata.nasa.gov/search/concepts/C1214593917-SCIOPS.umm_json Records of the occurrences of marine and estuarine sponges, bryozoans and ascideans on the coast of Maine have been compiled from the historic literature spanning the time frame of 1843 to 1980. These records variously include information on location, abundance, depth and habitat notes. Also available in many cases are common synonymies and scientific author. Sources include the primary literature, scientific and technical reports and unpublished records and field notes of marine researchers. The taxonomy of the species has been verified on the website WoRMS and by taxonomic experts. A few records need further investigation. These data have been georeferenced and entered into the OBIS database providing world-wide access and various search capabilities. proprietary
MaineInvasives A Historical Record of Sponges, Bryozoa and Ascidians on the Coast of Maine: 1843-1980 (Bigelow Laboratory for Ocean Sciences) ALL STAC Catalog 1843-01-01 1980-12-31 -70.7, 42.6, -66.9, 45.2 https://cmr.earthdata.nasa.gov/search/concepts/C1214593917-SCIOPS.umm_json Records of the occurrences of marine and estuarine sponges, bryozoans and ascideans on the coast of Maine have been compiled from the historic literature spanning the time frame of 1843 to 1980. These records variously include information on location, abundance, depth and habitat notes. Also available in many cases are common synonymies and scientific author. Sources include the primary literature, scientific and technical reports and unpublished records and field notes of marine researchers. The taxonomy of the species has been verified on the website WoRMS and by taxonomic experts. A few records need further investigation. These data have been georeferenced and entered into the OBIS database providing world-wide access and various search capabilities. proprietary
+MaineInvasives A Historical Record of Sponges, Bryozoa and Ascidians on the Coast of Maine: 1843-1980 (Bigelow Laboratory for Ocean Sciences) SCIOPS STAC Catalog 1843-01-01 1980-12-31 -70.7, 42.6, -66.9, 45.2 https://cmr.earthdata.nasa.gov/search/concepts/C1214593917-SCIOPS.umm_json Records of the occurrences of marine and estuarine sponges, bryozoans and ascideans on the coast of Maine have been compiled from the historic literature spanning the time frame of 1843 to 1980. These records variously include information on location, abundance, depth and habitat notes. Also available in many cases are common synonymies and scientific author. Sources include the primary literature, scientific and technical reports and unpublished records and field notes of marine researchers. The taxonomy of the species has been verified on the website WoRMS and by taxonomic experts. A few records need further investigation. These data have been georeferenced and entered into the OBIS database providing world-wide access and various search capabilities. proprietary
Maps_AGB_North_Slope_AK_1565_1 ABoVE: Gridded 30-m Aboveground Biomass, Shrub Dominance, North Slope, AK, 2007-2016 ALL STAC Catalog 2007-06-01 2016-08-31 -168.58, 64.73, -111.55, 76.23 https://cmr.earthdata.nasa.gov/search/concepts/C2170971358-ORNL_CLOUD.umm_json This dataset includes 30-m gridded estimates of total plant aboveground biomass (AGB), the shrub AGB, and the shrub dominance (shrub/plant AGB) for non-water portions of the Beaufort Coastal Plain and Brooks Foothills ecoregions of the North Slope of Alaska. The estimates were derived by linking biomass harvests from 28 published field site datasets with NDVI from a regional Landsat mosaic derived from Landsat 5 and 7 satellite imagery. The data cover the period 2007-06-01 to 2016-08-31. proprietary
Maps_AGB_North_Slope_AK_1565_1 ABoVE: Gridded 30-m Aboveground Biomass, Shrub Dominance, North Slope, AK, 2007-2016 ORNL_CLOUD STAC Catalog 2007-06-01 2016-08-31 -168.58, 64.73, -111.55, 76.23 https://cmr.earthdata.nasa.gov/search/concepts/C2170971358-ORNL_CLOUD.umm_json This dataset includes 30-m gridded estimates of total plant aboveground biomass (AGB), the shrub AGB, and the shrub dominance (shrub/plant AGB) for non-water portions of the Beaufort Coastal Plain and Brooks Foothills ecoregions of the North Slope of Alaska. The estimates were derived by linking biomass harvests from 28 published field site datasets with NDVI from a regional Landsat mosaic derived from Landsat 5 and 7 satellite imagery. The data cover the period 2007-06-01 to 2016-08-31. proprietary
Marine Debris Archive (MARIDA)_1 Marine Debris Archive (MARIDA) MLHUB STAC Catalog 2020-01-01 2023-01-01 -88.8557904, -29.8973351, 129.0745722, 56.4061985 https://cmr.earthdata.nasa.gov/search/concepts/C2781412537-MLHUB.umm_json Marine Debris Archive (MARIDA) is a marine debris-oriented dataset on Sentinel-2 satellite images. It also includes various sea features (clear & turbid water, waves, etc.) and floating materials (Sargassum macroalgae, ships, natural organic material, etc) that co-exist. MARIDA is primarily focused on the weakly supervised pixel-level semantic segmentation task. proprietary
Marine Debris Dataset for Object Detection in Planetscope Imagery_1 Marine Debris Dataset for Object Detection in Planetscope Imagery MLHUB STAC Catalog 2020-01-01 2023-01-01 -88.2971191, 5.4683637, 34.5300293, 39.1087514 https://cmr.earthdata.nasa.gov/search/concepts/C2781412735-MLHUB.umm_json Floating marine debris is a global pollution problem which leads to the loss of marine and terrestrial biodiversity. Large swaths of marine debris are also navigational hazards to ocean vessels. The use of Earth observation data and artificial intelligence techniques can revolutionize the detection of floating marine debris on satellite imagery and pave the way to a global monitoring system for controlling and preventing the accumulation of marine debris in oceans. This dataset consists of images of marine debris which are 256 by 256 pixels in size and labels which are bounding boxes with geographical coordinates. The images were obtained from PlanetScope optical imagery which has a spatial resolution of approximately 3 meters. In this dataset, marine debris consists of floating objects on the ocean surface which can belong to one or more classes namely plastics, algae, sargassum, wood, and other artificial items. Several studies were used for data collection and validation. While a small percentage of the dataset represents the coastlines of Ghana and Greece, most of the observations surround the Bay Islands in Honduras. The marine debris detection models created and the relevant code for using this dataset can be found [here](https://github.com/NASA-IMPACT/marine_debris_ML). proprietary
Marine_Debris_Bibliography_1 Marine Debris Bibliography AU_AADC STAC Catalog 1939-01-01 -180, -70, 180, -47 https://cmr.earthdata.nasa.gov/search/concepts/C1214313632-AU_AADC.umm_json Marine Debris Bibliography compiled by Frederique Olivier contains 210 records. The fields in this dataset are: Bibliography index Subset Date of Publication Author/s Title Source Area Keywords Abstract proprietary
Marine_Plastics_Heard_Macquarie_1 Marine plastics found at Heard Island and Macquarie Island AU_AADC STAC Catalog 1986-01-01 1989-12-31 73.23212, -54.78327, 158.97079, -52.95195 https://cmr.earthdata.nasa.gov/search/concepts/C1214313612-AU_AADC.umm_json This project monitored plastics at the four-bays area on Heard Island and at Sandell Bay on Macquarie Island. It characterised plastics by infra-red spectroscopy both from the beach collection and small pieces from fur-seal stomachs and cormorant boluses. The aim was to assess human impact on the ocean by measuring plastic abundance and type. proprietary
-Marine_Virus_Southern_Ocean_Evans_IPY71_NL_1 Abundances of algae, bacteria, viruses, and heterotrophic nanoflagellates in the Southern Ocean and determination of grazing and viral lysis of the algae SCIOPS STAC Catalog 2007-01-16 2007-02-18 140, -54, 155, -43 https://cmr.earthdata.nasa.gov/search/concepts/C1214594314-SCIOPS.umm_json Samples were collected during the SAZ-Sense cruise (January - February 2007) in the Southern Ocean south of Tasmania, Australia on board RV Aurora Australis. Twenty four stations were sampled in an area between 43 oS to 54 oS and 140 oE to 155 oE. At 3 of the stations designated Process Stations 1, 2 and 3 repeated sampling was completed over a number of days to examine temporal variation. Process Stations 1 to 3 were located in the SAZ to the southwest of Tasmania, the PFZ and in the productive SAZ region southeast of Tasmania respectively, the latter being potentially representative of the future SAZ. Abundances of algae, bacteria, viruses and heterotrophic nanoflagellates were measured using flow cytometry and viral production was determined by an incubation based method. A dilution method was also used to determine grazing and viral lysis of the algae. proprietary
Marine_Virus_Southern_Ocean_Evans_IPY71_NL_1 Abundances of algae, bacteria, viruses, and heterotrophic nanoflagellates in the Southern Ocean and determination of grazing and viral lysis of the algae ALL STAC Catalog 2007-01-16 2007-02-18 140, -54, 155, -43 https://cmr.earthdata.nasa.gov/search/concepts/C1214594314-SCIOPS.umm_json Samples were collected during the SAZ-Sense cruise (January - February 2007) in the Southern Ocean south of Tasmania, Australia on board RV Aurora Australis. Twenty four stations were sampled in an area between 43 oS to 54 oS and 140 oE to 155 oE. At 3 of the stations designated Process Stations 1, 2 and 3 repeated sampling was completed over a number of days to examine temporal variation. Process Stations 1 to 3 were located in the SAZ to the southwest of Tasmania, the PFZ and in the productive SAZ region southeast of Tasmania respectively, the latter being potentially representative of the future SAZ. Abundances of algae, bacteria, viruses and heterotrophic nanoflagellates were measured using flow cytometry and viral production was determined by an incubation based method. A dilution method was also used to determine grazing and viral lysis of the algae. proprietary
+Marine_Virus_Southern_Ocean_Evans_IPY71_NL_1 Abundances of algae, bacteria, viruses, and heterotrophic nanoflagellates in the Southern Ocean and determination of grazing and viral lysis of the algae SCIOPS STAC Catalog 2007-01-16 2007-02-18 140, -54, 155, -43 https://cmr.earthdata.nasa.gov/search/concepts/C1214594314-SCIOPS.umm_json Samples were collected during the SAZ-Sense cruise (January - February 2007) in the Southern Ocean south of Tasmania, Australia on board RV Aurora Australis. Twenty four stations were sampled in an area between 43 oS to 54 oS and 140 oE to 155 oE. At 3 of the stations designated Process Stations 1, 2 and 3 repeated sampling was completed over a number of days to examine temporal variation. Process Stations 1 to 3 were located in the SAZ to the southwest of Tasmania, the PFZ and in the productive SAZ region southeast of Tasmania respectively, the latter being potentially representative of the future SAZ. Abundances of algae, bacteria, viruses and heterotrophic nanoflagellates were measured using flow cytometry and viral production was determined by an incubation based method. A dilution method was also used to determine grazing and viral lysis of the algae. proprietary
Marlon_Lewis_92_0 Marlon Lewis drifting buoys 1992 OB_DAAC STAC Catalog 1992-08-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360473-OB_DAAC.umm_json Data from 3 drifting buoys deployed in fall, 1992. Two of the buoys were air launched near 140W, -999 degrees in the Pacific Ocean, and one was deployed in Monterey Bay attached to a fixed mooring. The fixed mooring was recovered and subjected to post-calibration. proprietary
Marn10k_1 Marine Plain 1:10000 Topographic GIS Dataset AU_AADC STAC Catalog 1958-01-06 1979-01-26 78.0007, -68.666, 78.216, -68.597 https://cmr.earthdata.nasa.gov/search/concepts/C1214313613-AU_AADC.umm_json This dataset details features of Marine Plain in the Vestfold Hills, Antarctica. The dataset includes coastline, 5 metre interval contours and lake shores. These data were captured from aerial photography and are the basis of the Marine Plain Orthophoto Map published for the Australian Antarctic Division in 1993. This map is available from a URL provided in this metadata record. proprietary
Maryland_Temperature_Humidity_1319_1 In-situ Air Temperature and Relative Humidity in Greenbelt, MD, 2013-2015 ORNL_CLOUD STAC Catalog 2013-09-05 2015-12-28 -76.86, 38.99, -76.84, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2736724792-ORNL_CLOUD.umm_json This data set describes the temperature and relative humidity at 12 locations around Goddard Space Flight Center in Greenbelt MD at 15 minute intervals between November 2013 and November 2015. These data were collected to study the impact of surface type on heating in a campus setting and to improve the understanding of urban heating and potential mitigation strategies on the campus scale. Sensors were mounted on posts at 2 m above surface and placed on 7 different surface types around the centre: asphalt parking lot, bright surface roof, grass field, forest, and stormwater mitigation features (bio-retention pond and rain garden). Data were also recorded in an office setting and a garage, both pre- and post-deployment, for calibration purposes. This dataset could be used to validate satellite-based study or could be used as a stand-alone study of the impact of surface type on heating in a campus setting. proprietary
MassBay_LongTerm Long-Term Oceanographic Observations in Massachusetts Bay, 1989-2006 CEOS_EXTRA STAC Catalog 1989-01-01 2006-12-31 -71, 42, -70.5, 42.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231552981-CEOS_EXTRA.umm_json This data report presents long-term oceanographic observations made in western Massachusetts Bay at long-term site LT-A (42° 22.6' N., 70° 47.0' W.; nominal water depth 32 meters) from December 1989 through February 2006 and long-term site B LT-B (42° 9.8' N., 70° 38.4' W.; nominal water depth 22 meters) from October 1997 through February 2004. The observations were collected as part of a U.S. Geological Survey (USGS) study designed to understand the transport and long-term fate of sediments and associated contaminants in Massachusetts Bay. The observations include time-series measurements of current, temperature, salinity, light transmission, pressure, oxygen, fluorescence, and sediment-trapping rate. About 160 separate mooring or tripod deployments were made on about 90 research cruises to collect these long-term observations. This report presents a description of the 16-year field program and the instrumentation used to make the measurements, an overview of the data set, more than 2,500 pages of statistics and plots that summarize the data, and the digital data in Network Common Data Form (NetCDF) format. This research was conducted by the USGS in cooperation with the Massachusetts Water Resources Authority and the U.S. Coast Guard. proprietary
-MassGIS_GISDATA.COQHMOSAICSCDS_POLY 2001 MrSID Mosaics CD-ROM Index ALL STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592880-SCIOPS.umm_json CD-ROM index scheme for the 2001 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQHMOSAICSCDS_POLY 2001 MrSID Mosaics CD-ROM Index SCIOPS STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592880-SCIOPS.umm_json CD-ROM index scheme for the 2001 color ortho image MrSID mosaics. proprietary
-MassGIS_GISDATA.COQHMOSAICSDVDS_POLY.xm 2001 MrSID Mosaics DVD Index ALL STAC Catalog 2007-02-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592858-SCIOPS.umm_json DVD index scheme for the 2001 color ortho image MrSID mosaics. proprietary
+MassGIS_GISDATA.COQHMOSAICSCDS_POLY 2001 MrSID Mosaics CD-ROM Index ALL STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592880-SCIOPS.umm_json CD-ROM index scheme for the 2001 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQHMOSAICSDVDS_POLY.xm 2001 MrSID Mosaics DVD Index SCIOPS STAC Catalog 2007-02-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592858-SCIOPS.umm_json DVD index scheme for the 2001 color ortho image MrSID mosaics. proprietary
+MassGIS_GISDATA.COQHMOSAICSDVDS_POLY.xm 2001 MrSID Mosaics DVD Index ALL STAC Catalog 2007-02-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592858-SCIOPS.umm_json DVD index scheme for the 2001 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQHMOSAICS_POLY 2001 MrSID Mosaics Index SCIOPS STAC Catalog 2002-08-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592815-SCIOPS.umm_json This data layer is used to index the half-meter MrSID mosaics for the 2001/03 1:5,000 Color Ortho Imagery. proprietary
MassGIS_GISDATA.COQHMOSAICS_POLY 2001 MrSID Mosaics Index ALL STAC Catalog 2002-08-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592815-SCIOPS.umm_json This data layer is used to index the half-meter MrSID mosaics for the 2001/03 1:5,000 Color Ortho Imagery. proprietary
-MassGIS_GISDATA.COQMOSAICS2005_POLY 2005 MrSID Mosaics Index ALL STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592900-SCIOPS.umm_json Index scheme for the 2005 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQMOSAICS2005_POLY 2005 MrSID Mosaics Index SCIOPS STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592900-SCIOPS.umm_json Index scheme for the 2005 color ortho image MrSID mosaics. proprietary
+MassGIS_GISDATA.COQMOSAICS2005_POLY 2005 MrSID Mosaics Index ALL STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592900-SCIOPS.umm_json Index scheme for the 2005 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQMOSAICSCDS2005_POLY. 2005 MrSID Mosaics CD-ROM Index SCIOPS STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592882-SCIOPS.umm_json CD-ROM index scheme for the 2005 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQMOSAICSCDS2005_POLY. 2005 MrSID Mosaics CD-ROM Index ALL STAC Catalog 2006-08-03 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592882-SCIOPS.umm_json CD-ROM index scheme for the 2005 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQMOSAICSDVDS2005_POLY 2005 MrSID Mosaics DVD Index SCIOPS STAC Catalog 2007-02-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592901-SCIOPS.umm_json DVD index scheme for the 2005 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.COQMOSAICSDVDS2005_POLY 2005 MrSID Mosaics DVD Index ALL STAC Catalog 2007-02-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592901-SCIOPS.umm_json DVD index scheme for the 2005 color ortho image MrSID mosaics. proprietary
MassGIS_GISDATA.IMG_BWORTHOS 1:5,000 Black and White Digital Orthophoto Images SCIOPS STAC Catalog 1992-01-01 1999-12-31 -73.54455, 41.198524, -69.87159, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592889-SCIOPS.umm_json "These medium resolution images provide a high-quality ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). As of March 31, 2000, the entire state is available. The imagery was captured during the spring from 1992 through 1999. Pixel resolution is 0.5 meters. In ArcSDE the layer is named IMG_BWORTHOS." proprietary
MassGIS_GISDATA.IMG_BWORTHOS 1:5,000 Black and White Digital Orthophoto Images ALL STAC Catalog 1992-01-01 1999-12-31 -73.54455, 41.198524, -69.87159, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592889-SCIOPS.umm_json "These medium resolution images provide a high-quality ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). As of March 31, 2000, the entire state is available. The imagery was captured during the spring from 1992 through 1999. Pixel resolution is 0.5 meters. In ArcSDE the layer is named IMG_BWORTHOS." proprietary
-MassGIS_GISDATA.IMG_COQ2001 1:5,000 Color Ortho Imagery SCIOPS STAC Catalog 2001-04-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592921-SCIOPS.umm_json "These medium resolution true color images are considered the new ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). MassGIS/EOEA and the Massachusetts Highway Department jointly funded the project. The photography for the mainland was captured in April 2001 when deciduous trees were mostly bare and the ground was generally free of snow." proprietary
MassGIS_GISDATA.IMG_COQ2001 1:5,000 Color Ortho Imagery ALL STAC Catalog 2001-04-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592921-SCIOPS.umm_json "These medium resolution true color images are considered the new ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). MassGIS/EOEA and the Massachusetts Highway Department jointly funded the project. The photography for the mainland was captured in April 2001 when deciduous trees were mostly bare and the ground was generally free of snow." proprietary
+MassGIS_GISDATA.IMG_COQ2001 1:5,000 Color Ortho Imagery SCIOPS STAC Catalog 2001-04-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592921-SCIOPS.umm_json "These medium resolution true color images are considered the new ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). MassGIS/EOEA and the Massachusetts Highway Department jointly funded the project. The photography for the mainland was captured in April 2001 when deciduous trees were mostly bare and the ground was generally free of snow." proprietary
MassGIS_GISDATA.IMG_COQ2005 1:5,000 Color Ortho Imagery (2005) SCIOPS STAC Catalog 2005-04-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592911-SCIOPS.umm_json "These medium resolution true color images are considered the new ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). The photography for the entire commonwealth was captured in April 2005 when deciduous trees were mostly bare and the ground was generally free of snow. Image type is 4-band (RGBN) natural color (Red, Green, Blue) and Near infrared in 8 bits (values ranging 0-255) per band format. Image horizontal accuracy is +/-3 meters at the 95% confidence level at the nominal scale of 1:5,000. This digital orthoimagery can serve a variety of purposes, from general planning, to field reference for spatial analysis, to a tool for development and revision of vector maps. It can also serve as a reference layer or basemap for myriad applications inside geographic information system (GIS) software. The project was funded by the Executive Office of Environmental Affairs, the Department of Environmental Protection, the Massachusetts Highway Department, and the Department of Public Health." proprietary
MassGIS_GISDATA.IMG_COQ2005 1:5,000 Color Ortho Imagery (2005) ALL STAC Catalog 2005-04-01 -73.54455, 41.19853, -69.8716, 42.908627 https://cmr.earthdata.nasa.gov/search/concepts/C1214592911-SCIOPS.umm_json "These medium resolution true color images are considered the new ""basemap"" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). The photography for the entire commonwealth was captured in April 2005 when deciduous trees were mostly bare and the ground was generally free of snow. Image type is 4-band (RGBN) natural color (Red, Green, Blue) and Near infrared in 8 bits (values ranging 0-255) per band format. Image horizontal accuracy is +/-3 meters at the 95% confidence level at the nominal scale of 1:5,000. This digital orthoimagery can serve a variety of purposes, from general planning, to field reference for spatial analysis, to a tool for development and revision of vector maps. It can also serve as a reference layer or basemap for myriad applications inside geographic information system (GIS) software. The project was funded by the Executive Office of Environmental Affairs, the Department of Environmental Protection, the Massachusetts Highway Department, and the Department of Public Health." proprietary
-MassGIS_GISDATA.VCPEATLAND_POLY Acidic Peatland Community Systems SCIOPS STAC Catalog 2003-04-01 -71.36416, 41.53563, -70.51623, 42.859413 https://cmr.earthdata.nasa.gov/search/concepts/C1214592150-SCIOPS.umm_json Acidic Peatland Community Systems include evergreen forest and shrub bogs, Atlantic White Cedar (AWC) swamps and bogs, and shrub and graminoid fens. This data was created by starting with the DEP Wetlands, creating a new set of just the bog, coniferous and mixed forested wetland types, and then adding, deleting and changing polygon shapes and labels based on aerial photo interpretation of the 1999/2000 photos and field information. In some areas where this wetland layer did not exist, the wetlands were interpreted and digitized from the aerial photos. The Acidic Peatland datalayer is named VCPEATLAND_POLY in ArcSDE. This layer is part of the MassGIS Priority Natural Vegetation Communities dataset, which depicts the distribution of the eight natural community systems identified by the Massachusetts Natural Heritage and Endangered Species Program (NHESP) as most critical to the conservation of the Commonwealth’s biological diversity (Barbour et al., 1998). proprietary
MassGIS_GISDATA.VCPEATLAND_POLY Acidic Peatland Community Systems ALL STAC Catalog 2003-04-01 -71.36416, 41.53563, -70.51623, 42.859413 https://cmr.earthdata.nasa.gov/search/concepts/C1214592150-SCIOPS.umm_json Acidic Peatland Community Systems include evergreen forest and shrub bogs, Atlantic White Cedar (AWC) swamps and bogs, and shrub and graminoid fens. This data was created by starting with the DEP Wetlands, creating a new set of just the bog, coniferous and mixed forested wetland types, and then adding, deleting and changing polygon shapes and labels based on aerial photo interpretation of the 1999/2000 photos and field information. In some areas where this wetland layer did not exist, the wetlands were interpreted and digitized from the aerial photos. The Acidic Peatland datalayer is named VCPEATLAND_POLY in ArcSDE. This layer is part of the MassGIS Priority Natural Vegetation Communities dataset, which depicts the distribution of the eight natural community systems identified by the Massachusetts Natural Heritage and Endangered Species Program (NHESP) as most critical to the conservation of the Commonwealth’s biological diversity (Barbour et al., 1998). proprietary
+MassGIS_GISDATA.VCPEATLAND_POLY Acidic Peatland Community Systems SCIOPS STAC Catalog 2003-04-01 -71.36416, 41.53563, -70.51623, 42.859413 https://cmr.earthdata.nasa.gov/search/concepts/C1214592150-SCIOPS.umm_json Acidic Peatland Community Systems include evergreen forest and shrub bogs, Atlantic White Cedar (AWC) swamps and bogs, and shrub and graminoid fens. This data was created by starting with the DEP Wetlands, creating a new set of just the bog, coniferous and mixed forested wetland types, and then adding, deleting and changing polygon shapes and labels based on aerial photo interpretation of the 1999/2000 photos and field information. In some areas where this wetland layer did not exist, the wetlands were interpreted and digitized from the aerial photos. The Acidic Peatland datalayer is named VCPEATLAND_POLY in ArcSDE. This layer is part of the MassGIS Priority Natural Vegetation Communities dataset, which depicts the distribution of the eight natural community systems identified by the Massachusetts Natural Heritage and Endangered Species Program (NHESP) as most critical to the conservation of the Commonwealth’s biological diversity (Barbour et al., 1998). proprietary
MatthewsVegetation_419_1 Global Vegetation Types, 1971-1982 (Matthews) ORNL_CLOUD STAC Catalog 1971-01-01 1982-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2808090466-ORNL_CLOUD.umm_json A global digital data base of vegetation was compiled at 1 degree latitude by 1 degree longitude resolution, drawing on approximately 100 published sources. Vegetation data from varied sources were consistently recorded using the hierarchical UNESCO classification system. The raw data base distinguishes about 180 vegetation types that have been collapsed to 32. proprietary
Mawson_Escarpment_Geo_1 Mawson Escarpment Geology GIS Dataset AU_AADC STAC Catalog 1998-04-10 1998-06-30 67.98, -73.71, 69.13, -72.47 https://cmr.earthdata.nasa.gov/search/concepts/C1214313616-AU_AADC.umm_json There are several ArcInfo coverages described by this metadata record - FRAME, GEOL, MAPGRID, SITES, STRLINE and STRUC (in that order). Each coverage is described below. The data is also provided as shapefiles and ArcInfo interchange files. The data was used for the Mawson Escarpment Geology map published in 1998. This map is available from a URL provided in this metadata record. FRAME: The coverage FRAME contains (arcs) and (polygon, label) and forms the limits of the data sets or map coverage of the MAWSON ESCARPMENT area of the AUSTRALIAN ANTARCTIC TERRITORY. The purpose or intentions for this dataset is to form a cookie cutter for future data which may be aquired and require clipping to the map/data area. GEOL: The coverage GEOL is historical geological data covering the MAWSON ESCARPMENT area. The data were captured in ARC/INFO format and combined with geological outcrops that were accurately digitised over a March 1989 Landsat Thematic Mapper image at a scale of 1:100000. It is not recomended that this data be used beyond this scale. The coverage contains Arcs (lines) and polygons (polygon labels). These object are attributed as fully as possible in their .aat file for arcs and .pat for polygon labels and conform with the Geoscience Australia Geoscience Data Dictionary Version 98.04 The purpose or intentions for the dataset is that it become part of a greater geological database of the Australian Antarctic Territory. (1998-04-10 - 1998-06-30) MAPGRID: MAPGRID is a graticule that was generated as a 5 minute by 5 minute grid mainly to allow for good location/registration of source materials for digitising and adding some locational anno.mapgrat This covers other function was to be used for a proof plot. (1998-04-22 - 1998-06-30) SITES: The purpose or intentions for this dataset is to provide the approximate location of this historic data on sample sites in the MAWSON ESCARPMENT region of the AUSTRALIAN ANTARCTIC TERRITORY, for future expansion or more accurate positioning when improved records of location are found. (1998-05-11 - 1998-06-30) STRLINE: This Structural lines for geology coverage is named (STRLINE). The purpose or intentions for the dataset is to have the linear structural features in their own coverage containing only structure which does not form polygon boundaries. (1998-05-28 - 1998-06-30) STRUC: This coverage called STRUC for structural measurements is a point coverage. It can be described as Mesoscopic structures at a site or outcrop. The purpose or intentions for the dataset is to provide all the known structural point data information in the one coverage. (1998-05-28 - 1998-06-30) proprietary
Mawson_SAM_1 Mawson Station GIS Dataset AU_AADC STAC Catalog 1996-03-18 1996-03-18 62.8583, -67.6072, 62.8886, -67.5936 https://cmr.earthdata.nasa.gov/search/concepts/C1214313636-AU_AADC.umm_json This dataset represents topographic features and facilities at Mawson and its immediate environs. Feature types include buildings, masts, tanks, roads, coastline and contours (1 metre interval). The data are included in the data available for download from a Related URL below. The data conform to the SCAR Feature Catalogue which include data quality information. See a Related URL below. Data described by this metadata record has Dataset_id = 111. Each feature has a Qinfo number which, when entered at the 'Search datasets and quality' tab, provides data quality information for the feature. Changes have occurred at the station since this dataset was produced. For example some buildings and other structures have been removed and some added. As a result the data available for download from a Related URL below is updated with new data having different Dataset_id(s). proprietary
Mawson_Tide_Gauges_2 Mawson Tide Gauge Data 1992-2016 AU_AADC STAC Catalog 1992-03-05 2016-11-04 62.83356, -67.61863, 62.90771, -67.58619 https://cmr.earthdata.nasa.gov/search/concepts/C1667370710-AU_AADC.umm_json "Over time there have been a number of tide gauges deployed at Mawson Station, Antarctica. The data download files contain further information about the gauges, but some of the information has been summarised here. Note that this metadata record only describes tide gauge data from 1992 to 2016. More recent data are described elsewhere. Tide Gauge 1 (TG001) 1992-03-05 - 1992-05-13 This folder contains monthly download files from the first deployment of a submerged tide gauge at Mawson in March 1992. These files are ASCII hexadecimal files. They need to be converted to decimal. The resultant values are absolute seawater pressures in mbar. Tide Gauge 4 (TG004) 1993-03-22 - 1999-12-29 This folder contains the following folders:- old_tidedata monthly download files from the second deployment of a submerged tide gauge at Mawson in March 1993. These files are ASCII hexadecimal files. They need to be converted to decimal. The resultant values are absolute seawater pressures in mbar. raw memory images from submerged tide gauge. file extension is memory bank number. These files are processed by a utility called tgxtract.exe which creates files in same format as those in old_tidedata folder. These file have extension .srt. They are then converted to decimal pressure values. interim files produced during processing of .raw files. output output file (.srt) which have been sent to BoM. Tide Gauge 13 (TG013) 2014-06-04 - 2016-11-04 Tide Gauge 20 (TG020) 1999-11-05 - 2009-12-21 This folder contains the following folders:- raw memory images from submerged tide gauge. file extension is memory bank number. These files are processed by a utility called tgxtract.exe which creates files in same format as original download format. These file have extension .srt. These files are ASCII hexadecimal files. They need to be converted to decimal. The resultant values are absolute seawater pressures in mbar. interim files produced during processing of .raw files. output output file (.srt) which have been sent to BoM. Tide Gauge 41 (TG041) 2008-03-02 - 2010-11-16 This folder contains the following folders:- raw memory images from submerged tide gauge. file extension is memory bank number. These files are processed by a utility called tgxtract.exe which creates files in same format as original download format. These file have extension .srt. These files are ASCII hexadecimal files. They need to be converted to decimal. The resultant values are absolute seawater pressures in mbar. interim files produced during processing of .raw files. output output file (.srt) which have been sent to BoM. Documentation from older metadata record: Documentation dated 2001-03-26 Mawson Submerged Tide Gauge The gauge used at Mawson was designed in 1991/2 by Platypus Engineering, Hobart, Tasmania. It was intended to be submerged in about 7 metres of water in a purpose made concrete mooring in the shape of a truncated pyramid. The gauge measures pressure using a Paroscientific Digiquartz Pressure Transducer with a full scale pressure of 30 psi absolute. The accuracy of the transducer is 1 in 10,000 of full scale over the calibrated temperature range. The overall accuracy of the system is better than +/- 3 mm for a known water density. Data is retrieved from the gauges by lowering a coil assembly on the end of a cable over a projecting knob on the top of the gauge and by use of an interface unit ,a serial connection can be established to the gauge. Time setting and data retrieval can be then achieved. The first of these gauges were first deployed Mawson in early 1992 in a a mooring in Horseshoe Harbour. The gauge was found to have some communications problems and was removed in May 1992. Tidal records from 6/3/92 to present have been retrieved from it. A new gauge was deployed at Mawson in March 1993. Data has been retrieved from these gauges irregularly since then. The records are complete since deployment except for a few days in late 1995. The loss was caused by a fault in the software which allows directory entries to overwrites data when the directory memory has been filled. The first gauge used at Mawson in 1992 was refitted with a higher pressure transducer and was later deployed at Heard Island in Atlas Cove. Conversion of raw data to tidal records is done as detailed in document DATAFORMAT1.DOC . As the current gauge is expected to require a new battery soon, a new mooring has been placed close to the original and a new gauge has been deployed. Levelling Several attempts have been made at precise levelling of the gauge. The first was in the Summer of 1995/6. Roger Handsworth, Tom Gordon and Natasha Adams physically measured the level of the top of the gauge in its mooring and derived a reading when a known column of water was over the gauge. The next attempt was in the Summer of 1996/7 when Roger Handsworth and Paul Delaney made timed water level measurements close to the gauge and the tide gauge benchmark. From this work, and from tidal records, a value for MSL for Mawson was derived. Permanent Gauge In the summer of 1995/6 two possible sites for a permanent Aquatrak type tide gauge were identified. As neither of these sites were approved, a survey in the Summer of 1996/7 identified two more suitable sites. One of these, the site at the base of East arm, near the Variometer Building, was approved and a bore hole was drilled to exit about 6 metres below MSL. A power cable was run from the variometer building to provide two phase 240V power to the site. A heated borehole liner containing an Aquatrak wave guide and a Druck pressure transducer was inserted into the bore hole. Two datalogger will be added to the installation in 2001 to complete the installation. A radio modem will be used to link the dataloggers to the AAD network. Documentation dated 2008-10-17 Mawson A new submerged gauge ,TG41, was deployed at Mawson on 2008-03-03. Submerged Tide gauge TG20 was removed on 2008-08-26. There is a useful overlap of data between the gauges of about 104 days. The dataloggers used in the shored based tide gauge installation have been replaced with Campbell Scientific CR1000 dataloggers. The aquatrak shore based gauge at Mawson has not been operating since march 2008. The shore base pressure gauge is still operating." proprietary
MawsonsHuts2008_2009_1 Mawson's Huts Preservation Program 2007/2008, 2008/2009 and 2009/2010 Data Entry AU_AADC STAC Catalog 2008-10-01 2010-03-31 142.65, -67.1, 142.67, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214313539-AU_AADC.umm_json "723 images where loaded into the AAD image library, ""Image Antarctica"" and attached to records in the Antarctic Heritage Register database. The images documented the condition of the interior and exterior of Mawsons Huts located at Cape Denison including the main hut, the absolute hut, the magnetograph hut and the transit hut during the 2007/2008 season and the 2008/2009 season. The images were taken in both high resolution jpgs as well as raw files. The camera used was a Nikon D80. Also included were images of conserved artefacts as well as details of the conservation treatments uploaded to the Antarctic Heritage Register Database and linked to specific catalogue records. 2011-04-21 - the record was updated to include a file of data from the 2009/2010 season. Raw data from 2008/2009 and 2009/2010 have also been archived in the AADC servers, and are available to AAD personnel upon request." proprietary
Mawsons_Huts_Dataloggers_2 Dataloggers at Mawson's Hut, Cape Denison - microclimate measurements AU_AADC STAC Catalog 1998-01-26 2008-01-30 142.66, -67.009, 142.662, -67.007 https://cmr.earthdata.nasa.gov/search/concepts/C1214313538-AU_AADC.umm_json Dataloggers were installed in a number of locations inside and outside Mawson's Huts at Cape Denison. The dataloggers measure temperature and relative humidity for the purpose of helping gauge corrosivity in the huts. The data are used to assess whether the removal of ice and snow from inside the Hut is affecting the internal microclimate and, therefore, the condition of the building fabric and other artefacts. Currently the data are downloaded by the Research Centre for Materials Conservation and the Built Environment at the Australian Museum, Sydney. Copies of the data are stored in the Australian Antarctic Data Centre. The fields in this dataset are: Date Time Temperature Relative Humidity Thermocouple Site proprietary
-Maxwell_Bay_Beaches_data Ages and Elevations of Raised Beaches around Maxwell Bay, South Shetland Islands ALL STAC Catalog 0500-01-01 2007-04-30 -59, -62.3, -58.833, -62.1 https://cmr.earthdata.nasa.gov/search/concepts/C1214590771-SCIOPS.umm_json This data set includes elevations, OSL ages, and one suspect radiocarbon date from several raised beaches around Maxwell Bay in the South Shetland Islands. It also includes some basic textural parameters (grain size, sorting, and roundness) from modern beaches, talus slopes, and moraines in the area. We also compiled a map of recent moraines in the Gerlache Straight. proprietary
Maxwell_Bay_Beaches_data Ages and Elevations of Raised Beaches around Maxwell Bay, South Shetland Islands SCIOPS STAC Catalog 0500-01-01 2007-04-30 -59, -62.3, -58.833, -62.1 https://cmr.earthdata.nasa.gov/search/concepts/C1214590771-SCIOPS.umm_json This data set includes elevations, OSL ages, and one suspect radiocarbon date from several raised beaches around Maxwell Bay in the South Shetland Islands. It also includes some basic textural parameters (grain size, sorting, and roundness) from modern beaches, talus slopes, and moraines in the area. We also compiled a map of recent moraines in the Gerlache Straight. proprietary
+Maxwell_Bay_Beaches_data Ages and Elevations of Raised Beaches around Maxwell Bay, South Shetland Islands ALL STAC Catalog 0500-01-01 2007-04-30 -59, -62.3, -58.833, -62.1 https://cmr.earthdata.nasa.gov/search/concepts/C1214590771-SCIOPS.umm_json This data set includes elevations, OSL ages, and one suspect radiocarbon date from several raised beaches around Maxwell Bay in the South Shetland Islands. It also includes some basic textural parameters (grain size, sorting, and roundness) from modern beaches, talus slopes, and moraines in the area. We also compiled a map of recent moraines in the Gerlache Straight. proprietary
McMurdo_Predator_Prey_Acoustics Acoustic records near McMurdo Station, Antarctica, 2012 - 2015. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1351106925-SCIOPS.umm_json Sonar data were collected to determine prey fields (krill, fishes) in McMurdo Sound, Antarctica proprietary
McMurdo_Predator_Prey_Acoustics Acoustic records near McMurdo Station, Antarctica, 2012 - 2015. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1351106925-SCIOPS.umm_json Sonar data were collected to determine prey fields (krill, fishes) in McMurdo Sound, Antarctica proprietary
McMurdo_Predator_Prey_Adelie_Penguins Adelie Penguins at Cape Royds, Antarctica, 2012 - 2015. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1351106459-SCIOPS.umm_json Adelie penguin data will be deposited in the California Avian Data Center (CADC) hosted by Point Blue Conservation Science (http://data.prbo.org/apps/penguinscience/). proprietary
@@ -11875,10 +11875,10 @@ Menz50k_1 Mount Menzies 1:50000 Topographic GIS Dataset AU_AADC STAC Catalog 197
MetOpA_GOME2_SIF_V2_2292_2 L2 Daily Solar-Induced Fluorescence (SIF) from MetOp-A GOME-2, 2007-2018, V2 ORNL_CLOUD STAC Catalog 2007-02-01 2018-02-01 -180, -89.78, 180, 89.6 https://cmr.earthdata.nasa.gov/search/concepts/C2847115945-ORNL_CLOUD.umm_json This dataset provides Level 2 (L2) Solar-Induced Fluorescence (SIF) of chlorophyll estimates derived from the Global Ozone Monitoring Experiment 2 (GOME-2) instrument on the European Meteorological Satellite (EUMETSAT) MetOp-A with ~0.5 nm spectral resolution and wavelengths between 734 and 758 nm. GOME-2 covers global land on an orbital basis at a resolution of approximately 40 km x 80 km (before 15 July 2013) or 40 km x 40 km (since 15 July 2013). Data are provided for the period from 2007-02-01 to 2018-02-01. Each file contains daily raw and bias-adjusted solar-induced fluorescence, quality control information, and ancillary data. SIF measurements can provide information on vegetation's functional status, including light-use efficiency and global primary productivity, which can be used for global carbon cycle modeling and agricultural applications. The GOME-2 SIF product is inherently noisy due to low signal levels and has undergone only a limited amount of validation. The data are provided in netCDF format. proprietary
MetOpB_GOME2_SIF_2182_1 L2 Daily Solar-Induced Fluorescence (SIF) from MetOp-B GOME-2, 2013-2021 ORNL_CLOUD STAC Catalog 2013-04-01 2021-06-07 -180, -89.77, 180, 89.59 https://cmr.earthdata.nasa.gov/search/concepts/C2840822442-ORNL_CLOUD.umm_json This dataset provides Level 2 (L2) Solar-Induced Fluorescence (SIF) of chlorophyll estimates derived from the Global Ozone Monitoring Experiment 2 (GOME-2) instrument on the European Meteorological Satellite (EUMETSAT) MetOp-B with ~0.5 nm spectral resolution and wavelengths between 734 and 758 nm. GOME-2 covers global land (observations up to 75-degree solar zenith angle) at a resolution of approximately 40 km x 80. Data are provided for the period from 2013-04-01 to 2021-06-07. Each file contains daily raw and bias-adjusted solar-induced fluorescence along with quality control information and ancillary data. SIF measurements can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. The GOME-2 SIF product is inherently noisy owing to low signal levels and has undergone only a limited amount of validation. The data are provided in netCDF (*.nc) format. proprietary
Meteorological_1065_1 BIGFOOT Meteorological Data for North and South American Sites, 1991-2004 ORNL_CLOUD STAC Catalog 1991-01-01 2004-12-31 -156.61, -2.87, -54.96, 71.27 https://cmr.earthdata.nasa.gov/search/concepts/C2751482070-ORNL_CLOUD.umm_json The BigFoot Project has compiled daily meteorological measurements for nine EOS Land Validation Sites located from Alaska to Brazil from 1991 to 2004. Each site is representative of one or two distinct biomes, including the Arctic tundra; boreal evergreen needleleaf forest; temperate cropland, grassland, evergreen needleleaf forest, and deciduous broadleaf forest; desert grassland and shrubland; and tropical evergreen broadleaf forest.The BigFoot Project needed meteorological data to run the ecosystem process models used for scaling GPP and NPP products, for monitoring interannual variability, and for model testing. Meteorological data were obtained from various agencies collecting data in the vicinity of the BigFoot sites and for more recent years, collected on co-located CO2 flux measurement towers. A comparable set of original measurements from all sites were aggregated to a common daily time step for use in the BIOME-BGC model. proprietary
-Meteorology_Log_Commonwealth_Bay_1977_1978_1 A log of meteorological observations made at Commonwealth Bay between 1977 and 1978 ALL STAC Catalog 1977-01-01 1978-12-31 142.5, -67, 142.5, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311178-AU_AADC.umm_json This document contains a report/log on meteorological observations from Commonwealth Bay in 1977-1978. Some references are also made to the Australasian Antarctic Expedition of Sir Douglas Mawson, 1911-1914. The hard copy of the log has been archived by the Australian Antarctic Division library. proprietary
Meteorology_Log_Commonwealth_Bay_1977_1978_1 A log of meteorological observations made at Commonwealth Bay between 1977 and 1978 AU_AADC STAC Catalog 1977-01-01 1978-12-31 142.5, -67, 142.5, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311178-AU_AADC.umm_json This document contains a report/log on meteorological observations from Commonwealth Bay in 1977-1978. Some references are also made to the Australasian Antarctic Expedition of Sir Douglas Mawson, 1911-1914. The hard copy of the log has been archived by the Australian Antarctic Division library. proprietary
-Methane_Ebullition_Lakes_AK_1861_1 ABoVE: Methane Ebullition Hotspots in Frozen Lakes near Fairbanks, Alaska, Oct 2014 ORNL_CLOUD STAC Catalog 2014-10-08 2014-10-08 -147.94, 64.86, -147.77, 64.94 https://cmr.earthdata.nasa.gov/search/concepts/C2143401746-ORNL_CLOUD.umm_json This dataset includes maps of the locations and number of methane ebullition hotspots in 15 frozen lakes in the southern portion of the Goldstream Valley and the surrounding landscape just north of Fairbanks, Alaska, USA. Hotspots were identified from early winter high resolution aerial photographs acquired three days after lake-ice formation in October 2014. Hotspot ebullition seeps are defined as point-sources of high ebullition that release methane from lake sediments year-round. High rates of bubbling impede ice formation. In early winter, bubbling leads to dark, round open holes in lake ice which were visible in the aerial photos. This project investigated the role of theromkarst lakes in thawing of permafrost and mobilization of organic carbon in frozen soils. proprietary
+Meteorology_Log_Commonwealth_Bay_1977_1978_1 A log of meteorological observations made at Commonwealth Bay between 1977 and 1978 ALL STAC Catalog 1977-01-01 1978-12-31 142.5, -67, 142.5, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311178-AU_AADC.umm_json This document contains a report/log on meteorological observations from Commonwealth Bay in 1977-1978. Some references are also made to the Australasian Antarctic Expedition of Sir Douglas Mawson, 1911-1914. The hard copy of the log has been archived by the Australian Antarctic Division library. proprietary
Methane_Ebullition_Lakes_AK_1861_1 ABoVE: Methane Ebullition Hotspots in Frozen Lakes near Fairbanks, Alaska, Oct 2014 ALL STAC Catalog 2014-10-08 2014-10-08 -147.94, 64.86, -147.77, 64.94 https://cmr.earthdata.nasa.gov/search/concepts/C2143401746-ORNL_CLOUD.umm_json This dataset includes maps of the locations and number of methane ebullition hotspots in 15 frozen lakes in the southern portion of the Goldstream Valley and the surrounding landscape just north of Fairbanks, Alaska, USA. Hotspots were identified from early winter high resolution aerial photographs acquired three days after lake-ice formation in October 2014. Hotspot ebullition seeps are defined as point-sources of high ebullition that release methane from lake sediments year-round. High rates of bubbling impede ice formation. In early winter, bubbling leads to dark, round open holes in lake ice which were visible in the aerial photos. This project investigated the role of theromkarst lakes in thawing of permafrost and mobilization of organic carbon in frozen soils. proprietary
+Methane_Ebullition_Lakes_AK_1861_1 ABoVE: Methane Ebullition Hotspots in Frozen Lakes near Fairbanks, Alaska, Oct 2014 ORNL_CLOUD STAC Catalog 2014-10-08 2014-10-08 -147.94, 64.86, -147.77, 64.94 https://cmr.earthdata.nasa.gov/search/concepts/C2143401746-ORNL_CLOUD.umm_json This dataset includes maps of the locations and number of methane ebullition hotspots in 15 frozen lakes in the southern portion of the Goldstream Valley and the surrounding landscape just north of Fairbanks, Alaska, USA. Hotspots were identified from early winter high resolution aerial photographs acquired three days after lake-ice formation in October 2014. Hotspot ebullition seeps are defined as point-sources of high ebullition that release methane from lake sediments year-round. High rates of bubbling impede ice formation. In early winter, bubbling leads to dark, round open holes in lake ice which were visible in the aerial photos. This project investigated the role of theromkarst lakes in thawing of permafrost and mobilization of organic carbon in frozen soils. proprietary
Methane_Ethane_MA_NH_1982_1 Methane and Ethane Observations for Boston, MA, 2012-2020 ORNL_CLOUD STAC Catalog 2012-08-01 2020-05-31 -72.4, 41.5, -69.8, 43.71 https://cmr.earthdata.nasa.gov/search/concepts/C2345793484-ORNL_CLOUD.umm_json This dataset provides the hourly average of continuous atmospheric measurements of methane (CH4) from two urban sites and three boundary sites in and around Boston, Massachusetts, U.S., from September 2012-May 2020, measured with Picarro cavity ring down spectrometers (CRDS). Five-minute average atmospheric measurements of ethane (C2H6) and methane at Copley Square in Boston, MA, are also provided, with ethane measured with a laser spectrometer and methane measured with a Picarro CRDS. Background CH4 concentrations for the urban sites were determined using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model trajectories at the boundary of the study region based on measurements at three boundary sites and wind direction from the North American Mesoscale Forecast System (NAM) 12-kilometer meteorology. proprietary
Methane_Flaring_Sites_VIIRS_1874_1 Global Gas Flare Survey by Infrared Imaging, VIIRS Nightfire, 2012-2019 ORNL_CLOUD STAC Catalog 2012-01-01 2019-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2345877554-ORNL_CLOUD.umm_json This dataset contains annual global flare site surveys from 2012-2019 derived from Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (SNPP) satellite. Gas flaring sites were identified from heat anomalies first estimated by the VIIRS Nightfire (VNF) algorithm from which high-temperature biomass burning and low-temperature gas flaring were separated based on temperature and persistence. Nightly observations for each flare site were drawn to determine their activity in the given calendar year. Data include flare location, temperature, and estimated flared gas volume; flaring data summarized by country; and KMZ files for viewing flaring locations in Google Earth. This dataset is valuable for measuring the current status of global gas flaring, which can have significant environmental impacts. proprietary
Microbiome_0 Tara microbiome OB_DAAC STAC Catalog 2020-12-26 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108362424-OB_DAAC.umm_json Tara microbiome is the latest Tara expedition focused on plankton. The Microbiome Mission will help us understand the services provided by this essential ecosystem of the Ocean, its microbiome, an increasingly crucial challenge for scientific research and is done in conjunction with the AtlantECO program where additional ships will collect similar variables. proprietary
@@ -12045,17 +12045,17 @@ NAWQAHIS GIS Coverage for the National Water-Quality Assessment (NAWQA) Program
NA_MODIS_Surface_Biophysics_1210_1 MODIS-derived Biophysical Parameters for 5-km Land Cover, North America, 2000-2012 ORNL_CLOUD STAC Catalog 2000-01-01 2012-12-31 -160, 20, -40, 60 https://cmr.earthdata.nasa.gov/search/concepts/C2784871888-ORNL_CLOUD.umm_json This data set provides MODIS-derived surface biophysical climatologies of bidirectional distribution function (BRDF), BDRF/albedo, land surface temperature (LST), leaf area index (LAI), and evapotranspiration (ET) as separate files for each of the MODIS land cover types, and four radiative forcing data files for four scenarios of potential vegetation shifts in North America. Each biophysical variable has temporal periods that represent the average of all 8-day periods from the years 2000-2012. The data have a spatial resolution of 0.05 degree (~5 km) and a temporal resolution of eight days. Additionally, a file containing diffuse fraction of surface downward solar radiation (DiffuseFraction) at a monthly scale, and a file containing snow water equivalent (SWE) are provided. The extent of the data covers the land area of North America, from 20 to 60 degrees N. The land-cover map used was synthesized from nine yearly 500-m MODIS land-cover layers (MCD12 Q1 Collection 5) for 2001-2008. These high-resolution land data were originally developed for quantifying biophysical forcing from land-use changes associated with forestry activities, such as radiative forcing from altered surface albedo. proprietary
NA_TreeAge_1096_1 NACP Forest Age Maps at 1-km Resolution for Canada (2004) and the U.S.A. (2006) ORNL_CLOUD STAC Catalog 1950-01-01 2006-12-31 179.25, 7.71, -39.87, 67.01 https://cmr.earthdata.nasa.gov/search/concepts/C2556019064-ORNL_CLOUD.umm_json This data set provides forest age map products at 1-km resolution for Canada and the United States (U.S.A.). These continental forest age maps were compiled from forest inventory data, historical fire data, optical satellite data, and the images from the NASA Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project. These input data products have various sources and creation dates as described in the source paper by Pan et al. (2011). Canadian maps were produced with data available through 2004 and U.S.A. maps with data available through 2006. A supplementary map of the standard deviations for age estimates was developed for quantifying uncertainty.Note that the Pan et al. (2011) paper is included as a companion file with this data set and was the source of descriptions in the guide.Forest age, implicitly reflecting the past disturbance legacy, is a simple and direct surrogate for the time since disturbance and may be used in various forest carbon analyses that concern the impact of disturbances. By combining geographic information about forest age with estimated carbon dynamics by forest type, it is possible to conduct a simple but powerful analysis of the net CO2 uptake by forests, and the potential for increasing (or decreasing) this rate as a result of direct human intervention in the disturbance/age status. proprietary
NBCD2000_V2_1161_2 NACP Aboveground Biomass and Carbon Baseline Data, V.2 (NBCD 2000), U.S.A., 2000 ORNL_CLOUD STAC Catalog 1999-01-01 2002-12-31 -126.46, 26.52, -67.96, 49.79 https://cmr.earthdata.nasa.gov/search/concepts/C2539954386-ORNL_CLOUD.umm_json The NBCD 2000 (National Biomass and Carbon Dataset for the Year 2000) data set provides a high-resolution (30 m) map of year-2000 baseline estimates of basal area-weighted canopy height, aboveground live dry biomass, and standing carbon stock for the conterminous United States. This data set distributes, for each of 66 map zones, a set of six raster files in GeoTIFF format. There is a detailed README companion file for each map zone. There is also an ArcGIS shapefile (mapping_zone_shapefile.shp) with the boundaries of all the map zones. A mosaic image of biomass at 240 m resolution for the whole conterminous U.S. is also included.Please read this important note regarding the differences of Version 2 from Version 1 of the NBCD 2000 data. With Version 1, in some mapping zones, certain land cover types (in particular Shrubs, NLCD Type 52) were missing from and unaccounted for in modeled estimates because of a lack of reference data. In Version 1, when landcover types were missing in the models, the model for the deciduous tree cover type was applied. While more woody vegetation was mapped, the authors think this had little effect on model performance as in most cases NLCD version 1 cover type was not a strong predictor of modeled estimates (See companion Mapping Zone Readme files). In Version 2, after renewed modeling efforts and user feedback, these previously unaccounted for cover types are now included in modeled estimates.All 66 mapping zones were updated with the previously unmapped land cover types now mapped. The authors recommend use of the new version for all analyses and will only support the updated version.Development of the data set used an empirical modeling approach that combined USDA Forest Service Forest Inventory and Analysis (FIA) data with high-resolution InSAR data acquired from the 2000 Shuttle Radar Topography Mission (SRTM) and optical remote sensing data acquired from the Landsat ETM+ sensor. Three-season Landsat ETM+ data were systematically compiled by the Multi-Resolution Land Characteristics Consortium (MRLC) between 1999 and 2002 for the entire U.S. and were the foundation for development of both the USGS National Land Cover Dataset 2001 (NLCD 2001) and the Landscape Fire and Resource Management Planning Tools Project (LANDFIRE). Products from both the NLCD 2001 (landcover and canopy density) and LANDFIRE (existing vegetation type) projects as well as topographic information from the USGS National Elevation Dataset (NED) were used within the NBCD 2000 project as spatial predictor layers for canopy height and biomass estimation. Forest survey data provided by the USDA Forest Service FIA program were made available to the project under a national Memorandum of Understanding. The response variables (canopy height and biomass) used in model development and validation were derived from the FIA database (FIADB). Production of the NLCD 2001 and LANDFIRE projects was based on a mapping zone approach in which the conterminous U.S. was split into 66 ecoregionally distinct mapping zones. This mapping zone approach was also adopted by the NBCD 2000 project. proprietary
-NBId0001_101 Africa Outline, Integrated Terrain Units, Agric. Landuse, Soils, Vegetation ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849282-CEOS_EXTRA.umm_json These datasets (Africa Outline, Agricultural Landuse, Africa Soils, Vegetation, Surface Hydrography, Hydrologic Basins, Desertification Hazard Model) are part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses in this case on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP) as part of a project initiated by UNEP. The base maps used were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit and the Rand-McNally New International Atlas (1982) to clarify unit boundaries. All sources were re-registered to the basemap by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm developed by the US Geological Survey and ESRI to create coverage's for one-degree graticules. For details about each dataset, visit the individual entries. proprietary
NBId0001_101 Africa Outline, Integrated Terrain Units, Agric. Landuse, Soils, Vegetation CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849282-CEOS_EXTRA.umm_json These datasets (Africa Outline, Agricultural Landuse, Africa Soils, Vegetation, Surface Hydrography, Hydrologic Basins, Desertification Hazard Model) are part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses in this case on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP) as part of a project initiated by UNEP. The base maps used were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit and the Rand-McNally New International Atlas (1982) to clarify unit boundaries. All sources were re-registered to the basemap by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm developed by the US Geological Survey and ESRI to create coverage's for one-degree graticules. For details about each dataset, visit the individual entries. proprietary
+NBId0001_101 Africa Outline, Integrated Terrain Units, Agric. Landuse, Soils, Vegetation ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849282-CEOS_EXTRA.umm_json These datasets (Africa Outline, Agricultural Landuse, Africa Soils, Vegetation, Surface Hydrography, Hydrologic Basins, Desertification Hazard Model) are part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses in this case on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP) as part of a project initiated by UNEP. The base maps used were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit and the Rand-McNally New International Atlas (1982) to clarify unit boundaries. All sources were re-registered to the basemap by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm developed by the US Geological Survey and ESRI to create coverage's for one-degree graticules. For details about each dataset, visit the individual entries. proprietary
NBId0006_101 African Meteorology (GIS Coverage of Precipitation and Winds) ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848036-CEOS_EXTRA.umm_json New-ID: NBI06 Dataset covers mean annual rainfall distribution, number of wet days, wind speed and velocity. The Africa Meteorological Dataset documentation The Africa Meteorological dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focused on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were hand drawn climate maps from FAO. All sources were re-registered to the FAO Soil Map of the world (1984) in Miller Oblated Stereographic projection by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/ longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. proprietary
NBId0006_101 African Meteorology (GIS Coverage of Precipitation and Winds) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848036-CEOS_EXTRA.umm_json New-ID: NBI06 Dataset covers mean annual rainfall distribution, number of wet days, wind speed and velocity. The Africa Meteorological Dataset documentation The Africa Meteorological dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focused on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were hand drawn climate maps from FAO. All sources were re-registered to the FAO Soil Map of the world (1984) in Miller Oblated Stereographic projection by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/ longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. proprietary
-NBId0007_101 Africa Administrative Units (GIS Coverage of Administrative Boundaries) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847851-CEOS_EXTRA.umm_json "New-ID: NBI07 This dataset shows adminstrative boundries of Africa at continental, national, second and third levels in lat/long. The Administrative units Dataset documentation Files: ADMINLL.E00 Code: 100012-002 Vector Member The files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. The administrative units dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP as part of a project initiated by UNEP. The base maps used were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit (1983), and the Rand-McNally New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverage""'""s for one-degree graticules. Contact: UNEP/GRID-Nairobi, P O Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service 00100, Rome, Italy. ESRI, 380 New York Street, Redlands, CA 92373, USA The ADMINLL file shows adminstrative boundries at continental, national, second and third levels in lat/long References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication ESRI, FAO and UNEP FAO, UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning Charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. G.M.Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society Washington DC. Source : FAO Soil Map of the World, scale 1:5000000 Publication Date : Dec 1984 Projection : Geographic Lat/Long Type : Polygon Format : Arc/Info Export non-compressed Related Datasets : All UNEP/FAO/ESRI Datasets TOWNS2 100022-002, Human settlements and airports ROADS2 100021-001, major roads" proprietary
NBId0007_101 Africa Administrative Units (GIS Coverage of Administrative Boundaries) ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847851-CEOS_EXTRA.umm_json "New-ID: NBI07 This dataset shows adminstrative boundries of Africa at continental, national, second and third levels in lat/long. The Administrative units Dataset documentation Files: ADMINLL.E00 Code: 100012-002 Vector Member The files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. The administrative units dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP as part of a project initiated by UNEP. The base maps used were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit (1983), and the Rand-McNally New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverage""'""s for one-degree graticules. Contact: UNEP/GRID-Nairobi, P O Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service 00100, Rome, Italy. ESRI, 380 New York Street, Redlands, CA 92373, USA The ADMINLL file shows adminstrative boundries at continental, national, second and third levels in lat/long References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication ESRI, FAO and UNEP FAO, UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning Charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. G.M.Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society Washington DC. Source : FAO Soil Map of the World, scale 1:5000000 Publication Date : Dec 1984 Projection : Geographic Lat/Long Type : Polygon Format : Arc/Info Export non-compressed Related Datasets : All UNEP/FAO/ESRI Datasets TOWNS2 100022-002, Human settlements and airports ROADS2 100021-001, major roads" proprietary
+NBId0007_101 Africa Administrative Units (GIS Coverage of Administrative Boundaries) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847851-CEOS_EXTRA.umm_json "New-ID: NBI07 This dataset shows adminstrative boundries of Africa at continental, national, second and third levels in lat/long. The Administrative units Dataset documentation Files: ADMINLL.E00 Code: 100012-002 Vector Member The files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. The administrative units dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP as part of a project initiated by UNEP. The base maps used were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit (1983), and the Rand-McNally New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverage""'""s for one-degree graticules. Contact: UNEP/GRID-Nairobi, P O Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service 00100, Rome, Italy. ESRI, 380 New York Street, Redlands, CA 92373, USA The ADMINLL file shows adminstrative boundries at continental, national, second and third levels in lat/long References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication ESRI, FAO and UNEP FAO, UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning Charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. G.M.Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society Washington DC. Source : FAO Soil Map of the World, scale 1:5000000 Publication Date : Dec 1984 Projection : Geographic Lat/Long Type : Polygon Format : Arc/Info Export non-compressed Related Datasets : All UNEP/FAO/ESRI Datasets TOWNS2 100022-002, Human settlements and airports ROADS2 100021-001, major roads" proprietary
NBId0012_101 Cattle and Buffalo distribution (Africa) CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848567-CEOS_EXTRA.umm_json The Cattle and Buffalo distribution dataset shows cattle and buffalo distribution for sub-Saharan, East and Central Africa. It is part of the East Coast Fever (ECF) dataset. The ECF study determined both areas at risk and potential migration of the disease by cattle and a potential pool of infection for transmitting the disease to domestic cattle by Buffalo. Buffalo is the main wildlife host of the ECF. The study was carried out in Nairobi in collaboration with United Nations Environment Program, Global Resource Information Database (UNEP/GRID) and the International Laboratory for Research on Animal Diseases (ILRAD), now called International Livestock Research Institute (ILRI). proprietary
NBId0016_101 Africa FAO Agro-Ecological Zones (GIS Coverage) ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848041-CEOS_EXTRA.umm_json New-ID: NBI16 Agro-ecological zones datasets is made up of AEZBLL08, AEZBLL09, AEZBLL10. The Africa Agro-ecological Zones Dataset documentation Files: AEZBLL08.E00 Code: 100025-011 AEZBLL09.E00 100025-012 AEZBLL10.E00 100025-013 Vector Members The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. The Africa agro-ecological zones dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. The daset was developed by United Nations Environment Program (UNEP), Kenya. The base maps that were used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the Global Navigation and Planning Charts (various 1976-1982) and the National Geographic Atlas of the World (1975). basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. This edit step required appending the country boundaries from Administrative Unit map and then producing the computer plot. Contact: UNEP/GRID-Nairobi, P O Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA 92373, USA The AEZBLL08 data covers North-West of African continent The AEZBLL09 data covers North-East of African continent The AEZBLL10 data covers South of African continent References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO/UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning Charts for Africa (various dates:1976-1982). Scale 1:5000000. Washington DC. G.M. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society, Washington DC. FAO. Statistical Data on Existing Animal Units by Agro-ecological Zones for Africa (1983). Prepared by Todor Boyadgiev of the Soil Resources, Management and Conservation Services Division. FAO. Statistical Data on Existing and Potential Populations by Agro-ecological Zones for Africa (1983). Prepared by Marina Zanetti of the Soil Resources, Management and Conservation Services Division. FAO. Report on the Agro-ecological Zones Project. Vol.I (1978), Methodology & Result for Africa. World Soil Resources No.48. Source : UNESCO/FAO Soil Map of the World, scale 1:5000000 Publication Date : Dec 1984 Projection : Miller Type : Polygon Format : Arc/Info Export non-compressed Related Datasets : All UNEP/FAO/ESRI Datasets, Landuse (100013/05, New-ID: 05 FAO Irrigable Soils Datasets and Water balance (100050/53) proprietary
NBId0016_101 Africa FAO Agro-Ecological Zones (GIS Coverage) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848041-CEOS_EXTRA.umm_json New-ID: NBI16 Agro-ecological zones datasets is made up of AEZBLL08, AEZBLL09, AEZBLL10. The Africa Agro-ecological Zones Dataset documentation Files: AEZBLL08.E00 Code: 100025-011 AEZBLL09.E00 100025-012 AEZBLL10.E00 100025-013 Vector Members The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. The Africa agro-ecological zones dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. The daset was developed by United Nations Environment Program (UNEP), Kenya. The base maps that were used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the Global Navigation and Planning Charts (various 1976-1982) and the National Geographic Atlas of the World (1975). basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. This edit step required appending the country boundaries from Administrative Unit map and then producing the computer plot. Contact: UNEP/GRID-Nairobi, P O Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA 92373, USA The AEZBLL08 data covers North-West of African continent The AEZBLL09 data covers North-East of African continent The AEZBLL10 data covers South of African continent References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO/UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning Charts for Africa (various dates:1976-1982). Scale 1:5000000. Washington DC. G.M. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society, Washington DC. FAO. Statistical Data on Existing Animal Units by Agro-ecological Zones for Africa (1983). Prepared by Todor Boyadgiev of the Soil Resources, Management and Conservation Services Division. FAO. Statistical Data on Existing and Potential Populations by Agro-ecological Zones for Africa (1983). Prepared by Marina Zanetti of the Soil Resources, Management and Conservation Services Division. FAO. Report on the Agro-ecological Zones Project. Vol.I (1978), Methodology & Result for Africa. World Soil Resources No.48. Source : UNESCO/FAO Soil Map of the World, scale 1:5000000 Publication Date : Dec 1984 Projection : Miller Type : Polygon Format : Arc/Info Export non-compressed Related Datasets : All UNEP/FAO/ESRI Datasets, Landuse (100013/05, New-ID: 05 FAO Irrigable Soils Datasets and Water balance (100050/53) proprietary
-NBId0018_101 Africa FAO Major Infrastructure and Human Settlements (GIS Coverage) ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849221-CEOS_EXTRA.umm_json New-ID: NBI18 The Africa Major Infrastructure and Human Settlements Dataset Files: TOWNS2.E00 Code: 100022-002 ROADS2.E00 100021-002 Vector Members: The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename The Africa major infrastructure and human settlements dataset form part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the DMA Global Navigation and Planning charts for Africa (various dates: 1976-1982) and the Rand-McNally, New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap those of the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. The Population Centers were selected based upon their inclusion in the list of major cities and populated areas in the Rand McNally New International Atlas Contact: UNEP/GRID-Nairobi, P.O. Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA. 92373, USA The ROADS2 file shows major roads of the African continent The TOWNS2 file shows human settlements and airports for the African continent References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:850000. National Geographic Society Washington DC. DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC. Rand-McNally. The new International Atlas (1982). Scale 1:6,000,000. Rand McNally & Co.Chicago Source: FAO Soil Map of the World. Scale 1:5000000 Publication Date: Dec 1984 Projection: Miller Type: Points Format: Arc/Info export non-compressed Related Datasets: All UNEP/FAO/ESRI Datasets ADMINLL (100012-002) administrative boundries AFURBAN (100082) urban percentage coverage Comments: There is no outline of Africa proprietary
NBId0018_101 Africa FAO Major Infrastructure and Human Settlements (GIS Coverage) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849221-CEOS_EXTRA.umm_json New-ID: NBI18 The Africa Major Infrastructure and Human Settlements Dataset Files: TOWNS2.E00 Code: 100022-002 ROADS2.E00 100021-002 Vector Members: The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename The Africa major infrastructure and human settlements dataset form part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the DMA Global Navigation and Planning charts for Africa (various dates: 1976-1982) and the Rand-McNally, New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap those of the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. The Population Centers were selected based upon their inclusion in the list of major cities and populated areas in the Rand McNally New International Atlas Contact: UNEP/GRID-Nairobi, P.O. Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA. 92373, USA The ROADS2 file shows major roads of the African continent The TOWNS2 file shows human settlements and airports for the African continent References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:850000. National Geographic Society Washington DC. DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC. Rand-McNally. The new International Atlas (1982). Scale 1:6,000,000. Rand McNally & Co.Chicago Source: FAO Soil Map of the World. Scale 1:5000000 Publication Date: Dec 1984 Projection: Miller Type: Points Format: Arc/Info export non-compressed Related Datasets: All UNEP/FAO/ESRI Datasets ADMINLL (100012-002) administrative boundries AFURBAN (100082) urban percentage coverage Comments: There is no outline of Africa proprietary
+NBId0018_101 Africa FAO Major Infrastructure and Human Settlements (GIS Coverage) ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849221-CEOS_EXTRA.umm_json New-ID: NBI18 The Africa Major Infrastructure and Human Settlements Dataset Files: TOWNS2.E00 Code: 100022-002 ROADS2.E00 100021-002 Vector Members: The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename The Africa major infrastructure and human settlements dataset form part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the DMA Global Navigation and Planning charts for Africa (various dates: 1976-1982) and the Rand-McNally, New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the basemap those of the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. The Population Centers were selected based upon their inclusion in the list of major cities and populated areas in the Rand McNally New International Atlas Contact: UNEP/GRID-Nairobi, P.O. Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy ESRI, 380 New York Street, Redlands, CA. 92373, USA The ROADS2 file shows major roads of the African continent The TOWNS2 file shows human settlements and airports for the African continent References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:850000. National Geographic Society Washington DC. DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC. Rand-McNally. The new International Atlas (1982). Scale 1:6,000,000. Rand McNally & Co.Chicago Source: FAO Soil Map of the World. Scale 1:5000000 Publication Date: Dec 1984 Projection: Miller Type: Points Format: Arc/Info export non-compressed Related Datasets: All UNEP/FAO/ESRI Datasets ADMINLL (100012-002) administrative boundries AFURBAN (100082) urban percentage coverage Comments: There is no outline of Africa proprietary
NBId0019_101 FAO Major Elevation Zones of Africa (GIS Coverage) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849111-CEOS_EXTRA.umm_json New-ID: NBI19 The Africa Major Elevation Zones Dataset documentation File: ELEVLL Code: 100070-003 Vector Member The above file is in Arc/Info Export format and should be imported using the Arc/Info command Import cover In-Filename Out-Filename The Africa elevation major zones dataset is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This dataset was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The manuscript derived from the topographic film separates of the UNESCO/FAO Soil Map of the World (1977) in Miller Oblated Stereographic projection was used to provide a generalized coverage of elevation values providing information as both line-related and polygonal form. The map was prepared by overlaying the topography film separate with a matte drafting film and then delineating the selected elevation contours. Some of the line crenulation was removed during the delineation process, because this map was designed to define general elevation zones rather than constitute a true topographic base. Code values were recorded directly on the map and were key-entered during the digitizing process with a spatial resolution of 0.002 inches, as part of the polygon or line sequence indentification number. The map was then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. Contact: UNEP/GRID-Nairobi, P.O. Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy. ESRI, 380 New York Street, Redlands, CA 92373, USA The ELEVLL2 data shows Major Elevation zones of Africa, in lat/lon References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO/FAO Soil Map of the World(1977). Scale 1:5000000. UNESCO, Paris DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC. G.M. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:8500000. National Geographic Society Washington DC. Source: FAO Soil Map of the World, scale 1:5000000 Publication Date: Dec 1984 Projection: Miller Type: Polygon and line Format: Arc/Info export non compressed Related Datasets: All UNEP/FAO/ESRI Datasets AFELBA elevation and Bathymetry (100048) proprietary
NBId0020_101 Countries, Coasts and Islands of Africa (Global Change Data Base - Digital Boundaries and Coastlines) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848088-CEOS_EXTRA.umm_json New-ID: NBI20 Countries, Coasts and Islands Dataset documentation (Micro World Data Bank II) Files: COASTS.E00 Code: 100051-001 COUNTRY.E00 100052-001 ISLANDS.E00 100054-001 Vector Members Original files were in IDRISI VEC format coverted to Arc/Info. The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. Micro World Data Bank II (MWDB-II) comprising Coastlines, Country boundries and Islands data sets is part of NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II and is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact: NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The COASTS file shows African Coastlines The COUNTRY file shows African Country Boundaries without coast, no names - only lines The ISLANDS file shows African Islands References: NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds. Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, Vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map: digitized from available sources Publication Date: Jun 1992 Projection: Lat/Lon Type: Polygon and line Format: Arc/Info Export non-compressed proprietary
NBId0022_101 Africa Olson World Ecosystems CEOS_EXTRA STAC Catalog 1970-01-01 16, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232846860-CEOS_EXTRA.umm_json "New-ID: NBI22 OLSON WORLD ECOSYSTEMS DATASET DOCUMENTATION File: AFWE20.IMG Code: 100032-001 Raster Member This IMG file is in IDRISI format Olson World Ecosystems data base is part of Global Change Data Base produced by The World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysycal Data Center (NGDC) and for cooperative project called Global Ecosystems Database Project between NDAA(National Oceanic & Atmospheric Administration, USA)/NGDC and the U.S. Environmental Protection Agency. The software (known as IDRISI) was developed and adopted for this project at Clark University. The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California, has joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/Latitude) projection. Each data set is accompanied by an ASCII documentation file. Which contains information necessary for use of the data set in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFWE20 file shows Olson ecosystem classes version 1.4 References: Olson, J.S. Earth""'""s Vegetation and Atmospheric Carbon Dioxide, in Carbon Dioxide Review: 1982. Ed. by W.C. Clark (1983), Exford Univ. Press, New York, pp.388-398. Olson, J.S., J.A. Watts, and L.J. Allison. Carbon in Live Vegetation of Major World Ecosystems (1983). Report ORNL-5862, Oark Ridge Laboratory, Oak Ridge, Tennessee. Olson, J.S. and J.A. Watts. Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation (1982). Oak Ridge National Laboratory, Oak Ridge, Tennesse (map). Source map : from available maps and observations. Publication Date : 1989 Projection : lat/lon. Type : Raster Format : IDRISI" proprietary
@@ -12064,16 +12064,16 @@ NBId0023_101 Africa Holdridge Life Zone Classification (Vegetation and Climate)
NBId0023_101 Africa Holdridge Life Zone Classification (Vegetation and Climate) CEOS_EXTRA STAC Catalog 1970-01-01 16, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847334-CEOS_EXTRA.umm_json New-ID: NBI23 Holdridge Life Zone is a coverage showing zone classification, vegetation relation to climate and vice versa. proprietary
NBId0024_101 Africa Soil Classification by Wilson and Henderson-Sellers CEOS_EXTRA STAC Catalog 1970-01-01 12.88, 6.67, 24.97, 24.19 https://cmr.earthdata.nasa.gov/search/concepts/C2232848824-CEOS_EXTRA.umm_json New-ID: NBI24 Wilson and Henderson-Sellers soil classes and soil class reliability. The Wilson and Henderson-Sellers Soil Classes Dataset Files: AFWSOILS.IMG Code: 100043-001 AFWSOILR.IMG 100043-002 Raster Members The IMG files are in IDRISI format. The Wilson and Henderson-Sellers soils data set is part of Wilson Henderson-Sellers land cover and soils for global circulation modeling project was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II. This data Bank is provided on a Database on diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : Roy Jenne, NCAR, P.O. Box 3000, Boulder, CO 80307-3000 The AFWSOILS file shows Wilson/Henderson-Sellers Soil Classes The ASWSOILR file shows Wilson/Henderson-Sellers Soil Class Reliability References: Wilson, M.F/ and A. Henderson-Sellers. A global archive of land cover and soils data for use in general ciruclation climate models. Journal of Climatology, vol.5, pp.119-143. Source : Digitized from available sources: FAO/UNESCO Soil Map of the World. Oxford Regional Economic Atlas of USSR and Eastern Europe Publication Date : 1985 Projection : Lat/Lon Type : Raster Format : IDRISI proprietary
NBId0024_101 Africa Soil Classification by Wilson and Henderson-Sellers ALL STAC Catalog 1970-01-01 12.88, 6.67, 24.97, 24.19 https://cmr.earthdata.nasa.gov/search/concepts/C2232848824-CEOS_EXTRA.umm_json New-ID: NBI24 Wilson and Henderson-Sellers soil classes and soil class reliability. The Wilson and Henderson-Sellers Soil Classes Dataset Files: AFWSOILS.IMG Code: 100043-001 AFWSOILR.IMG 100043-002 Raster Members The IMG files are in IDRISI format. The Wilson and Henderson-Sellers soils data set is part of Wilson Henderson-Sellers land cover and soils for global circulation modeling project was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II. This data Bank is provided on a Database on diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : Roy Jenne, NCAR, P.O. Box 3000, Boulder, CO 80307-3000 The AFWSOILS file shows Wilson/Henderson-Sellers Soil Classes The ASWSOILR file shows Wilson/Henderson-Sellers Soil Class Reliability References: Wilson, M.F/ and A. Henderson-Sellers. A global archive of land cover and soils data for use in general ciruclation climate models. Journal of Climatology, vol.5, pp.119-143. Source : Digitized from available sources: FAO/UNESCO Soil Map of the World. Oxford Regional Economic Atlas of USSR and Eastern Europe Publication Date : 1985 Projection : Lat/Lon Type : Raster Format : IDRISI proprietary
-NBId0025_101 Africa Soil Classification by Zobler CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848306-CEOS_EXTRA.umm_json New-ID: NBI25 Africa ZOBLER Soil Type, Soil Texture, Surface Slope Classes Dataset Documentation Files: AFZSOILS.IMG Code: 100090-001 AFZTEX.IMG 100090-002 AFZSUBSD.IMG 100090-003 AFZSP3.IMG 100090-004 AFZPHS.IMG 100090-005 AFZSLOPE.IMG 100092-001 Raster Members The IMG files are in IDRISI format The Zobler soil type, soil texture and surface slope dataset was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of a larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFZSOILS file shows Zobler soil types The AFZTEX file shows Zobler soil texture The AFZSUBSD file shows subsidiary soil units The AFZSP3 file shows Zobler special codes The AFZPHS file shows Zobler phase codes The AFZSLOPE file shows Zobler surface slope References: FAO. FAO-UNESCO Soil Map of the World (1974). Scale 1:5000000. UNESCO, Paris. Staub, Brad and Cynthia Rosenzweig. Global Digital Data Sets of Soil Type, Soil Texture, Surface Slope, and other properties: Documentation of Archived Tape Data. NASA Technical Memorandum No.100685. Henderson-Sellers, A., M.F. Wilson, G. Thomas, R.E. Dickinson. Current Global Land Surface Data Sets for Use in Climate-Related Studies. (1986). Matthews, E. Global vegetation and land use: New high resolution data bases for climate studies (1983). J. Clim. Appl. Meteor., vol.22, pp.474-487. -----. Vegetation, Land-use and Seasonal Albedo Data Sets: Documentation of Archived Data Tape (1984). NASA Technical Memorandum. No.86107. Wilson. M.F. and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models (1985). Journal of Climatology, vol.5, pp.119-143. Source map : various Publication Date : 1987 Projection : Lat/lon Type : Raster Format : IDRISI proprietary
NBId0025_101 Africa Soil Classification by Zobler ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848306-CEOS_EXTRA.umm_json New-ID: NBI25 Africa ZOBLER Soil Type, Soil Texture, Surface Slope Classes Dataset Documentation Files: AFZSOILS.IMG Code: 100090-001 AFZTEX.IMG 100090-002 AFZSUBSD.IMG 100090-003 AFZSP3.IMG 100090-004 AFZPHS.IMG 100090-005 AFZSLOPE.IMG 100092-001 Raster Members The IMG files are in IDRISI format The Zobler soil type, soil texture and surface slope dataset was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of a larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFZSOILS file shows Zobler soil types The AFZTEX file shows Zobler soil texture The AFZSUBSD file shows subsidiary soil units The AFZSP3 file shows Zobler special codes The AFZPHS file shows Zobler phase codes The AFZSLOPE file shows Zobler surface slope References: FAO. FAO-UNESCO Soil Map of the World (1974). Scale 1:5000000. UNESCO, Paris. Staub, Brad and Cynthia Rosenzweig. Global Digital Data Sets of Soil Type, Soil Texture, Surface Slope, and other properties: Documentation of Archived Tape Data. NASA Technical Memorandum No.100685. Henderson-Sellers, A., M.F. Wilson, G. Thomas, R.E. Dickinson. Current Global Land Surface Data Sets for Use in Climate-Related Studies. (1986). Matthews, E. Global vegetation and land use: New high resolution data bases for climate studies (1983). J. Clim. Appl. Meteor., vol.22, pp.474-487. -----. Vegetation, Land-use and Seasonal Albedo Data Sets: Documentation of Archived Data Tape (1984). NASA Technical Memorandum. No.86107. Wilson. M.F. and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models (1985). Journal of Climatology, vol.5, pp.119-143. Source map : various Publication Date : 1987 Projection : Lat/lon Type : Raster Format : IDRISI proprietary
-NBId0036_101 Africa Lakes and Rivers (World Data Bank II) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849206-CEOS_EXTRA.umm_json New-ID: NBI36 Africa Lakes and Rivers. Lakes and Rivers Dataset documentation (Micro World Data Bank II) Files: LAKES.VEC Code: 100055-001 RIVERS.VEC 100061-001 AFRIVER.IMG 100002-001 Raster Members The VEC and IMG files are in IDRISI format Africa lakes and rivers datasets are part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The LAKES file shows African lakes The RIVERS file shows African rivers The AFRIVER file shows African rivers References: NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds. Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. vol. 2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : digitized from available sources Publication Date : 1988 Projection : Lat/lon Type : Raster Format : IDRISI proprietary
+NBId0025_101 Africa Soil Classification by Zobler CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848306-CEOS_EXTRA.umm_json New-ID: NBI25 Africa ZOBLER Soil Type, Soil Texture, Surface Slope Classes Dataset Documentation Files: AFZSOILS.IMG Code: 100090-001 AFZTEX.IMG 100090-002 AFZSUBSD.IMG 100090-003 AFZSP3.IMG 100090-004 AFZPHS.IMG 100090-005 AFZSLOPE.IMG 100092-001 Raster Members The IMG files are in IDRISI format The Zobler soil type, soil texture and surface slope dataset was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of a larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFZSOILS file shows Zobler soil types The AFZTEX file shows Zobler soil texture The AFZSUBSD file shows subsidiary soil units The AFZSP3 file shows Zobler special codes The AFZPHS file shows Zobler phase codes The AFZSLOPE file shows Zobler surface slope References: FAO. FAO-UNESCO Soil Map of the World (1974). Scale 1:5000000. UNESCO, Paris. Staub, Brad and Cynthia Rosenzweig. Global Digital Data Sets of Soil Type, Soil Texture, Surface Slope, and other properties: Documentation of Archived Tape Data. NASA Technical Memorandum No.100685. Henderson-Sellers, A., M.F. Wilson, G. Thomas, R.E. Dickinson. Current Global Land Surface Data Sets for Use in Climate-Related Studies. (1986). Matthews, E. Global vegetation and land use: New high resolution data bases for climate studies (1983). J. Clim. Appl. Meteor., vol.22, pp.474-487. -----. Vegetation, Land-use and Seasonal Albedo Data Sets: Documentation of Archived Data Tape (1984). NASA Technical Memorandum. No.86107. Wilson. M.F. and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models (1985). Journal of Climatology, vol.5, pp.119-143. Source map : various Publication Date : 1987 Projection : Lat/lon Type : Raster Format : IDRISI proprietary
NBId0036_101 Africa Lakes and Rivers (World Data Bank II) ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849206-CEOS_EXTRA.umm_json New-ID: NBI36 Africa Lakes and Rivers. Lakes and Rivers Dataset documentation (Micro World Data Bank II) Files: LAKES.VEC Code: 100055-001 RIVERS.VEC 100061-001 AFRIVER.IMG 100002-001 Raster Members The VEC and IMG files are in IDRISI format Africa lakes and rivers datasets are part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The LAKES file shows African lakes The RIVERS file shows African rivers The AFRIVER file shows African rivers References: NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds. Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. vol. 2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : digitized from available sources Publication Date : 1988 Projection : Lat/lon Type : Raster Format : IDRISI proprietary
+NBId0036_101 Africa Lakes and Rivers (World Data Bank II) CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849206-CEOS_EXTRA.umm_json New-ID: NBI36 Africa Lakes and Rivers. Lakes and Rivers Dataset documentation (Micro World Data Bank II) Files: LAKES.VEC Code: 100055-001 RIVERS.VEC 100061-001 AFRIVER.IMG 100002-001 Raster Members The VEC and IMG files are in IDRISI format Africa lakes and rivers datasets are part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The LAKES file shows African lakes The RIVERS file shows African rivers The AFRIVER file shows African rivers References: NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds. Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. vol. 2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : digitized from available sources Publication Date : 1988 Projection : Lat/lon Type : Raster Format : IDRISI proprietary
NBId0041_101 FNOC Elevation (meters), Terrain and Surface Characteristics for Africa CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847281-CEOS_EXTRA.umm_json New-ID: NBI41 Africa FNOC Elevation (meters), Terrain and Surface characteristics. Africa Elevation (meters), Terrain, and Surface Characteristics Dataset Documentation Files: AFMAX.IMG Code: 100082-001 AFMIN.IMG 100082-002 AFMOD.IMG 100082-003 Raster Members The IMG files are in IDRISI format Africa elevation dataset is part of the revised FNOC elevation, terrain and surface characteritics. It formed part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFMAX file shows maximum elevation (meters) The AFMIN file shows minimum elevation (meters) The AFMOD shows modal elevation (meters) Reference: Cuming, Michael J. and Barbara A. Hawkins. TERDAT: The FNOC System for Terrain Data Extraction and Processing (1981). Techn. Report MII Project M-254 (2nd Ed.) Prepared for Fleet Numerical Oceanography Center (Monterey, CA). Published by Meteorology International Incorporated. Source map : Digitized from available maps and reprocessed: US Defense Operational Navigation Charts (ONC), scale 1:1000000; some World Aeronautical Charts and charts from Jet Navigation. Publication Date : 1985 Projection : Lat/Lon Type : Raster Format : IDRISI proprietary
NBId0042_101 NOAA Monthly 10-Minute Normalized Vegetation Index (April 1985-December 1988) for Africa CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848152-CEOS_EXTRA.umm_json "New-ID: NBI42 NOAA monthly Normalized Vegetation Index (NDVI) for Africa. NOAA Monthly 10-Min Normalized Vegetation Index Dataset (APRIL 1985 - DECEMBER 1988) Files: AFAPR85.IMG-AFDEC85.IMG Code: 100041-001 AFJAN86.IMG-AFDEC86.IMG 100041-001 AFJAN87.IMG-AFDEC87.IMG 100041-001 AFJAN88.IMG-AFDEC88.IMG 100041-001 Raster Members The IMG files are in IDRISI format Africa monthly 10-min normalized difference vegetation index dataset is part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysycal Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA AFAPR85-AFDEC88 (45 months) show monthly Normalized Vegetation Index (NDVI) References: Kidwell, Katherin B. (ed.). Global Vegetion Index User""'""s Guide (1990). NOAA/NHESDIS/SDSD. for additional references see Appendix A-26-A32 of the Global Change Data Base documentation Source map : digitized from available maps and reprocessed Publication Date : Jun 1992 Projection : Lat/lon Type : Raster Format : IDRISI" proprietary
-NBId0043_101 Africa Integrated Elevation and Bathymetry ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847599-CEOS_EXTRA.umm_json "New-ID: NBI43 Africa Integrated Elevation and Bathymetry (feet). Integrated Elevation and Bathymetry Dataset Documentation File: AFELBA.IMG Code: 100048-001 Raster Member This IMG file is in IDRISI format Integrated elevation and bathymetry data set is part of UNEP-GRID/FAO Africa data base incorporated into World Data Bank II by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. Sources used were the USSCS World Soil Map, UNESCO/FAO Soil Map of the World, DMA Topographic Maps of Africa, Raize Landform Map of North Africa, and Landsat mosaics. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFELBA file shows integrated elevation and bathymetry (feet) References: Edwards, Margaret Helen. Digital Image Processing of Local and Global Bathymetric Data (1986). Master""'""s Thesis. Washington University, Dept. of Earch and Planetary Sciences, St. Louis, Missouri, p.106. Haxby, W.F., et al. Digital Images of Combined Oceanic and Continental Data Sets and Their Use in Tectonic Studies (1983). EOS Transaction of the American Geophysical Union, vol.64, no.52, pp.995-1004. NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : various sources Publication Date : Jun1992 Projection : Miller Oblated Stereographic resampled to lat/lon. Type : Raster Format : IDRISI" proprietary
NBId0043_101 Africa Integrated Elevation and Bathymetry CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847599-CEOS_EXTRA.umm_json "New-ID: NBI43 Africa Integrated Elevation and Bathymetry (feet). Integrated Elevation and Bathymetry Dataset Documentation File: AFELBA.IMG Code: 100048-001 Raster Member This IMG file is in IDRISI format Integrated elevation and bathymetry data set is part of UNEP-GRID/FAO Africa data base incorporated into World Data Bank II by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. Sources used were the USSCS World Soil Map, UNESCO/FAO Soil Map of the World, DMA Topographic Maps of Africa, Raize Landform Map of North Africa, and Landsat mosaics. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFELBA file shows integrated elevation and bathymetry (feet) References: Edwards, Margaret Helen. Digital Image Processing of Local and Global Bathymetric Data (1986). Master""'""s Thesis. Washington University, Dept. of Earch and Planetary Sciences, St. Louis, Missouri, p.106. Haxby, W.F., et al. Digital Images of Combined Oceanic and Continental Data Sets and Their Use in Tectonic Studies (1983). EOS Transaction of the American Geophysical Union, vol.64, no.52, pp.995-1004. NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : various sources Publication Date : Jun1992 Projection : Miller Oblated Stereographic resampled to lat/lon. Type : Raster Format : IDRISI" proprietary
-NBId0044_101 Africa Ocean Mask CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849137-CEOS_EXTRA.umm_json "New-ID: NBI44 Ocean mask for Africa. Integrated Elevation and Bathymetry Dataset Documentation File: AFELBA.IMG Code: 100048-001 Raster Member This IMG file is in IDRISI format Integrated elevation and bathymetry data set is part of UNEP-GRID/FAO Africa data base incorporated into World Data Bank II by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. Sources used were the USSCS World Soil Map, UNESCO/FAO Soil Map of the World, DMA Topographic Maps of Africa, Raize Landform Map of North Africa, and Landsat mosaics. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFELBA file shows integrated elevation and bathymetry (feet) References: Edwards, Margaret Helen. Digital Image Processing of Local and Global Bathymetric Data (1986). Master""'""s Thesis. Washington University, Dept. of Earch and Planetary Sciences, St. Louis, Missouri, p.106. Haxby, W.F., et al. Digital Images of Combined Oceanic and Continental Data Sets and Their Use in Tectonic Studies (1983). EOS Transaction of the American Geophysical Union, vol.64, no.52, pp.995-1004. NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : various sources Publication Date : Jun1985 Projection : Miller Oblated Stereographic resampled to lat/lon. Type : Raster Format : IDRISI" proprietary
+NBId0043_101 Africa Integrated Elevation and Bathymetry ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847599-CEOS_EXTRA.umm_json "New-ID: NBI43 Africa Integrated Elevation and Bathymetry (feet). Integrated Elevation and Bathymetry Dataset Documentation File: AFELBA.IMG Code: 100048-001 Raster Member This IMG file is in IDRISI format Integrated elevation and bathymetry data set is part of UNEP-GRID/FAO Africa data base incorporated into World Data Bank II by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. Sources used were the USSCS World Soil Map, UNESCO/FAO Soil Map of the World, DMA Topographic Maps of Africa, Raize Landform Map of North Africa, and Landsat mosaics. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFELBA file shows integrated elevation and bathymetry (feet) References: Edwards, Margaret Helen. Digital Image Processing of Local and Global Bathymetric Data (1986). Master""'""s Thesis. Washington University, Dept. of Earch and Planetary Sciences, St. Louis, Missouri, p.106. Haxby, W.F., et al. Digital Images of Combined Oceanic and Continental Data Sets and Their Use in Tectonic Studies (1983). EOS Transaction of the American Geophysical Union, vol.64, no.52, pp.995-1004. NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : various sources Publication Date : Jun1992 Projection : Miller Oblated Stereographic resampled to lat/lon. Type : Raster Format : IDRISI" proprietary
NBId0044_101 Africa Ocean Mask ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849137-CEOS_EXTRA.umm_json "New-ID: NBI44 Ocean mask for Africa. Integrated Elevation and Bathymetry Dataset Documentation File: AFELBA.IMG Code: 100048-001 Raster Member This IMG file is in IDRISI format Integrated elevation and bathymetry data set is part of UNEP-GRID/FAO Africa data base incorporated into World Data Bank II by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. Sources used were the USSCS World Soil Map, UNESCO/FAO Soil Map of the World, DMA Topographic Maps of Africa, Raize Landform Map of North Africa, and Landsat mosaics. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFELBA file shows integrated elevation and bathymetry (feet) References: Edwards, Margaret Helen. Digital Image Processing of Local and Global Bathymetric Data (1986). Master""'""s Thesis. Washington University, Dept. of Earch and Planetary Sciences, St. Louis, Missouri, p.106. Haxby, W.F., et al. Digital Images of Combined Oceanic and Continental Data Sets and Their Use in Tectonic Studies (1983). EOS Transaction of the American Geophysical Union, vol.64, no.52, pp.995-1004. NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : various sources Publication Date : Jun1985 Projection : Miller Oblated Stereographic resampled to lat/lon. Type : Raster Format : IDRISI" proprietary
+NBId0044_101 Africa Ocean Mask CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849137-CEOS_EXTRA.umm_json "New-ID: NBI44 Ocean mask for Africa. Integrated Elevation and Bathymetry Dataset Documentation File: AFELBA.IMG Code: 100048-001 Raster Member This IMG file is in IDRISI format Integrated elevation and bathymetry data set is part of UNEP-GRID/FAO Africa data base incorporated into World Data Bank II by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. Sources used were the USSCS World Soil Map, UNESCO/FAO Soil Map of the World, DMA Topographic Maps of Africa, Raize Landform Map of North Africa, and Landsat mosaics. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFELBA file shows integrated elevation and bathymetry (feet) References: Edwards, Margaret Helen. Digital Image Processing of Local and Global Bathymetric Data (1986). Master""'""s Thesis. Washington University, Dept. of Earch and Planetary Sciences, St. Louis, Missouri, p.106. Haxby, W.F., et al. Digital Images of Combined Oceanic and Continental Data Sets and Their Use in Tectonic Studies (1983). EOS Transaction of the American Geophysical Union, vol.64, no.52, pp.995-1004. NOAA. Global Change Data Base, Digital Data with Documentation (1992). National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. Hastings, David A., and Liping Di. Modeling of global change phenomena with GIS using the Global Change Data Base (1992). Remote sensing of environment, in review. Clark, David M., Hastings, David A. and Kineman, John J. Global databases and their implications for GIS (1991). IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. Kineman, J.J., Clark, D.M., and Croze, H. Data integration and modelling for global change: An international experiment (1990). Proceeding of the International Conference and workshop on Global Natural Resource Monitoring and Assessments. Preparing for the 21st Century (Venice, Italy, 24-30 September 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, vol. 2, pp. 660-669. CERL. The Geographic Resources Analysis Support System (GRASS-GIS) version 4.0 (1991). U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. Source map : various sources Publication Date : Jun1985 Projection : Miller Oblated Stereographic resampled to lat/lon. Type : Raster Format : IDRISI" proprietary
NBId0053_101 Africa Revised FNOC Percent Water Cover CEOS_EXTRA STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847596-CEOS_EXTRA.umm_json New-ID: NBI53 Africa Revised FNOC Percent Water Cover Dataset Documentation File: AFWATER.IMG Code: 100082-005 Raster Member The IMG file is in IDRISI format The percent water cover dataset is part of the revised FNOC elevation, terrain and surface characteritics. It formed part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFWATER file shows the revised FNOC percent water cover for Africa. Reference: Cuming, Michael J. and Barbara A. Hwakins. TERDAT: The FNOC System for Terrain Data Extraction and Processing (1981). Techn. Report MII Project M-254 (2nd Ed.) Prepared for Fleet Numerical Oceanography Center (Monterey, CA). Published by Meteorology International Incorporated. Source map : Digitized from available maps and reprocessed: US Defense Operational Navigation Charts (ONC), scale 1:1000000; some World Aeronautical Charts and charts from Jet Navigation. Publication Date : 1985 Projection : Lon/lat Type : Raster Format : IDRISI proprietary
NBId0053_101 Africa Revised FNOC Percent Water Cover ALL STAC Catalog 1970-01-01 -30, -45, 60, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847596-CEOS_EXTRA.umm_json New-ID: NBI53 Africa Revised FNOC Percent Water Cover Dataset Documentation File: AFWATER.IMG Code: 100082-005 Raster Member The IMG file is in IDRISI format The percent water cover dataset is part of the revised FNOC elevation, terrain and surface characteritics. It formed part of the NOAA project that was developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The dataset is part of the World Data Bank II provided on a diskette called The Global Change Data Base. The Data Bank II is part of larger project called Global Ecosystems Database Project. This is a cooperation between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A scale was chosen that corresponds closely with the resolution of global AVHRR coverage was chosen to provide compatibility with other scales. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. Contact : NGDC, 325 Broadway E/GC, Boulder, Colorado 80303, USA The AFWATER file shows the revised FNOC percent water cover for Africa. Reference: Cuming, Michael J. and Barbara A. Hwakins. TERDAT: The FNOC System for Terrain Data Extraction and Processing (1981). Techn. Report MII Project M-254 (2nd Ed.) Prepared for Fleet Numerical Oceanography Center (Monterey, CA). Published by Meteorology International Incorporated. Source map : Digitized from available maps and reprocessed: US Defense Operational Navigation Charts (ONC), scale 1:1000000; some World Aeronautical Charts and charts from Jet Navigation. Publication Date : 1985 Projection : Lon/lat Type : Raster Format : IDRISI proprietary
NBId0079_101 Lake Chad Datasets, Africa CEOS_EXTRA STAC Catalog 1970-01-01 13, 7, 24, 23 https://cmr.earthdata.nasa.gov/search/concepts/C2232848788-CEOS_EXTRA.umm_json The Lake Chad Dataset which is a detailed case study of the UNEP/FAO/ESRI Family was developed by UNEP/GRID, on behalf of the UNEP/Fresh Water Unit for the Lake Chad Commission on Sustainable Development. Lake Chad Dataset covers parts of 7 countries: Cameroon, Chad, Nigeria and Niger, Sudan, Central African Republic and Libya and is a clip (regional version) of Africa Outline Dataset (NBI01). The base maps used for the continental version were the FAO/UNESCO Soil Map of the World (1977) in Miller Oblated Stereographic projection, FAO Maps and Statistical Data by Administrative Unit and the Rand-McNally New International Atlas (1982) to clarify unit boundaries. Files: ADMIN.E00 Code: 115001-001 BASE.E00 115002-001 COUNTRIES.E00 115003-001 Vector Members The E00 files are in Arc/Info Export format and should be imported with the Arc/Info command Import cover In-Filename Out-Filename. The ADMIN polygon dataset showing administrative areas for 7 countries around Lake Chad. The BASE is a polygon Dataset showing the countries with inland water bodies. The COUNTRIES is a polygon Dataset showing only the country boundaries. References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. FAO/UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris FAO. Maps and Statistical Data by Administrative Unit (unpublished) Rand-McNally. New International Atlas (1982). Rand-McNally & Company. Chicago Source: FAO/UNESCO Soil Map of the World. Scale 1:5000000 Publication Date: Dec 1988 Projection: Miller Type: Polygon and line Format: Arc/Info Export, non-compressed Related Datasets: All the Lake Chad Datasets of the UNEP/FAO/ESRI family. proprietary
@@ -12093,25 +12093,25 @@ NBId0153_101 Benito River dataset of Equatorial Guinea CEOS_EXTRA STAC Catalog 1
NBId0161_101 Climate Dataset of Senegal CEOS_EXTRA STAC Catalog 1970-01-01 -17.53, 12.02, -10.89, 17.14 https://cmr.earthdata.nasa.gov/search/concepts/C2232849116-CEOS_EXTRA.umm_json New-ID: NBI161 The Climate Dataset of Senegal documentation Files: SENEGAL4.IMG Code: 146005-001 SENEGAL5.IMG 146006-001 SENEGAL6.IMG 146007-001 Raster Members IMG files are in IDRISI format The Senegal Climate Dataset was originally digitized for the UNEP/FAO/ESRI Database for Africa from hand-drawn maps provided by FAO for the Desertification Hazard Mapping project. GRID-Geneva rasterized the coverages for UNEP/GRID/WHO/CISFAM Senegal Database with a cell size of 30 seconds and two minutes lat/lon (approximately one- and four kilometeter-square pixels, respectively). Contact: UNEP/GRID-Nairobi, P.O. Box 30552 Nairobi, Kenya FAO, Soil Resources, Management and Conservation Service, 00100, Rome, Italy The SENEGAL4 file shows mean annual wind velocity meters per second (8 classes). The SENEGAL5 file shows number of wet days per year (6 classes). The SENEGAL6 file shows mean annual rainfall in millimeters (10 classes). REMARK: file may have limited applicability at national scale as was extracted from continental. References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP. CISFAM. Consolidated Information System for Famine Management in Africa, Phase I Report (Apr. 1987), Univ. of Louvain, Brussels, Belgium. Source and scale : unknown Report Publication Date : Dec 1988 Projection : lat/lon Type : Raster Format : IDRISI Related Datasets : All UNEP/FAO/ESRI climate Datasets proprietary
NBId0169_101 Baringo (Kenya) Pilot Study for Desertification Assessment and Mapping CEOS_EXTRA STAC Catalog 1984-01-01 1992-12-30 35, -1, 36, 0 https://cmr.earthdata.nasa.gov/search/concepts/C2232849286-CEOS_EXTRA.umm_json The purpose of the Kenya Pilot Study was to evaluate the FAO/UNEP Provisional Methodology for Assessment and Mapping of Desertification, and to recommend an effective, simple methodology for desertification assessment within Kenya. The FAO/UNEP Provisional Methodology (1984) proposes seven processes for consideration in desertification assessment: degradation of vegetation, water erosion, wind erosion, salinization, reduction of organic content, soil crusting and compaction. In late 1985, a pilot project for the assessment of the FAO/UNEP Methodology within Kenya was proposed, and in 1987 a memorandum of understanding between the Government of Kenya and UNEP for the implementation of that study was signed. The study areas were: 1) Models can be useful to assist in desertification assessment. Models can be developed from FAO/UNEP Methodology. 2) Any modeling output requires verification. 3) Ground survey and remote sensing can be important sources of data. 4) An evaluation of data and methodologies necessary to allow verification of desertification assessment modeling is required. 5) A human use component should be incorporated into desertification assessment that considers management implications and social, as well as, economic context. 6) Computer implementation of desertificaiton assessment can be effective, however, procedures should be well defined. This study within the Baringo Study Area was designed to address these concerns. The Baringo Study Area identified in this study would be typical of such a training area. The models developed during this study could be applied to the general region. The study area lies between 0 15'-1 N and 35 30' -36 30' E. It is located between the Laikipia escarpment to the East and the Tugen Hills to the West. Topographic elevations vary from 900m on the Njemps flats to 2000m in the Puka, Tangulbei and Pokot highlands. The size of the study area is approximately 15ookm2. 4.0 DATA COLLECTION A wide variety of data was collected. Detailed data was required to provide a basis for evaluating more general cost effective data gathering techniques and to provide a basis for model verification, particularly the socio/economic data. Physical Environment Topographic Data Topographic contours were digitized directly from 1:250,000 Survey of Kenya topographic maps. The contour interval was 200 feet. A digital elevation model was constructed using triangular irregular networks (TIN). Soil Data Soil types were mapped at 1:100,000 scale using existing soil maps, manual interpretation of SPOT imagery, and field investigations (Figure 3). During field trips, soil samples were taken from each soil unit and analyzed by the Kenya National Agricultural Center. 4.2 Climate Data 4.2.1 Rainfall Data Rainfall data from the Kenya Meteorological Department was analyzed for 33 stations within and surrounding the study area. A rainfall erosivity index was calculated based on the Fourier Index (R). 12 RE (p /P) 12 where P = annual rainfall p = monthly rainfall A relationship between this erosivity index and the annual rainfall for each station was calculated using linear regression (Bake, 1988). A map of rainfall erosivity was generated for the study area by relating annual rainfall isoheyts to the following: y = 0.108x - 0.68 This data was coded and digitized. Wind Erosion Potential The following required conditions were determined to create high wind erosion potential (Kinuthia, 1989): 1) Annual rainfall less than 300mm. 2) P/E greater than zero and less than 1, where: P=mean monthly rainfall (cm). E=mean monthly PET (cm). 3) Wind velocity greater than 4 m/s at 10m height. Vegetation Data A vegetation map for the study area was produced at a scale of 1:100,000 through manual interpretation of a SPOT image and field investigations (Figure 6). A structural classification system as adopted by DRSRS was used for naming vegetation types (Grunb). Systematic Reconnaissance Flight Data Since 1977, DRSRS has been conducting aerial surveys of Kenyan rangelands. In addition to data on the number of wildlife and livestock, observations of land use and environmental condition are also made. Socio/economic Data Social Factors A wide variety of data was collected through literature review and a field administered questionnaire. Nutritional status was estimated by measurement of childrens' mid upper arm. Such data is useful for a Level 1 type assessment. Permanent Structures Data For the Level 2 assessment, data on permanent structures was extracted from DRSRS SRF data. This data was used to indicate presence and concentration of sedentary populations. Example Files: VDS.E00 (Vegetation degradation) DES.E00 (Plant Species) Others available on request. proprietary
NBId0177_101 Laikipia (Kenya) Research Programme GIS Datasets CEOS_EXTRA STAC Catalog 1990-01-01 1994-12-30 36, 0, 37, 1 https://cmr.earthdata.nasa.gov/search/concepts/C2232848187-CEOS_EXTRA.umm_json Laikipia Research Programme GIS Datasets are divided into two main different study area scales: the Regional level [Laikipia district, the Ewaso Ng'iro Basin] and the Local level [Land parcels-farm(s), catchments of a few kilometer square]. Coordinate Reference System Coverage data is organized thematically as a series of layers. The coordinate reference systems used in LRP dataset are:- (a) global coordinate system - Universal Transverse Mercator (UTM), (b) Local coordinate system. Digitizing Scale and Fuzzy Tolerance The initial digitizing scale for the LRP GIS Dataset is dependent on the scale of the study areas. There are two major research levels carried by LRP namely Regional and Local. The scales used for regional level are 1:250,000 and 1:50,000. FUZZY TOLERANCE is the minimum distance between coordinates in a coverage. The resolution of a coverage is defined by the minimum distance separating the coordinates used to store coverage features. Resolution is limited by the map scale in initial digitizing. The fuzzy tolerance can be calculated as follows for digitizing table: Initial Scale for Coverage of Fuzzy Tolerance Digitizing Units Value 1;250,000 Meters 6.35 1:50,000 Meters 1.25 1:10,000 Meters 0.25 1:5,000 Meters 0.125 1:2,500 Meters 0.0625 Files: Roads.E00 (Roads) Settle.E00 (Settlement Pattern) Centres.E00 (Urban Centres) (other files exist also) proprietary
-NBId0203_101 Africa Water Balance high/lowland crops, 1987 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847252-CEOS_EXTRA.umm_json "The Africa Water Balance data set which is prepared by watershed and by country, belongs to the group of ""Irrigation and Water Resources Potential"" study. It covers 55 countries and 25 major basins which contain 335 watersheds. The digitized data base for Africa and the World was originally prepared for an FAO/UNEP project on Desertification in 1982-1984. UNEP financed preparation and analysis of the digitized map data and FAO prepared the data and methodology. The main input maps (all in Miller Oblated Stereographic projection) are the 1975 UNESCO Geological Map of Africa (originally at a scale of 1:10 million); the FAO/UNESCO Soil Map of Africa; Mean Annual Rainfall Map from hand drawn FAO/AGS climate maps; Template; Watersheds; and Administrative Units map - all at a scale 1:5 m. The methodology was based on water balance approach. This determines the suitability of the soil for irrigation and estimates the amount of water the soil requires. Estimates of the surface and groundwater are then compared to the potential irrigation use. If use exceeds available water resources, the irrigable area is correspondingly reduced; in the event of water surplus, some of the water is routed to the downstream basin. The classification was done for two major crop types: lowland crops (flooded rice), and upland crops (for all other irrigated crops except lowland crops). For further details refer to FAO contact for the 1987 FAO Irrigation and Water Resources Potential for Africa AGL/MISC/11/87. FAO, Land and Water Development Division via Delle Terme di Caracalla, 00100, Rome, Italy Vector Member The file is in Arc/Info Export format. Reference: FAO. Irrigation and Water Resources Potential for Africa. (1987) FAO. Final Report UNEP/FAO world and Africa GIS data base (1984), unpublished publication of ESRI, FAO and UNEP. UNESCO. Geological Map of Africa (1975). Scale 1:5 000 000." proprietary
NBId0203_101 Africa Water Balance high/lowland crops, 1987 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847252-CEOS_EXTRA.umm_json "The Africa Water Balance data set which is prepared by watershed and by country, belongs to the group of ""Irrigation and Water Resources Potential"" study. It covers 55 countries and 25 major basins which contain 335 watersheds. The digitized data base for Africa and the World was originally prepared for an FAO/UNEP project on Desertification in 1982-1984. UNEP financed preparation and analysis of the digitized map data and FAO prepared the data and methodology. The main input maps (all in Miller Oblated Stereographic projection) are the 1975 UNESCO Geological Map of Africa (originally at a scale of 1:10 million); the FAO/UNESCO Soil Map of Africa; Mean Annual Rainfall Map from hand drawn FAO/AGS climate maps; Template; Watersheds; and Administrative Units map - all at a scale 1:5 m. The methodology was based on water balance approach. This determines the suitability of the soil for irrigation and estimates the amount of water the soil requires. Estimates of the surface and groundwater are then compared to the potential irrigation use. If use exceeds available water resources, the irrigable area is correspondingly reduced; in the event of water surplus, some of the water is routed to the downstream basin. The classification was done for two major crop types: lowland crops (flooded rice), and upland crops (for all other irrigated crops except lowland crops). For further details refer to FAO contact for the 1987 FAO Irrigation and Water Resources Potential for Africa AGL/MISC/11/87. FAO, Land and Water Development Division via Delle Terme di Caracalla, 00100, Rome, Italy Vector Member The file is in Arc/Info Export format. Reference: FAO. Irrigation and Water Resources Potential for Africa. (1987) FAO. Final Report UNEP/FAO world and Africa GIS data base (1984), unpublished publication of ESRI, FAO and UNEP. UNESCO. Geological Map of Africa (1975). Scale 1:5 000 000." proprietary
+NBId0203_101 Africa Water Balance high/lowland crops, 1987 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847252-CEOS_EXTRA.umm_json "The Africa Water Balance data set which is prepared by watershed and by country, belongs to the group of ""Irrigation and Water Resources Potential"" study. It covers 55 countries and 25 major basins which contain 335 watersheds. The digitized data base for Africa and the World was originally prepared for an FAO/UNEP project on Desertification in 1982-1984. UNEP financed preparation and analysis of the digitized map data and FAO prepared the data and methodology. The main input maps (all in Miller Oblated Stereographic projection) are the 1975 UNESCO Geological Map of Africa (originally at a scale of 1:10 million); the FAO/UNESCO Soil Map of Africa; Mean Annual Rainfall Map from hand drawn FAO/AGS climate maps; Template; Watersheds; and Administrative Units map - all at a scale 1:5 m. The methodology was based on water balance approach. This determines the suitability of the soil for irrigation and estimates the amount of water the soil requires. Estimates of the surface and groundwater are then compared to the potential irrigation use. If use exceeds available water resources, the irrigable area is correspondingly reduced; in the event of water surplus, some of the water is routed to the downstream basin. The classification was done for two major crop types: lowland crops (flooded rice), and upland crops (for all other irrigated crops except lowland crops). For further details refer to FAO contact for the 1987 FAO Irrigation and Water Resources Potential for Africa AGL/MISC/11/87. FAO, Land and Water Development Division via Delle Terme di Caracalla, 00100, Rome, Italy Vector Member The file is in Arc/Info Export format. Reference: FAO. Irrigation and Water Resources Potential for Africa. (1987) FAO. Final Report UNEP/FAO world and Africa GIS data base (1984), unpublished publication of ESRI, FAO and UNEP. UNESCO. Geological Map of Africa (1975). Scale 1:5 000 000." proprietary
NBId0207_101 IGADD Member Countries Crop types and distribution by administrative units, 1987 CEOS_EXTRA STAC Catalog 1970-01-01 22, -12, 51, 23 https://cmr.earthdata.nasa.gov/search/concepts/C2232849119-CEOS_EXTRA.umm_json "The IGADD (Inter-Governmental Authority on Drought and Development) crop zones dataset is part of the Africa UNEP/FAO/ESRI Crops Data. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. The data was provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service, Land and Water Development Division, Italy. The datasets were then developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the Administrative Units map and the World Atlas of Agriculture (1969). All sources were re-registered to the base map by comparing known features on the base map and the source maps. In the original Database (Africa), a considerable study was made of crop water requirements for a range of crops in the various African climates during the time of the year when irrigation would be required. It was found that a relatively simple relationship exists between annual rainfall and the crop irrigation water requirements for the African food grain crops. It was also observed that water requirements for food grains vary between fruit and vegetable crops on the one side and fiber crops and fodder on the other. No attempt was made to produce complex crop patterns. There is a maximum of 13 crop types in one country. References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO/UNESCO Soil Map of the Africa (1977). Scale 1:5000000. UNESCO, Paris. FAO. Administration units map. Scale 1:5 000 000. Rome. FAO. Irrigation and Water Resources Potential for Africa. (1987) Source :UNESCO/FAO Soil Map of the World. Scale 1:5000000 Publication Date :Nov 1987 Projection :Miller Type :Polygon Format :Arc/Info Export non-compressed Related Data sets :All UNEP/FAO/ESRI Data sets FAO Irrigable Data sets 100050: "" IRRIGLB lowland crops, best soils "" IRRIGLT lowland crops, best plus suitable soils "" IRRIGUB upland crops, best soils "" IRRIGUT upland crops, best plus suitable soils FAO Soil water balance 100053: "" WATBALLB lowland crops, best soils "" WATBALLT lowland crops, best plus suitable soils "" WATBALUB upland crops, best soils "" WATBALUT upland crops, best plus suitable soils FAO Agro-ecological zones AEZBLL08 North-west of continent AEZBLL09 North-east of continent AEZBLL10 South of continent" proprietary
NBId0208_101 Africa Major Human Settlements and Landuse, 1984 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848068-CEOS_EXTRA.umm_json The Africa Human Settlements and Landuse data sets form part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This data set was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the DMA Global Navigation and Planning charts for Africa (various dates: 1976-1982) and the Rand-McNally, New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the base map those of the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. The Population Centers were selected based upon their inclusion in the list of major cities and populated areas in the Rand McNally New International Atlas. References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:850000. National Geographic Society Washington DC. DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC. Rand-McNally. The new International Atlas (1982). Scale 1:6,000,000. Rand McNally & Co.Chicago Source :FAO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Miller Type :Points Format :Arc/Info export non-compressed Related Data sets :All UNEP/FAO/ESRI Data sets ADMINLL (100012-002) administrative boundries AFURBAN (100082) urban percentage coverage Comments : no outline of Africa proprietary
NBId0208_101 Africa Major Human Settlements and Landuse, 1984 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848068-CEOS_EXTRA.umm_json The Africa Human Settlements and Landuse data sets form part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Soil Resources, Management and Conservation Service, Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. This data set was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were the UNESCO/FAO Soil Map of the world (1977) in Miller Oblated Stereographic projection, the DMA Global Navigation and Planning charts for Africa (various dates: 1976-1982) and the Rand-McNally, New International Atlas (1982). All sources were re-registered to the basemap by comparing known features on the base map those of the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm of the US Geological Survey and ESRI to create coverages for one-degree graticules. The Population Centers were selected based upon their inclusion in the list of major cities and populated areas in the Rand McNally New International Atlas. References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1984). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris Defence Mapping Agency. Global Navigation and Planning charts for Africa (various dates: 1976-1982). Scale 1:5000000. Washington DC. Grosvenor. National Geographic Atlas of the World (1975). Scale 1:850000. National Geographic Society Washington DC. DMA. Topographic Maps of Africa (various dates). Scale 1:2000000 Washington DC. Rand-McNally. The new International Atlas (1982). Scale 1:6,000,000. Rand McNally & Co.Chicago Source :FAO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Miller Type :Points Format :Arc/Info export non-compressed Related Data sets :All UNEP/FAO/ESRI Data sets ADMINLL (100012-002) administrative boundries AFURBAN (100082) urban percentage coverage Comments : no outline of Africa proprietary
NBId0211_101 Africa Irrigation Potential, Best soils, 1987 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848204-CEOS_EXTRA.umm_json The Africa Irrigation Potential data set, which represents the best soils suitable for upland, is part of the FAO Irrigation and Water Resources Potential Database. The main input maps were the 1977 FAO/UNESCO Soil Map of the Africa, UNESCO Geological World Atlas (scale 1:10 m), Mean Annual Rainfall map from hand drawn FAO/AGS climate maps, Template with water related features, Administrative Units map, and Watersheds map. All maps, apart from where specified were at a scale of 1:5 million, and all in Miller Oblated Stereographic projection. The soil suitability for irrigation was determined by evaluating the properties of all soil components: dominant soil, associations and inclusions, phases, slope, drainage, and texture. The classification was done for two major crop types: lowland crops (flooded rice), and upland crops (for all other irrigated crops except the lowland crops). The soils source includes a list of attributes for each soil unit including: slope, drainage, texture and phase (re: UNEP/FAO/ESRI ITU 100004). Then for both cases (lowland crops (flooded rice), and upland crops (for all other irrigated crops except the lowland crops)), two maps were generated. One with all soils which are suitable, and one where slope, texture, drainage and phase were considered. Each different soil type is classed according to suitability, S1 irrigation with no constraints, S2 irrigation with some constraints, N1 not suitable without major improvements, N2 permanently not suitable. Because one soil unit can consist of more soil components (unit Af26-a can mean 30%Bf and 70% Af) the suitability is expressed in percentage of the unit that is suitable (1 >50% suitable, 2 = 25-50% etc.). Then the soil characteristics are used to refine the ranking. This refining is done were the original soil rank is increased decreased or changed from their original suitability to a new suitability (so or soil gets new class S1, N1 etc. or ranking changes like, -1 lower soil rank by one, +1 raise soil rank with one). The Ranking of Soils is as follows The soils considered not suitable are: Lithosols, Arenosols, Rendzinas, Yermosols, Podzols, Thionic Fluvisols, Miscellaneous land units such as rock debris, desert debris, Gypsum units, Soils with stonic, lythic or petrogypsic phase. proprietary
NBId0211_101 Africa Irrigation Potential, Best soils, 1987 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848204-CEOS_EXTRA.umm_json The Africa Irrigation Potential data set, which represents the best soils suitable for upland, is part of the FAO Irrigation and Water Resources Potential Database. The main input maps were the 1977 FAO/UNESCO Soil Map of the Africa, UNESCO Geological World Atlas (scale 1:10 m), Mean Annual Rainfall map from hand drawn FAO/AGS climate maps, Template with water related features, Administrative Units map, and Watersheds map. All maps, apart from where specified were at a scale of 1:5 million, and all in Miller Oblated Stereographic projection. The soil suitability for irrigation was determined by evaluating the properties of all soil components: dominant soil, associations and inclusions, phases, slope, drainage, and texture. The classification was done for two major crop types: lowland crops (flooded rice), and upland crops (for all other irrigated crops except the lowland crops). The soils source includes a list of attributes for each soil unit including: slope, drainage, texture and phase (re: UNEP/FAO/ESRI ITU 100004). Then for both cases (lowland crops (flooded rice), and upland crops (for all other irrigated crops except the lowland crops)), two maps were generated. One with all soils which are suitable, and one where slope, texture, drainage and phase were considered. Each different soil type is classed according to suitability, S1 irrigation with no constraints, S2 irrigation with some constraints, N1 not suitable without major improvements, N2 permanently not suitable. Because one soil unit can consist of more soil components (unit Af26-a can mean 30%Bf and 70% Af) the suitability is expressed in percentage of the unit that is suitable (1 >50% suitable, 2 = 25-50% etc.). Then the soil characteristics are used to refine the ranking. This refining is done were the original soil rank is increased decreased or changed from their original suitability to a new suitability (so or soil gets new class S1, N1 etc. or ranking changes like, -1 lower soil rank by one, +1 raise soil rank with one). The Ranking of Soils is as follows The soils considered not suitable are: Lithosols, Arenosols, Rendzinas, Yermosols, Podzols, Thionic Fluvisols, Miscellaneous land units such as rock debris, desert debris, Gypsum units, Soils with stonic, lythic or petrogypsic phase. proprietary
-NBId0216_101 Africa Number of Wet Days per Year and Wind Velocity, 1984 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849224-CEOS_EXTRA.umm_json "The Africa Number of Wet Days per year and Wind Velocity data sets are part of the UNEP/FAO/ESRI Database project that covers the entire world but focused on Africa in this case. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. This data set was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were hand drawn climate maps from FAO. All sources were re-registered to the FAO Soil Map of the world (1984) in Miller Oblated Stereographic projection by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/ longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). ""Internal Publication from ESRI, FAO and UNEP ""FAO/UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris ""FAO. Map of Mean Annual Rainfall and general Climate zones for P/Pet for Africa. (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resources, Management and Conservation Service. FAO, Rome ""FAO. Maps of Mean annual Wind Velocity for Africa (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resourcs, Management and Conservation Service. FAO, Rome"" ""FAO. Maps of Number of Wet Days per Year (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resourcs, Management and Conservation Service. FAO, Rome Source :FAO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Geographic (lat/lon) Type :Polygon and line Format :Arc/Info Export non-compressed Related Datasets :All UNEP/FAO/ESRI Data sets" proprietary
NBId0216_101 Africa Number of Wet Days per Year and Wind Velocity, 1984 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849224-CEOS_EXTRA.umm_json "The Africa Number of Wet Days per year and Wind Velocity data sets are part of the UNEP/FAO/ESRI Database project that covers the entire world but focused on Africa in this case. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. This data set was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were hand drawn climate maps from FAO. All sources were re-registered to the FAO Soil Map of the world (1984) in Miller Oblated Stereographic projection by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/ longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). ""Internal Publication from ESRI, FAO and UNEP ""FAO/UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris ""FAO. Map of Mean Annual Rainfall and general Climate zones for P/Pet for Africa. (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resources, Management and Conservation Service. FAO, Rome ""FAO. Maps of Mean annual Wind Velocity for Africa (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resourcs, Management and Conservation Service. FAO, Rome"" ""FAO. Maps of Number of Wet Days per Year (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resourcs, Management and Conservation Service. FAO, Rome Source :FAO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Geographic (lat/lon) Type :Polygon and line Format :Arc/Info Export non-compressed Related Datasets :All UNEP/FAO/ESRI Data sets" proprietary
-NBId0218_101 Africa Surface Hydrography, 1984 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848062-CEOS_EXTRA.umm_json The First-Third Order Stream Network member of the African Surface Hydrography data set is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP), as part of a project initiated by the same. The base map used was the FAO/UNESCO Soil Map of the World, scale 1:5000000 (1977) in Miller Oblated Stereographic projection. All sources were re-registered to the base map by comparing known features on the base map and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm by US Geological Survey and ESRI) to create coverage for one-degree graticules. References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1977). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World.(1977). Scale 1:5000000. UNESCO, Paris Source :FAO/UNESCO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Geographic (lat/lon) Feature type :line Related Data sets :All UNEP/FAO/ESRI Data sets, Outline of Africa OUTLINE3.E00, HYDRMAJLL, HYDRMINLL (Surface Hydrography), Hydrologic Basins Comment : No boundary (outline) for Africa. proprietary
+NBId0216_101 Africa Number of Wet Days per Year and Wind Velocity, 1984 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849224-CEOS_EXTRA.umm_json "The Africa Number of Wet Days per year and Wind Velocity data sets are part of the UNEP/FAO/ESRI Database project that covers the entire world but focused on Africa in this case. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by Food and Agriculture Organization (FAO), the Soil Resources, Management and Conservation Service Land and Water Development Division, Italy. This data set was developed in collaboration with the United Nations Environment Program (UNEP), Kenya. The base maps used were hand drawn climate maps from FAO. All sources were re-registered to the FAO Soil Map of the world (1984) in Miller Oblated Stereographic projection by comparing known features on the basemap and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/ longitude degrees. The transformation was done by an unpublished algorithm (by US Geological Survey and ESRI) to create coverages for one-degree graticules. References: ESRI. Final Report UNEP/FAO world and Africa GIS data base (1984). ""Internal Publication from ESRI, FAO and UNEP ""FAO/UNESCO. Soil Map of the World (1977). Scale 1:5000000. UNESCO, Paris ""FAO. Map of Mean Annual Rainfall and general Climate zones for P/Pet for Africa. (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resources, Management and Conservation Service. FAO, Rome ""FAO. Maps of Mean annual Wind Velocity for Africa (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resourcs, Management and Conservation Service. FAO, Rome"" ""FAO. Maps of Number of Wet Days per Year (1983). Scale 1:5000000. Todor Boyadgiev, Soil Resourcs, Management and Conservation Service. FAO, Rome Source :FAO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Geographic (lat/lon) Type :Polygon and line Format :Arc/Info Export non-compressed Related Datasets :All UNEP/FAO/ESRI Data sets" proprietary
NBId0218_101 Africa Surface Hydrography, 1984 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848062-CEOS_EXTRA.umm_json The First-Third Order Stream Network member of the African Surface Hydrography data set is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP), as part of a project initiated by the same. The base map used was the FAO/UNESCO Soil Map of the World, scale 1:5000000 (1977) in Miller Oblated Stereographic projection. All sources were re-registered to the base map by comparing known features on the base map and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm by US Geological Survey and ESRI) to create coverage for one-degree graticules. References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1977). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World.(1977). Scale 1:5000000. UNESCO, Paris Source :FAO/UNESCO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Geographic (lat/lon) Feature type :line Related Data sets :All UNEP/FAO/ESRI Data sets, Outline of Africa OUTLINE3.E00, HYDRMAJLL, HYDRMINLL (Surface Hydrography), Hydrologic Basins Comment : No boundary (outline) for Africa. proprietary
+NBId0218_101 Africa Surface Hydrography, 1984 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848062-CEOS_EXTRA.umm_json The First-Third Order Stream Network member of the African Surface Hydrography data set is part of the UNEP/FAO/ESRI Database project that covers the entire world but focuses here on Africa. The maps were prepared by Environmental Systems Research Institute (ESRI), USA. Most data for the database were provided by the Land and Water Development Division of the Food and Agriculture Organization (FAO), Italy. The database was developed by the United Nations Environment Program (UNEP), as part of a project initiated by the same. The base map used was the FAO/UNESCO Soil Map of the World, scale 1:5000000 (1977) in Miller Oblated Stereographic projection. All sources were re-registered to the base map by comparing known features on the base map and the source maps. The digitizing was done with a spatial resolution of 0.002 inches. The maps were then transformed from inch coordinates to latitude/longitude degrees. The transformation was done using an unpublished algorithm by US Geological Survey and ESRI) to create coverage for one-degree graticules. References: ESRI. Final Report UNEP/FAO World and Africa GIS data base (1977). Internal Publication by ESRI, FAO and UNEP FAO. UNESCO Soil Map of the World.(1977). Scale 1:5000000. UNESCO, Paris Source :FAO/UNESCO Soil Map of the World. Scale 1:5000000 Publication Date :Dec 1984 Projection :Geographic (lat/lon) Feature type :line Related Data sets :All UNEP/FAO/ESRI Data sets, Outline of Africa OUTLINE3.E00, HYDRMAJLL, HYDRMINLL (Surface Hydrography), Hydrologic Basins Comment : No boundary (outline) for Africa. proprietary
NBId0220_101 Africa Rainfall and Maximum Temperature Measuring Stations (12 average monthly), 1989 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849335-CEOS_EXTRA.umm_json "The Africa Rain Measuring Stations data set, for monthly rainfall is part of the UNEP/ILRAD, now ILRI East Coast Fever (ECF) Database project. The point data was reformatted (Miller, scale 1:5 000 000) from CIAT tabular data based on 12 average monthly rainfall, evaporation, and minimum/maximum temperature. The data was used in the calculation of interpolated surfaces for rainfall and temperature distribution as the basis for modeling of climatic stress factors that constrain the distribution of ticks that transfer ECF. Vector Member The file is in Arc/Info Export format. The RAINSTNS point data represents rainfall measuring stations (12 average monthly) should go with file DATREAD.ME References: P. Lessard, R. L'Eppattenier, R.A. Norval, B.D. Perry, T.T. Dolan, K. Kundert, H. Croze, J.B. Walker, A.D. Irvin. Geographic Information System for studying the Epidemiology of East Coast Fever (Theileria parva) (1989). K. Kundert. Isolating East Coast Fever High risk Areas (1989). Arc/Info European User Conference, Rome, October 1989. CSIRO. Users guide to CLIMEX, A computer program for comparing climates in ecology. CSIRO Aust. Div Rep No.35, pp.-29 Source : CIAT tabular data Publication Date :Jan 1989 Projection :Miller Type :Point Format :Arc/Info Export non-compressed ""Related Data sets :East Coast Fever (100057-002-/66-002): ECFMAP, TICKSUIT, BUFFALO2, CATTLE, CATTYP, BUFCAT2, RAPOLY, RAPNTS, RDPNTS, RNPNTS and RZPNTS. Comment : No boundary (outline) for Africa" proprietary
NBId0220_101 Africa Rainfall and Maximum Temperature Measuring Stations (12 average monthly), 1989 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232849335-CEOS_EXTRA.umm_json "The Africa Rain Measuring Stations data set, for monthly rainfall is part of the UNEP/ILRAD, now ILRI East Coast Fever (ECF) Database project. The point data was reformatted (Miller, scale 1:5 000 000) from CIAT tabular data based on 12 average monthly rainfall, evaporation, and minimum/maximum temperature. The data was used in the calculation of interpolated surfaces for rainfall and temperature distribution as the basis for modeling of climatic stress factors that constrain the distribution of ticks that transfer ECF. Vector Member The file is in Arc/Info Export format. The RAINSTNS point data represents rainfall measuring stations (12 average monthly) should go with file DATREAD.ME References: P. Lessard, R. L'Eppattenier, R.A. Norval, B.D. Perry, T.T. Dolan, K. Kundert, H. Croze, J.B. Walker, A.D. Irvin. Geographic Information System for studying the Epidemiology of East Coast Fever (Theileria parva) (1989). K. Kundert. Isolating East Coast Fever High risk Areas (1989). Arc/Info European User Conference, Rome, October 1989. CSIRO. Users guide to CLIMEX, A computer program for comparing climates in ecology. CSIRO Aust. Div Rep No.35, pp.-29 Source : CIAT tabular data Publication Date :Jan 1989 Projection :Miller Type :Point Format :Arc/Info Export non-compressed ""Related Data sets :East Coast Fever (100057-002-/66-002): ECFMAP, TICKSUIT, BUFFALO2, CATTLE, CATTYP, BUFCAT2, RAPOLY, RAPNTS, RDPNTS, RNPNTS and RZPNTS. Comment : No boundary (outline) for Africa" proprietary
NBId0223_101 Africa Zobler Soils (Texture Classes, Slope, Phases), 1987 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848713-CEOS_EXTRA.umm_json "The Zobler soil datasets were developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The data set is part of the World Data Bank II and is part of ""The Global Change Data Base"". The World Data Bank II is part of a larger project called ""Global Ecosystems Database Project"". The project was a joint effort between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. The texture data is based on the FAO Soil Map of the World, and compiled into digital form by Zobler. Each matrix element represents the near-surface texture (upper 30 cm) of the dominant soil unit in a one-degree square cell of the earth's surface. The data conforms in location, and nominal classification (land, land-ice, water) to Matthew's vegetation data set. References: FAO. FAO-UNESCO Soil Map of the World (1974). Scale 1:5000000. UNESCO, Paris. Staub, Brad and Cynthia Rosenzweig. Global Digital Data Sets of Soil Type, Soil Texture, Surface Slope, and other properties: Documentation of Archived Tape Data. NASA Technical Memorandum No.100685. Henderson-Sellers, A., M.F. Wilson, G. Thomas, R.E. Dickinson. Current Global Land Surface Data Sets for Use in Climate-Related Studies. (1986). Matthews, E. Global vegetation and land use: New high resolution data bases for climate studies (1983). J. Clim. Appl. Meteor., vol.22, pp.474-487. Vegetation, Land-use and Seasonal Albedo Data Sets: Documentation of Archived Data Tape (1984). NASA Technical Memorandum. No.86107. Wilson. M.F. and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models (1985). Journal of Climatology, vol.5, pp.119-143. Source map :FAO/UNESCO Soil Map of the World Publication Date :1987 Projection :lat/lon Type :Raster Format :IDRISI" proprietary
NBId0223_101 Africa Zobler Soils (Texture Classes, Slope, Phases), 1987 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848713-CEOS_EXTRA.umm_json "The Zobler soil datasets were developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the U.S. National Geophysical Data Center (NGDC). The data set is part of the World Data Bank II and is part of ""The Global Change Data Base"". The World Data Bank II is part of a larger project called ""Global Ecosystems Database Project"". The project was a joint effort between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the U.S. Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The dataset is accompanied by an ASCII documentation file which contains information necessary for use of the dataset in a GIS or other software. The texture data is based on the FAO Soil Map of the World, and compiled into digital form by Zobler. Each matrix element represents the near-surface texture (upper 30 cm) of the dominant soil unit in a one-degree square cell of the earth's surface. The data conforms in location, and nominal classification (land, land-ice, water) to Matthew's vegetation data set. References: FAO. FAO-UNESCO Soil Map of the World (1974). Scale 1:5000000. UNESCO, Paris. Staub, Brad and Cynthia Rosenzweig. Global Digital Data Sets of Soil Type, Soil Texture, Surface Slope, and other properties: Documentation of Archived Tape Data. NASA Technical Memorandum No.100685. Henderson-Sellers, A., M.F. Wilson, G. Thomas, R.E. Dickinson. Current Global Land Surface Data Sets for Use in Climate-Related Studies. (1986). Matthews, E. Global vegetation and land use: New high resolution data bases for climate studies (1983). J. Clim. Appl. Meteor., vol.22, pp.474-487. Vegetation, Land-use and Seasonal Albedo Data Sets: Documentation of Archived Data Tape (1984). NASA Technical Memorandum. No.86107. Wilson. M.F. and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models (1985). Journal of Climatology, vol.5, pp.119-143. Source map :FAO/UNESCO Soil Map of the World Publication Date :1987 Projection :lat/lon Type :Raster Format :IDRISI" proprietary
NBId0233_101 Africa Population Density Model (Land Degradation Project), 1992 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848719-CEOS_EXTRA.umm_json The Africa Population density model represents ranges of population density of inhabitants per square kilometer. The estimated population densities are expressed on a regularly spaced latitude/longitude raster grid covering Africa with an approximate resolution of 10 km x 10 km at the Equator. The data set which is an assessment of one of the factors causing soil degradation, namely the spatial distribution and density of population. It was developed for the GEMS/UNITAR Africa Database and later used for GLASOD. The data sources include: 600 African towns and cities with figures standardized to 1988 values ( a combination of 479 cities from Birkbeck College and 363 cities in 51 African countries from PC Globe 3.0); UNEP/FAO population data from the 1984 Africa database; the Sierra Club Wilderness Area IUCN Protected Areas, used to delimit areas with extremely sparse populations and treated as having a density of less than one person per square kilometer. For methodology and further detail refer to references listed: UN Institute for Training & Research (UNITAR). GEMS/UNITAR Africa Database. Deichmann, U. and Lars Eklundh. Global Digital Datasets for Land Degradation Studies (1991), GRID Case Studies No.4. UNEP/GRID, Nairobi. UNEP. World Atlas of Desertification (1992). Edward Arnold: A division of Hodder and Stoughton, London. Projection :Geographic Type :Raster Format :IDRISI Related files :POPDENSL.E00, POPDENGR.E00 Associated files :POPDENS.DOC and POPDENS.PAL proprietary
NBId0233_101 Africa Population Density Model (Land Degradation Project), 1992 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848719-CEOS_EXTRA.umm_json The Africa Population density model represents ranges of population density of inhabitants per square kilometer. The estimated population densities are expressed on a regularly spaced latitude/longitude raster grid covering Africa with an approximate resolution of 10 km x 10 km at the Equator. The data set which is an assessment of one of the factors causing soil degradation, namely the spatial distribution and density of population. It was developed for the GEMS/UNITAR Africa Database and later used for GLASOD. The data sources include: 600 African towns and cities with figures standardized to 1988 values ( a combination of 479 cities from Birkbeck College and 363 cities in 51 African countries from PC Globe 3.0); UNEP/FAO population data from the 1984 Africa database; the Sierra Club Wilderness Area IUCN Protected Areas, used to delimit areas with extremely sparse populations and treated as having a density of less than one person per square kilometer. For methodology and further detail refer to references listed: UN Institute for Training & Research (UNITAR). GEMS/UNITAR Africa Database. Deichmann, U. and Lars Eklundh. Global Digital Datasets for Land Degradation Studies (1991), GRID Case Studies No.4. UNEP/GRID, Nairobi. UNEP. World Atlas of Desertification (1992). Edward Arnold: A division of Hodder and Stoughton, London. Projection :Geographic Type :Raster Format :IDRISI Related files :POPDENSL.E00, POPDENGR.E00 Associated files :POPDENS.DOC and POPDENS.PAL proprietary
-NBId0236_101 Africa Cattle Type (East Coast Fever Project), 1989 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847818-CEOS_EXTRA.umm_json The Cattle Type data set is part of the East Coast Fever (ECF) database covering sub-Saharan, East, and Central Africa. The ECF study determined both areas at risk and potential migration of the disease by cattle and a potential pool of infection for transmitting the disease to domestic cattle by buffalo which is the main wildlife host of the ECF. The study was carried out in Nairobi by United Nations Environment Program, Global Resource Information Database (UNEP/GRID) in collaboration with the International Laboratory for Research on Animal Diseases (ILRAD), now called International Livestock Research Institute (ILRI). proprietary
NBId0236_101 Africa Cattle Type (East Coast Fever Project), 1989 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847818-CEOS_EXTRA.umm_json The Cattle Type data set is part of the East Coast Fever (ECF) database covering sub-Saharan, East, and Central Africa. The ECF study determined both areas at risk and potential migration of the disease by cattle and a potential pool of infection for transmitting the disease to domestic cattle by buffalo which is the main wildlife host of the ECF. The study was carried out in Nairobi by United Nations Environment Program, Global Resource Information Database (UNEP/GRID) in collaboration with the International Laboratory for Research on Animal Diseases (ILRAD), now called International Livestock Research Institute (ILRI). proprietary
+NBId0236_101 Africa Cattle Type (East Coast Fever Project), 1989 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847818-CEOS_EXTRA.umm_json The Cattle Type data set is part of the East Coast Fever (ECF) database covering sub-Saharan, East, and Central Africa. The ECF study determined both areas at risk and potential migration of the disease by cattle and a potential pool of infection for transmitting the disease to domestic cattle by buffalo which is the main wildlife host of the ECF. The study was carried out in Nairobi by United Nations Environment Program, Global Resource Information Database (UNEP/GRID) in collaboration with the International Laboratory for Research on Animal Diseases (ILRAD), now called International Livestock Research Institute (ILRI). proprietary
NBId0248_101 Africa Wilson & Henderson-Sellers Secondary Vegetation Classes and Class Reliability, 1985 ALL STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848868-CEOS_EXTRA.umm_json "The Wilson and Henderson-Sellers Secondary Vegetation Classes and Class Reliability data sets are part of the ""Wilson Henderson-Sellers land cover and soils for global circulation modeling project "" and were developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the US National Geophysical Data Center (NGDC). The data sets are part of the World Data Bank II. This data Bank is provided in a Database on diskette called """"The Global Change Data Base"""". The Data Bank II is part of larger project called ""Global Ecosystems Database Project"". This is a cooperative effort between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the US Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The data sets are accompanied by an ASCII documentation file which contains information necessary for the use of the dataset in GIS or other software. References: Wilson, M.F./ and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models. Journal of Climatology, vol.5, pp.119-143. Source : Digitized from available sources: FAO/UNESCO Soil Map of the World Publication Date : 1985 Projection : lat/lon Type : Raster Format : IDRISI" proprietary
NBId0248_101 Africa Wilson & Henderson-Sellers Secondary Vegetation Classes and Class Reliability, 1985 CEOS_EXTRA STAC Catalog 1970-01-01 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232848868-CEOS_EXTRA.umm_json "The Wilson and Henderson-Sellers Secondary Vegetation Classes and Class Reliability data sets are part of the ""Wilson Henderson-Sellers land cover and soils for global circulation modeling project "" and were developed by the World Data Center-A (WDC-A) for Solid Earth Geophysics, operated by the US National Geophysical Data Center (NGDC). The data sets are part of the World Data Bank II. This data Bank is provided in a Database on diskette called """"The Global Change Data Base"""". The Data Bank II is part of larger project called ""Global Ecosystems Database Project"". This is a cooperative effort between the National Oceanic and Atmospheric Administration (NOAA), NGDC and the US Environmental Protection Agency (EPA). The National Center for Geographic Information and Analyses (NCGIA) in Santa Barbara, California joined the project to assist with training and evaluation. A nominal 10 arc-minute scale was chosen to provide compatibility with other scales and because this corresponds closely with the resolution of global AVHRR coverage. All data are provided in geographic (longitude/latitude) projection. The data sets are accompanied by an ASCII documentation file which contains information necessary for the use of the dataset in GIS or other software. References: Wilson, M.F./ and A. Henderson-Sellers. A global archive of land cover and soils data for use in general circulation climate models. Journal of Climatology, vol.5, pp.119-143. Source : Digitized from available sources: FAO/UNESCO Soil Map of the World Publication Date : 1985 Projection : lat/lon Type : Raster Format : IDRISI" proprietary
NBId0270_101 Desertification Atlas (Africa) Maps 1-17 CEOS_EXTRA STAC Catalog 1990-01-01 1992-12-30 -20, -35, 55, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2232847403-CEOS_EXTRA.umm_json INTRODUCTION Desertification/Land Degradation - The Background More than 6.1 billion hectares, over one third of the Earth's land area, is dryland. Nearly one billion hectares of this area are naturally hvperarid deserts, with very low biological productivity. The remaining 5.1 billion hectares are made up of arid, semiarid and dry subhumid areas, part of which have become desert since the dawn of civilization while other parts of these areas are still being degraded by human action today. These lands are the habitat and the source of livelihood for one quarter of the world's population. They are areas characterized by the persistent natural menace of recurrent drought, a natural hazard accentuated by imbalanced management of natural resources. Particularly acute drought years in the Sahelian region of Africa from 1968 to 1973, and their tragic effects on the peoples of the region, drew worldwide attention to the problems of human survival and development in drylands, particularly on desert margins. These problems have been addressed by the United Nations (UN) General Assembly, in conformity with the Charter of the United Nations. The UN General Assembly's Resolution 3202 (vi) of 1 May 1974 recommended that the international community undertake concrete and speedy measures to arrest desertification and assist the economic development of affected areas. The Economic and Social Council's Resolution 1878 (LVII) of 16 July 1974 requested all the concerned organizations of the UN system to pursue a broad attack on the drought problem. Decisions of the Governing Councils of the UN Development Programme (UNDP) and the UN Environment Programme (UNEP) emphasized the need for undertaking measures to check the spread of desert conditions. The General Assembly then decided, by Resolution 3337 (xxix) of 17 December 1974, to initiate concerted international action to combat desertification and, in order to provide an impetus to this action, to convene a UN Conference on Desertification (UNCOD), between 29 August and 9 September 1977 in Nairobi, Kenya, which would produce an effective, comprehensive and coordinated programme for solving the problem. For the purposes of this atlas, desertification/land degradation is defined as: Land degradation in arid, semiarid and dry subhumid areas resulting mainly from adverse human impact. proprietary
@@ -12120,14 +12120,14 @@ NBPalmer_Transect_and_Ross_Sea_Sulfur_Data_1 2005 NBPalmer sulfur data. Surface
NBPalmer_Transect_and_Ross_Sea_Sulfur_Data_1 2005 NBPalmer sulfur data. Surface transect (NZ to Ross Sea) and Ross Sea depth profiles and rates ALL STAC Catalog 2004-12-17 2005-11-30 -179.488, -77.642, -166.989, -49.014 https://cmr.earthdata.nasa.gov/search/concepts/C1214590838-SCIOPS.umm_json This data set contains concentration and rate data for the following sulfur compounds: dimethylsulfide (DMS), dimethylsulfoxide (DMSO) and dimethylsulfoniopropionate (DMSP). Data were obtained in a transect from New Zealand to the Ross Sea, Antarctica, and in the Ross Sea Polynya. Data were obtained during two research cruises to the Ross Sea aboard the RIV Nathaniel B. Palmer in December 2004 to January 2005 (NBP04-09) and in October to November 2005 (NBP05-08). A data set is also provide for biological data (bacterial biomass, bacterial productivity), CTD data and GUV irradiance data obtained during our Nathanial B. Palmer (NBP) cruises to the Ross Sea in 2004 and 2005 (NBP04-09 and NBP05-08). proprietary
NCALDAS_NOAH0125_D_2.0 NCA-LDAS Noah-3.3 Land Surface Model L4 Daily 0.125 x 0.125 degree V2.0 (NCALDAS_NOAH0125_D) at GES DISC GES_DISC STAC Catalog 1979-01-02 2016-12-31 -125, 25, -67, 53 https://cmr.earthdata.nasa.gov/search/concepts/C1454297282-GES_DISC.umm_json The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is a terrestrial water reanalysis in support of the United States Global Change Research Program's NCA activities. NCA-LDAS features high resolution, gridded, daily time series data products of terrestrial water and energy balance stores, states, and fluxes over the continental U.S., derived from land surface hydrologic modeling with multivariate assimilation of satellite Environmental Data Records (EDRs). The overall goal is to provide the highest quality terrestrial hydrology products that enable improved scientific understanding, adaptation, and management of water and related energy resources during a changing climate. An overview of NCA-LDAS and its capability for developing climate change indicators are provided in Jasinski et al. (2019). Details on the data assimilation used in NCA-LDAS are described in Kumar et al. (2019). Sample mean annual trends are provided in the NCA-LDAS V2.0 README document. This NCA-LDAS version 2.0 data product was simulated for the continental United States for the satellite era from January 1979 to December 2016. The core of NCA-LDAS is the multivariate assimilation of past and current satellite based data records within the Noah Version 3.3 land-surface model (LSM) at 1/8th degree resolution using NASA's Land Information System (LIS; Kumar et al. 2006) software framework during the Earth observing satellite era. The temporal resolution is daily. NCA-LDAS V001 data will no longer be available and have been superseded by V2.0. NCA-LDAS includes 42 variables including land-surface fluxes (e.g. precipitation, radiation and latent and sensible heat, etc.), stores (e.g. soil moisture and snow), states (e.g., surface temperature), and routing variables (e.g., runoff, streamflow, flooded area, etc.), driven by the atmospheric forcing data from North American Land Data Assimilation System Phase 2 (NLDAS-2; Xia et al., 2012). NCA-LDAS builds upon NLDAS through the addition of multivariate assimilation of earth observations such as soil moisture (Kumar et al, 2014), snow (Liu et al, 2015; Kumar et al, 2015a) and irrigation (Ozdagon et al, 2010; Kumar et al, 2015b). The EDRs that have been assimilated into the NCA-LDAS include soil moisture and snow depth from principally microwave sensors including SMMR, SSM/I, AMSR-E, ASCAT, AMSR-2, SMOS, and SMAP, irrigation intensity estimates from MODIS, and snow covered area from MODIS and from the multisensor IMS snow product. proprietary
NCALDAS_NOAH0125_Trends_2.0 NCA-LDAS Noah-3.3 Land Surface Model L4 Trends 0.125 x 0.125 degree V2.0 (NCALDAS_NOAH0125_Trends) at GES DISC GES_DISC STAC Catalog 1979-10-01 2015-09-30 -125, 25, -67, 53 https://cmr.earthdata.nasa.gov/search/concepts/C1646132439-GES_DISC.umm_json The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is a terrestrial water reanalysis in support of the United States Global Change Research Program's NCA activities. NCA-LDAS features high resolution, gridded, daily time series data products of terrestrial water and energy balance stores, states, and fluxes over the continental U.S., derived from land surface hydrologic modeling with multivariate assimilation of satellite Environmental Data Records (EDRs). The overall goal is to provide the highest quality terrestrial hydrology products that enable improved scientific understanding, adaptation, and management of water and related energy resources during a changing climate. This dataset consists of a suite of historical trends in terrestrial hydrology over the conterminous United States estimated for the water years of 1980-2015 using the NCA-LDAS daily reanalysis. NCA-LDAS provides gridded daily outputs from the uncoupled Noah version 3.3 land surface model (LSM) at 1/8th degree resolution forced with NLDAS-2 meteorology (Xia et al., 2012), rescaled Climate Prediction Center precipitation, and assimilated satellite-based soil moisture, snow depth, and irrigation products (Jasinski et al., 2019; Kumar et al., 2019). Trends in annual hydrologic indicators are reported using the nonparametric Mann-Kendall test at p < 0.1 significance. An additional precipitation trend field (annual total), with no significance test applied, is included for comparison purposes. Collectively, these fields represent the bulk of the results presented in Jasinski et al. (2019). proprietary
-NCAR_DS474.0 AARI Russian North Polar Drifting Station Data, from NSIDC ALL STAC Catalog 1937-05-01 1991-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214056415-SCIOPS.umm_json This dataset consists of 31 Russian north polar drifting stations which took observations of surface variables for the periods 1937-1938 and 1950-1991. We received the latest version of this data from the Arctic and Antarctic Research Institute (AARI) via the National Snow and Ice Data Center (NSIDC). proprietary
NCAR_DS474.0 AARI Russian North Polar Drifting Station Data, from NSIDC SCIOPS STAC Catalog 1937-05-01 1991-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214056415-SCIOPS.umm_json This dataset consists of 31 Russian north polar drifting stations which took observations of surface variables for the periods 1937-1938 and 1950-1991. We received the latest version of this data from the Arctic and Antarctic Research Institute (AARI) via the National Snow and Ice Data Center (NSIDC). proprietary
-NCAR_DS510.5 A Quality-Controlled Dataset for Long-Term U.S. Snowfall Trends SCIOPS STAC Catalog 1890-01-01 2007-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214110939-SCIOPS.umm_json NCDC's U.S. Cooperative Summary of Data (DSI3200) dataset was screened for stations with long continuous observations for use in assessing 20th-century U.S. snowfall trends. The result is a subset of 424 stations with quality-controlled snowfall, precipitation, and temperature data for snow-season months (October through May). Most of the stations have observations that begin prior to the winter of 1930-31, making for station periods of longer than 77 winters. Several stations have data as far back as the 1890s. proprietary
+NCAR_DS474.0 AARI Russian North Polar Drifting Station Data, from NSIDC ALL STAC Catalog 1937-05-01 1991-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214056415-SCIOPS.umm_json This dataset consists of 31 Russian north polar drifting stations which took observations of surface variables for the periods 1937-1938 and 1950-1991. We received the latest version of this data from the Arctic and Antarctic Research Institute (AARI) via the National Snow and Ice Data Center (NSIDC). proprietary
NCAR_DS510.5 A Quality-Controlled Dataset for Long-Term U.S. Snowfall Trends ALL STAC Catalog 1890-01-01 2007-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214110939-SCIOPS.umm_json NCDC's U.S. Cooperative Summary of Data (DSI3200) dataset was screened for stations with long continuous observations for use in assessing 20th-century U.S. snowfall trends. The result is a subset of 424 stations with quality-controlled snowfall, precipitation, and temperature data for snow-season months (October through May). Most of the stations have observations that begin prior to the winter of 1930-31, making for station periods of longer than 77 winters. Several stations have data as far back as the 1890s. proprietary
-NCAR_DS744.7 ADEOS Scatterometer Winds, Level 2B SCIOPS STAC Catalog 2002-06-04 2002-06-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214055329-SCIOPS.umm_json Sea surface wind estimated by scatterometer instruments on the ADEOS satellite. JPL PO.DAAC [http://podaac.jpl.nasa.gov/] has initiated reprocessing of all ADEOS and QuikSCAT data with superior algorithms for retrievals in high wind speed and light rain areas. This reprocessing could affect this dataset. proprietary
+NCAR_DS510.5 A Quality-Controlled Dataset for Long-Term U.S. Snowfall Trends SCIOPS STAC Catalog 1890-01-01 2007-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214110939-SCIOPS.umm_json NCDC's U.S. Cooperative Summary of Data (DSI3200) dataset was screened for stations with long continuous observations for use in assessing 20th-century U.S. snowfall trends. The result is a subset of 424 stations with quality-controlled snowfall, precipitation, and temperature data for snow-season months (October through May). Most of the stations have observations that begin prior to the winter of 1930-31, making for station periods of longer than 77 winters. Several stations have data as far back as the 1890s. proprietary
NCAR_DS744.7 ADEOS Scatterometer Winds, Level 2B ALL STAC Catalog 2002-06-04 2002-06-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214055329-SCIOPS.umm_json Sea surface wind estimated by scatterometer instruments on the ADEOS satellite. JPL PO.DAAC [http://podaac.jpl.nasa.gov/] has initiated reprocessing of all ADEOS and QuikSCAT data with superior algorithms for retrievals in high wind speed and light rain areas. This reprocessing could affect this dataset. proprietary
-NCAR_DS871.0 ADAPTE: Minimum and Maximum Temperature and Relative Humidity for Latin American Cities Data SCIOPS STAC Catalog 2000-01-01 2006-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214110979-SCIOPS.umm_json Temperature data classified as maximum, mean, and minimum temperature and relative humidity measures from the meteorological station located at the regional airport in Bogota and Buenos Aries, called the National Service of Hydrology and Meteorology. Mexico data was collected from the National Polytechnic Institute of Mexico and National Meteorological System. In Santiago, Chile weather data was provided by the air pollution monitoring network with stations across the city, the REDCAM2 (Red de Monitoreo Automatica de la Calidad del Aire Metropolitana) Automatic Monitoring Network of Metropolitan Air Quality. The data from these stations were averaged to obtain temperature values for the Gran Santiago region. Daily temperature and relative humidity readings were made by automatic-recording instruments. proprietary
+NCAR_DS744.7 ADEOS Scatterometer Winds, Level 2B SCIOPS STAC Catalog 2002-06-04 2002-06-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214055329-SCIOPS.umm_json Sea surface wind estimated by scatterometer instruments on the ADEOS satellite. JPL PO.DAAC [http://podaac.jpl.nasa.gov/] has initiated reprocessing of all ADEOS and QuikSCAT data with superior algorithms for retrievals in high wind speed and light rain areas. This reprocessing could affect this dataset. proprietary
NCAR_DS871.0 ADAPTE: Minimum and Maximum Temperature and Relative Humidity for Latin American Cities Data ALL STAC Catalog 2000-01-01 2006-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214110979-SCIOPS.umm_json Temperature data classified as maximum, mean, and minimum temperature and relative humidity measures from the meteorological station located at the regional airport in Bogota and Buenos Aries, called the National Service of Hydrology and Meteorology. Mexico data was collected from the National Polytechnic Institute of Mexico and National Meteorological System. In Santiago, Chile weather data was provided by the air pollution monitoring network with stations across the city, the REDCAM2 (Red de Monitoreo Automatica de la Calidad del Aire Metropolitana) Automatic Monitoring Network of Metropolitan Air Quality. The data from these stations were averaged to obtain temperature values for the Gran Santiago region. Daily temperature and relative humidity readings were made by automatic-recording instruments. proprietary
+NCAR_DS871.0 ADAPTE: Minimum and Maximum Temperature and Relative Humidity for Latin American Cities Data SCIOPS STAC Catalog 2000-01-01 2006-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214110979-SCIOPS.umm_json Temperature data classified as maximum, mean, and minimum temperature and relative humidity measures from the meteorological station located at the regional airport in Bogota and Buenos Aries, called the National Service of Hydrology and Meteorology. Mexico data was collected from the National Polytechnic Institute of Mexico and National Meteorological System. In Santiago, Chile weather data was provided by the air pollution monitoring network with stations across the city, the REDCAM2 (Red de Monitoreo Automatica de la Calidad del Aire Metropolitana) Automatic Monitoring Network of Metropolitan Air Quality. The data from these stations were averaged to obtain temperature values for the Gran Santiago region. Daily temperature and relative humidity readings were made by automatic-recording instruments. proprietary
NCEI DSI 1167_01_Not Applicable Active Marine Station Metadata NOAA_NCEI STAC Catalog 2012-05-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2107093639-NOAA_NCEI.umm_json The Active Marine Station Metadata is a daily metadata report for active marine bouy and C-MAN (Coastal Marine Automated Network) platforms from the National Data Buoy Center (NDBC). Metadata includes the station id, latitude/longitude (resolution to thousandths of a degree), the station name, the station owner, the program the station is associated with (e.g., TAO, NDBC, tsunami, NOS, etc.), station type (e.g., buoy, fixed, oil rig, etc.), notification if the station observes meteorology, currents, and water quality (signified by 'y' for yes and 'n' for no). If there is a 'y' associated with one of these tags, then the station has reported data in that category within the last 8 hours (or 24 hours for DART stations--Deep-Ocean Assessment Reporting of Tsunamis). If there is an 'n', data has not been received within those times. Stations are removed from the list when they are dismantled. The metadata information is written to a daily XML-formatted file. proprietary
NCEI DSI 1167_01_Not Applicable Active Marine Station Metadata ALL STAC Catalog 2012-05-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2107093639-NOAA_NCEI.umm_json The Active Marine Station Metadata is a daily metadata report for active marine bouy and C-MAN (Coastal Marine Automated Network) platforms from the National Data Buoy Center (NDBC). Metadata includes the station id, latitude/longitude (resolution to thousandths of a degree), the station name, the station owner, the program the station is associated with (e.g., TAO, NDBC, tsunami, NOS, etc.), station type (e.g., buoy, fixed, oil rig, etc.), notification if the station observes meteorology, currents, and water quality (signified by 'y' for yes and 'n' for no). If there is a 'y' associated with one of these tags, then the station has reported data in that category within the last 8 hours (or 24 hours for DART stations--Deep-Ocean Assessment Reporting of Tsunamis). If there is an 'n', data has not been received within those times. Stations are removed from the list when they are dismantled. The metadata information is written to a daily XML-formatted file. proprietary
NCEI DSI 2001_01_Not Applicable Climate Forecast System Version 2 (CFSv2) Operational Forecasts NOAA_NCEI STAC Catalog 2011-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2107093673-NOAA_NCEI.umm_json The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the interaction between the Earth's oceans, land and atmosphere. The four-times-daily, 9-month control runs, consist of all 6-hourly forecasts, and the monthly means and variable time-series (all variables). The CFSv2 outputs include: 2-D Energetics (EGY); 2-D Surface and Radiative Fluxes (FLX); 3-D Pressure Level Data (PGB); 3-D Isentropic Level Data (IPV); 3-D Ocean Data (OCN); Low-resolution output (GRBLOW); Dumps (DMP); and High- and Low-resolution Initial Conditions (HIC and LIC). The monthly CDAS variable timeseries includes all variables. The CFSv2 period of record begins on April 1, 2011 and continues onward. CFS output is in GRIB-2 file format. proprietary
@@ -12219,12 +12219,12 @@ NEMSN5L2_001 NEMS/Nimbus-5 Level 2 Output Data V001 (NEMSN5L2) at GES DISC GES_D
NES-LTER_0 Northeast U.S. Shelf (NES), Long-Term Ecological Research (LTER) OB_DAAC STAC Catalog 2018-01-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2208430341-OB_DAAC.umm_json The Northeast U.S. Shelf (NES) Long-Term Ecological Research (LTER) project integrates observations, experiments, and models to understand and predict how planktonic food webs are changing, and how those changes impact the productivity of higher trophic levels. The NES-LTER is co-located with the Northeast U.S. Continental Shelf Large Marine Ecosystem, spanning the Middle Atlantic Bight and Gulf of Maine. Our focal cross-shelf transect extends about 150 km southward from Martha's Vineyard, MA, to just beyond the shelf break. proprietary
NESP_2015_SRW 2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2015-02-09 2015-07-09 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1381760732-SCIOPS.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in September 2015. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2015. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the ?western? Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the ?eastern? subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected ?western? count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. proprietary
NESP_2015_SRW 2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia SCIOPS STAC Catalog 2015-02-09 2015-07-09 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1381760732-SCIOPS.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in September 2015. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2015. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the ?western? Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the ?eastern? subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected ?western? count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. proprietary
-NESP_2015_SRW_3 2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2015-02-09 2015-07-09 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1333031622-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in September 2015. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2015. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. A data update was provided in August, 2020 to correct some incorrectly given longitude values. proprietary
NESP_2015_SRW_3 2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia AU_AADC STAC Catalog 2015-02-09 2015-07-09 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1333031622-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in September 2015. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2015. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. A data update was provided in August, 2020 to correct some incorrectly given longitude values. proprietary
+NESP_2015_SRW_3 2015 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2015-02-09 2015-07-09 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1333031622-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in September 2015. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2015. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. A data update was provided in August, 2020 to correct some incorrectly given longitude values. proprietary
NESP_2016_SRW_3 2016 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2016-08-24 2016-08-29 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1412710076-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2016. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2016. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. A data update was provided in August, 2020 to correct some incorrectly given longitude values. proprietary
NESP_2016_SRW_3 2016 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia AU_AADC STAC Catalog 2016-08-24 2016-08-29 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1412710076-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2016. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 23-year period 1993-2016. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. A data update was provided in August, 2020 to correct some incorrectly given longitude values. proprietary
-NESP_2017_SRW_1 2017 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia AU_AADC STAC Catalog 2017-08-23 2017-08-27 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1968847804-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2017. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 25-year period 1993-2017. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future proprietary
NESP_2017_SRW_1 2017 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2017-08-23 2017-08-27 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1968847804-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2017. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 25-year period 1993-2017. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future proprietary
+NESP_2017_SRW_1 2017 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia AU_AADC STAC Catalog 2017-08-23 2017-08-27 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1968847804-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2017. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 25-year period 1993-2017. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future proprietary
NESP_2018_SRW_1 2018 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2018-08-18 2018-08-23 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1968847807-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2018. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 26-year period 1993-2018. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. proprietary
NESP_2018_SRW_1 2018 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia AU_AADC STAC Catalog 2018-08-18 2018-08-23 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1968847807-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2018. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 26-year period 1993-2018. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. proprietary
NESP_2019_SRW_1 2019 Aerial survey data of southern right whales (Eubalaena australis) off southern Australia ALL STAC Catalog 2019-08-18 2019-08-24 113.02734, -36.59789, 138.69141, -29.993 https://cmr.earthdata.nasa.gov/search/concepts/C1968847810-AU_AADC.umm_json These aerial survey data of southern right whales (Eubalaena australis) off southern Australia were collected in August 2019. Such annual flights in winter/spring between Cape Leeuwin (Western Australia) and Ceduna (South Australia) have now been conducted over a 27-year period 1993-2019. These surveys have provided evidence of a population trend of around 6% per year, and a current (at 2014) population size of approximately 2300 of what has been regarded as the 'western' Australian right whale subpopulation. With estimated population size in the low thousands, it is presumed to be still well below carrying capacity. No trend information is available for the 'eastern' subpopulation of animals occurring around the remainder of the southern Australian Coast, to at least as far as Sydney, New South Wales and the populations size is relatively small, probably in the low hundreds. A lower than expected 'western' count in 2015 gives weak evidence that the growth rate may be starting to show signs of slowing, though an exponential increase remains the best description of the data. If the low 2015 count is anomalous, future counts may be expected to show an exponential increase, but if it is not, modelling growth as other than simple exponential may be useful to explore in future. proprietary
@@ -12235,18 +12235,18 @@ NEWS_WEB_MCLIM_1.0 NASA Energy and Water cycle Study (NEWS) Monthly Climatology
NEX-DCP30_1 Downscaled 30 Arc-Second CMIP5 Climate Projections for Studies of Climate Change Impacts in the United States NCCS STAC Catalog 1950-01-01 2099-12-31 -125.0208333, 24.0625, -66.4791667, 49.9375 https://cmr.earthdata.nasa.gov/search/concepts/C1542175061-NCCS.umm_json This NASA dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future climate patterns and climate impacts at the scale of individual neighborhoods and communities. This dataset is intended for use in scientific research only, and use of this dataset for other purposes, such as commercial applications, and engineering or design studies is not recommended without consultation with a qualified expert. Community feedback to improve and validate the dataset for modeling usage is appreciated. Email comments to bridget@climateanalyticsgroup.org. Dataset File Name: NASA Earth Exchange (NEX) Downscaled Climate Projections (NEXDCP30), https://portal.nccs.nasa.gov/portal_home/published/NEX.html proprietary
NEX-GDDP_1 NASA Earth Exchange Global Daily Downscaled Projections NCCS STAC Catalog 1950-01-01 2100-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1374483929-NCCS.umm_json The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds. Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). proprietary
NFRDI_0 National Fisheries Research and Development Institute (NFRDI) OB_DAAC STAC Catalog 2000-02-22 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360518-OB_DAAC.umm_json Measurements made by the National Fisheries Research and Development Institute (NFRDI), Ministry of Oceans and Fisheries for Korea, in the East China Sea in 2000. proprietary
-"NGA178
- _1.0" Advanced Terrestrial Simulator SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388528-SCIOPS.umm_json The Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology. Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more. proprietary
"NGA178
_1.0" Advanced Terrestrial Simulator ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388528-SCIOPS.umm_json The Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology. Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more. proprietary
-"NGA183
- _1.0" Active Layer Hydrology in an Arctic Tundra Ecosystem: Quantifying Water Sources and Cycling Using Water Stable Isotopes: Supporting Data SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388529-SCIOPS.umm_json Data include results from water isotope analyses (one *.csv file) for samples collected in Utqiagvik (Barrow), Alaska during August and September 2012. Samples were from surface and soil pore waters from 17 drainages that could be interlake (basins with polygonal terrain), different-aged drain thaw lake basins (young, medium, old, or ancient), or a combination of different aged basins. Samples taken in different drainage flow types at three different depths at each location in and around the Barrow Environmental Observatory. Precipitation stable isotope data are also included (added in October 2019 with no changes to previously released data). This dataset used in Throckmorton, et.al. 2016.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM). proprietary
+"NGA178
+ _1.0" Advanced Terrestrial Simulator SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388528-SCIOPS.umm_json The Advanced Terrestrial Simulator (formerly sometimes known as the Arctic Terrestrial Simulator) is a code for solving ecosystem-based, integrated, distributed hydrology. Capabilities are largely based on solving various forms of Richards equation coupled to a surface flow equation, along with the needed sources and sinks for ecosystem and climate models. This can (but need not) include thermal processes (especially ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and much more. proprietary
"NGA183
_1.0" Active Layer Hydrology in an Arctic Tundra Ecosystem: Quantifying Water Sources and Cycling Using Water Stable Isotopes: Supporting Data ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388529-SCIOPS.umm_json Data include results from water isotope analyses (one *.csv file) for samples collected in Utqiagvik (Barrow), Alaska during August and September 2012. Samples were from surface and soil pore waters from 17 drainages that could be interlake (basins with polygonal terrain), different-aged drain thaw lake basins (young, medium, old, or ancient), or a combination of different aged basins. Samples taken in different drainage flow types at three different depths at each location in and around the Barrow Environmental Observatory. Precipitation stable isotope data are also included (added in October 2019 with no changes to previously released data). This dataset used in Throckmorton, et.al. 2016.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM). proprietary
-"NGA232
- _1.0" A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388919-SCIOPS.umm_json Remote sensing data collected from Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform – the Osprey – operated by the Terrestrial Ecosystem Science and Technology (TEST) group. Data was collected from a single flight over the Kougarok hillslope site on 26 July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as surface reflectance at 1nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model. Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM). proprietary
+"NGA183
+ _1.0" Active Layer Hydrology in an Arctic Tundra Ecosystem: Quantifying Water Sources and Cycling Using Water Stable Isotopes: Supporting Data SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388529-SCIOPS.umm_json Data include results from water isotope analyses (one *.csv file) for samples collected in Utqiagvik (Barrow), Alaska during August and September 2012. Samples were from surface and soil pore waters from 17 drainages that could be interlake (basins with polygonal terrain), different-aged drain thaw lake basins (young, medium, old, or ancient), or a combination of different aged basins. Samples taken in different drainage flow types at three different depths at each location in and around the Barrow Environmental Observatory. Precipitation stable isotope data are also included (added in October 2019 with no changes to previously released data). This dataset used in Throckmorton, et.al. 2016.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM). proprietary
"NGA232
_1.0" A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388919-SCIOPS.umm_json Remote sensing data collected from Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform – the Osprey – operated by the Terrestrial Ecosystem Science and Technology (TEST) group. Data was collected from a single flight over the Kougarok hillslope site on 26 July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as surface reflectance at 1nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model. Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM). proprietary
+"NGA232
+ _1.0" A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra: Supporting Data SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2108388919-SCIOPS.umm_json Remote sensing data collected from Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform – the Osprey – operated by the Terrestrial Ecosystem Science and Technology (TEST) group. Data was collected from a single flight over the Kougarok hillslope site on 26 July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as surface reflectance at 1nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. Derived image products include ortho-mosaiced RGB and TIR images, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, digital terrain model (DTM), and a canopy height model. Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM). proprietary
NGLI_Lake_Bourne_0 Northern Gulf Littoral Initiative (NGLI) measurements in Lake Bourne, Louisiana OB_DAAC STAC Catalog 2001-04-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360520-OB_DAAC.umm_json Measurements made under the Northern Gulf Littoral Initiative (NGLI) in the Gulf of Mexico near the Mississippi River outflow region in 2001. proprietary
NHAP National High Altitude Photography USGS_LTA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566467-USGS_LTA.umm_json The National High Altitude Photography (NHAP) program, which was operated from 1980 - 1989, was coordinated by the U.S. Geological Survey as an interagency project to eliminate duplicate photography in various Government programs. The aim of the program was to cover the 48 conterminous states of the USA over a 5-year span. In the NHAP program, black-and-white and color-infrared aerial photographs were obtained on 9-inch film from an altitude of 40,000 feet above mean terrain elevation and are centered over USGS 7.5-minute quadrangles. The color-infrared photographs are at a scale of 1:58,000 (1 inch equals about .9 miles) and the black-and-white photographs are at a scale of 1:80,000 (1 inch equals about 1.26 miles). proprietary
NHICEM_001 Northern Hemisphere Ice Cover Monthly Statistics at 1 Degree Resolution V001 (NHICEM) at GES DISC GES_DISC STAC Catalog 2000-01-01 2014-11-30 -180, 0, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239898024-GES_DISC.umm_json This product is monthly Ice Cover Statistics. The dataset was prepared by Dr. Peter Romanov at Cooperative Institute for Climate Studies(CICS) of the University of Maryland for Northern Eurasia Earth Science Partnership Initiative (NEESPI) program. The product includes the monthly ice statistics (frequency of occurrence) for Northern Hemisphere at 1x1 degree spatial resolution. The dataset covers the time period starting January 2000 to November 2014. The data was derived from daily ice cover charts produced at NOAA/NESDIS within Interactive Multisensor Ice Mapping System (IMS). proprietary
@@ -12256,10 +12256,10 @@ NIH-NSF_Lake_Erie_0 Lake Erie optical measurements OB_DAAC STAC Catalog 2013-08-
NIMBUS7_ERB_Ch10C_TSI_NAT_1 Nimbus-7 Total Solar Irradiance Data in Native Format LARC_ASDC STAC Catalog 1978-11-16 1993-12-13 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1373953856-LARC_ASDC.umm_json The NIMBUS7_ERB_Ch10C_TSI_NAT data set is the Nimbus-7 Channel 10C (Ch10C) Total Solar Irradiance (TSI) aboard the Earth Radiation Budget (ERB) satellite Data in Native (NAT) format.The Nimbus 7 research-and-development satellite served as a stabilized, earth-oriented platform for the testing of advanced systems for sensing and collecting data in the pollution, oceanographic and meteorological disciplines. The polar-orbiting spacecraft consisted of three major structures: (1) a hollow torus-shaped sensor mount, (2) solar paddles, and (3) a control housing unit that was connected to the sensor mount by a tripod truss structure. proprietary
NIMBUS7_ERB_SEFDT_1 Nimbus-7 Solar and Earth Flux Data in Native Binary Format LARC_ASDC STAC Catalog 1978-01-01 1993-12-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C4211374-LARC_ASDC.umm_json The NIMBUS7_ERB_SEFDT data set is the Solar and Earth Flux Data Tape (SEFDT) generated from Nimbus-7 Earth Radiation Budget (ERB) instrument data. The main purpose of the SEFDT program was to produce a tape containing the solar data and the wide angle terrestrial flux data only. On Nimbus-7, the ERB had two total irradiance channels, Channel 3 and Channel 10C.The Nimbus 7 research-and-development satellite served as a stabilized, earth-oriented platform for the testing of advanced systems for sensing and collecting data in the pollution, oceanographic and meteorological disciplines. The polar-orbiting spacecraft consisted of three major structures: (1) a hollow torus-shaped sensor mount, (2) solar paddles, and (3) a control housing unit that was connected to the sensor mount by a tripod truss structure. proprietary
NIMBUS7_NFOV_MLCE_1 Nimbus-7 Narrow Field of View (NFOV) Maximum Likelihood Cloud Estimation (MLCE) Data in Native Format LARC_ASDC STAC Catalog 1979-05-01 1980-05-31 180, -90, -180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1328028152-LARC_ASDC.umm_json NIMBUS7_NFOV_MLCE data are Nimbus 7 Narrow Field of View (NFOV) Maximum Likelihood Cloud Estimation (MLCE) Data in Native Format.The NIMBUS7_NFOV_MLCE data set uses the Nimbus-7 measurements and the MLCE algorithm for better regional and temporal resolution. The Earth Radiation Budget (ERB) parameters, derived from the Nimbus-7 scanner measurements, were rederived in 1990 using a Maximum Likelihood Cloud Estimation (MLCE) algorithm similar, but not identical, to the Earth Radiation Budget Experiment (ERBE) algorithm. Daily and monthly means are presented on two commensurate equal area world grids: (167 km by 167 km) and (500 km by 500 km). The MLCE procedure also yielded a rough estimate of the regional cloud cover.The scanner took measurements from November 16, 1978 through June 20, 1980; however, only 13 months (May 1979 through May 1980) of data sampling were reprocessed using the Sorting into Angular Bins and MLCE algorithms. There was poorer temporal sampling during the first five months of the experiment.The Nimbus 7 research-and-development satellite served as a stabilized, earth-oriented platform for the testing of advanced systems for sensing and collecting data in the pollution, oceanographic and meteorological disciplines. The polar-orbiting spacecraft consisted of three major structures: (1) a hollow torus-shaped sensor mount, (2) solar paddles, and (3) a control housing unit that was connected to the sensor mount by a tripod truss structure. proprietary
-NIPR-GEO-1 Airborne Magnetic Survey Data in Antarctica by JARE SCIOPS STAC Catalog 1980-01-01 20, -72, 60, -68 https://cmr.earthdata.nasa.gov/search/concepts/C1214584952-SCIOPS.umm_json The digital data which can be supplied are total intensity raw data, and not reduced to magnetic anomaly data. However, the user can analyze the data by him/herself with the Data Reports. The data processing is still being made at NIPR. proprietary
NIPR-GEO-1 Airborne Magnetic Survey Data in Antarctica by JARE ALL STAC Catalog 1980-01-01 20, -72, 60, -68 https://cmr.earthdata.nasa.gov/search/concepts/C1214584952-SCIOPS.umm_json The digital data which can be supplied are total intensity raw data, and not reduced to magnetic anomaly data. However, the user can analyze the data by him/herself with the Data Reports. The data processing is still being made at NIPR. proprietary
-NIPR_GEO_SEIS_SEAL_MIZUHO Acitve source digital seismic waveforms by SEAL exploration ALL STAC Catalog 2000-01-01 38, -70, 45, -68 https://cmr.earthdata.nasa.gov/search/concepts/C1214590137-SCIOPS.umm_json "Deep Seismic Surveys (DSS) were carried out in 2000 and 2002 austral summers on the continental ice-sheet of the Lutzow-Holm Complex (LHC), Eastern Dronning Maud Land, East Antarctica . The surveys were carried out as a program of the ""Structure and Evolution of the East Antarctic Lithosphere (SEAL)"" by JARE. Detailed crustal velocity models and reflection sections were obtained in the LHC. In both surveys, more than 170 plant-type 2 Hz geophones were installed on the continental ice-sheet totally 190 km in length. A total of 8,300kg dynamite charge at the fourteen sites on the Mizuho Plateau gave information concerning the deep structure of a continental margin of the LHC. Archived digital waveforms are available from Library Server of Polar Data Center of NIPR." proprietary
+NIPR-GEO-1 Airborne Magnetic Survey Data in Antarctica by JARE SCIOPS STAC Catalog 1980-01-01 20, -72, 60, -68 https://cmr.earthdata.nasa.gov/search/concepts/C1214584952-SCIOPS.umm_json The digital data which can be supplied are total intensity raw data, and not reduced to magnetic anomaly data. However, the user can analyze the data by him/herself with the Data Reports. The data processing is still being made at NIPR. proprietary
NIPR_GEO_SEIS_SEAL_MIZUHO Acitve source digital seismic waveforms by SEAL exploration SCIOPS STAC Catalog 2000-01-01 38, -70, 45, -68 https://cmr.earthdata.nasa.gov/search/concepts/C1214590137-SCIOPS.umm_json "Deep Seismic Surveys (DSS) were carried out in 2000 and 2002 austral summers on the continental ice-sheet of the Lutzow-Holm Complex (LHC), Eastern Dronning Maud Land, East Antarctica . The surveys were carried out as a program of the ""Structure and Evolution of the East Antarctic Lithosphere (SEAL)"" by JARE. Detailed crustal velocity models and reflection sections were obtained in the LHC. In both surveys, more than 170 plant-type 2 Hz geophones were installed on the continental ice-sheet totally 190 km in length. A total of 8,300kg dynamite charge at the fourteen sites on the Mizuho Plateau gave information concerning the deep structure of a continental margin of the LHC. Archived digital waveforms are available from Library Server of Polar Data Center of NIPR." proprietary
+NIPR_GEO_SEIS_SEAL_MIZUHO Acitve source digital seismic waveforms by SEAL exploration ALL STAC Catalog 2000-01-01 38, -70, 45, -68 https://cmr.earthdata.nasa.gov/search/concepts/C1214590137-SCIOPS.umm_json "Deep Seismic Surveys (DSS) were carried out in 2000 and 2002 austral summers on the continental ice-sheet of the Lutzow-Holm Complex (LHC), Eastern Dronning Maud Land, East Antarctica . The surveys were carried out as a program of the ""Structure and Evolution of the East Antarctic Lithosphere (SEAL)"" by JARE. Detailed crustal velocity models and reflection sections were obtained in the LHC. In both surveys, more than 170 plant-type 2 Hz geophones were installed on the continental ice-sheet totally 190 km in length. A total of 8,300kg dynamite charge at the fourteen sites on the Mizuho Plateau gave information concerning the deep structure of a continental margin of the LHC. Archived digital waveforms are available from Library Server of Polar Data Center of NIPR." proprietary
NIPR_PMG_AIR_ARCHIVE_ANT Air samples for archive SCIOPS STAC Catalog 1995-02-01 2009-01-31 39.5, -69, 39.5, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214590122-SCIOPS.umm_json Air samples for archive proprietary
NIPR_PMG_AIR_ARCHIVE_ANT Air samples for archive ALL STAC Catalog 1995-02-01 2009-01-31 39.5, -69, 39.5, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214590122-SCIOPS.umm_json Air samples for archive proprietary
NISE_2 Near-Real-Time SSM/I EASE-Grid Daily Global Ice Concentration and Snow Extent V002 NSIDC_ECS STAC Catalog 1995-05-04 2009-09-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1647528934-NSIDC_ECS.umm_json "The Near-real-time Ice and Snow Extent (NISE) data set provides daily, global maps of sea ice concentrations and snow extent. These data are not suitable for time series, anomalies, or trends analyses. They are meant to provide a best estimate of current ice and snow conditions based on information and algorithms available at the time the data are acquired. Near-real-time products are not intended for operational use in assessing sea ice conditions for navigation. This NISE Version 2 product contains SSMIS-derived sea ice concentrations and snow extents derived from the Special Sensor Microwave Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F13 satellite. For DMSP-F16, SSMIS-derived data, see NISE Version 3. For DMSP-F17, SSMIS-derived data, see NISE Version 4. For DMSP-F18, SSMIS-derived data, see NISE Version 5." proprietary
@@ -12439,8 +12439,8 @@ NSF-ANT-1142074-penguins_1.0 Adelie penguin satellite position and dive data for
NSF-ANT-1142074-penguins_1.0 Adelie penguin satellite position and dive data for NSF-ANT-1142074 from the California Avian Data Center hosted by Point Blue Conservation Science ALL STAC Catalog 2012-12-15 2013-01-31 165.9, -77.6, 169.4, -76.9 https://cmr.earthdata.nasa.gov/search/concepts/C1219899602-SCIOPS.umm_json Satellite positions and dive data collected on Adelie penguins in the 2012-13 season for purposes of evaluating food-web dynamics.. proprietary
NSF-ANT02-28842 Boron in Antarctic granulite-facies rocks: under what conditions is boron retained in the middle crust? AMD_USAPDC STAC Catalog 2003-06-01 2009-11-30 76, -69.5, 76.5, -69.3 https://cmr.earthdata.nasa.gov/search/concepts/C2534797156-AMD_USAPDC.umm_json This award, provided by the Antarctic Geology and Geophysics Program of the Office of Polar Programs, supports a project to investigate the role and fate of Boron in high-grade metamorphic rocks of the Larsemann Hills region of Antarctica. Trace elements provide valuable information on the changes sedimentary rocks undergo as temperature and pressure increase during burial. One such element, boron, is particularly sensitive to increasing temperature because of its affinity for aqueous fluids, which are lost as rocks are buried. Boron contents of unmetamorphosed pelitic sediments range from 20 to over 200 parts per million, but rarely exceed 5 parts per million in rocks subjected to conditions of the middle and lower crust, that is, temperatures of 700 degrees C or more in the granulite-facies, which is characterized by very low water activities at pressures of 5 to 10 kbar (18-35 km burial). Devolatization reactions with loss of aqueous fluid and partial melting with removal of melt have been cited as primary causes for boron depletion under granulite-facies conditions. Despite the pervasiveness of both these processes, rocks rich in boron are locally found in the granulite-facies, that is, there are mechanisms for retaining boron during the metamorphic process. The Larsemann Hills, Prydz Bay, Antarctica, are a prime example. More than 20 lenses and layered bodies containing four borosilicate mineral species crop out over a 50 square kilometer area, which thus would be well suited for research on boron-rich granulite-facies metamorphic rocks. While most investigators have focused on the causes for loss of boron, this work will investigate how boron is retained during high-grade metamorphism. Field observations and mapping in the Larsemann Hills, chemical analyses of minerals and their host rocks, and microprobe age dating will be used to identify possible precursors and deduce how the precursor materials recrystallized into borosilicate rocks under granulite-facies conditions. The working hypothesis is that high initial boron content facilitates retention of boron during metamorphism because above a certain threshold boron content, a mechanism 'kicks in' that facilitates retention of boron in metamorphosed rocks. For example, in a rock with large amounts of the borosilicate tourmaline, such as stratabound tourmalinite, the breakdown of tourmaline to melt could result in the formation of prismatine and grandidierite, two borosilicates found in the Larsemann Hills. This situation is rarely observed in rocks with modest boron content, in which breakdown of tourmaline releases boron into partial melts, which in turn remove boron when they leave the system. Stratabound tourmalinite is associated with manganese-rich quartzite, phosphorus-rich rocks and sulfide concentrations that could be diagnostic for recognizing a tourmalinite protolith in a highly metamorphosed complex where sedimentary features have been destroyed by deformation. Because partial melting plays an important role in the fate of boron during metamorphism, our field and laboratory research will focus on the relationship between the borosilicate units, granite pegmatites and other granitic intrusives. The results of our study will provide information on cycling of boron at deeper levels in the Earth's crust and on possible sources of boron for granites originating from deep-seated rocks. An undergraduate student will participate in the electron microprobe age-dating of monazite and xenotime as part of a senior project, thereby integrating the proposed research into the educational mission of the University of Maine. In response to a proposal for fieldwork, the Australian Antarctic Division, which maintains Davis station near the Larsemann Hills, has indicated that they will support the Antarctic fieldwork. proprietary
NSF-ANT04-36190_1 Biodiversity, Buoyancy and Morphological Studies of Non-Antarctic Notothenioid Fishes AMD_USAPDC STAC Catalog 2005-04-01 2009-03-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532069293-AMD_USAPDC.umm_json Patterns of biodiversity, as revealed by basic research in organismal biology, may be derived from ecological and evolutionary processes expressed in unique settings, such as Antarctica. The polar regions and their faunas are commanding increased attention as declining species diversity, environmental change, commercial fisheries, and resource management are now being viewed in a global context. Commercial fishing is known to have a direct and pervasive effect on marine biodiversity, and occurs in the Southern Ocean as far south as the Ross Sea. The nature of fish biodiversity in the Antarctic is different than in all other ocean shelf areas. Waters of the Antarctic continental shelf are ice covered for most of the year and water temperatures are nearly constant at -1.5 C. In these waters components of the phyletically derived Antarctic clade of Notothenioids dominate fish diversity. In some regions, including the southwestern Ross Sea, Notothenioids are overwhelmingly dominant in terms of number of species, abundance, and biomass. Such dominance by a single taxonomic group is unique among shelf faunas of the world. In the absence of competition from a taxonomically diverse fauna, Notothenioids underwent a habitat or depth related diversification keyed to the utilization of unfilled niches in the water column, especially pelagic or partially pelagic zooplanktivory and piscivory. This has been accomplished in the absence of a swim bladder for buoyancy control. They also may form a special type of adaptive radiation known as a species flock, which is an assemblage of a disproportionately high number of related species that have evolved rapidly within a defined area where most species are endemic. Diversification in buoyancy is the hallmark of the notothenioid radiation. Buoyancy is the feature of notothenioid biology that determines whether a species lives on the substrate, in the water column or both. Buoyancy also influences other key aspects of life history including swimming, feeding and reproduction and thus has implications for the role of the species in the ecosystem. With similarities to classic evolutionary hot spots, the Antarctic shelf and its Notothenioid radiation merit further exploration. The 2004 'International Collaborative Expedition to collect and study Fish Indigenous to Sub-Antarctic Habitats,' or, 'ICEFISH,' provided a platform for collection of notothenioid fishes from sub-Antarctic waters between South America and Africa, which will be examined in this project. This study will determine buoyancy for samples of all notothenioid species captured during the ICEFISH cruise. This essential aspect of the biology is known for only 19% of the notothenioid fauna. Also, the gross and microscopic anatomy of brains and sense organs of the phyletically basal families Bovichtidae, Eleginopidae, and of the non-Antarctic species of the primarily Antarctic family Nototheniidae will be examined. The fish biodiversity and endemicity in poorly known localities along the ICEFISH cruise track, seamounts and deep trenches will be quantified. Broader impacts include improved information for comprehending and conserving biodiversity, a scientific and societal priority. proprietary
-NSF-ANT04-39906_1 Abandoned Elephant Seal Colonies in Antarctica: Integration of Genetic, Isotopic, and Geologic Approaches toward Understanding Holocene Environmental Change AMD_USAPDC STAC Catalog 2005-09-15 2009-08-31 162, -78, 168, -72 https://cmr.earthdata.nasa.gov/search/concepts/C2532069615-AMD_USAPDC.umm_json During previous NSF-sponsored research, the PI's discovered that southern elephant seal colonies once existed along the Victoria Land coast (VLC) of Antarctica, a region where they are no longer observed. Molted seal skin and hair occur along 300 km of coastline, more than 1000 km from any extant colony. The last record of a seal at a former colony site is at ~A.D. 1600. Because abandonment occurred prior to subantarctic sealing, disappearance of the VLC colony probably was due to environmental factors, possibly cooling and encroachment of land-fast, perennial sea ice that made access to haul-out sites difficult. The record of seal inhabitation along the VLC, therefore, has potential as a proxy for climate change. Elephant seals are a predominantly subantarctic species with circumpolar distribution. Genetic studies have revealed significant differentiation among populations, particularly with regard to that at Macquarie I., which is the extant population nearest to the abandoned VLC colony. Not only is the Macquarie population unique genetically, but it is has undergone unexplained decline of 2%/yr over the last 50 years3. In a pilot study, genetic analyses showed a close relationship between the VLC seals and those at Macquarie I. An understanding of the relationship between the two populations, as well as of the environmental pressures that led to the demise of the VLC colonies, will provide a better understanding of present-day population genetic structure, the effect of environmental change on seal populations, and possibly the reasons underlying the modern decline at Macquarie Island. This project addresses several key research problems: (1) Why did elephant seals colonize and then abandon the VLC? (2) What does the elephant seal record reveal about Holocene climate change and sea-ice conditions? (3) What were the foraging strategies of the seals and did these strategies change over time as climate varied? (4) How does the genetic structure of the VLC seals relate to extant populations? (5) How did genetic diversity change over time and with colony decline? (6) Using ancient samples to estimate mtDNA mutation rates, what can be learned about VLC population dynamics over time? (7) What was the ecological relationship between elephant seals and Adelie penguins that occupied the same sites, but apparently at different times? The proposed work includes the professional training of young researchers and incorporation of data into graduate and undergraduate courses. Because of extreme isolation of the Antarctic continent since the Early Oligocene, one expects a unique invertebrate benthic fauna with a high degree of endemism. Yet some invertebrate taxa that constitute important ecological components of sedimentary benthic communities include more than 40 percent non-endemic species (e.g., benthic polychaetes). To account for non-endemic species, intermittent genetic exchange must occur between Antarctic and other (e.g. South American) populations. The most likely mechanism for such gene flow, at least for in-faunal and mobile macrobenthos, is dispersal of planktonic larvae across the sub- Antarctic and Antarctic polar fronts. To test for larval dispersal as a mechanism of maintaining genetic continuity across polar fronts, the scientists propose to (1) take plankton samples along transects across Drake passage during both the austral summer and winter seasons while concurrently collecting the appropriate hydrographic data. Such data will help elucidate the hydrographic mechanisms that allow dispersal across Drake Passage. Using a molecular phylogenetic approach, they will (2) compare seemingly identical adult forms from Antarctic and South America continents to identify genetic breaks, historical gene flow, and control for the presence of cryptic species. (3) Similar molecular tools will be used to relate planktonic larvae to their adult forms. Through this procedure, they propose to link the larval forms respectively to their Antarctic or South America origins. The proposed work builds on previous research that provides the basis for this effort to develop a synthetic understanding of historical gene flow and present day dispersal mechanism in South American/Drake Passage/ Antarctic Peninsular region. Furthermore, this work represents one of the first attempts to examine recent gene flow in Antarctic benthic invertebrates. Graduate students and a postdoctoral fellow will be trained during this research proprietary
NSF-ANT04-39906_1 Abandoned Elephant Seal Colonies in Antarctica: Integration of Genetic, Isotopic, and Geologic Approaches toward Understanding Holocene Environmental Change ALL STAC Catalog 2005-09-15 2009-08-31 162, -78, 168, -72 https://cmr.earthdata.nasa.gov/search/concepts/C2532069615-AMD_USAPDC.umm_json During previous NSF-sponsored research, the PI's discovered that southern elephant seal colonies once existed along the Victoria Land coast (VLC) of Antarctica, a region where they are no longer observed. Molted seal skin and hair occur along 300 km of coastline, more than 1000 km from any extant colony. The last record of a seal at a former colony site is at ~A.D. 1600. Because abandonment occurred prior to subantarctic sealing, disappearance of the VLC colony probably was due to environmental factors, possibly cooling and encroachment of land-fast, perennial sea ice that made access to haul-out sites difficult. The record of seal inhabitation along the VLC, therefore, has potential as a proxy for climate change. Elephant seals are a predominantly subantarctic species with circumpolar distribution. Genetic studies have revealed significant differentiation among populations, particularly with regard to that at Macquarie I., which is the extant population nearest to the abandoned VLC colony. Not only is the Macquarie population unique genetically, but it is has undergone unexplained decline of 2%/yr over the last 50 years3. In a pilot study, genetic analyses showed a close relationship between the VLC seals and those at Macquarie I. An understanding of the relationship between the two populations, as well as of the environmental pressures that led to the demise of the VLC colonies, will provide a better understanding of present-day population genetic structure, the effect of environmental change on seal populations, and possibly the reasons underlying the modern decline at Macquarie Island. This project addresses several key research problems: (1) Why did elephant seals colonize and then abandon the VLC? (2) What does the elephant seal record reveal about Holocene climate change and sea-ice conditions? (3) What were the foraging strategies of the seals and did these strategies change over time as climate varied? (4) How does the genetic structure of the VLC seals relate to extant populations? (5) How did genetic diversity change over time and with colony decline? (6) Using ancient samples to estimate mtDNA mutation rates, what can be learned about VLC population dynamics over time? (7) What was the ecological relationship between elephant seals and Adelie penguins that occupied the same sites, but apparently at different times? The proposed work includes the professional training of young researchers and incorporation of data into graduate and undergraduate courses. Because of extreme isolation of the Antarctic continent since the Early Oligocene, one expects a unique invertebrate benthic fauna with a high degree of endemism. Yet some invertebrate taxa that constitute important ecological components of sedimentary benthic communities include more than 40 percent non-endemic species (e.g., benthic polychaetes). To account for non-endemic species, intermittent genetic exchange must occur between Antarctic and other (e.g. South American) populations. The most likely mechanism for such gene flow, at least for in-faunal and mobile macrobenthos, is dispersal of planktonic larvae across the sub- Antarctic and Antarctic polar fronts. To test for larval dispersal as a mechanism of maintaining genetic continuity across polar fronts, the scientists propose to (1) take plankton samples along transects across Drake passage during both the austral summer and winter seasons while concurrently collecting the appropriate hydrographic data. Such data will help elucidate the hydrographic mechanisms that allow dispersal across Drake Passage. Using a molecular phylogenetic approach, they will (2) compare seemingly identical adult forms from Antarctic and South America continents to identify genetic breaks, historical gene flow, and control for the presence of cryptic species. (3) Similar molecular tools will be used to relate planktonic larvae to their adult forms. Through this procedure, they propose to link the larval forms respectively to their Antarctic or South America origins. The proposed work builds on previous research that provides the basis for this effort to develop a synthetic understanding of historical gene flow and present day dispersal mechanism in South American/Drake Passage/ Antarctic Peninsular region. Furthermore, this work represents one of the first attempts to examine recent gene flow in Antarctic benthic invertebrates. Graduate students and a postdoctoral fellow will be trained during this research proprietary
+NSF-ANT04-39906_1 Abandoned Elephant Seal Colonies in Antarctica: Integration of Genetic, Isotopic, and Geologic Approaches toward Understanding Holocene Environmental Change AMD_USAPDC STAC Catalog 2005-09-15 2009-08-31 162, -78, 168, -72 https://cmr.earthdata.nasa.gov/search/concepts/C2532069615-AMD_USAPDC.umm_json During previous NSF-sponsored research, the PI's discovered that southern elephant seal colonies once existed along the Victoria Land coast (VLC) of Antarctica, a region where they are no longer observed. Molted seal skin and hair occur along 300 km of coastline, more than 1000 km from any extant colony. The last record of a seal at a former colony site is at ~A.D. 1600. Because abandonment occurred prior to subantarctic sealing, disappearance of the VLC colony probably was due to environmental factors, possibly cooling and encroachment of land-fast, perennial sea ice that made access to haul-out sites difficult. The record of seal inhabitation along the VLC, therefore, has potential as a proxy for climate change. Elephant seals are a predominantly subantarctic species with circumpolar distribution. Genetic studies have revealed significant differentiation among populations, particularly with regard to that at Macquarie I., which is the extant population nearest to the abandoned VLC colony. Not only is the Macquarie population unique genetically, but it is has undergone unexplained decline of 2%/yr over the last 50 years3. In a pilot study, genetic analyses showed a close relationship between the VLC seals and those at Macquarie I. An understanding of the relationship between the two populations, as well as of the environmental pressures that led to the demise of the VLC colonies, will provide a better understanding of present-day population genetic structure, the effect of environmental change on seal populations, and possibly the reasons underlying the modern decline at Macquarie Island. This project addresses several key research problems: (1) Why did elephant seals colonize and then abandon the VLC? (2) What does the elephant seal record reveal about Holocene climate change and sea-ice conditions? (3) What were the foraging strategies of the seals and did these strategies change over time as climate varied? (4) How does the genetic structure of the VLC seals relate to extant populations? (5) How did genetic diversity change over time and with colony decline? (6) Using ancient samples to estimate mtDNA mutation rates, what can be learned about VLC population dynamics over time? (7) What was the ecological relationship between elephant seals and Adelie penguins that occupied the same sites, but apparently at different times? The proposed work includes the professional training of young researchers and incorporation of data into graduate and undergraduate courses. Because of extreme isolation of the Antarctic continent since the Early Oligocene, one expects a unique invertebrate benthic fauna with a high degree of endemism. Yet some invertebrate taxa that constitute important ecological components of sedimentary benthic communities include more than 40 percent non-endemic species (e.g., benthic polychaetes). To account for non-endemic species, intermittent genetic exchange must occur between Antarctic and other (e.g. South American) populations. The most likely mechanism for such gene flow, at least for in-faunal and mobile macrobenthos, is dispersal of planktonic larvae across the sub- Antarctic and Antarctic polar fronts. To test for larval dispersal as a mechanism of maintaining genetic continuity across polar fronts, the scientists propose to (1) take plankton samples along transects across Drake passage during both the austral summer and winter seasons while concurrently collecting the appropriate hydrographic data. Such data will help elucidate the hydrographic mechanisms that allow dispersal across Drake Passage. Using a molecular phylogenetic approach, they will (2) compare seemingly identical adult forms from Antarctic and South America continents to identify genetic breaks, historical gene flow, and control for the presence of cryptic species. (3) Similar molecular tools will be used to relate planktonic larvae to their adult forms. Through this procedure, they propose to link the larval forms respectively to their Antarctic or South America origins. The proposed work builds on previous research that provides the basis for this effort to develop a synthetic understanding of historical gene flow and present day dispersal mechanism in South American/Drake Passage/ Antarctic Peninsular region. Furthermore, this work represents one of the first attempts to examine recent gene flow in Antarctic benthic invertebrates. Graduate students and a postdoctoral fellow will be trained during this research proprietary
NSF-ANT04-53680 Application of a New Method for Isotopic Analysis of Diatom Microfossil-bound Nitrogen AMD_USAPDC STAC Catalog 2005-05-01 2009-04-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532069333-AMD_USAPDC.umm_json The Southern Ocean may play a central role in causing ice ages and general global climate change. This work will reveal key characteristics of the glacial ocean, and may explain the cause of glacial/interglacial cycles by measuring the abundances of certain isotopes of nitrogen found in fossil diatoms from Antarctic marine sediments. Diatom-bound N is a potentially important recorder of nutrient utilization. The Southern Ocean's nutrient status, productivity and circulation may be central to setting global atmospheric CO2 contents and other aspects of climate. Previous attempts to make these measurements have yielded ambiguous results. This project includes both technique development and analyses, including measurements on diatoms from both sediment traps and culture experiments. With regard to broader impacts, this grant is focused around the education and academic development of a graduate student, by coupling their research with mentorship of an undergraduate researcher. proprietary
NSF-ANT05-37371 A Broadband Seismic Experiment to Image the Lithosphere Beneath the Gamburtsev Mountains and Surrounding Areas, East Antarctica ALL STAC Catalog 2007-10-01 2013-09-30 40, -84, 140, -76 https://cmr.earthdata.nasa.gov/search/concepts/C2532069799-AMD_USAPDC.umm_json This award supports a seismological study of the Gamburtsev Subglacial Mountains (GSM), a Texas-sized mountain range buried beneath the ice sheets of East Antarctica. The project will perform a passive seismic experiment deploying twenty-three seismic stations over the GSM to characterize the structure of the crust and upper mantle, and determine the processes driving uplift. The outcomes will also offer constraints on the terrestrial heat flux, a key variable in modeling ice sheet formation and behavior. Virtually unexplored, the GSM represents the largest unstudied area of crustal uplift on earth. As well, the region is the starting point for growth of the Antarctic ice sheets. Because of these outstanding questions, the GSM has been identified by the international Antarctic science community as a research focus for the International Polar Year (2007-2009). In addition to this seismic experiment, NSF is also supporting an aerogeophysical survey of the GSM under award number 0632292. Major international partners in the project include Germany, China, Australia, and the United Kingdom. For more information see IPY Project #67 at IPY.org. In terms of broader impacts, this project also supports postdoctoral and graduate student research, and various forms of outreach. proprietary
NSF-ANT05-37371 A Broadband Seismic Experiment to Image the Lithosphere Beneath the Gamburtsev Mountains and Surrounding Areas, East Antarctica AMD_USAPDC STAC Catalog 2007-10-01 2013-09-30 40, -84, 140, -76 https://cmr.earthdata.nasa.gov/search/concepts/C2532069799-AMD_USAPDC.umm_json This award supports a seismological study of the Gamburtsev Subglacial Mountains (GSM), a Texas-sized mountain range buried beneath the ice sheets of East Antarctica. The project will perform a passive seismic experiment deploying twenty-three seismic stations over the GSM to characterize the structure of the crust and upper mantle, and determine the processes driving uplift. The outcomes will also offer constraints on the terrestrial heat flux, a key variable in modeling ice sheet formation and behavior. Virtually unexplored, the GSM represents the largest unstudied area of crustal uplift on earth. As well, the region is the starting point for growth of the Antarctic ice sheets. Because of these outstanding questions, the GSM has been identified by the international Antarctic science community as a research focus for the International Polar Year (2007-2009). In addition to this seismic experiment, NSF is also supporting an aerogeophysical survey of the GSM under award number 0632292. Major international partners in the project include Germany, China, Australia, and the United Kingdom. For more information see IPY Project #67 at IPY.org. In terms of broader impacts, this project also supports postdoctoral and graduate student research, and various forms of outreach. proprietary
@@ -12448,8 +12448,8 @@ NSF-ANT05-37609_1 An Integrated Geomagnetic and Petrologic Study of the Dufek Co
NSF-ANT05-38580 Antarctica's Geological History Reflected in Sedimentary Radiogenic Isotopes AMD_USAPDC STAC Catalog 2006-09-15 2010-08-31 60, -70, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532069644-AMD_USAPDC.umm_json This project studies sediment from the ocean floor to understand Antarctica's geologic history. Glacially eroded from the Antarctic continent, these sediments may offer insight into the 99% Antarctica covered by ice. The work's central focus is determining crust formation ages and thermal histories for three key areas of East Antarctica--Prydz Bay, eastern Weddell Sea, and Wilkes Land--through a combination of petrography, bulk sediment geochemistry and radiogenic isotopes, as well as isotope chronology of individual mineral grains. One specific objective is characterizing the composition of the Gamburtsev Mountains through studies of Eocene fluvial sediments from Prydz Bay. In addition to furthering our understanding of the hidden terrains of Antarctica, these terrigenous sediments will also serve as a natural laboratory to evaluate the effects of continental weathering on the Hf/Nd isotope systematics of seawater. An important broader impact of the project is providing exciting research projects for graduate and postdoctoral students using state of the art techniques in geochemistry. proprietary
NSF-ANT06-36850 Central Scotia Seafloor and the Drake Passage Deep Ocean Current Gateway AMD_USAPDC STAC Catalog 2007-07-15 2009-06-30 -70, -62, -35, -52 https://cmr.earthdata.nasa.gov/search/concepts/C2532069299-AMD_USAPDC.umm_json This project studies the opening of the Drake Passage between South America and Antarctica through a combined marine geophysical survey and geochemical study of dredged ocean floor basalts. Dating the passage's opening is key to understanding the formation of the circum-Antarctic current, which plays a major role in worldwide ocean circulation, and whose formation is connected with growth of the Antarctic ice sheet. Dredge samples will undergo various geochemical studies to determine their age and constrain mantle flow beneath the region. Broader impacts include support for graduate education, as well as undergraduate and K12 teacher involvement in a research cruise. The project also involves international collaboration with the UK and is part of IPY Project #77: Plates&Gates, which aims to reconstruct the geologic history of polar ocean basins and gateways for computer simulations of climate change. See http://www.ipy.org/index.php?/ipy/detail/plates_gates/ for more information. proprietary
NSF-ANT06-36899_1 Antarctic Auroral Imaging AMD_USAPDC STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2532069257-AMD_USAPDC.umm_json Auroral protons are not energized by electric fields directly above the auroral atmosphere and therefore they are a much better diagnostic of processes deep in the magnetosphere. It has been shown from measurements from space by the IMAGE spacecraft that the dayside hydrogen emission is directly related to dayside reconnection processes. A four channel all-sky images had been operating at South Pole during 2004-2007 to observe auroral features in specific wavelengths channels that allowed a quantitative investigation of proton aurora. This was accomplished by measuring the Hydrogen Balmer beta line at 486.1 nm and by monitoring another wavelength band for subtracting non proton produced background emissions. South Pole allows these measurements because of the 24 hour darkness and favorable conditions even on the dayside. To increase the scientific return it was also attempted to measure the Doppler shift of the hydrogen emissions because that provides diagnostics regarding the energy of the protons. Thus the proton camera measured 3 wavelength bands simultaneously in the vicinity of the Balmer beta line to provide the line intensity near zero Doppler shift, at a substantial Doppler shift and a third channel for background. The 4-channel all-sky camera at South Pole was modified in 2008 in order to observe several types of auroras, and to distinguish the cusp reconnection aurora from the normal plasma sheet precipitation. The camera simultaneously operates in four wavelength regions that allow a distinction between auroras that are created by higher energy electrons (greater than 1 keV) and those created by low energy (less than 500 eV) precipitation. The cusp is the location where plasma enters the magnetosphere through the process of magnetic reconnection. This reconnection occurs where the Interplanetary Magnetic Field (IMF) and the terrestrial magnetic field are oriented in opposite directions. The data are represented as keograms (geomagnetic north-south slices through the time series of images) for the four different wavelengths. The top of the keogram points to the magnetic south pole. The time series allows a very quick assessment about the presence of aurora, motion, intensity, and brightness differences in the four simultaneously registered channels. proprietary
-NSF-ANT06-36928 A VLF Beacon Transmitter at South Pole ALL STAC Catalog 2007-09-15 2011-08-31 -180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2532069583-AMD_USAPDC.umm_json This proposal seeks funding to resume operation of the VLF Beacon Transmitter at the South Pole Station used to quantify temporal and spatial variations in the state of the lower ionosphere between the polar cap and subauroral zone, to determine the ionosphere's response to precipitation of highly energetic radiation belt electrons and solar protons, and to monitor the loss of these particles into the atmosphere. Although fluctuations in the relativistic particle population are extensively observed on satellites, little is known about the extent of associated precipitation into the ionosphere. Upon precipitation, these highly energetic particles penetrate to altitudes as low as 30-40 km, producing ionization, X-rays, and possibly affecting chemical reactions involving ozone production. It is proposed to continue recording the VLF beacon's signal at various Antarctic coastal stations (Palmer, Halley, etc). The broader impact of the proposed program includes the synergistic use of the South Pole VLF beacon with ongoing satellite-based measurements of trapped and precipitating high-energy electrons both at low and high altitudes and with other Antarctic Upper Atmospheric research efforts, such as the Automatic Geophysical Observatory programs and routine upper atmospheric observations at manned bases. The proposed project also promotes international collaboration via multi-points recording of the South Pole VLF beacon signal while providing the basis of a graduate or doctoral student thesis. proprietary
NSF-ANT06-36928 A VLF Beacon Transmitter at South Pole AMD_USAPDC STAC Catalog 2007-09-15 2011-08-31 -180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2532069583-AMD_USAPDC.umm_json This proposal seeks funding to resume operation of the VLF Beacon Transmitter at the South Pole Station used to quantify temporal and spatial variations in the state of the lower ionosphere between the polar cap and subauroral zone, to determine the ionosphere's response to precipitation of highly energetic radiation belt electrons and solar protons, and to monitor the loss of these particles into the atmosphere. Although fluctuations in the relativistic particle population are extensively observed on satellites, little is known about the extent of associated precipitation into the ionosphere. Upon precipitation, these highly energetic particles penetrate to altitudes as low as 30-40 km, producing ionization, X-rays, and possibly affecting chemical reactions involving ozone production. It is proposed to continue recording the VLF beacon's signal at various Antarctic coastal stations (Palmer, Halley, etc). The broader impact of the proposed program includes the synergistic use of the South Pole VLF beacon with ongoing satellite-based measurements of trapped and precipitating high-energy electrons both at low and high altitudes and with other Antarctic Upper Atmospheric research efforts, such as the Automatic Geophysical Observatory programs and routine upper atmospheric observations at manned bases. The proposed project also promotes international collaboration via multi-points recording of the South Pole VLF beacon signal while providing the basis of a graduate or doctoral student thesis. proprietary
+NSF-ANT06-36928 A VLF Beacon Transmitter at South Pole ALL STAC Catalog 2007-09-15 2011-08-31 -180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2532069583-AMD_USAPDC.umm_json This proposal seeks funding to resume operation of the VLF Beacon Transmitter at the South Pole Station used to quantify temporal and spatial variations in the state of the lower ionosphere between the polar cap and subauroral zone, to determine the ionosphere's response to precipitation of highly energetic radiation belt electrons and solar protons, and to monitor the loss of these particles into the atmosphere. Although fluctuations in the relativistic particle population are extensively observed on satellites, little is known about the extent of associated precipitation into the ionosphere. Upon precipitation, these highly energetic particles penetrate to altitudes as low as 30-40 km, producing ionization, X-rays, and possibly affecting chemical reactions involving ozone production. It is proposed to continue recording the VLF beacon's signal at various Antarctic coastal stations (Palmer, Halley, etc). The broader impact of the proposed program includes the synergistic use of the South Pole VLF beacon with ongoing satellite-based measurements of trapped and precipitating high-energy electrons both at low and high altitudes and with other Antarctic Upper Atmospheric research efforts, such as the Automatic Geophysical Observatory programs and routine upper atmospheric observations at manned bases. The proposed project also promotes international collaboration via multi-points recording of the South Pole VLF beacon signal while providing the basis of a graduate or doctoral student thesis. proprietary
NSF-ANT06-49609_1 Aging in Weddell Seals: Proximate Mechanisms of Age-Related Changes in Adaptations to Breath-Hold Hunting in an Extreme Environment AMD_USAPDC STAC Catalog 2006-08-01 2010-08-31 165.975, -77.849, 166.856, -77.54 https://cmr.earthdata.nasa.gov/search/concepts/C2532069573-AMD_USAPDC.umm_json The primary objectives of this research are to investigate the proximate effects of aging on diving capability in the Weddell Seal and to describe mechanisms by which aging may influence foraging ecology, through physiology and behavior. This model pinniped species has been the focus of three decades of research in McMurdo Sound, Antarctica. Compared to the knowledge of pinniped diving physiology and ecology during early development and young adulthood, little is known about individuals nearing the upper limit of their normal reproductive age range. Evolutionary aging theories predict that elderly diving seals should exhibit senescence. This should be exacerbated by surges in the generation of oxygen free radicals via hypoxia-reoxygenation during breath-hold diving and hunting, which are implicated in age-related damage to cellular mitochondria. Surprisingly, limited observations of non-threatened pinniped populations indicate that senescence does not occur to a level where reproductive output is affected. The ability of pinnipeds to avoid apparent senescence raises two major questions: what specific physiological and morphological changes occur with advancing age in pinnipeds; and what subtle adjustments are made by these animals to cope with such changes? This investigation will focus on specific, functional physiological and behavioral changes relating to dive capability with advancing age. Data will be compared between Weddell seals in the peak, and near the end, of their reproductive age range. The investigators will quantify age-related changes in general health and body condition, combined with fine scale assessments of external and internal ability to do work in the form of diving. Specifically, patterns of muscle morphology, oxidant status and oxygen storage with age will be examined. The effects of age on skeletal muscular function and exercise performance will also be examined. The investigators hypothesize that senescence does occur in Weddell seals at the level of small-scale, proximate physiological effects and performance, but that behavioral plasticity allows for a given degree of compensation. Broader impacts include the training of students and outreach activities including interviews and articles written for the popular media. This study should also establish diving seals as a novel model for the study of cardiovascular and muscular physiology of aging and develop a foundation for similar research on other species. Advancement of the understanding of aging by medical science has been impressive in recent years but basic mammalian aging is an area of study the still requires considerable effort. The development of new models for the study of aging has tremendous potential benefits to society at large. proprietary
NSF-ANT06-49609_1 Aging in Weddell Seals: Proximate Mechanisms of Age-Related Changes in Adaptations to Breath-Hold Hunting in an Extreme Environment ALL STAC Catalog 2006-08-01 2010-08-31 165.975, -77.849, 166.856, -77.54 https://cmr.earthdata.nasa.gov/search/concepts/C2532069573-AMD_USAPDC.umm_json The primary objectives of this research are to investigate the proximate effects of aging on diving capability in the Weddell Seal and to describe mechanisms by which aging may influence foraging ecology, through physiology and behavior. This model pinniped species has been the focus of three decades of research in McMurdo Sound, Antarctica. Compared to the knowledge of pinniped diving physiology and ecology during early development and young adulthood, little is known about individuals nearing the upper limit of their normal reproductive age range. Evolutionary aging theories predict that elderly diving seals should exhibit senescence. This should be exacerbated by surges in the generation of oxygen free radicals via hypoxia-reoxygenation during breath-hold diving and hunting, which are implicated in age-related damage to cellular mitochondria. Surprisingly, limited observations of non-threatened pinniped populations indicate that senescence does not occur to a level where reproductive output is affected. The ability of pinnipeds to avoid apparent senescence raises two major questions: what specific physiological and morphological changes occur with advancing age in pinnipeds; and what subtle adjustments are made by these animals to cope with such changes? This investigation will focus on specific, functional physiological and behavioral changes relating to dive capability with advancing age. Data will be compared between Weddell seals in the peak, and near the end, of their reproductive age range. The investigators will quantify age-related changes in general health and body condition, combined with fine scale assessments of external and internal ability to do work in the form of diving. Specifically, patterns of muscle morphology, oxidant status and oxygen storage with age will be examined. The effects of age on skeletal muscular function and exercise performance will also be examined. The investigators hypothesize that senescence does occur in Weddell seals at the level of small-scale, proximate physiological effects and performance, but that behavioral plasticity allows for a given degree of compensation. Broader impacts include the training of students and outreach activities including interviews and articles written for the popular media. This study should also establish diving seals as a novel model for the study of cardiovascular and muscular physiology of aging and develop a foundation for similar research on other species. Advancement of the understanding of aging by medical science has been impressive in recent years but basic mammalian aging is an area of study the still requires considerable effort. The development of new models for the study of aging has tremendous potential benefits to society at large. proprietary
NSF-ANT07-32625_1 Collaborative Research in IPY: Abrupt Environmental Change in the Larsen Ice Shelf System, a Multidisciplinary Approach - Marine and Quaternary Geosciences AMD_USAPDC STAC Catalog 2007-10-01 2013-09-30 -65.4, -66.1, -57.8, -57 https://cmr.earthdata.nasa.gov/search/concepts/C2532069808-AMD_USAPDC.umm_json This award supports a research cruise to perform geologic studies in the area under and surrounding the former Larsen B ice shelf, on the Antarctic Peninsula. The ice shelf's disintegration in 2002 coupled with the unique marine geology of the area make it possible to understand the conditions leading to ice shelf collapse. Bellwethers of climate change that reflect both oceanographic and atmospheric conditions, ice shelves also hold back glacial flow in key areas of the polar regions. Their collapse results in glacial surging and could cause rapid rise in global sea levels. This project characterizes the Larsen ice shelf's history and conditions leading to its collapse by determining: 1) the size of the Larsen B during warmer climates and higher sea levels back to the Eemian interglacial, 125,000 years ago; 2) the configuration of the Antarctic Peninsula ice sheet during the LGM and its subsequent retreat; 3) the causes of the Larsen B's stability through the Holocene, during which other shelves have come and gone; 4) the controls on the dynamics of ice shelf margins, especially the roles of surface melting and oceanic processes, and 5) the changes in sediment flux, both biogenic and lithogenic, after large ice shelf breakup. The broader impacts include graduate and undergraduate education through research projects and workshops; outreach to the general public through a television documentary and websites, and international collaboration with scientists from Belgium, Spain, Argentina, Canada, Germany and the UK. The work also has important societal relevance. Improving our understanding of how ice shelves behave in a warming world will improve models of sea level rise. The project is supported under NSF's International Polar Year (IPY) research emphasis area on 'Understanding Environmental Change in Polar Regions'. proprietary
@@ -12461,22 +12461,22 @@ NSF-ANT08-38955_1 Alternative Nutritional Strategies in Antarctic Protists AMD_U
NSF-ANT08-38996_1 Ammonia Oxidation Versus Heterotrophy in Crenarchaeota Populations from Marine Environments West of the Antarctic Peninsula AMD_USAPDC STAC Catalog 2009-08-15 2013-12-31 -79, -71, -64, -63 https://cmr.earthdata.nasa.gov/search/concepts/C2532069861-AMD_USAPDC.umm_json Ammonia oxidation is the first step in the conversion of regenerated nitrogen to dinitrogen gas, a 3-step pathway mediated by 3 distinct guilds of bacteria and archaea. Ammonia oxidation and the overall process of nitrification-denitrification have received relatively little attention in polar oceans where the effects of climate change on biogeochemical rates are likely to be pronounced. Previous work on Ammonia Oxidizing Archaea (AOA) in the Palmer LTER study area West of the Antarctic Peninsula (WAP), has suggested strong vertical segregation of crenarchaeote metabolism, with the 'winter water' (WW, ~50-100 m depth range) dominated by non-AOA crenarchaeotes, while Crenarchaeota populations in the 'circumpolar deep water' (CDW), which lies immediately below the winter water (150-3500 m), are dominated by AOA. Analysis of a limited number of samples from the Arctic Ocean did not reveal a comparable vertical segregation of AOA, and suggested that AOA and Crenarchaeota abundance is much lower there than in the Antarctic. These findings led to 3 hypotheses that will be tested in this project: 1) the apparent low abundance of Crenarchaeota and AOA in Arctic Ocean samples may be due to spatial or temporal variability in populations; 2) the WW population of Crenarchaeota in the WAP is dominated by a heterotroph; 3) the WW population of Crenarchaeota in the WAP 'grows in' during spring and summer after this water mass forms. The study will contribute substantially to understanding an important aspect of the nitrogen cycle in the Palmer LTER (Long Term Ecological Research) study area by providing insights into the ecology and physiology of AOA. The natural segregation of crenarchaeote phenotypes in waters of the WAP, coupled with metagenomic studies in progress in the same area by others (A. Murray, H. Ducklow), offers the possibility of major breakthroughs in understanding of the metabolic capabilities of these organisms. This knowledge is needed to model how water column nitrification will respond to changes in polar ecosystems accompanying global climate change. The Principal Investigator will participate fully in the education and outreach efforts of the Palmer LTER, including making highlights of our findings available for posting to their project web site and participating in outreach (for example, Schoolyard LTER). The research also will involve undergraduates (including the field work if possible) and will support high school interns in the P.I.'s laboratory over the summer. proprietary
NSF-ANT09-44042 Acoustic Assessment of Southern Ocean Salps and Their Ecosystem Impact AMD_USAPDC STAC Catalog 2010-09-01 2013-08-31 -70, -66, -50, -59 https://cmr.earthdata.nasa.gov/search/concepts/C2532069797-AMD_USAPDC.umm_json The importance of gelatinous zooplankton in marine systems worldwide is increasing. In Southern Ocean, increasing salp densities could have a detrimental effect on higher predators, including penguins, fur seals, and baleen whales. The proposed research is a methods-develoment project that will improve the capability to indirectly assess abundances and distributions of salps in the Southern Ocean through acoustic surveys. Hydrographic, net tow, and acoustic backscatter data will be collected in the waters surrounding the South Shetland Islands and the Antarctic peninsula, where both krill and salps are found and compete for food. Shipboard experimental manipulations and measurements will lead to improved techniques for assessment of salp biomass acoustically. Experiments will focus on material properties (density and sound speed), size and shape of salps, as well as how these physical properties will vary with the salp\'s environment, feeding rate, and reproductive status. In the field, volume backscattering data from an acoustic echosounder will be collected at the same locations as the net tows to enable comparison of net and acoustic estimates of salp abundance. A physics-based scattering model for salps will be developed and validated, to determine if multiple acoustic frequencies can be used to discriminate between scattering associated with krill swarms and that from salp blooms. During the same period as the Antarctic field work, a parallel outreach and education study will be undertaken in Long Island, New York examining local gelatinous zooplankton. This study will enable project participants to learn and practice research procedures and methods before traveling to Antarctica; provide a comparison time-series that will be used for educational purposes; and include many more students and teachers in the research project than would be able to participate in the Antarctic field component. proprietary
NSF-ANT09-44042 Acoustic Assessment of Southern Ocean Salps and Their Ecosystem Impact ALL STAC Catalog 2010-09-01 2013-08-31 -70, -66, -50, -59 https://cmr.earthdata.nasa.gov/search/concepts/C2532069797-AMD_USAPDC.umm_json The importance of gelatinous zooplankton in marine systems worldwide is increasing. In Southern Ocean, increasing salp densities could have a detrimental effect on higher predators, including penguins, fur seals, and baleen whales. The proposed research is a methods-develoment project that will improve the capability to indirectly assess abundances and distributions of salps in the Southern Ocean through acoustic surveys. Hydrographic, net tow, and acoustic backscatter data will be collected in the waters surrounding the South Shetland Islands and the Antarctic peninsula, where both krill and salps are found and compete for food. Shipboard experimental manipulations and measurements will lead to improved techniques for assessment of salp biomass acoustically. Experiments will focus on material properties (density and sound speed), size and shape of salps, as well as how these physical properties will vary with the salp\'s environment, feeding rate, and reproductive status. In the field, volume backscattering data from an acoustic echosounder will be collected at the same locations as the net tows to enable comparison of net and acoustic estimates of salp abundance. A physics-based scattering model for salps will be developed and validated, to determine if multiple acoustic frequencies can be used to discriminate between scattering associated with krill swarms and that from salp blooms. During the same period as the Antarctic field work, a parallel outreach and education study will be undertaken in Long Island, New York examining local gelatinous zooplankton. This study will enable project participants to learn and practice research procedures and methods before traveling to Antarctica; provide a comparison time-series that will be used for educational purposes; and include many more students and teachers in the research project than would be able to participate in the Antarctic field component. proprietary
-NSF-ANT09-44358 Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels - NSF-ANT09-44358 AMD_USAPDC STAC Catalog 2010-09-15 2015-08-31 165.9, -77.6, 169.4, -76.9 https://cmr.earthdata.nasa.gov/search/concepts/C2532070119-AMD_USAPDC.umm_json While changes in populations typically are tracked to gauge the impact of climate or habitat change, the process involves the response of individuals as each copes with an altered environment. In a study of Adelie penguins that spans 13 breeding seasons, results indicate that only 20% of individuals within a colony successfully raise offspring, and that they do so because of their exemplary foraging proficiency. Moreover, foraging appears to require more effort at the largest colony, where intraspecific competition is higher than at small colonies, and also requires more proficiency during periods of environmental stress. When conditions are particularly daunting, emigration dramatically increases, countering the long-standing assumption that Ad?lie penguins are highly philopatric. The research project will 1) determine the effect of age, experience and physiology on individual foraging efficiency; 2) determine the effect of age, experience, and individual quality on breeding success and survival in varying environmental and competitive conditions at the colony level; and 3) develop a comprehensive model for the Ross-Beaufort Island metapopulation dynamics. Broader impacts include training of interns, continuation of public outreach through the highly successful project website penguinscience.com, development of classroom materials and other standards-based instructional resources. proprietary
NSF-ANT09-44358 Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels - NSF-ANT09-44358 ALL STAC Catalog 2010-09-15 2015-08-31 165.9, -77.6, 169.4, -76.9 https://cmr.earthdata.nasa.gov/search/concepts/C2532070119-AMD_USAPDC.umm_json While changes in populations typically are tracked to gauge the impact of climate or habitat change, the process involves the response of individuals as each copes with an altered environment. In a study of Adelie penguins that spans 13 breeding seasons, results indicate that only 20% of individuals within a colony successfully raise offspring, and that they do so because of their exemplary foraging proficiency. Moreover, foraging appears to require more effort at the largest colony, where intraspecific competition is higher than at small colonies, and also requires more proficiency during periods of environmental stress. When conditions are particularly daunting, emigration dramatically increases, countering the long-standing assumption that Ad?lie penguins are highly philopatric. The research project will 1) determine the effect of age, experience and physiology on individual foraging efficiency; 2) determine the effect of age, experience, and individual quality on breeding success and survival in varying environmental and competitive conditions at the colony level; and 3) develop a comprehensive model for the Ross-Beaufort Island metapopulation dynamics. Broader impacts include training of interns, continuation of public outreach through the highly successful project website penguinscience.com, development of classroom materials and other standards-based instructional resources. proprietary
-NSF-ANT09-44411 Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels AMD_USAPDC STAC Catalog 2010-09-15 2015-08-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532069734-AMD_USAPDC.umm_json While changes in populations typically are tracked to gauge the impact of climate or habitat change, the process involves the response of individuals as each copes with an altered environment. In a study of Adelie penguins that spans 13 breeding seasons, results indicate that only 20% of individuals within a colony successfully raise offspring, and that they do so because of their exemplary foraging proficiency. Moreover, foraging appears to require more effort at the largest colony, where intraspecific competition is higher than at small colonies, and also requires more proficiency during periods of environmental stress. When conditions are particularly daunting, emigration dramatically increases, countering the long-standing assumption that Adélie penguins are highly philopatric. The research project will 1) determine the effect of age, experience and physiology on individual foraging efficiency; 2) determine the effect of age, experience, and individual quality on breeding success and survival in varying environmental and competitive conditions at the colony level; and 3) develop a comprehensive model for the Ross-Beaufort Island metapopulation dynamics. Broader impacts include training of interns, continuation of public outreach through the highly successful project website penguinscience.com, development of classroom materials and other standards-based instructional resources. proprietary
+NSF-ANT09-44358 Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels - NSF-ANT09-44358 AMD_USAPDC STAC Catalog 2010-09-15 2015-08-31 165.9, -77.6, 169.4, -76.9 https://cmr.earthdata.nasa.gov/search/concepts/C2532070119-AMD_USAPDC.umm_json While changes in populations typically are tracked to gauge the impact of climate or habitat change, the process involves the response of individuals as each copes with an altered environment. In a study of Adelie penguins that spans 13 breeding seasons, results indicate that only 20% of individuals within a colony successfully raise offspring, and that they do so because of their exemplary foraging proficiency. Moreover, foraging appears to require more effort at the largest colony, where intraspecific competition is higher than at small colonies, and also requires more proficiency during periods of environmental stress. When conditions are particularly daunting, emigration dramatically increases, countering the long-standing assumption that Ad?lie penguins are highly philopatric. The research project will 1) determine the effect of age, experience and physiology on individual foraging efficiency; 2) determine the effect of age, experience, and individual quality on breeding success and survival in varying environmental and competitive conditions at the colony level; and 3) develop a comprehensive model for the Ross-Beaufort Island metapopulation dynamics. Broader impacts include training of interns, continuation of public outreach through the highly successful project website penguinscience.com, development of classroom materials and other standards-based instructional resources. proprietary
NSF-ANT09-44411 Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels ALL STAC Catalog 2010-09-15 2015-08-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532069734-AMD_USAPDC.umm_json While changes in populations typically are tracked to gauge the impact of climate or habitat change, the process involves the response of individuals as each copes with an altered environment. In a study of Adelie penguins that spans 13 breeding seasons, results indicate that only 20% of individuals within a colony successfully raise offspring, and that they do so because of their exemplary foraging proficiency. Moreover, foraging appears to require more effort at the largest colony, where intraspecific competition is higher than at small colonies, and also requires more proficiency during periods of environmental stress. When conditions are particularly daunting, emigration dramatically increases, countering the long-standing assumption that Adélie penguins are highly philopatric. The research project will 1) determine the effect of age, experience and physiology on individual foraging efficiency; 2) determine the effect of age, experience, and individual quality on breeding success and survival in varying environmental and competitive conditions at the colony level; and 3) develop a comprehensive model for the Ross-Beaufort Island metapopulation dynamics. Broader impacts include training of interns, continuation of public outreach through the highly successful project website penguinscience.com, development of classroom materials and other standards-based instructional resources. proprietary
+NSF-ANT09-44411 Adelie Penguin Response to Climate Change at the Individual, Colony and Metapopulation Levels AMD_USAPDC STAC Catalog 2010-09-15 2015-08-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532069734-AMD_USAPDC.umm_json While changes in populations typically are tracked to gauge the impact of climate or habitat change, the process involves the response of individuals as each copes with an altered environment. In a study of Adelie penguins that spans 13 breeding seasons, results indicate that only 20% of individuals within a colony successfully raise offspring, and that they do so because of their exemplary foraging proficiency. Moreover, foraging appears to require more effort at the largest colony, where intraspecific competition is higher than at small colonies, and also requires more proficiency during periods of environmental stress. When conditions are particularly daunting, emigration dramatically increases, countering the long-standing assumption that Adélie penguins are highly philopatric. The research project will 1) determine the effect of age, experience and physiology on individual foraging efficiency; 2) determine the effect of age, experience, and individual quality on breeding success and survival in varying environmental and competitive conditions at the colony level; and 3) develop a comprehensive model for the Ross-Beaufort Island metapopulation dynamics. Broader impacts include training of interns, continuation of public outreach through the highly successful project website penguinscience.com, development of classroom materials and other standards-based instructional resources. proprietary
NSF-ANT09-44532 Application of Detrital Zircon Isotope Characteristics and Sandstone Analysis of Beacon Strata to the Tectonic Evolution of the Antarctic Sector of Gondwana AMD_USAPDC STAC Catalog 2010-07-01 2013-06-30 158.9, -85.1, 165.73, -83 https://cmr.earthdata.nasa.gov/search/concepts/C2532069801-AMD_USAPDC.umm_json Intellectual Merit: The goal of this project is to address relationships between foreland basins and their tectonic settings by combining detrital zircon isotope characteristics and sedimentological data. To accomplish this goal the PIs will develop a detailed geochronology and analyze Hf- and O-isotopes of detrital zircons in sandstones of the Devonian Taylor Group and the Permian-Triassic Victoria Group. These data will allow them to better determine provenance and basin fill, and to understand the nature of the now ice covered source regions in East and West Antarctica. The PIs will document possible unexposed/unknown crustal terrains in West Antarctica, investigate sub-glacial terrains of East Antarctica that were exposed to erosion during Devonian to Triassic time, and determine the evolving provenance and tectonic history of the Devonian to Triassic Gondwana basins in the central Transantarctic Mountains. Detrital zircon data will be interpreted in the context of fluvial dispersal/drainage patterns, sandstone petrology, and sequence stratigraphy. This interpretation will identify source terrains and evolving sediment provenances. Paleocurrent analysis and sequence stratigraphy will determine the timing and nature of changing tectonic conditions associated with development of the depositional basins and document the tectonic history of the Antarctic sector of Gondwana. Results from this study will answer questions about the Panthalassan margin of Gondwana, the Antarctic craton, and the Beacon depositional basin and their respective roles in global tectonics and the geologic and biotic history of Antarctica. The Beacon basin and adjacent uplands played an important role in the development and demise of Gondwanan glaciation through modification of polar climates, development of peat-forming mires, colonization of the landscape by plants, and were a migration route for Mesozoic vertebrates into Antarctica. Broader impacts: This proposal includes support for two graduate students who will participate in the fieldwork, and also support for other students to participate in laboratory studies. Results of the research will be incorporated in classroom teaching at the undergraduate and graduate levels and will help train the next generation of field geologists. Interactions with K-12 science classes will be achieved by video/computer conferencing and satellite phone connections from Antarctica. Another outreach effort is the developing cooperation between the Byrd Polar Research Center and the Center of Science and Industry in Columbus. proprietary
NSF-ANT09-44653_1 Annual Satellite Era Accumulation Patterns Over WAIS Divide: A Study Using Shallow Ice Cores, Near-Surface Radars and Satellites AMD_USAPDC STAC Catalog 2010-08-01 2015-07-31 -110, -80, -119.4, -78.1 https://cmr.earthdata.nasa.gov/search/concepts/C2532069942-AMD_USAPDC.umm_json This award supports a project to broaden the knowledge of annual accumulation patterns over the West Antarctic Ice Sheet by processing existing near-surface radar data taken on the US ITASE traverse in 2000 and by gathering and validating new ultra/super-high-frequency (UHF) radar images of near surface layers (to depths of ~15 m), expanding abilities to monitor recent annual accumulation patterns from point source ice cores to radar lines. Shallow (15 m) ice cores will be collected in conjunction with UHF radar images to confirm that radar echoed returns correspond with annual layers, and/or sub-annual density changes in the near-surface snow, as determined from ice core stable isotopes. This project will additionally improve accumulation monitoring from space-borne instruments by comparing the spatial-radar-derived-annual accumulation time series to the passive microwave time series dating back over 3 decades and covering most of Antarctica. The intellectual merit of this project is that mapping the spatial and temporal variations in accumulation rates over the Antarctic ice sheet is essential for understanding ice sheet responses to climate forcing. Antarctic precipitation rate is projected to increase up to 20% in the coming century from the predicted warming. Accumulation is a key component for determining ice sheet mass balance and, hence, sea level rise, yet our ability to measure annual accumulation variability over the past 5 decades (satellite era) is mostly limited to point-source ice cores. Developing a radar and ice core derived annual accumulation dataset will provide validation data for space-born remote sensing algorithms, climate models and, additionally, establish accumulation trends. The broader impacts of the project are that it will advance discovery and understanding within the climatology, glaciology and remote sensing communities by verifying the use of UHF radars to monitor annual layers as determined by visual, chemical and isotopic analysis from corresponding shallow ice cores and will provide a dataset of annual to near-annual accumulation measurements over the past ~5 decades across WAIS divide from existing radar data and proposed radar data. By determining if temporal changes in the passive microwave signal are correlated with temporal changes in accumulation will help assess the utility of passive microwave remote sensing to monitor accumulation rates over ice sheets for future decades. The project will promote teaching, training and learning, and increase representation of underrepresented groups by becoming involved in the NASA History of Winter project and Thermochron Mission and by providing K-12 teachers with training to monitor snow accumulation and temperature here in the US, linking polar research to the student's backyard. The project will train both undergraduate and graduate students in polar research and will encouraging young investigators to become involved in careers in science. In particular, two REU students will participate in original research projects as part of this larger project, from development of a hypothesis to presentation and publication of the results. The support of a new, young woman scientist will help to increase gender diversity in polar research. proprietary
NSF-ANT09-44727 ASPIRE: Amundsen Sea Polynya International Research Expedition AMD_USAPDC STAC Catalog 2010-10-01 2014-09-30 -118.3, -74.2, -111, -71.6 https://cmr.earthdata.nasa.gov/search/concepts/C2532069918-AMD_USAPDC.umm_json ASPIRE is an NSF-funded project that will examine the ecology of the Amundsen Sea during the Austral summer of 2010. ASPIRE includes an international team of trace metal and carbon chemists, phytoplankton physiologists, microbial and zooplankton ecologists, and physical oceanographers, that will investigate why and how the Amundsen Sea Polynya is so much more productive than other polynyas and whether interannual variability can provide insight to climate-sensitive mechanisms driving carbon fluxes. This project will compliment the existing ASPIRE effort by using 1) experimental manipulations to understand photoacclimation of the dominant phytoplankton taxa under conditions of varying light and trace metal abundance, 2) nutrient addition bioassays to determine the importance of trace metal versus nitrogen limitation of phytoplankton growth, and 3) a numerical ecosystem model to understand the importance of differences in mixing regime, flow field, and Fe sources in controlling phytoplankton bloom dynamics and community composition in this unusually productive polynya system. The research strategy will integrate satellite remote sensing, field-based experimental manipulations, and numerical modeling. Outreach and education include participation in Stanford's Summer Program for Professional Development for Science Teachers, Stanford's School of Earth Sciences high school internship program, and development of curriculum for local science training centers, including the Chabot Space and Science Center. Undergraduate participation and training will include support for both graduate students and undergraduate assistants. proprietary
NSF-ANT10-43145_1 Bromide in Snow in the Sea Ice Zone AMD_USAPDC STAC Catalog 2011-08-15 2015-07-31 164.1005, -77.8645, 166.7398, -77.1188 https://cmr.earthdata.nasa.gov/search/concepts/C2532070132-AMD_USAPDC.umm_json A range of chemical and microphysical pathways in polar latitudes, including spring time (tropospheric) ozone depletion, oxidative pathways for mercury, and cloud condensation nuclei (CCN) production leading to changes in the cloud cover and attendant surface energy budgets, have been invoked as being dependent upon the emission of halogen gases formed in sea-ice. The prospects for climate warming induced reductions in sea ice extent causing alteration of these incompletely known surface-atmospheric feedbacks and interactions requires confirmation of mechanistic details in both laboratory studies and field campaigns. One such mechanistic question is how bromine (BrO and Br) enriched snow migrates or is formed through processes in sea-ice, prior to its subsequent mobilization as an aerosol fraction into the atmosphere by strong winds. Once aloft, it may react with ozone and other atmospheric species. Dartmouth researchers will collect snow from the surface of sea ice, from freely blowing snow and in sea-ice cores from Cape Byrd, Ross Sea. A range of spectroscopic, microanalytic and and microstructural approaches will be subsequently used to determine the Br distribution gradients through sea-ice, in order to shed light on how sea-ice first forms and then releases bromine species into the polar atmospheric boundary layer. proprietary
-NSF-ANT10-43485_1 A New Reconstruction of the Last West Antarctic Ice Sheet Deglaciation in the Ross Sea AMD_USAPDC STAC Catalog 2011-07-01 2015-06-30 -160, -78, -150, -68 https://cmr.earthdata.nasa.gov/search/concepts/C2532069944-AMD_USAPDC.umm_json This award supports a project to develop a better understanding of the response of the WAIS to climate change. The timing of the last deglaciation of the western Ross Sea will be improved using in situ terrestrial cosmogenic nuclides (3He, 10Be, 14C, 26Al, 36Cl) to date glacial erratics at key areas and elevations along the western Ross Sea coast. A state-of-the art ice sheet-shelf model will be used to identify mechanisms of deglaciation of the Ross Sea sector of WAIS. The model results and forcing will be compared with observations including the new cosmogenic data proposed here, with the aim of better determining and understanding the history and causes of WAIS deglaciation in the Ross Sea. There is considerable uncertainty, however, in the history of grounding line retreat from its last glacial maximum position, and virtually nothing is known about the timing of ice- surface lowering prior to ~10,000 years ago. Given these uncertainties, we are currently unable to assess one of the most important questions regarding the last deglaciation of the global ice sheets, namely as to whether the Ross Sea sector of WAIS contributed significantly to meltwater pulse 1A (MWP-1A), an extraordinarily rapid (~500-year duration) episode of ~20 m sea-level rise that occurred ~14,500 years ago. The intellectual merit of this project is that recent observations of startling changes at the margins of the Greenland and Antarctic ice sheets indicate that dynamic responses to warming may play a much greater role in the future mass balance of ice sheets than considered in current numerical projections of sea level rise. The broader impacts of this work are that it has direct societal relevance to developing an improved understanding of the response of the West Antarctic ice sheet to current and possible future environmental changes including the sea-level response to glacier and ice sheet melting due to global warming. The PI will communicate results from this project to a variety of audiences through the publication of peer-reviewed papers and by giving talks to public audiences. Finally the project will support a graduate student and undergraduate students in all phases of field-work, laboratory work and data interpretation. proprietary
NSF-ANT10-43485_1 A New Reconstruction of the Last West Antarctic Ice Sheet Deglaciation in the Ross Sea ALL STAC Catalog 2011-07-01 2015-06-30 -160, -78, -150, -68 https://cmr.earthdata.nasa.gov/search/concepts/C2532069944-AMD_USAPDC.umm_json This award supports a project to develop a better understanding of the response of the WAIS to climate change. The timing of the last deglaciation of the western Ross Sea will be improved using in situ terrestrial cosmogenic nuclides (3He, 10Be, 14C, 26Al, 36Cl) to date glacial erratics at key areas and elevations along the western Ross Sea coast. A state-of-the art ice sheet-shelf model will be used to identify mechanisms of deglaciation of the Ross Sea sector of WAIS. The model results and forcing will be compared with observations including the new cosmogenic data proposed here, with the aim of better determining and understanding the history and causes of WAIS deglaciation in the Ross Sea. There is considerable uncertainty, however, in the history of grounding line retreat from its last glacial maximum position, and virtually nothing is known about the timing of ice- surface lowering prior to ~10,000 years ago. Given these uncertainties, we are currently unable to assess one of the most important questions regarding the last deglaciation of the global ice sheets, namely as to whether the Ross Sea sector of WAIS contributed significantly to meltwater pulse 1A (MWP-1A), an extraordinarily rapid (~500-year duration) episode of ~20 m sea-level rise that occurred ~14,500 years ago. The intellectual merit of this project is that recent observations of startling changes at the margins of the Greenland and Antarctic ice sheets indicate that dynamic responses to warming may play a much greater role in the future mass balance of ice sheets than considered in current numerical projections of sea level rise. The broader impacts of this work are that it has direct societal relevance to developing an improved understanding of the response of the West Antarctic ice sheet to current and possible future environmental changes including the sea-level response to glacier and ice sheet melting due to global warming. The PI will communicate results from this project to a variety of audiences through the publication of peer-reviewed papers and by giving talks to public audiences. Finally the project will support a graduate student and undergraduate students in all phases of field-work, laboratory work and data interpretation. proprietary
+NSF-ANT10-43485_1 A New Reconstruction of the Last West Antarctic Ice Sheet Deglaciation in the Ross Sea AMD_USAPDC STAC Catalog 2011-07-01 2015-06-30 -160, -78, -150, -68 https://cmr.earthdata.nasa.gov/search/concepts/C2532069944-AMD_USAPDC.umm_json This award supports a project to develop a better understanding of the response of the WAIS to climate change. The timing of the last deglaciation of the western Ross Sea will be improved using in situ terrestrial cosmogenic nuclides (3He, 10Be, 14C, 26Al, 36Cl) to date glacial erratics at key areas and elevations along the western Ross Sea coast. A state-of-the art ice sheet-shelf model will be used to identify mechanisms of deglaciation of the Ross Sea sector of WAIS. The model results and forcing will be compared with observations including the new cosmogenic data proposed here, with the aim of better determining and understanding the history and causes of WAIS deglaciation in the Ross Sea. There is considerable uncertainty, however, in the history of grounding line retreat from its last glacial maximum position, and virtually nothing is known about the timing of ice- surface lowering prior to ~10,000 years ago. Given these uncertainties, we are currently unable to assess one of the most important questions regarding the last deglaciation of the global ice sheets, namely as to whether the Ross Sea sector of WAIS contributed significantly to meltwater pulse 1A (MWP-1A), an extraordinarily rapid (~500-year duration) episode of ~20 m sea-level rise that occurred ~14,500 years ago. The intellectual merit of this project is that recent observations of startling changes at the margins of the Greenland and Antarctic ice sheets indicate that dynamic responses to warming may play a much greater role in the future mass balance of ice sheets than considered in current numerical projections of sea level rise. The broader impacts of this work are that it has direct societal relevance to developing an improved understanding of the response of the West Antarctic ice sheet to current and possible future environmental changes including the sea-level response to glacier and ice sheet melting due to global warming. The PI will communicate results from this project to a variety of audiences through the publication of peer-reviewed papers and by giving talks to public audiences. Finally the project will support a graduate student and undergraduate students in all phases of field-work, laboratory work and data interpretation. proprietary
NSF-ANT10-43517 A new reconstruction of the last West Antarctic Ice Sheet deglaciation in the Ross Sea ALL STAC Catalog 2011-07-01 2015-06-30 163.5, -78.32, 165.35, -77.57 https://cmr.earthdata.nasa.gov/search/concepts/C2532070432-AMD_USAPDC.umm_json This award supports a project to develop a better understanding of the response of the WAIS to climate change. The timing of the last deglaciation of the western Ross Sea will be improved using in situ terrestrial cosmogenic nuclides (3He, 10Be, 14C, 26Al, 36Cl) to date glacial erratics at key areas and elevations along the western Ross Sea coast. A state-of-the art ice sheet-shelf model will be used to identify mechanisms of deglaciation of the Ross Sea sector of WAIS. The model results and forcing will be compared with observations including the new cosmogenic data proposed here, with the aim of better determining and understanding the history and causes of WAIS deglaciation in the Ross Sea. There is considerable uncertainty, however, in the history of grounding line retreat from its last glacial maximum position, and virtually nothing is known about the timing of ice- surface lowering prior to ~10,000 years ago. Given these uncertainties, we are currently unable to assess one of the most important questions regarding the last deglaciation of the global ice sheets, namely as to whether the Ross Sea sector of WAIS contributed significantly to meltwater pulse 1A (MWP-1A), an extraordinarily rapid (~500-year duration) episode of ~20 m sea-level rise that occurred ~14,500 years ago. The intellectual merit of this project is that recent observations of startling changes at the margins of the Greenland and Antarctic ice sheets indicate that dynamic responses to warming may play a much greater role in the future mass balance of ice sheets than considered in current numerical projections of sea level rise. The broader impacts of this work are that it has direct societal relevance to developing an improved understanding of the response of the West Antarctic ice sheet to current and possible future environmental changes including the sea-level response to glacier and ice sheet melting due to global warming. The PI will communicate results from this project to a variety of audiences through the publication of peer-reviewed papers and by giving talks to public audiences. Finally the project will support a graduate student and undergraduate students in all phases of field-work, laboratory work and data interpretation. proprietary
NSF-ANT10-43517 A new reconstruction of the last West Antarctic Ice Sheet deglaciation in the Ross Sea AMD_USAPDC STAC Catalog 2011-07-01 2015-06-30 163.5, -78.32, 165.35, -77.57 https://cmr.earthdata.nasa.gov/search/concepts/C2532070432-AMD_USAPDC.umm_json This award supports a project to develop a better understanding of the response of the WAIS to climate change. The timing of the last deglaciation of the western Ross Sea will be improved using in situ terrestrial cosmogenic nuclides (3He, 10Be, 14C, 26Al, 36Cl) to date glacial erratics at key areas and elevations along the western Ross Sea coast. A state-of-the art ice sheet-shelf model will be used to identify mechanisms of deglaciation of the Ross Sea sector of WAIS. The model results and forcing will be compared with observations including the new cosmogenic data proposed here, with the aim of better determining and understanding the history and causes of WAIS deglaciation in the Ross Sea. There is considerable uncertainty, however, in the history of grounding line retreat from its last glacial maximum position, and virtually nothing is known about the timing of ice- surface lowering prior to ~10,000 years ago. Given these uncertainties, we are currently unable to assess one of the most important questions regarding the last deglaciation of the global ice sheets, namely as to whether the Ross Sea sector of WAIS contributed significantly to meltwater pulse 1A (MWP-1A), an extraordinarily rapid (~500-year duration) episode of ~20 m sea-level rise that occurred ~14,500 years ago. The intellectual merit of this project is that recent observations of startling changes at the margins of the Greenland and Antarctic ice sheets indicate that dynamic responses to warming may play a much greater role in the future mass balance of ice sheets than considered in current numerical projections of sea level rise. The broader impacts of this work are that it has direct societal relevance to developing an improved understanding of the response of the West Antarctic ice sheet to current and possible future environmental changes including the sea-level response to glacier and ice sheet melting due to global warming. The PI will communicate results from this project to a variety of audiences through the publication of peer-reviewed papers and by giving talks to public audiences. Finally the project will support a graduate student and undergraduate students in all phases of field-work, laboratory work and data interpretation. proprietary
NSF-ANT10-43554_1 Activation of high-elevation alluvial fans in the Transantarctic Mountains - a proxy for Plio-Pleistocene warmth along East Antarctic ice margins AMD_USAPDC STAC Catalog 2011-07-01 2015-06-30 161.5, -77.5, 161.5, -77.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532070458-AMD_USAPDC.umm_json The PIs propose to address the question of whether ice surface melting zones developed at high elevations during warm climatic phases in the Transantarctic Mountains. Evidence from sediment cores drilled by the ANDRILL program indicates that open water in the Ross Sea could have been a source of warmth during Pliocene and Pleistocene. The question is whether marine warmth penetrated inland to the ice sheet margins. The glacial record may be ill suited to answer this question, as cold-based glaciers may respond too slowly to register brief warmth. Questions also surround possible orbital controls on regional climate and ice sheet margins. Northern Hemisphere insolation at obliquity and precession timescales is thought to control Antarctic climate through oceanic or atmospheric connections, but new thinking suggests that the duration of Southern Hemisphere summer may be more important. The PIs propose to use high elevation alluvial deposits in the Transantarctic Mountains as a proxy for inland warmth. These relatively young fans, channels, and debris flow levees stand out as visible evidence for the presence of melt water in an otherwise ancient, frozen landscape. Based on initial analyses of an alluvial fan in the Olympus Range, these deposits are sensitive recorders of rare melt events that occur at orbital timescales. For their study they will 1) map alluvial deposits using aerial photography, satellite imagery and GPS assisted field surveys to establish water sources and to quantify parameters effecting melt water production, 2) date stratigraphic sequences within these deposits using OSL, cosmogenic nuclide, and interbedded volcanic ash chronologies, 3) use paired nuclide analyses to estimate exposure and burial times, and rates of deposition and erosion, and 4) use micro and regional scale climate modeling to estimate paleoenvironmental conditions associated with melt events. This study will produce a record of inland melting from sites adjacent to ice sheet margins to help determine controls on regional climate along margins of the East Antarctic Ice Sheet to aid ice sheet and sea level modeling studies. The proposal will support several graduate and undergraduates. A PhD student will be supported on existing funding. The PIs will work with multiple K-12 schools to conduct interviews and webcasts from Antarctica and they will make follow up visits to classrooms after the field season is complete. proprietary
NSF-ANT10-43554_1 Activation of high-elevation alluvial fans in the Transantarctic Mountains - a proxy for Plio-Pleistocene warmth along East Antarctic ice margins ALL STAC Catalog 2011-07-01 2015-06-30 161.5, -77.5, 161.5, -77.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532070458-AMD_USAPDC.umm_json The PIs propose to address the question of whether ice surface melting zones developed at high elevations during warm climatic phases in the Transantarctic Mountains. Evidence from sediment cores drilled by the ANDRILL program indicates that open water in the Ross Sea could have been a source of warmth during Pliocene and Pleistocene. The question is whether marine warmth penetrated inland to the ice sheet margins. The glacial record may be ill suited to answer this question, as cold-based glaciers may respond too slowly to register brief warmth. Questions also surround possible orbital controls on regional climate and ice sheet margins. Northern Hemisphere insolation at obliquity and precession timescales is thought to control Antarctic climate through oceanic or atmospheric connections, but new thinking suggests that the duration of Southern Hemisphere summer may be more important. The PIs propose to use high elevation alluvial deposits in the Transantarctic Mountains as a proxy for inland warmth. These relatively young fans, channels, and debris flow levees stand out as visible evidence for the presence of melt water in an otherwise ancient, frozen landscape. Based on initial analyses of an alluvial fan in the Olympus Range, these deposits are sensitive recorders of rare melt events that occur at orbital timescales. For their study they will 1) map alluvial deposits using aerial photography, satellite imagery and GPS assisted field surveys to establish water sources and to quantify parameters effecting melt water production, 2) date stratigraphic sequences within these deposits using OSL, cosmogenic nuclide, and interbedded volcanic ash chronologies, 3) use paired nuclide analyses to estimate exposure and burial times, and rates of deposition and erosion, and 4) use micro and regional scale climate modeling to estimate paleoenvironmental conditions associated with melt events. This study will produce a record of inland melting from sites adjacent to ice sheet margins to help determine controls on regional climate along margins of the East Antarctic Ice Sheet to aid ice sheet and sea level modeling studies. The proposal will support several graduate and undergraduates. A PhD student will be supported on existing funding. The PIs will work with multiple K-12 schools to conduct interviews and webcasts from Antarctica and they will make follow up visits to classrooms after the field season is complete. proprietary
-NSF-ANT10-43621 A Comparison of Conjugate Auroral Electojet Indices ALL STAC Catalog 2011-06-01 2013-05-31 -180, -79.5, 180, -54.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532069751-AMD_USAPDC.umm_json The auroral electrojet index (AE) is used as an indicator of geomagnetic activity at high latitudes representing the strength of auroral electrojet currents in the Northern polar ionosphere. A similar AE index for the Southern hemisphere is not available due to lack of complete coverage the Southern auroral zone (half of which extends over the ocean) with continuous magnetometer observations. While in general global auroral phenomena are expected to be conjugate, differences have been observed in the conjugate observations from the ground and from the Earth's satellites. These differences indicate a need for an equivalent Southern auroral geomagnetic activity index. The goal of this award is to create the Southern AE (SAE) index that would accurately reflect auroral activity in that hemisphere. With this index, it would be possible to investigate the similarities and the cause of differences between the SAE and 'standard' AE index from the Northern hemisphere. It would also make it possible to identify when the SAE does not provide a reliable calculation of the Southern hemisphere activity, and to determine when it is statistically beneficial to consider the SAE index in addition to the standard AE while analyzing geospace data from the Northern and Southern polar regions. The study will address these questions by creating the SAE index and its 'near-conjugate' NAE index from collected Antarctic magnetometer data, and will analyze variations in the cross-correlation of these indices and their differences as a function of geomagnetic activity, season, Universal Time, Magnetic Local Time, and interplanetary magnetic field and solar wind plasma parameters. The broader impact resulting from the proposed effort is in its importance to the worldwide geospace scientific community that currently uses only the standard AE index in a variety of geospace models as necessary input. proprietary
NSF-ANT10-43621 A Comparison of Conjugate Auroral Electojet Indices AMD_USAPDC STAC Catalog 2011-06-01 2013-05-31 -180, -79.5, 180, -54.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532069751-AMD_USAPDC.umm_json The auroral electrojet index (AE) is used as an indicator of geomagnetic activity at high latitudes representing the strength of auroral electrojet currents in the Northern polar ionosphere. A similar AE index for the Southern hemisphere is not available due to lack of complete coverage the Southern auroral zone (half of which extends over the ocean) with continuous magnetometer observations. While in general global auroral phenomena are expected to be conjugate, differences have been observed in the conjugate observations from the ground and from the Earth's satellites. These differences indicate a need for an equivalent Southern auroral geomagnetic activity index. The goal of this award is to create the Southern AE (SAE) index that would accurately reflect auroral activity in that hemisphere. With this index, it would be possible to investigate the similarities and the cause of differences between the SAE and 'standard' AE index from the Northern hemisphere. It would also make it possible to identify when the SAE does not provide a reliable calculation of the Southern hemisphere activity, and to determine when it is statistically beneficial to consider the SAE index in addition to the standard AE while analyzing geospace data from the Northern and Southern polar regions. The study will address these questions by creating the SAE index and its 'near-conjugate' NAE index from collected Antarctic magnetometer data, and will analyze variations in the cross-correlation of these indices and their differences as a function of geomagnetic activity, season, Universal Time, Magnetic Local Time, and interplanetary magnetic field and solar wind plasma parameters. The broader impact resulting from the proposed effort is in its importance to the worldwide geospace scientific community that currently uses only the standard AE index in a variety of geospace models as necessary input. proprietary
+NSF-ANT10-43621 A Comparison of Conjugate Auroral Electojet Indices ALL STAC Catalog 2011-06-01 2013-05-31 -180, -79.5, 180, -54.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532069751-AMD_USAPDC.umm_json The auroral electrojet index (AE) is used as an indicator of geomagnetic activity at high latitudes representing the strength of auroral electrojet currents in the Northern polar ionosphere. A similar AE index for the Southern hemisphere is not available due to lack of complete coverage the Southern auroral zone (half of which extends over the ocean) with continuous magnetometer observations. While in general global auroral phenomena are expected to be conjugate, differences have been observed in the conjugate observations from the ground and from the Earth's satellites. These differences indicate a need for an equivalent Southern auroral geomagnetic activity index. The goal of this award is to create the Southern AE (SAE) index that would accurately reflect auroral activity in that hemisphere. With this index, it would be possible to investigate the similarities and the cause of differences between the SAE and 'standard' AE index from the Northern hemisphere. It would also make it possible to identify when the SAE does not provide a reliable calculation of the Southern hemisphere activity, and to determine when it is statistically beneficial to consider the SAE index in addition to the standard AE while analyzing geospace data from the Northern and Southern polar regions. The study will address these questions by creating the SAE index and its 'near-conjugate' NAE index from collected Antarctic magnetometer data, and will analyze variations in the cross-correlation of these indices and their differences as a function of geomagnetic activity, season, Universal Time, Magnetic Local Time, and interplanetary magnetic field and solar wind plasma parameters. The broader impact resulting from the proposed effort is in its importance to the worldwide geospace scientific community that currently uses only the standard AE index in a variety of geospace models as necessary input. proprietary
NSF-ANT10-44978 BICEP2 and SPUD - A Search for Inflation with Degree-Scale Polarimetry from the South Pole AMD_USAPDC STAC Catalog 2008-05-15 2017-09-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532070162-AMD_USAPDC.umm_json BICEP2 and SPUD - A Search for Inflation with Degree-Scale Polarimetry from the South Pole. The proposed work is a four-year program of research activities directed toward upgrading the BICEP (Background Imaging of Cosmic Extragalactic Polarization) telescope operating at South Pole since early 2006 to reach far =stretching goals of detection of the Cosmic Gravitational-wave Background (CGB). This telescope is a first Cosmic Microwave Background (CMB) B-mode polarimeter, specifically designed to search for CGB signatures while mapping ~2% of the southern sky that is free of the Milky Way foreground galactic radiation at 100 GH and 150 GHz. The BICEP1 telescope will reach its designed sensitivity by the end of 2008. A coordinated series of upgrades to BICEP1 will provide the increased sensitivity and more exacting control of instrumental effects and potential confusion from galactic foregrounds necessary to search for the B-mode signal more deeply through space. A powerful new 150 GHz receiver, BICEP2, will replace the current detector at the beginning of 2009, increasing the mapping speed almost ten-fold. In 2010, the first of a series of compact, mechanically-cooled receivers (called SPUD - Small Polarimeter Upgrade for DASI) will be deployed on the existing DASI mount and tower, providing similar mapping speed at 100 GHz in parallel with BICEP2. The latter instrument will reach (and exceed with the addition of a SPUD polarimeter) the target sensitivity r = 0.15 set forth by the Interagency (NSF/NASA/DoE) Task Force on CMB Research for a future space mission dedicated to the detection and characterization of primordial gravitational waves. This Task Force has identified detection of the Inflation's gravitational waves as the number one priority for the modern cosmology. More broadly, as the cosmology captures a lot of the public imagination, it is a remarkably effective vehicle for stimulating interest in basic science. The CGB detection would be to Inflation what the discovery of the CMB radiation was to the Big Bang. The project will contribute to the training of the next generation of cosmologists by integrating graduate and undergraduate education with the technology and instrumentation development, astronomical observations and scientific analysis. Sharing of the forefront research results with public extends the new knowledge beyond the universities. This project will be undertaken in collaboration between the California Institute of Technology and the University of Chicago. proprietary
NSF-ANT10-48343_1 CAREER: Deciphering Antarctic Climate Variability during the Temperate/Polar Transition and Improving Climate Change Literacy in Louisiana through a Companion Outreach Program AMD_USAPDC STAC Catalog 2011-03-01 2016-02-29 57.217, -70.373, 153.359, -63.664 https://cmr.earthdata.nasa.gov/search/concepts/C2532069731-AMD_USAPDC.umm_json Intellectual Merit: The PI proposes a high-resolution paleoenvironmental study of pollen, spore, fresh-water algae, and dinoflagellate cyst assemblages to investigate the palynological record of sudden warming events in the Antarctic as recorded by the ANDRILL SMS drill core and terrestrial sections. These data will be used to derive causal mechanisms for these rapid climate events. Terrestrial samples will be obtained at various altitudes in the Dry Valleys region. The pollen and spores will provide data on atmospheric conditions, while the algae will provide data on sea-surface conditions. These data will help identify the triggers for sudden climatic shifts. If they are caused by changes in oceanic currents, a signal will be visible in the dinocyst assemblages first as currents influence their distribution. Conversely, if these shifts are triggered by atmospheric factors, then the shifts will first affect plants and be visible in the pollen record. Broader impacts: The PI proposes a suite of activities to bring field-based climate change research to a broader audience. The PI will advise a diverse group of students and educators. The palynological data collected as part of this research will be utilized, in part, to develop new lectures on Antarctic palynology and these new lectures will be made available via a collaboration with the LSU HHMI program. In addition, the PI will direct three Louisiana middle-school teachers as they pursue a Masters of Natural Science for science educators. These teachers will help the PI develop a professional development program for science teachers. Community-based activities will be organized to raise science awareness and alert students and the public of opportunities in science. proprietary
NSF-ANT10-63592_1 Application for an Early-concept Grant for Exploratory Reasearch (EAGER) to develop a Pathway/Genome Database (PGDB) for the Southern Ocean Haptophyte Phaeocystis Antarctica. AMD_USAPDC STAC Catalog 2011-05-15 2015-04-30 -75.8, -67.12, -62.37, -61.08 https://cmr.earthdata.nasa.gov/search/concepts/C2532069964-AMD_USAPDC.umm_json Phaeocystis antarctica is capable of forming blooms that are denser and more extensive than any other member of the Southern Ocean phytoplankton community. The factors that enable P Antarctica to dominate its competitors are not clear but are likely related to its colonial lifestyle. The goal of the project is to map all the reactions in metabolic pathways that are key to defining the ecological niche of Phaeocystis antarctica by developing a Pathway/Genome Database (PGDB) using Pathway Tools software. The investigators will assign proteins and enzymes to key pathways in P. Antarctica, continually improve and edit the database as the full Phaeocystis genome comes online, and host the database on the BioCyc webpage. The end product will be the first database for a eukaryotic phytoplankton genome where researchers can query extant metabolic pathways and place new proteins and enzymes of interest within metabolic networks. The risk is that a substantial percentage of catalytic enzymes may belong to pathways that are poorly characterized. The science impact is to link genomes to metabolic potential in the context of Phaeocystis life history but also in comparison to other organisms across the tree of life. The education and outreach includes work with a high school teacher and intern and curriculum development. proprietary
@@ -12573,8 +12573,8 @@ NSIDC-0314_1 Atmospheric CO2 and Climate: Byrd Ice Core, Antarctica AMD_USAPDC S
NSIDC-0315_1 Atmospheric CO2 and Climate: Taylor Dome Ice Core, Antarctica AMD_USAPDC STAC Catalog 1970-01-01 158, -77.666667, 158, -77.666667 https://cmr.earthdata.nasa.gov/search/concepts/C2532070838-AMD_USAPDC.umm_json Using new and existing ice core CO2 data from 65 - 30 ka BP a new chronology for Taylor Dome ice core CO2 is established and synchronized with Greenland ice core records to study how high latitude climate change and the carbon cycle were linked during the last glacial period. The new data and chronology should provide a better target for models attempting to explain CO2 variability and abrupt climate change. proprietary
NSIDC-0318_1 Antarctic Mean Annual Temperature Map AMD_USAPDC STAC Catalog 1957-01-01 2003-12-31 -180, -90, 180, -65 https://cmr.earthdata.nasa.gov/search/concepts/C2532070844-AMD_USAPDC.umm_json The Mean Annual Temperature map was calculated by creating a contour map using compiled 10 meter firn temperature data from NSIDC and other mean annual temperature data from both cores and stations. The 10 meter data contains temperature measurements dating back to 1957 and the International Geophysical Year, including measurements from several major recent surveys. Data cover the entire continental ice sheet and several ice shelves, but coverage density is generally low. Data are stored in Microsoft Excel and Tagged Image File Format (TIFF), and are available sporadically from 1957 to 2003 via FTP. proprietary
NSIDC-0321_1 Global EASE-Grid 8-day Blended SSM/I and MODIS Snow Cover, Version 1 NSIDCV0 STAC Catalog 2000-03-05 2008-02-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1386250333-NSIDCV0.umm_json This data set comprises global, 8-day Snow-Covered Area (SCA) and Snow Water Equivalent (SWE) data from 2000 through 2008. Global SWE data are derived from the Special Sensor Microwave Imager (SSM/I) and are enhanced with MODIS/Terra Snow Cover 8-Day Level 3 Global 0.05 degree Climate Modeling Grid (CMG) data. Global data are gridded to the Northern and Southern 25 km Equal-Area Scalable Earth Grids (EASE-Grids). These data are suitable for continental-scale time-series studies of snow cover and snow water equivalent. proprietary
-NSIDC-0326_1 Ablation Rates of Taylor Glacier, Antarctica AMD_USAPDC STAC Catalog 2002-11-19 2011-01-12 160.1, -77.9, 162.2, -77.6 https://cmr.earthdata.nasa.gov/search/concepts/C2532070867-AMD_USAPDC.umm_json This data set provides glacier surface ablation rates for a network of approximately 250 sites on Taylor Glacier, spanning a period from 2003 to 2011. Here sublimation is the dominant ablation mechanism, though a few sites have accumulation. Ablation data are provided in meters water equivalent per year. Data are available via FTP in space-delimited ASCII format. proprietary
NSIDC-0326_1 Ablation Rates of Taylor Glacier, Antarctica ALL STAC Catalog 2002-11-19 2011-01-12 160.1, -77.9, 162.2, -77.6 https://cmr.earthdata.nasa.gov/search/concepts/C2532070867-AMD_USAPDC.umm_json This data set provides glacier surface ablation rates for a network of approximately 250 sites on Taylor Glacier, spanning a period from 2003 to 2011. Here sublimation is the dominant ablation mechanism, though a few sites have accumulation. Ablation data are provided in meters water equivalent per year. Data are available via FTP in space-delimited ASCII format. proprietary
+NSIDC-0326_1 Ablation Rates of Taylor Glacier, Antarctica AMD_USAPDC STAC Catalog 2002-11-19 2011-01-12 160.1, -77.9, 162.2, -77.6 https://cmr.earthdata.nasa.gov/search/concepts/C2532070867-AMD_USAPDC.umm_json This data set provides glacier surface ablation rates for a network of approximately 250 sites on Taylor Glacier, spanning a period from 2003 to 2011. Here sublimation is the dominant ablation mechanism, though a few sites have accumulation. Ablation data are provided in meters water equivalent per year. Data are available via FTP in space-delimited ASCII format. proprietary
NSIDC-0334_1 Airborne Laser Altimetry of the Thwaites Glacier Catchment, West Antarctica AMD_USAPDC STAC Catalog 2004-12-10 2005-01-29 -130, -80, -95, -75 https://cmr.earthdata.nasa.gov/search/concepts/C2532070878-AMD_USAPDC.umm_json This data set includes airborne altimetry collected over the catchment and main trunk of Thwaites Glacier, one of Antarctica's most active ice streams. The airborne altimetry comprises 35,000 line-kilometers sampled at 20 meters along track. The full dataset has an internal error of �20 cm; a primary subset has an error of �8 cm. We find a +20 cm bias with Geoscience Laser Altimeter System data over a flat interior region. These data will serve as an additional temporal reference for the evolution of Thwaites Glacier surface, as well as aid the construction of future high resolution Digital Elevation Models (DEM). Line data are available in space-delimited ASCII format and are available via FTP. proprietary
NSIDC-0334_1 Airborne Laser Altimetry of the Thwaites Glacier Catchment, West Antarctica ALL STAC Catalog 2004-12-10 2005-01-29 -130, -80, -95, -75 https://cmr.earthdata.nasa.gov/search/concepts/C2532070878-AMD_USAPDC.umm_json This data set includes airborne altimetry collected over the catchment and main trunk of Thwaites Glacier, one of Antarctica's most active ice streams. The airborne altimetry comprises 35,000 line-kilometers sampled at 20 meters along track. The full dataset has an internal error of �20 cm; a primary subset has an error of �8 cm. We find a +20 cm bias with Geoscience Laser Altimeter System data over a flat interior region. These data will serve as an additional temporal reference for the evolution of Thwaites Glacier surface, as well as aid the construction of future high resolution Digital Elevation Models (DEM). Line data are available in space-delimited ASCII format and are available via FTP. proprietary
NSIDC-0336_1 Antarctic Subglacial Lake Classification Inventory AMD_USAPDC STAC Catalog 1998-12-01 2001-02-28 -160, -90, 15, -70 https://cmr.earthdata.nasa.gov/search/concepts/C2532070882-AMD_USAPDC.umm_json This data set is an Antarctic radar-based subglacial lake classification collection, which focuses on the radar reflection properties of each given lake. The Subglacial lakes are separated into four categories specified by radar reflection properties. Additional information includes: latitude, longitude, length (in kilometers), hydro-potential (in meters), bed elevation (in meters above WGS84), and ice thickness (in meters). Source data used to compile this data set were collected between 1998 and 2001. Data are available via FTP as a Microsoft Excel Spreadsheet (XLS), and Tagged Image File Format (TIF). proprietary
@@ -12635,8 +12635,8 @@ NSIDC-0611_4 EASE-Grid Sea Ice Age, Version 4 NSIDCV0 STAC Catalog 1984-01-01 20
NSIDC-0627_1 Borehole Temperatures at Pine Island Glacier, Antarctica AMD_USAPDC STAC Catalog 2012-12-20 2013-05-10 -100.5, -75.1, -100.5, -75.1 https://cmr.earthdata.nasa.gov/search/concepts/C2532070657-AMD_USAPDC.umm_json This data set is a time series of borehole temperatures at different depths from three thermistor strings deployed in three boreholes drilled through the Pine Island Glacier ice shelf, Antarctica. proprietary
NSIDC-0630_1 MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature ESDR V001 NSIDC_ECS STAC Catalog 1978-10-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1371883515-NSIDC_ECS.umm_json This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, is an improved, enhanced-resolution, gridded passive microwave Earth System Data Record (ESDR) for monitoring cryospheric and hydrologic time series from SMMR, SSM/I-SSMIS, and AMSR-E. It is derived from the most mature and available Level-2 satellite passive microwave records from 1978 through the present. proprietary
NSIDC-0630_2 Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature ESDR V002 NSIDC_ECS STAC Catalog 1978-10-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776464104-NSIDC_ECS.umm_json The Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature ESDR, Version 2 data set is a multi-sensor Level 3 Earth Science Data Record (ESDR) with improvements upon Version 1 in cross-sensor calibration and quality checking, modern file formats, better quality control, improved projection grids, and local time-of-day (LTOD) processing. These data are gridded to three EASE-Grid 2.0 projections (North Azimuthal, South Azimuthal, and Cylindrical) and include enhanced-resolution imagery, as well as coarse-resolution, averaged imagery. Inputs include brightness temperature data from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave/Imager (SSM/I), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2). proprietary
-NSIDC-0634_1 Alaska Tidewater Glacier Terminus Positions, Version 1 NSIDCV0 STAC Catalog 1948-01-01 2012-12-31 -151, 56.5, -132, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C1386250732-NSIDCV0.umm_json This data set contains Alaska tidewater glacier terminus positions digitized from USGS topographic maps and Landsat images. proprietary
NSIDC-0634_1 Alaska Tidewater Glacier Terminus Positions, Version 1 ALL STAC Catalog 1948-01-01 2012-12-31 -151, 56.5, -132, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C1386250732-NSIDCV0.umm_json This data set contains Alaska tidewater glacier terminus positions digitized from USGS topographic maps and Landsat images. proprietary
+NSIDC-0634_1 Alaska Tidewater Glacier Terminus Positions, Version 1 NSIDCV0 STAC Catalog 1948-01-01 2012-12-31 -151, 56.5, -132, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C1386250732-NSIDCV0.umm_json This data set contains Alaska tidewater glacier terminus positions digitized from USGS topographic maps and Landsat images. proprietary
NSIDC-0637_1 Borehole Temperature Measurement in WDC05A in January 2008 and January 2009 AMD_USAPDC STAC Catalog 2008-01-01 2009-01-01 -112.125, -79.463, -112.125, -79.463 https://cmr.earthdata.nasa.gov/search/concepts/C2532071518-AMD_USAPDC.umm_json This data set includes borehole temperature measurements performed in January 2008 and January 2009 at the West Antarctic Ice sheet divide from the 300 m hole WDC05A. proprietary
NSIDC-0642_2 MEaSUREs Annual Greenland Outlet Glacier Terminus Positions from SAR Mosaics V002 NSIDC_ECS STAC Catalog 1972-09-16 2021-03-25 -75, 60, -14, 83 https://cmr.earthdata.nasa.gov/search/concepts/C2139015179-NSIDC_ECS.umm_json "This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, consists of annual, digitized (polyline) ice front positions for 239 outlet glaciers in Greenland. Ice front positions are derived from Sentinel-1A, Sentinel-1B, and RADARSAT-1 synthetic aperture radar (SAR) mosaics, plus imagery from Landsat 1 through Landsat 5 and Landsat 7 and Landsat 8. Although temporal coverage varies by glacier, data are available for the winter seasons 1972–1973 through 2020–2021. Data are provided as shapefiles. See Greenland Ice Mapping Project (GrIMP) for related data." proprietary
NSIDC-0644_1 Greenland Annual Accumulation along the EGIG Line, 1959–2004, from Airborne Radar and Neutron Probe Densities, Version 1 NSIDCV0 STAC Catalog 1959-10-01 2004-09-30 -42.838297, 70.585609, -36.232431, 71.207715 https://cmr.earthdata.nasa.gov/search/concepts/C1436304012-NSIDCV0.umm_json This data set reports mean annual snow accumulation rates in meters water equivalent (m·w.e.) from 1959 to 2004 along a 250 km segment of the Expéditions Glaciologiques Internationales au Groenland (EGIG) line. Accumulation rates are derived from Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) data and high resolution neutron-probe (NP) density profiles. proprietary
@@ -12698,8 +12698,8 @@ NVAP_OCEAN_Total-Precipitable-Water_1 NASA Water Vapor Project MEaSUREs (NVAP-M)
NVAP_WEATHER_Layered-Precipitable-Water_1 NASA Water Vapor Project MEaSUREs (NVAP-M) WEATHER Layered Precipitable Water LARC_ASDC STAC Catalog 1988-01-01 2009-12-01 180, -90, -179.9, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1596748680-LARC_ASDC.umm_json NVAP_WEATHER_Layered-Precipitable-Water data set is designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Land GPS sites were added beginning in 1997. The new NASA Water Vapor Project (NVAP) data sets are produced under the NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program and is named NVAP-M. It supersedes the previous NVAP data set. NVAP-M continues the legacy of providing high-quality, model-independent global estimates of total column and layered water vapor. The use of improved, intercalibrated data sets and algorithms that were not available for the heritage NVAP data set results in an improved and extended water vapor data set that is stable enough for climate research and of a resolution appropriate for studies on smaller spatial and temporal scales. The true value of NVAP-M will be seen in outcomes from applied and research users of the data set in various fields. Some initial NVAP-M findings are presented in Vonder Haar et al. (2012). In addition to the time-dependent artifacts present in the previous NVAP data set, a wealth of new data has become available since the last NVAP processing in 2003. These include an additional SSM/I instrument, additional NOAA satellites, the NASA Earth Observing System (EOS)-Aqua Satellite, which carries the Atmospheric Infrared Sounder (AIRS), as well as water vapor information from Global Positioning System (GPS) satellites. This extension and reprocessing effort increases the temporal coverage from 14 to 22 (1988-2009) years, making the data set more useful and consistent for investigation of the long-term trends which are hypothesized to occur as Earth warms. In addition to the long-standing daily, 1-degree gridded Total Precipitable Water (TPW) and layered Precipitable Water (PW) products, NVAP-M includes additional products geared towards different scientific needs. Three separate processing streams produced products directed towards specific research goals. These are NVAP-M Climate, designed to provide the most stable water vapor data set over time for use in climate applications, and NVAP-M Weather, designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Additionally, an ocean-only (NVAP-M Ocean) version includes only data from the SSM/I and is intended to mirror other available SSM/I-only water vapor data sets. proprietary
NVAP_WEATHER_Total-Precipitable-Water_1 NASA Water Vapor Project MEaSUREs (NVAP-M) NVAP WEATHER Total Precipitable Water LARC_ASDC STAC Catalog 1988-01-01 2009-12-01 180, -90, -179.9, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1600355222-LARC_ASDC.umm_json NVAP_WEATHER_Total-Precipitable-Water data set is designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. The new NASA Water Vapor Project (NVAP) data sets are produced under the NASA Making Earth Science Data Records for Use in Research Environments (MEaSUREs) program and is named NVAP-M. It supersedes the previous NVAP data set. NVAP-M continues the legacy of providing high-quality, model-independent global estimates of total column and layered water vapor. The use of improved, intercalibrated data sets and algorithms that were not available for the heritage NVAP data set results in an improved and extended water vapor data set that is stable enough for climate research and of a resolution appropriate for studies on smaller spatial and temporal scales. The true value of NVAP-M will be seen in outcomes from applied and research users of the data set in various fields. Some initial NVAP-M findings are presented in Vonder Haar et al. (2012). In addition to the time-dependent artifacts present in the previous NVAP data set, a wealth of new data has become available since the last NVAP processing in 2003. These include an additional SSM/I instrument, additional NOAA satellites, the NASA Earth Observing System (EOS)-Aqua Satellite, which carries the Atmospheric Infrared Sounder (AIRS), as well as water vapor information from Global Positioning System (GPS) satellites. This extension and reprocessing effort increases the temporal coverage from 14 to 22 (1988-2009) years, making the data set more useful and consistent for investigation of the long-term trends which are hypothesized to occur as Earth warms. In addition to the long-standing daily, 1-degree gridded Total Precipitable Water (TPW) and layered Precipitable Water (PW) products, NVAP-M includes additional products geared towards different scientific needs. Three separate processing streams produced products directed towards specific research goals. These are NVAP-M Climate, designed to provide the most stable water vapor data set over time for use in climate applications, and NVAP-M Weather, designed to provide higher spatial and temporal resolution products for use in studies on shorter time scales as well as weather case studies. Additionally, an ocean-only (NVAP-M Ocean) version includes only data from the SSM/I and is intended to mirror other available SSM/I-only water vapor data sets. proprietary
NWS0007 Compilation/Evaluation of Historical Tsunamis in the Pacific Using the USGS/NEIC Earthquake Data, NOAA/NGDC Tsunami Data, and Imamura-Iida Scale CEOS_EXTRA STAC Catalog 1690-01-01 95, -60, -65, 65 https://cmr.earthdata.nasa.gov/search/concepts/C2231550342-CEOS_EXTRA.umm_json These data sets are based on an area-by-area study of the Pacific Basin to document historical tsunamis and quantify historical coastal damage both near the source and at far-field locations. An operational modification of the Imamura-Iida Scale is used for this purpose. proprietary
-NWT_Burn_Severity_Maps_1694_1 ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015 ALL STAC Catalog 2014-05-01 2015-10-01 -124.03, 58.29, -108.83, 65.55 https://cmr.earthdata.nasa.gov/search/concepts/C2143402644-ORNL_CLOUD.umm_json This dataset provides maps at 30-m resolution of landscape surface burn severity (surface litter and soil organic layers) from the 2014-2015 fires in the Northwest Territories and Northern Alberta, Canada. The maps were derived from Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) imagery and two separate multiple linear regression models trained with field data; one for the Plains and a second for the Shield ecoregion. Field observations were used to estimate area burned in each of five severity classes (unburned, singed, light, moderate, severely burned) in six stratified randomly selected plots of 10 x 10-m in size across a 1-ha site. Using this five class scale a burn severity index (BSI) for each 1-ha site was calculated using multiple weighted and averaged field parameters. Pre- and post-fire phenologically paired Landsat 8 images were used to model the five discrete severity classes using midpoints as breaks. proprietary
NWT_Burn_Severity_Maps_1694_1 ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015 ORNL_CLOUD STAC Catalog 2014-05-01 2015-10-01 -124.03, 58.29, -108.83, 65.55 https://cmr.earthdata.nasa.gov/search/concepts/C2143402644-ORNL_CLOUD.umm_json This dataset provides maps at 30-m resolution of landscape surface burn severity (surface litter and soil organic layers) from the 2014-2015 fires in the Northwest Territories and Northern Alberta, Canada. The maps were derived from Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) imagery and two separate multiple linear regression models trained with field data; one for the Plains and a second for the Shield ecoregion. Field observations were used to estimate area burned in each of five severity classes (unburned, singed, light, moderate, severely burned) in six stratified randomly selected plots of 10 x 10-m in size across a 1-ha site. Using this five class scale a burn severity index (BSI) for each 1-ha site was calculated using multiple weighted and averaged field parameters. Pre- and post-fire phenologically paired Landsat 8 images were used to model the five discrete severity classes using midpoints as breaks. proprietary
+NWT_Burn_Severity_Maps_1694_1 ABoVE: Burn Severity of Soil Organic Matter, Northwest Territories, Canada, 2014-2015 ALL STAC Catalog 2014-05-01 2015-10-01 -124.03, 58.29, -108.83, 65.55 https://cmr.earthdata.nasa.gov/search/concepts/C2143402644-ORNL_CLOUD.umm_json This dataset provides maps at 30-m resolution of landscape surface burn severity (surface litter and soil organic layers) from the 2014-2015 fires in the Northwest Territories and Northern Alberta, Canada. The maps were derived from Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) imagery and two separate multiple linear regression models trained with field data; one for the Plains and a second for the Shield ecoregion. Field observations were used to estimate area burned in each of five severity classes (unburned, singed, light, moderate, severely burned) in six stratified randomly selected plots of 10 x 10-m in size across a 1-ha site. Using this five class scale a burn severity index (BSI) for each 1-ha site was calculated using multiple weighted and averaged field parameters. Pre- and post-fire phenologically paired Landsat 8 images were used to model the five discrete severity classes using midpoints as breaks. proprietary
NW_microcosm_results_1 Mineralisation results using 14C octadecane at a range of water, nutrient levels and freeze thaw cycles AU_AADC STAC Catalog 2001-06-01 2001-10-29 110.45953, -66.31249, 110.59637, -66.261 https://cmr.earthdata.nasa.gov/search/concepts/C1214313663-AU_AADC.umm_json Geochemical, microbial and 14C data on remediation of petroleum hydrocarbons in Antarctica. This record is part of ASAC project 1163 (ASAC_1163). Microcosm study using Old Casey petroleum hydrocarbon contaminated sediment investgating the effect of water, nutrients and freze/thaw cycles on biodegradation. Temperature range -4 to 28 degrees. Microcosms with three different levels of nutrients and three different levels of water were investigated. The experiment was run over 95 days. Degradation was traced by radiometric methods and total aliphatic hydrocarbons were measured by gas chromatography. Radiometric data in file radiometric_01.xls, Gas Chromatography data in file gc_01.xls. This work was completed as part of ASAC project 1163 (ASAC_1163). The radiometric spreadsheet is divided up as follows: CODES is a summary of what went into each microcosm. CALCULATIONS is how much nutrients, water, radioactivity was added to the sediment. SUMMARY is what went into each microcosm flask. CT1, CT2 etc is the raw data, what was measured and calculations of radioactivity and recovery of isotope. Note that the Evaporation flasks (i.e., E10a) the number refers to the temperature that the flasks were incubated at, 'a' and 'b' refer to duplicates. AVERAGE is the average recoveries and first order rates of the triplicate microcosm for each treatment. GRAPHS is the graphs. The fields in this dataset are: Days Hours Initial flask weight NaOH removed NaOH added Weight of NaOH (g) Count (dpm) Discarded dpm's Volume NaOH (ml) dpm in trap Absolute dpm's %dpm recovered millimole octadecane mineralised proprietary
NatalMuseum Natal Museum - Mollusc Collection (Bivalvia and Gastropoda) CEOS_EXTRA STAC Catalog 1894-01-01 2005-07-09 11.38667, -43.19167, 55.13334, -11 https://cmr.earthdata.nasa.gov/search/concepts/C2232477685-CEOS_EXTRA.umm_json The Natal Museum's Department of Mollusca had its origins in the shell collection and library of Henry Burnup, a dedicated amateur who was honorary curator of molluscs until his death in 1928. Subsequently, the collection has been expanded many times over through field work, donation, exchange and purchase. Its historical value was greatly increased by absorption of important shell collections housed the Transvaal Museum (1978) and Albany Museum (1980), as well as the Rodney Wood collection from the Seychelles received from the Mutare Museum in Zimbabwe and the Kurt Grosch collection, built up over 25 years of residence in northern Mozambique. The mollusc collection now ranks among the 15 largest in the world and is certainly the largest both in Africa and on the Indian Ocean rim. It currently contains 7233 Bivalvia records, and 20112 Gastropoda records (total 27345 records of 282 families). The collection will be updated in the near future. proprietary
Nested_DGGE_1 Molecular comparison of bacterial diversity in uncontaminated and hydrocarbon contaminated marine sediment AU_AADC STAC Catalog 1997-11-01 1998-11-30 110.32471, -66.51764, 110.67627, -66.2226 https://cmr.earthdata.nasa.gov/search/concepts/C1214313662-AU_AADC.umm_json Sediment samples which were originally collected as part of ASAC 868 (ASAC_868) are now being investigated using molecular microbial techniques as part of ASAC 1228 (ASAC_1228). Samples were collected in a nested survey design in two hydrocarbon impacted areas and two unimpacted areas. Denaturing gradient gel electrophoresis (DGGE) of a region of the 16S RNA gene was used to investigate the microbial community structure. Banding patterns obtained from the DGGE were transformed into a presence / absence matrix and analysed with a multivariate statistical approach. The download file contains an excel spreadsheet, a csv version of the data, plus a readme file. proprietary
@@ -12854,68 +12854,68 @@ OCO3_L2_Standard_10 OCO-3 Level 2 geolocated XCO2 retrievals results, physical m
OCO3_L2_Standard_10r OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V10r (OCO3_L2_Standard) at GES DISC GES_DISC STAC Catalog 2019-08-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2082387252-GES_DISC.umm_json Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. proprietary
OCO3_L2_Standard_11 OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Forward Processing V11 (OCO3_L2_Standard) at GES DISC GES_DISC STAC Catalog 2019-08-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3272764617-GES_DISC.umm_json Version 11 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. proprietary
OCO3_L2_Standard_11r OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V11r (OCO3_L2_Standard) at GES DISC GES_DISC STAC Catalog 2019-08-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.umm_json Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r. The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations. The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. proprietary
-OCTS_L1_1 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034340-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L1_1 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034340-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L1_1 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034340-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L1_2 ADEOS-I OCTS Level-1A Data, version 2 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834679-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L1_2 ADEOS-I OCTS Level-1A Data, version 2 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834679-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_IOP_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Regional Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034360-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_IOP_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Regional Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034360-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_IOP_2022.0 ADEOS-I OCTS Level-2 Regional Inherent Optical Properties (IOP) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834690-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_IOP_2022.0 ADEOS-I OCTS Level-2 Regional Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834690-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L2_OC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Ocean Color (OC) Regional Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034380-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_OC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Ocean Color (OC) Regional Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034380-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L2_OC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Ocean Color (OC) Regional Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034380-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_OC_2022.0 ADEOS-I OCTS Level-2 Regional Ocean Color (OC) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834711-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L2_OC_2022.0 ADEOS-I OCTS Level-2 Regional Ocean Color (OC) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834711-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_CHL_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Chlorophyll (CHL) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034361-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_CHL_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Chlorophyll (CHL) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034361-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3b_CHL_2022.0 ADEOS-I OCTS Level-3 Global Binned Chlorophyll (CHL) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834719-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_CHL_2022.0 ADEOS-I OCTS Level-3 Global Binned Chlorophyll (CHL) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834719-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3b_CHL_2022.0 ADEOS-I OCTS Level-3 Global Binned Chlorophyll (CHL) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834719-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_IOP_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034381-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_IOP_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034381-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3b_IOP_2022.0 ADEOS-I OCTS Level-3 Global Binned Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834731-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_IOP_2022.0 ADEOS-I OCTS Level-3 Global Binned Inherent Optical Properties (IOP) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834731-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3b_IOP_2022.0 ADEOS-I OCTS Level-3 Global Binned Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834731-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_KD_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034362-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_KD_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034362-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_KD_2022.0 ADEOS-I OCTS Level-3 Global Binned Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834737-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_KD_2022.0 ADEOS-I OCTS Level-3 Global Binned Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834737-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_PAR_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Photosynthetically Available Radiation (PAR) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034341-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_PAR_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Photosynthetically Available Radiation (PAR) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034341-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3b_PAR_2022.0 ADEOS-I OCTS Level-3 Global Binned Photosynthetically Active Radiation (PAR) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834749-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_PAR_2022.0 ADEOS-I OCTS Level-3 Global Binned Photosynthetically Active Radiation (PAR) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834749-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3b_PAR_2022.0 ADEOS-I OCTS Level-3 Global Binned Photosynthetically Active Radiation (PAR) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834749-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_PIC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Inorganic Carbon (PIC) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034363-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_PIC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Inorganic Carbon (PIC) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034363-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3b_PIC_2022.0 ADEOS-I OCTS Level-3 Global Binned Particulate Inorganic Carbon (PIC) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834762-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_PIC_2022.0 ADEOS-I OCTS Level-3 Global Binned Particulate Inorganic Carbon (PIC) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834762-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3b_POC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034382-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3b_PIC_2022.0 ADEOS-I OCTS Level-3 Global Binned Particulate Inorganic Carbon (PIC) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834762-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_POC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034382-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3b_POC_2022.0 ADEOS-I OCTS Level-3 Global Binned Particulate Organic Carbon (POC) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834780-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3b_POC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034382-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_POC_2022.0 ADEOS-I OCTS Level-3 Global Binned Particulate Organic Carbon (POC) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834780-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3b_POC_2022.0 ADEOS-I OCTS Level-3 Global Binned Particulate Organic Carbon (POC) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834780-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_RRS_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Remote-Sensing Reflectance (RRS) Global Binned Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034364-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_RRS_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Remote-Sensing Reflectance (RRS) Global Binned Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034364-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_RRS_2022.0 ADEOS-I OCTS Level-3 Global Binned Remote-Sensing Reflectance (RRS) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834794-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3b_RRS_2022.0 ADEOS-I OCTS Level-3 Global Binned Remote-Sensing Reflectance (RRS) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834794-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_CHL_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Chlorophyll (CHL) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034342-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_CHL_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Chlorophyll (CHL) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034342-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3m_CHL_2022.0 ADEOS-I OCTS Level-3 Global Mapped Chlorophyll (CHL) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834809-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_CHL_2022.0 ADEOS-I OCTS Level-3 Global Mapped Chlorophyll (CHL) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834809-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3m_CHL_2022.0 ADEOS-I OCTS Level-3 Global Mapped Chlorophyll (CHL) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834809-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_IOP_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034365-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_IOP_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034365-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_IOP_2022.0 ADEOS-I OCTS Level-3 Global Mapped Inherent Optical Properties (IOP) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834819-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_IOP_2022.0 ADEOS-I OCTS Level-3 Global Mapped Inherent Optical Properties (IOP) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834819-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3m_KD_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034383-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_KD_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034383-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3m_KD_2022.0 ADEOS-I OCTS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834825-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3m_KD_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034383-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_KD_2022.0 ADEOS-I OCTS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834825-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3m_KD_2022.0 ADEOS-I OCTS Level-3 Global Mapped Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834825-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PAR_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Photosynthetically Available Radiation (PAR) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034366-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PAR_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Photosynthetically Available Radiation (PAR) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034366-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3m_PAR_2022.0 ADEOS-I OCTS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834829-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PAR_2022.0 ADEOS-I OCTS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834829-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3m_PAR_2022.0 ADEOS-I OCTS Level-3 Global Mapped Photosynthetically Active Radiation (PAR) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834829-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PIC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Inorganic Carbon (PIC) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034384-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PIC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Inorganic Carbon (PIC) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034384-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PIC_2022.0 ADEOS-I OCTS Level-3 Global Mapped Particulate Inorganic Carbon (PIC) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834831-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_PIC_2022.0 ADEOS-I OCTS Level-3 Global Mapped Particulate Inorganic Carbon (PIC) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834831-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
-OCTS_L3m_POC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034367-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_POC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034367-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
+OCTS_L3m_POC_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Particulate Organic Carbon (POC) Global Mapped Data OB_DAAC STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034367-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_POC_2022.0 ADEOS-I OCTS Level-3 Global Mapped Particulate Organic Carbon (POC) Data, version 2022.0 OB_CLOUD STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834842-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_POC_2022.0 ADEOS-I OCTS Level-3 Global Mapped Particulate Organic Carbon (POC) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834842-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
OCTS_L3m_RRS_2014 ADEOS-I Ocean Color and Temperature Scanner (OCTS) Remote-Sensing Reflectance (RRS) Global Mapped Data ALL STAC Catalog 1996-11-01 1997-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1200034385-OB_DAAC.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
@@ -12924,10 +12924,10 @@ OCTS_L3m_RRS_2022.0 ADEOS-I OCTS Level-3 Global Mapped Remote-Sensing Reflectanc
OCTS_L3m_RRS_2022.0 ADEOS-I OCTS Level-3 Global Mapped Remote-Sensing Reflectance (RRS) Data, version 2022.0 ALL STAC Catalog 1996-10-31 1997-06-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3300834849-OB_CLOUD.umm_json On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS. proprietary
ODIN.SMR_5.0 ODIN SMR data products ESA STAC Catalog 2001-02-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689700-ESA.umm_json The latest Odin Sub-Millimetre Radiometer (SMR) datasets have been generated by Chalmers University of Technology and Molflow within the Odin-SMR Recalibration and Harmonisation project (http://odin.rss.chalmers.se/), funded by the European Space Agency (ESA) to create a fully consistent and homogeneous dataset from the 20 years of satellite operations. The Odin satellite was launched in February 2001 as a joint undertaking between Sweden, Canada, France and Finland, and is part of the ESA Third Party Missions (TPM) programme since 2007. The complete Odin-SMR data archive was reprocessed applying a revised calibration scheme and upgraded algorithms. The Level 1b dataset is entirely reconsolidated, while Level 2 products are regenerated for the main mesospheric and stratospheric frequency modes (i.e., FM 01, 02, 08, 13, 14, 19, 21, 22, 24). The resulting dataset represents the first full-mission reprocessing campaign of the mission, which is still in operation. proprietary
ODU_CBM_0 Old Dominion University (ODU) - Chesapeake Bay Mouth (CBM) measurements OB_DAAC STAC Catalog 2004-05-05 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360566-OB_DAAC.umm_json Measurements made of the Chesapeake Bay Mouth (CBM) by Old Dominion University (ODU) between 2004 and 2006. proprietary
-OFR_94-212 A Compilation of Sulfur Dioxide and Carbon Dioxide Emission-Rate Data from Mount St. Helens during 1980-88 USGS Open File Report 94-212 CEOS_EXTRA STAC Catalog 1980-05-01 1988-09-06 -122, 46, -122, 46 https://cmr.earthdata.nasa.gov/search/concepts/C2232411623-CEOS_EXTRA.umm_json Airborne monitoring of Mount St. Helens by the USGS began in May 1980 for sulfur dioxide emissions and in July 1980 for carbon dioxide emissions. A correlation spectrometer, or COSPEC, was used to measure sulfur dioxide in Mount St. Helens' plume. The upward-looking COSPEC was mounted in a fixed-wing aircraft and flown below and at right angles to the plume. Typically, three to six traverses were made underneath the plume to determine the SO2 burden (concentration x pathlength) within a cross-section of the plume. Knowing the burden along with the plume width and plume velocity (assumed to be the same as ambient wind speed), we could then calculate the emission rate of SO2. The use of correlation spectroscopy for determining the sulfur dioxide output of volcanoes is well established and the technique has been discussed in detail by a number of investigators (Malinconico, 1979; Casadevall and others, 1981; Stoiber and others, 1983). Carbon dioxide in the Mount St. Helens plume was measured by an infrared spectrometer tuned to the 4.26 um CO2 absorption band. An external sample tube was attached to the fuselage of a twin-engine aircraft to deliver outside air to the gas cell of the spectrometer. The aircraft was then flown at several different elevations through the plume at right angles to plume trajectory to define plume area and carbon dioxide concentration in a vertical cross-section of the plume. These two parameters along with the density of CO2 for the altitude of the plume and the plume velocity (assumed as above to be equal to ambient wind speed) were then used to calculate the CO2 emission rate (Harris and others, 1981). proprietary
OFR_94-212 A Compilation of Sulfur Dioxide and Carbon Dioxide Emission-Rate Data from Mount St. Helens during 1980-88 USGS Open File Report 94-212 ALL STAC Catalog 1980-05-01 1988-09-06 -122, 46, -122, 46 https://cmr.earthdata.nasa.gov/search/concepts/C2232411623-CEOS_EXTRA.umm_json Airborne monitoring of Mount St. Helens by the USGS began in May 1980 for sulfur dioxide emissions and in July 1980 for carbon dioxide emissions. A correlation spectrometer, or COSPEC, was used to measure sulfur dioxide in Mount St. Helens' plume. The upward-looking COSPEC was mounted in a fixed-wing aircraft and flown below and at right angles to the plume. Typically, three to six traverses were made underneath the plume to determine the SO2 burden (concentration x pathlength) within a cross-section of the plume. Knowing the burden along with the plume width and plume velocity (assumed to be the same as ambient wind speed), we could then calculate the emission rate of SO2. The use of correlation spectroscopy for determining the sulfur dioxide output of volcanoes is well established and the technique has been discussed in detail by a number of investigators (Malinconico, 1979; Casadevall and others, 1981; Stoiber and others, 1983). Carbon dioxide in the Mount St. Helens plume was measured by an infrared spectrometer tuned to the 4.26 um CO2 absorption band. An external sample tube was attached to the fuselage of a twin-engine aircraft to deliver outside air to the gas cell of the spectrometer. The aircraft was then flown at several different elevations through the plume at right angles to plume trajectory to define plume area and carbon dioxide concentration in a vertical cross-section of the plume. These two parameters along with the density of CO2 for the altitude of the plume and the plume velocity (assumed as above to be equal to ambient wind speed) were then used to calculate the CO2 emission rate (Harris and others, 1981). proprietary
-OFR_95-55 A Compilation of Sulphur Dioxide and Carbon Dioxide Emission-Rate Data from Cook Inlet Volcanoes, Alaska During the Period from 1990 to 1994 ALL STAC Catalog 1990-03-20 1994-07-07 -154, 56, -152, 62 https://cmr.earthdata.nasa.gov/search/concepts/C2232411611-CEOS_EXTRA.umm_json This report contains all of the available daily sulfur dioxide and carbon dioxide emission rates from Cook Inlet volcanoes as determined by the U.S. Geological Survey (USGS) from March 1990 through July 1994. Airborne sulfur dioxide gas sampling of the Cook Inlet volcanoes (Redoubt, Spurr, Iliamna, and Augustine) began in 1986 when several measurements were carried out at Augustine volcano during the eruption of 1986. Systematic monitoring for sulfur dioxide and carbon dioxide began in March 1990 at Redoubt volcano and continues to the present. Intermittent measurements at Augustine and Iliamna volcanoes began in 1990 and continues to the present. Intermittent measurements began at Spurr volcano in 1991, and were continued at more regular intervals from June, 1992 through the 1992 eruption at the Crater Peak vent to the present. proprietary
+OFR_94-212 A Compilation of Sulfur Dioxide and Carbon Dioxide Emission-Rate Data from Mount St. Helens during 1980-88 USGS Open File Report 94-212 CEOS_EXTRA STAC Catalog 1980-05-01 1988-09-06 -122, 46, -122, 46 https://cmr.earthdata.nasa.gov/search/concepts/C2232411623-CEOS_EXTRA.umm_json Airborne monitoring of Mount St. Helens by the USGS began in May 1980 for sulfur dioxide emissions and in July 1980 for carbon dioxide emissions. A correlation spectrometer, or COSPEC, was used to measure sulfur dioxide in Mount St. Helens' plume. The upward-looking COSPEC was mounted in a fixed-wing aircraft and flown below and at right angles to the plume. Typically, three to six traverses were made underneath the plume to determine the SO2 burden (concentration x pathlength) within a cross-section of the plume. Knowing the burden along with the plume width and plume velocity (assumed to be the same as ambient wind speed), we could then calculate the emission rate of SO2. The use of correlation spectroscopy for determining the sulfur dioxide output of volcanoes is well established and the technique has been discussed in detail by a number of investigators (Malinconico, 1979; Casadevall and others, 1981; Stoiber and others, 1983). Carbon dioxide in the Mount St. Helens plume was measured by an infrared spectrometer tuned to the 4.26 um CO2 absorption band. An external sample tube was attached to the fuselage of a twin-engine aircraft to deliver outside air to the gas cell of the spectrometer. The aircraft was then flown at several different elevations through the plume at right angles to plume trajectory to define plume area and carbon dioxide concentration in a vertical cross-section of the plume. These two parameters along with the density of CO2 for the altitude of the plume and the plume velocity (assumed as above to be equal to ambient wind speed) were then used to calculate the CO2 emission rate (Harris and others, 1981). proprietary
OFR_95-55 A Compilation of Sulphur Dioxide and Carbon Dioxide Emission-Rate Data from Cook Inlet Volcanoes, Alaska During the Period from 1990 to 1994 CEOS_EXTRA STAC Catalog 1990-03-20 1994-07-07 -154, 56, -152, 62 https://cmr.earthdata.nasa.gov/search/concepts/C2232411611-CEOS_EXTRA.umm_json This report contains all of the available daily sulfur dioxide and carbon dioxide emission rates from Cook Inlet volcanoes as determined by the U.S. Geological Survey (USGS) from March 1990 through July 1994. Airborne sulfur dioxide gas sampling of the Cook Inlet volcanoes (Redoubt, Spurr, Iliamna, and Augustine) began in 1986 when several measurements were carried out at Augustine volcano during the eruption of 1986. Systematic monitoring for sulfur dioxide and carbon dioxide began in March 1990 at Redoubt volcano and continues to the present. Intermittent measurements at Augustine and Iliamna volcanoes began in 1990 and continues to the present. Intermittent measurements began at Spurr volcano in 1991, and were continued at more regular intervals from June, 1992 through the 1992 eruption at the Crater Peak vent to the present. proprietary
+OFR_95-55 A Compilation of Sulphur Dioxide and Carbon Dioxide Emission-Rate Data from Cook Inlet Volcanoes, Alaska During the Period from 1990 to 1994 ALL STAC Catalog 1990-03-20 1994-07-07 -154, 56, -152, 62 https://cmr.earthdata.nasa.gov/search/concepts/C2232411611-CEOS_EXTRA.umm_json This report contains all of the available daily sulfur dioxide and carbon dioxide emission rates from Cook Inlet volcanoes as determined by the U.S. Geological Survey (USGS) from March 1990 through July 1994. Airborne sulfur dioxide gas sampling of the Cook Inlet volcanoes (Redoubt, Spurr, Iliamna, and Augustine) began in 1986 when several measurements were carried out at Augustine volcano during the eruption of 1986. Systematic monitoring for sulfur dioxide and carbon dioxide began in March 1990 at Redoubt volcano and continues to the present. Intermittent measurements at Augustine and Iliamna volcanoes began in 1990 and continues to the present. Intermittent measurements began at Spurr volcano in 1991, and were continued at more regular intervals from June, 1992 through the 1992 eruption at the Crater Peak vent to the present. proprietary
OFR_95-78_1 Geometeorological data collected by the USGS Desert Winds Project at Gold Spring, Great Basin Desert, northeastern Arizona, 1979-1992 CEOS_EXTRA STAC Catalog 1979-01-27 1992-12-31 -111, 35, -111, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2231550505-CEOS_EXTRA.umm_json This data set contains meteorological data files pertaining to the Gold Spring Geomet research site. Documentation files and data-accessing display software are also included. The meteorological data are wind speed, peak gust, wind direction, precipitation, air temperature, soil temperature, barometric pressure, and humidity. Data from the monitoring station are voluminous; 14 observations from each station are made as often as ten times per hour, totaling more than a million observations per station per year. proprietary
OISSS_L4_multimission_7day_v1_1.0 Multi-Mission Optimally Interpolated Sea Surface Salinity Global Dataset V1 POCLOUD STAC Catalog 2011-08-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2095055342-POCLOUD.umm_json This is a level 4 product on a 0.25-degree spatial and 4-day temporal grid. The product is derived from the level 2 swath data of three satellite missions: the Aquarius/SAC-D, Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) using Optimal Interpolation (OI) with a 7-day decorrelation time scale. The product offers a continuous record from August 28, 2011 to present by concatenating the measurements from Aquarius (September 2011 - June 2015) and SMAP (April 2015 present). ESAs SMOS data was used to fill the gap in SMAP data between June and July 2019, when the SMAP satellite was in a safe mode. The two-month overlap (April - June 2015) between Aquarius and SMAP was used to ensure consistency and continuity in data record. The product covers the global ocean, including the Arctic and Antarctic in the areas free of sea ice, but does not cover internal seas such as Mediterranean and Baltic Sea. In-situ salinity from Argo floats and moored buoys are used to derive a large-scale bias correction and to ensure consistency and accuracy of the OISSS dataset. This dataset is produced by the International Pacific Research Center (IPRC) of the University of Hawaii at Manoa in collaboration with the Remote Sensing Systems (RSS), Santa Rosa, California. More details can be found in the users guide. proprietary
OISSS_L4_multimission_7day_v2_2.0 Multi-Mission Optimally Interpolated Sea Surface Salinity Global Dataset V2 POCLOUD STAC Catalog 2011-08-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2589160971-POCLOUD.umm_json This is a level 4 product on a 0.25-degree spatial and 4-day temporal grid. The product is derived from the level 2 swath data of three satellite missions: the Aquarius/SAC-D, Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) using Optimal Interpolation (OI) with a 7-day decorrelation time scale. The product offers a continuous record from August 28, 2011 to present by concatenating the measurements from Aquarius (September 2011 - June 2015) and SMAP (April 2015 present). ESAs SMOS data was used to fill the gap in SMAP data between June and July 2019, when the SMAP satellite was in a safe mode. The two-month overlap (April - June 2015) between Aquarius and SMAP was used to ensure consistency and continuity in data record. The product covers the global ocean, including the Arctic and Antarctic in the areas free of sea ice, but does not cover internal seas such as Mediterranean and Baltic Sea. In-situ salinity from Argo floats and moored buoys are used to derive a large-scale bias correction and to ensure consistency and accuracy of the OISSS dataset. This dataset is produced by the Earth and Space Research (ESR), Seattle, WA and the International Pacific Research Center (IPRC) of the University of Hawaii at Manoa in collaboration with the Remote Sensing Systems (RSS), Santa Rosa, California. More details can be found in the users guide. proprietary
@@ -13113,13 +13113,13 @@ OMPS_NPP_NPBUVO3_L2_2 OMPS-NPP L2 NP Ozone (O3) Vertical Profile swath orbital G
OMPS_NPP_NPBUVO3_L2_2.9 OMPS-NPP L2 NP Ozone (O3) Vertical Profile swath orbital V2.9 (OMPS_NPP_NPBUVO3_L2) at GES DISC GES_DISC STAC Catalog 2011-11-13 -180, -82, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C2821060582-GES_DISC.umm_json The OMPS-NPP L2 NP Ozone (O3) Total Column swath orbital product provides ozone profile retrievals from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Profiler (NP) instrument on the Suomi-NPP satellite. The V8 ozone profile algorithm relies on nadir profiler measurements made in the 250 to 310 nm range, as well as from measurements from the nadir mapper in the 300 to 380 nm range. Ozone mixing ratios are reported at 15 pressure levels between 50 and 0.5 hPa. Additionally, this data product contains measurements of total ozone, UV aerosol index and reflectivities at 331 and 380 nm. Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-82 to +82 degrees latitude), and there are about 14.5 orbits per day, each has typically 80 profiles. The NP footprint size is 250 km x 250 km. The files are written using the Hierarchical Data Format Version 5 or HDF5. proprietary
OMPS_NPP_NPEV_L1B_2 OMPS/NPP L1B NP Radiance EV Calibrated Geolocated Swath Orbital V2 (OMPS_NPP_NPEV_L1B) at GES DISC GES_DISC STAC Catalog 2011-11-13 -180, -82, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1279850611-GES_DISC.umm_json The OMPS-NPP L1B NP Radiance EV Calibrated Geolocated Swath Orbital collection contains calibrated and geolocated radiances from 300 to 380 nm measured by the OMPS Nadir-Profiler sensor on the Suomi-NPP satellite. Each granule typically contains data from the daylight portion of a single orbit (about 50 minutes). Spatial coverage is nearly global (-82 to 82 degrees latitude), and there are about 14.5 orbits per day each with a single nadir measurement along the satellite track. proprietary
OMSO2G_003 OMI/Aura Sulphur Dioxide (SO2) Total Column Daily L2 Global Gridded 0.125 degree x 0.125 degree V3 (OMSO2G) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136113-GES_DISC.umm_json This Level-2G daily global gridded product OMSO2G is based on the pixel level OMI Level-2 SO2 product OMSO2. OMSO2G data product is a special Level-2 gridded product where pixel level products are binned into 0.125x0.125 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999 . All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMSO2G data product contains almost all parameters that are contained in OMSO2 files. For example, in addition to three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the retrieval algorithm, and ancillary parameters, e.g., UV aerosol index, cloud fraction, cloud pressure, geolocation, solar and satellite viewing angles, and quality flags. The OMSO2G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 146 Mbytes. proprietary
-OMSO2_003 OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 (OMSO2) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966837-GES_DISC.umm_json The Aura Ozone Monitoring Instrument (OMI) level 2 sulphur dioxide (SO2) total column product (OMSO2) has been updated with a principal component analysis (PCA)-based algorithm (v2) with new SO2 Jacobian lookup tables and a priori profiles that significantly improve retrievals for anthropogenic SO2. The data files (or granules) contain different estimates of the vertical column density (VCD) of SO2 depending on the users investigating anthropogenic or volcanic sources. Files also contain quality flags, geolocation and other ancillary information. The lead scientist for the OMSO2 product is Can Li. The OMSO2 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the daylit half of an orbit (~53 minutes). There are approximately 14 orbits per day. The resolution of the data is 13x24 km2 at nadir, with a swath width of 2600 km and 60 pixels per scan line every 2 seconds. proprietary
OMSO2_003 OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000121-OMINRT.umm_json The Ozone Monitoring Instrument (OMI) was launched aboard the EOS-Aura satellite on July 15, 2004 (1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Space Office (NSO) in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO,NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. The Sulfer Dioxide Product 'OMSO2' from the Aura-OMI is now publicly available from NASA GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMSO2 product contains three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the retrieval algorithm. It also contains quality flags, geolocation and other ancillary information. The shortname for this Level-2 OMI total column SO2 product is OMSO2 and the algorithm leads for this product are NASA/UMBC OMI scientists Drs. Nikolay Krotkov (nickolay.a.krotkov@nasa.gov),Kai Yang(kai.yang@nasa.gov) and Arlin J. Krueger(krueger@umbc.edu). OMSO2 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMSO2 data product is about 21 Mbytes. On-line spatial and parameter subset options are available during data download A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMSO2 Readme Document that includes brief algorithm description and documents that provides known data quality related issues are available from the UMBC OMI site ( http://so2.gsfc.nasa.gov/docs.php ) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://so2.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/. For the full set of Aura products and other atmospheric composition data available from the GES DISC, please see the links below. http://disc.sci.gsfc.nasa.gov/Aura/ http://disc.gsfc.nasa.gov/acdisc/ proprietary
+OMSO2_003 OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 (OMSO2) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966837-GES_DISC.umm_json The Aura Ozone Monitoring Instrument (OMI) level 2 sulphur dioxide (SO2) total column product (OMSO2) has been updated with a principal component analysis (PCA)-based algorithm (v2) with new SO2 Jacobian lookup tables and a priori profiles that significantly improve retrievals for anthropogenic SO2. The data files (or granules) contain different estimates of the vertical column density (VCD) of SO2 depending on the users investigating anthropogenic or volcanic sources. Files also contain quality flags, geolocation and other ancillary information. The lead scientist for the OMSO2 product is Can Li. The OMSO2 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the daylit half of an orbit (~53 minutes). There are approximately 14 orbits per day. The resolution of the data is 13x24 km2 at nadir, with a swath width of 2600 km and 60 pixels per scan line every 2 seconds. proprietary
OMSO2_CPR_003 OMI/Aura Level 2 Sulphur Dioxide (SO2) Trace Gas Column Data 1-Orbit Subset and Collocated Swath along CloudSat V003 (OMSO2_CPR) at GES DISC GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350970-GES_DISC.umm_json "This is a CloudSat-collocated subset of the original product OMSO2, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this CloudSat-collocated subset of the original product OMSO2 Product is OMSO2_CPR_V003) This document describes the original OMI SO2 product (OMSO2) produced from global mode UV measurements of the Ozone Monitoring Instrument (OMI). OMI was launched on July 15, 2004 on the EOS Aura satellite, which is in a sun-synchronous ascending polar orbit with 1:45pm local equator crossing time. The data collection started on August 17, 2004 (orbit 482) and continues to this day with only minor data gaps. The minimum SO2 mass detectable by OMI is about two orders of magnitude smaller than the detection threshold of the legacy Total Ozone Mapping Spectrometer (TOMS) SO2 data (1978-2005) [Krueger et al 1995]. This is due to smaller OMI footprint and the use of wavelengths better optimized for separating O3 from SO2. The product file, called a data granule, covers the sunlit portion of the orbit with an approximately 2600 km wide swath containing 60 pixels per viewing line. During normal operations, 14 or 15 granules are produced daily, providing fully contiguous coverage of the globe. Currently, OMSO2 products are not produced when OMI goes into the ""zoom mode"" for one day every 452 orbits (~32 days). For each OMI pixel we provide 4 different estimates of the column density of SO2 in Dobson Units (1DU=2.69x10^16 molecules/cm2) obtained by making different assumptions about the vertical distribution of the SO2. However, it is important to note that in most cases the precise vertical distribution of SO2 is unimportant. The users can use either the SO2 plume height, or the center of mass altitude (CMA) derived from SO2 vertical distribution, to interpolate between the 4 values: 1)Planetary Boundary Layer (PBL) SO2 column (ColumnAmountSO2_PBL), corresponding to CMA of 0.9 km. 2)Lower tropospheric SO2 column (ColumnAmountSO2_TRL), corresponding to CMA of 2.5 km. 3)Middle tropospheric SO2 column, (ColumnAmountSO2_TRM), usually produced by volcanic degassing, corresponding to CMA of 7.5 km, 4)Upper tropospheric and Stratospheric SO2 column (ColumnAmountSO2_STL), usually produced by explosive volcanic eruption, corresponding to CMA of 17 km. The accuracy and precision of the derived SO2 columns vary significantly with the SO2 CMA and column amount, observational geometry, and slant column ozone. OMI becomes more sensitive to SO2 above clouds and snow/ice, and less sensitive to SO2 below clouds. Preliminary error estimates are discussed below (see Data Quality Assessment). OMSO2 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMSO2 data product is about 9 Mbytes." proprietary
OMSO2e_003 OMI/Aura Sulfur Dioxide (SO2) Total Column Daily L3 1 day Best Pixel in 0.25 degree x 0.25 degree V3 (OMSO2e) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136112-GES_DISC.umm_json "The OMI science team produces this Level-3 Aura/OMI Global OMSO2e Data Products (0.25 degree Latitude/Longitude grids). In this Level-3 daily global SO2 data product, each grid contains only one observation of Total Column Density of SO2 in the Planetary Boundary Layer (PBL), based on an improved Principal Component Analysis (PCA) Algorithm. This single observation is the ""best pixel"", selected from all ""good"" L2 pixels of OMSO2 that overlap this grid and have UTC time between UTC times of 00:00:00 and 23:59:59.999. In addition to the SO2 Vertical column value some ancillary parameters, e.g., cloud fraction, terrain height, scene number, solar and satellite viewing angles, row anomaly flags, and quality flags have been also made available corresponding to the best selected SO2 data pixel in each grid. The OMSO2e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5) using the grid model." proprietary
OMTO3G_003 OMI/Aura Ozone (O3) Total Column Daily L2 Global Gridded 0.25 degree x 0.25 degree V3 (OMTO3G) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136114-GES_DISC.umm_json This Level-2G daily global gridded product OMTO3G is based on the pixel level OMI Level-2 Total Ozone Product OMTO3. The OMTO3 product is from the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. The OMTO3G data product is a special Level-2 Global Gridded Product where pixel level data are binned into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved Without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products. The OMTO3G data product contains almost all parameters that are contained in the OMTO3. For example, in addition to the total column ozone it also contains UV aerosol index, cloud fraction, cloud pressure, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The OMTO3G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 150 Mbytes. proprietary
-OMTO3_003 OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ . proprietary
OMTO3_003 OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km V003 (OMTO3) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1239966818-GES_DISC.umm_json The Aura Ozone Monitoring Instrument (OMI) Level-2 Total Column Ozone Data Product OMTO3 (Version 003) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI provides two Level-2 (OMTO3 and OMDOAO3) total column ozone products at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms. This level-2 global total column ozone product (OMTO3) is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrievals (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3. The algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia. The OMTO3 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is approximately 35 MB. proprietary
+OMTO3_003 OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT STAC Catalog 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.umm_json The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. This level-2 global total column ozone product (OMTO3)is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ . proprietary
OMTO3_CPR_003 OMI/Aura Level 2 Ozone (O3) Total Column 1-Orbit Subset and Collocated Swath along CloudSat track 200-km wide at 13x24 km2 resolution GES_DISC STAC Catalog 2006-06-01 2018-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350982-GES_DISC.umm_json This is a CloudSat-collocated subset of the original product OMTO3, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications. (The shortname for this CloudSat-collocated OMI Level 2 Total Ozone Column subset is OMTO3_CPR_V003) proprietary
OMTO3d_003 OMI/Aura TOMS-Like Ozone, Aerosol Index, Cloud Radiance Fraction L3 1 day 1 degree x 1 degree V3 (OMTO3d) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136070-GES_DISC.umm_json The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids. The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes. proprietary
OMTO3e_003 OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC GES_DISC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.umm_json The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. proprietary
@@ -13214,6 +13214,7 @@ PACE_OCI_L2_BGC_NRT_2.0 PACE OCI Level-2 Regional Biogeochemical Properties, Nea
PACE_OCI_L2_IOP_NRT_2.0 PACE OCI Level-2 Regional Inherent Optical Properties (IOP) - Near Real-time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020920493-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
PACE_OCI_L2_PAR_NRT_2.0 PACE OCI Level-2 Regional Photosynthetically Available Radiation (PAR) - Near Real Time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020920715-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
PACE_OCI_L2_SFREFL_NRT_2.0 PACE OCI Level-2 Regional Surface Reflectance - Near Real-time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020920858-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
+PACE_OCI_L3B_AVW_NRT_2.0 PACE OCI Level-3 Global Binned Apparent Visible Wavelength (AVW) - Near Real Time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020922066-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
PACE_OCI_L3B_CHL_NRT_2.0 PACE OCI Level-3 Global Binned Chlorophyll (CHL) - NRT Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020922264-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
PACE_OCI_L3B_IOP_NRT_2.0 PACE OCI Level-3 Global Binned Inherent Optical Properties (IOP) - Near Real-time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020922543-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
PACE_OCI_L3B_KD_NRT_2.0 PACE OCI Level-3 Global Binned Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) - Near Real Time (NRT) Data, version 2.0 OB_CLOUD STAC Catalog 2024-02-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C3020922624-OB_CLOUD.umm_json The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit. proprietary
@@ -13241,14 +13242,14 @@ PAD_935_1 Surface Water Elevation and Quality, Peace-Athabasca Delta, Canada, 20
PAGESAntTemp2013_1 Antarctica continental-scale temperature variability during the past two millennia AU_AADC STAC Catalog 2013-01-01 2013-12-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214313668-AU_AADC.umm_json As part of a larger reconstruction of global temperatures over the last 2000 years, work was done to bring together all the Antarctic temperature datasets into one combined dataset. Taken from the PAGES website: Antarctica and the Southern Ocean play a key role in the global climate system (e.g. Mayewski et al., 2009; Convey et al., 2009). The processes that occur at these high southern latitudes play a pivotal role in global atmospheric and oceanic circulation, oceanic uptake of heat and carbon, and planetary energy balance, through the ice-albedo feedback. The ability to detect and attribute climate change in the Antarctic and Southern Ocean is dependent upon climate observations; however, this region is the most observation-sparse and record-length-limited part of the globe. There are few systematic observations extending back before the mid-20th century and good coverage is only available since the satellite era (i.e. the last 3-4 decades). In this context, key questions of the PAGES 2k Network underscore an acute need for good high resolution palaeoclimate data extending out to 2000 years before the present, but also with good coverage through the instrumental period so as to permit proxy calibration. Obtaining well-resolved ice cores over large parts of Antarctica is a challenge, but one that is becoming more tractable with the use of new technology. Antarctica2k seeks to integrate such records with other available proxies in order to address the goals of the 2k Network. proprietary
PAL-LTER_0 Palmer Station Antarctica (PAL) Long Term Ecological Research Network (LTER) OB_DAAC STAC Catalog 1991-12-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360585-OB_DAAC.umm_json Measurements made under the Long Term Ecological Research Network (LTER) Palmer Station Antarctica (PAL) program. proprietary
PARASOLRB_CPR_001 POLDER/Parasol L2 Radiation Budget subset along CloudSat track V001 (PARASOLRB_CPR) at GES DISC GES_DISC STAC Catalog 2006-06-01 2010-01-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236350976-GES_DISC.umm_json This is the POLDER/Parasol Level-2 Radiation Budget Subset, collocated with the CloudSat track. The subset is processed at the A-Train Data Depot of the GES DISC, NASA. The algorithm first converts the original POLDER binary data, which is Level-2 but nevertheless in a sinusoidal grid, into HDF4 format, and thus stores the full-sized data in HDF4. Then, it calculates the CloudSat ground track coordinates, and proceeds to extract the closest POLDER grid cells. Along with the extraction, the algorithm re-orders the subset grid cells in a line-by-line fashion, so that the output subset is in array format and resembles a swath. This array has a cross-track dimension of 11 columns. That makes about 200-km-wide coverage. All original parameters are preserved in the subset. As it is collocated with CloudSat, the subset is automatically collocated with CALIPSO as well. proprietary
-PASSCAL_ABBA Adirondack Broad Band Array (ABBA) ALL STAC Catalog 1995-01-01 1996-12-31 -74.5, 43.5, -73.8, 44.4 https://cmr.earthdata.nasa.gov/search/concepts/C1214608962-SCIOPS.umm_json Objective: Determination of anistropy and depth/characteristics of discontinuties in the mantle and the Moho beneath the Adirondacks. Preliminary results: Azimuthal Anisotropy is oriented ENE-WSW with a delay time of about 1 s. Discontinuity studies are still in progress. proprietary
PASSCAL_ABBA Adirondack Broad Band Array (ABBA) SCIOPS STAC Catalog 1995-01-01 1996-12-31 -74.5, 43.5, -73.8, 44.4 https://cmr.earthdata.nasa.gov/search/concepts/C1214608962-SCIOPS.umm_json Objective: Determination of anistropy and depth/characteristics of discontinuties in the mantle and the Moho beneath the Adirondacks. Preliminary results: Azimuthal Anisotropy is oriented ENE-WSW with a delay time of about 1 s. Discontinuity studies are still in progress. proprietary
+PASSCAL_ABBA Adirondack Broad Band Array (ABBA) ALL STAC Catalog 1995-01-01 1996-12-31 -74.5, 43.5, -73.8, 44.4 https://cmr.earthdata.nasa.gov/search/concepts/C1214608962-SCIOPS.umm_json Objective: Determination of anistropy and depth/characteristics of discontinuties in the mantle and the Moho beneath the Adirondacks. Preliminary results: Azimuthal Anisotropy is oriented ENE-WSW with a delay time of about 1 s. Discontinuity studies are still in progress. proprietary
PASSCAL_ALAR Aleutian Arc Seismic Experiment SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214610603-SCIOPS.umm_json "27 instruments were deployed at 18 different locations in the Aleutian Islands to record the airguns from the Ewing as it shot offshore. The full data report is available in PDF at the following URL: ""http://www.iris.edu/data/reports/1996/96-016.pdf""" proprietary
PASSCAL_ALAR Aleutian Arc Seismic Experiment ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214610603-SCIOPS.umm_json "27 instruments were deployed at 18 different locations in the Aleutian Islands to record the airguns from the Ewing as it shot offshore. The full data report is available in PDF at the following URL: ""http://www.iris.edu/data/reports/1996/96-016.pdf""" proprietary
-PASSCAL_KRAFLA 1994 Krafla Undershooting Experiment ALL STAC Catalog 1970-01-01 -24.55, 62.81, -12.79, 67.01 https://cmr.earthdata.nasa.gov/search/concepts/C1214610676-SCIOPS.umm_json Thirty-eight instruments were used to shoot two perpendicular refraction profiles across the Krafla central volcano. The North/South profile is 20 km long while the East/West profile is 55 km long. Average station spacing was 500 m in the caldera and 1-4 km elswhere. A total of three shots were used in the NS profile and 6 shots were used in the EW profile. proprietary
PASSCAL_KRAFLA 1994 Krafla Undershooting Experiment SCIOPS STAC Catalog 1970-01-01 -24.55, 62.81, -12.79, 67.01 https://cmr.earthdata.nasa.gov/search/concepts/C1214610676-SCIOPS.umm_json Thirty-eight instruments were used to shoot two perpendicular refraction profiles across the Krafla central volcano. The North/South profile is 20 km long while the East/West profile is 55 km long. Average station spacing was 500 m in the caldera and 1-4 km elswhere. A total of three shots were used in the NS profile and 6 shots were used in the EW profile. proprietary
-PASSCAL_WABASH A comprehensive geophysical investigation to assess seismic hazards in the coassesment of seismicity in the Wabash Valley SCIOPS STAC Catalog 1995-11-01 1996-06-30 -88.1706, 38.2057, -88.1706, 38.2057 https://cmr.earthdata.nasa.gov/search/concepts/C1214608969-SCIOPS.umm_json Recent paleoseismic evidence had shown there were 5-8 magnitude greater than 6 earthquakes in this region in the past 20,000 years. The study area has always been at the fringe of previously operated seismic networks. A focused, short-term deployment was designed to lower the detection threshold to determine seismicity rates for the region for comparison with estimates derived from paleoseismicity. The researchers hoped to relate observed seismicity to faults mapped in the subsurface through new seismic reflection data made available to the Illinois Basin Consortium. proprietary
+PASSCAL_KRAFLA 1994 Krafla Undershooting Experiment ALL STAC Catalog 1970-01-01 -24.55, 62.81, -12.79, 67.01 https://cmr.earthdata.nasa.gov/search/concepts/C1214610676-SCIOPS.umm_json Thirty-eight instruments were used to shoot two perpendicular refraction profiles across the Krafla central volcano. The North/South profile is 20 km long while the East/West profile is 55 km long. Average station spacing was 500 m in the caldera and 1-4 km elswhere. A total of three shots were used in the NS profile and 6 shots were used in the EW profile. proprietary
PASSCAL_WABASH A comprehensive geophysical investigation to assess seismic hazards in the coassesment of seismicity in the Wabash Valley ALL STAC Catalog 1995-11-01 1996-06-30 -88.1706, 38.2057, -88.1706, 38.2057 https://cmr.earthdata.nasa.gov/search/concepts/C1214608969-SCIOPS.umm_json Recent paleoseismic evidence had shown there were 5-8 magnitude greater than 6 earthquakes in this region in the past 20,000 years. The study area has always been at the fringe of previously operated seismic networks. A focused, short-term deployment was designed to lower the detection threshold to determine seismicity rates for the region for comparison with estimates derived from paleoseismicity. The researchers hoped to relate observed seismicity to faults mapped in the subsurface through new seismic reflection data made available to the Illinois Basin Consortium. proprietary
+PASSCAL_WABASH A comprehensive geophysical investigation to assess seismic hazards in the coassesment of seismicity in the Wabash Valley SCIOPS STAC Catalog 1995-11-01 1996-06-30 -88.1706, 38.2057, -88.1706, 38.2057 https://cmr.earthdata.nasa.gov/search/concepts/C1214608969-SCIOPS.umm_json Recent paleoseismic evidence had shown there were 5-8 magnitude greater than 6 earthquakes in this region in the past 20,000 years. The study area has always been at the fringe of previously operated seismic networks. A focused, short-term deployment was designed to lower the detection threshold to determine seismicity rates for the region for comparison with estimates derived from paleoseismicity. The researchers hoped to relate observed seismicity to faults mapped in the subsurface through new seismic reflection data made available to the Illinois Basin Consortium. proprietary
PATEX_0 PATagonia EXperiment (PATEX) Project OB_DAAC STAC Catalog 2004-11-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360589-OB_DAAC.umm_json PATagonia EXperiment (PATEX) Project is a Brazilian research project, which has the overall objective of characterizing the environmental constraints, phytoplankton assemblages, primary production rates, bio-optical characteristics, and air-sea CO2 fluxes waters along the Argentinean shelf-break during austral spring and summer. A set of seven PATEX cruises were conducted from 2004 to 2009. Garcia et al., 2011 (doi:10.1029/2010JC006595) proprietary
PAZ.ESA.archive_16.0 PAZ ESA archive ESA STAC Catalog 2018-09-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2547579176-ESA.umm_json "The PAZ ESA archive collection consists of PAZ Level 1 data previously requested by ESA supported projects over their areas of interest around the world and, as a consequence, the products are scattered and dispersed worldwide and in different time windows. The dataset regularly grows as ESA collects new products over the years. Available modes are: • StripMap mode (SM): SSD less than 3m for a scene 30km x 50km in single polarization or 15km x 50km in dual polarisation • ScanSAR mode (SC): the scene is 100 x 150 km2, SSD less than 18m in signle pol only • Wide ScanSAR mode (WS): single polarisation only, with SS less than 40m and scene size of 270 x 200 km2 • Spotlight modes (SL): SSD less than 2m for a scene 10km x 10km, both single and dual polarization are available • High Resolution Spotlight mode (HS): in both single and dual polarisation, the scene is 10x5 km2, SSD less than 1m • Staring Spotlight mode (ST): SSD is 25cm, the scene size is 4 x 4 km2, in single polarisation only. The available geometric projections are: • Single Look Slant Range Complex (SSC): single look product, no geocoding, no radiometric artifact included, the pixel spacing is equidistant in azimuth and in ground range • Multi Look Ground Range Detected (MGD): detected multi look product, simple polynomial slant-to-ground projection is performed in range, no image rotation to a map coordinate system is performed • Geocoded Ellipsoid Corrected (GEC): multi look detected product, projected and re-sampled to the WGS84 reference ellipsoid with no terrain corrections • Enhanced Ellipsoid Corrected (EEC): multi look detected product, projected and re-sampled to the WGS84 reference ellipsoid, the image distortions caused by varying terrain height are corrected using a DEM The following table summarises the offered product types EO-SIP product type Operation Mode Geometric Projection PSP_SM_SSC Stripmap (SM) Single Look Slant Range Complex (SSC) PSP_SM_MGD Stripmap (SM) Multi Look Ground Range Detected (MGD) PSP_SM_GEC Stripmap (SM) Geocoded Ellipsoid Corrected (GEC) PSP_SM_EEC Stripmap (SM) Enhanced Ellipsoid Corrected (EEC) PSP_SC_MGD ScanSAR (SC) Single Look Slant Range Complex (SSC) PSP_SC_GEC ScanSAR (SC) Multi Look Ground Range Detected (MGD) PSP_SC_EEC ScanSAR (SC) Geocoded Ellipsoid Corrected (GEC) PSP_SC_SSC ScanSAR (SC) Enhanced Ellipsoid Corrected (EEC) PSP_SL_SSC Spotlight (SL) Single Look Slant Range Complex (SSC) PSP_SL_MGD Spotlight (SL) Multi Look Ground Range Detected (MGD) PSP_SL_GEC Spotlight (SL) Geocoded Ellipsoid Corrected (GEC) PSP_SL_EEC Spotlight (SL) Enhanced Ellipsoid Corrected (EEC) PSP_HS_SSC High Resolution Spotlight (HS) Single Look Slant Range Complex (SSC) PSP_HS_MGD High Resolution Spotlight (HS) Multi Look Ground Range Detected (MGD) PSP_HS_GEC High Resolution Spotlight (HS) Geocoded Ellipsoid Corrected (GEC) PSP_HS_EEC High Resolution Spotlight (HS) Enhanced Ellipsoid Corrected (EEC) PSP_ST_SSC Staring Spotlight (ST) Single Look Slant Range Complex (SSC) PSP_ST_MGD Staring Spotlight (ST) Multi Look Ground Range Detected (MGD) PSP_ST_GEC Staring Spotlight (ST) Geocoded Ellipsoid Corrected (GEC) PSP_ST_EEC Staring Spotlight (ST) Enhanced Ellipsoid Corrected (EEC) PSP_WS_SSC Wide ScanSAR (WS) Single Look Slant Range Complex (SSC) PSP_WS_MGD Wide ScanSAR (WS) Multi Look Ground Range Detected (MGD) PSP_WS_GEC Wide ScanSAR (WS) Geocoded Ellipsoid Corrected (GEC) PSP_WS_EEC Wide ScanSAR (WS) Enhanced Ellipsoid Corrected (EEC)" proprietary
PAZ.Full.Archive.and.New.Tasking_7.0 PAZ Full Archive and New Tasking ESA STAC Catalog 2018-09-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689657-ESA.umm_json PAZ Image Products can be acquired in 8 image modes with flexible resolutions (from 1 m to 40 m) and scene sizes. Thanks to different polarimetric combinations and processing levels the delivered imagery can be tailored specifically to meet the requirements of the application. Available modes are: • StripMap mode (SM) in single and dual polarisation: The ground swath is illuminated with a continuous train of pulses while the antenna beam is pointed to a fixed angle, both in elevation and in azimuth. • ScanSAR mode (SC) in single polarisation: the swath width is increased respecting to the StripMap mode, it is composed of four different sub-swaths, which are obtained by antenna steering in elevation direction. • Wide ScanSAR mode (WS), in single polarisation: the usage of six sub-swaths allows to obtain a higher swath coverage product. • Spotlight modes: in single and dual polarisation: Spotlight modes take advantage of the beam steering capability in the azimuth plane to illuminate for a longer time the area of interest: a sensible improvement of the azimuth resolution is achieved at the expense of a shorter scene size. Spotlight mode (SL) is designed to maximise the azimuth scene extension at the expense of the spatial resolution, and High Resolution Spotlight mode (HS) is designed to maximize the spatial resolutions at the expense of the scene extension. • Staring Spotlight mode (ST), in single polarisation: The virtual rotation point coincides with the center of the beam: the image length in the flight direction is constrained by the projection on- ground of the azimuth beamwidth and it leads to a target azimuth illumination time increment and to achieve the best azimuth resolution. There are two main classes of products: • Spatially Enhanced products (SE): designed with the target of maximize the spatial resolution in pixels with squared size, so the larger resolution value of azimuth or ground range determines the square pixel size, and the smaller resolution value is adjusted to this size and the corresponding reduction of the bandwidth is used for speckle reduction. • Radiometrically Enhanced products (RE): designed with the target of maximize the radiometry, so the range and azimuth resolutions are intentionally decreased to significantly reduce speckle by averaging several looks. The following geometric projections are offered: • Single Look Slant Range Complex (SSC): single look product of the focused radar signal: the pixels are spaced equidistant in azimuth and in slant range. No geocoding is available, no radiometric artifacts included. Product delivered in the DLR-defined binary COSAR format. The SSC product is intended for applications that require the full bandwidth and phase information, e.g. for SAR interferometry and polarimetry. • Multi Look Ground Range Detected (MGD): detected multi look product in GeoTiff format with reduced speckle and approximately square resolution cells on ground. The image coordinates are oriented along flight direction and along ground range; the pixel spacing is equidistant in azimuth and in ground range. A simple polynomial slant to ground projection is performed in range using a WGS84 ellipsoid and an average, constant terrain height parameter. No image rotation to a map coordinate system is performed and interpolation artifacts are thus avoided. • Geocoded Ellipsoid Corrected (GEC): multi look detected product in GeoTiff format. It is projected and re-sampled to the WGS84 reference ellipsoid assuming one average terrain height. No terrain correction performed. UTM is the standard projection, for polar regions UPS is applied. • Enhanced Ellipsoid Corrected (EEC): multi look detected product in GeoTiff format. It is projected and re-sampled to the WGS84 reference ellipsoid. The image distortions caused by varying terrain height are corrected using an external DEM; therefore the pixel localization in these products is highly accurate. UTM is the standard projection, for polar regions UPS is applied. StripMap Single Mode ID: SM-S Polarizations: HH, VV, HV, VH Scene size (Range x Azimuth) [km]: 30 x 50 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 2.99 - 3.52 at (45° - 20°) - MGD, GEC, EEC (RE)[Ground range] 6.53 - 7.65 at (45° - 20°) - SSC[Slant range] 1.1 (150 MHz bandwidth) 1.7 (100 MHz bandwidth) Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 3.05 - MGD, GEC, EEC (RE) 6.53 - 7.60 at (45° - 20°) - SSC 3.01 StripMap Dual Mode ID: SM-D Polarizations: HH/VV, HH/HV, VV/VH Scene size (Range x Azimuth) [km]: 15 x 50 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 6 - MGD, GEC, EEC (RE)[Ground range] 7.51 - 10.43 at (45° - 20°) - SSC[Slant range] 1.18 Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 6.11 - MGD, GEC, EEC (RE) 7.52 - 10.4 at (45° - 20°) - SSC ScanSAR Mode ID: SC Polarizations: HH, VV, HV, VH Scene size (Range x Azimuth) [km]: 100 x 150 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] N/A - MGD, GEC, EEC (RE)[Ground range] 16.79 - 18.19 at (45° - 20°) - SSC[Slant range] 1.17 - 3.4 (depending on range bandwidth) Azimuth Resolution [m]: - MGD, GEC, EEC (SE) N/A - MGD, GEC, EEC (RE) 17.66 - 18.18 at (45° - 20°) - SSC 18.5 Wide ScanSAR Mode ID: WS Polarizations: HH, VV, HV, VH Scene size (Range x Azimuth) [km]: [273-196] x 208 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] N/A - MGD, GEC, EEC (RE)[Ground range] 35 - SSC[Slant range] 1.75 - 3.18 (depending on range bandwidth) Azimuth Resolution [m]: - MGD, GEC, EEC (SE) N/A - MGD, GEC, EEC (RE) 39 - SSC 38.27 Spotlight Single Mode ID: SL-S Polarizations: HH, VV, HV, VH Scene size (Range x Azimuth) [km]: 10 x 10 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 1.55 - 3.43 at (55° - 20°) - MGD, GEC, EEC (RE)[Ground range] 3.51 - 5.43 at (55° - 20°) - SSC[Slant range] 1.18 Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 1.56 - 2.9 at (55° - 20°) - MGD, GEC, EEC (RE) 3.51 - 5.4 at (55° - 20°) - SSC 1.46 Spotlight Dual Mode ID: SL-D Polarizations: HH/VV, HH/HV, VV/VH Scene size (Range x Azimuth) [km]: 10 x 10 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 3.09 - 3.5 at (55° - 20°) - MGD, GEC, EEC (RE)[Ground range] 4.98 - 7.63 at (55° - 20°) - SSC[Slant range] 1.17 Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 3.53 - MGD, GEC, EEC (RE) 4.99 - 7.64 at (55° - 20°) - SSC 3.1 HR Spotlight Single Mode ID: HS-S Polarizations: HH, VV, HV, VH Scene size (Range x Azimuth) [km]: 10-6 x 5 (depending on incident angle) Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 1 - 1.76 at (55° - 20°) - MGD, GEC, EEC (RE)[Ground range] 2.83 - 3.11 at (55° - 20°) - SSC[Slant range] 0.6 Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 1 - 1.49 at (55 °- 20°) - MGD, GEC, EEC (RE) 2.83 - 3.13 at (55° - 20°) - SSC 1.05 HR Spotlight Dual Mode ID: HS-D Polarizations: HH/VV, HH/HV, VV/VH Scene size (Range x Azimuth) [km]: 10 x 5 Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 2 - 3.5 at (55° - 20°) - MGD, GEC, EEC (RE)[Ground range] 4 - 6.2 at (55° - 20°) - SSC[Slant range] 1.17 Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 2.38 - 2.93 at (55° - 20°) - MGD, GEC, EEC (RE) 4 - 6.25 at (55° - 20°) - SSC 2.16 Staring Spotlight Mode ID: ST Polarizations: HH, VV, HV, VH Scene size (Range x Azimuth) [km]: [9-4.6] x [2.7-3.6] Range Resolution [m]: - MGD, GEC, EEC (SE)[Ground range] 0.96 - 1.78 at (45°- 20°) - MGD, GEC, EEC (RE)[Ground range] 0.97 - 1.78 at (45°-20°) - SSC[Slant range] 0.59 Azimuth Resolution [m]: - MGD, GEC, EEC (SE) 0.38 - 0.7 at (45°-20°) - MGD, GEC, EEC (RE) 0.97 - 1.42 at (45°-20°) - SSC 0.22 All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section. For archive data, the user is invited to search PAZ products by using the USP (User Service Provider) web portal (http://www.geos.hisdesat.es/) (self registration required) in order to verify the availability over the Area of Interest in the Time of Interest. proprietary
@@ -13284,10 +13285,10 @@ POLYNYA_ship_1 Mertz Polynya Experiment, Aurora Australis science cruises au9807
POMME_0 Programme Ocean Multidisciplinaire Meso-Echelle (POMME) OB_DAAC STAC Catalog 2001-02-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360620-OB_DAAC.umm_json Measurements made during the Programme Ocean Multidisciplinaire Meso-Echelle (POMME) or Multidisciplinary middle-level ocean program in 2001. proprietary
POSTER-03CYCLONE_Not Applicable 2003 Tropical Cyclones of the World ALL STAC Catalog 2003-01-08 2003-12-21 -180, -65, 180, 65 https://cmr.earthdata.nasa.gov/search/concepts/C2107093337-NOAA_NCEI.umm_json "Year 2003 Tropical Cyclones of the World poster. During calendar year 2003, fifty-one tropical cyclones with sustained surface winds of at least 64 knots were observed around the world. NOAA's Polar-Orbiting Operational Environmental Satellites (POES) captured these powerful storms near peak intensity, which are all presented in this colorful poster. Poster size is 36""x 27""." proprietary
POSTER-03CYCLONE_Not Applicable 2003 Tropical Cyclones of the World NOAA_NCEI STAC Catalog 2003-01-08 2003-12-21 -180, -65, 180, 65 https://cmr.earthdata.nasa.gov/search/concepts/C2107093337-NOAA_NCEI.umm_json "Year 2003 Tropical Cyclones of the World poster. During calendar year 2003, fifty-one tropical cyclones with sustained surface winds of at least 64 knots were observed around the world. NOAA's Polar-Orbiting Operational Environmental Satellites (POES) captured these powerful storms near peak intensity, which are all presented in this colorful poster. Poster size is 36""x 27""." proprietary
-POSTER-2004 Hurricanes_Not Applicable 2004 Landfalling Hurricanes Poster NOAA_NCEI STAC Catalog 2004-08-13 2004-09-25 -91, 8, -33, 46.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093388-NOAA_NCEI.umm_json "The 2004 U.S. Landfalling Hurricanes poster is a special edition poster which contains two sets of images of Hurricanes Charley, Frances, Ivan, and Jeanne, created from NOAA's operational satellites. In addtion to the images, the poster has a map depicting the general track of each storm; information on each storm's landfall location, date of landfall, and category level at time of landfall; as well as, a Saffir-Simpson Hurricane Scale chart. Poster size is 34""x27""." proprietary
POSTER-2004 Hurricanes_Not Applicable 2004 Landfalling Hurricanes Poster ALL STAC Catalog 2004-08-13 2004-09-25 -91, 8, -33, 46.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093388-NOAA_NCEI.umm_json "The 2004 U.S. Landfalling Hurricanes poster is a special edition poster which contains two sets of images of Hurricanes Charley, Frances, Ivan, and Jeanne, created from NOAA's operational satellites. In addtion to the images, the poster has a map depicting the general track of each storm; information on each storm's landfall location, date of landfall, and category level at time of landfall; as well as, a Saffir-Simpson Hurricane Scale chart. Poster size is 34""x27""." proprietary
-POSTER-2005 Atl Hurricanes_Not Applicable 2005 Atlantic Hurricanes Poster NOAA_NCEI STAC Catalog 2005-07-03 2005-12-08 -97, 20, -65, 40.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093322-NOAA_NCEI.umm_json "The 2005 Atlantic Hurricanes poster features high quality satellite images of 15 hurricanes which formed in the Atlantic Basin (includes Gulf of Mexico and Caribbean Sea) in the year 2005 which was the busiest season on record. The images show each storm near maximum intensity. Also, under each image there is additional information including, lowest pressure, maximum sustained winds, date range of the storm, highest category level reached on the Saffir-Simpson Hurricane Scale, and approximate position of each storm when the image was taken. Poster size is 35""x30""." proprietary
+POSTER-2004 Hurricanes_Not Applicable 2004 Landfalling Hurricanes Poster NOAA_NCEI STAC Catalog 2004-08-13 2004-09-25 -91, 8, -33, 46.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093388-NOAA_NCEI.umm_json "The 2004 U.S. Landfalling Hurricanes poster is a special edition poster which contains two sets of images of Hurricanes Charley, Frances, Ivan, and Jeanne, created from NOAA's operational satellites. In addtion to the images, the poster has a map depicting the general track of each storm; information on each storm's landfall location, date of landfall, and category level at time of landfall; as well as, a Saffir-Simpson Hurricane Scale chart. Poster size is 34""x27""." proprietary
POSTER-2005 Atl Hurricanes_Not Applicable 2005 Atlantic Hurricanes Poster ALL STAC Catalog 2005-07-03 2005-12-08 -97, 20, -65, 40.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093322-NOAA_NCEI.umm_json "The 2005 Atlantic Hurricanes poster features high quality satellite images of 15 hurricanes which formed in the Atlantic Basin (includes Gulf of Mexico and Caribbean Sea) in the year 2005 which was the busiest season on record. The images show each storm near maximum intensity. Also, under each image there is additional information including, lowest pressure, maximum sustained winds, date range of the storm, highest category level reached on the Saffir-Simpson Hurricane Scale, and approximate position of each storm when the image was taken. Poster size is 35""x30""." proprietary
+POSTER-2005 Atl Hurricanes_Not Applicable 2005 Atlantic Hurricanes Poster NOAA_NCEI STAC Catalog 2005-07-03 2005-12-08 -97, 20, -65, 40.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093322-NOAA_NCEI.umm_json "The 2005 Atlantic Hurricanes poster features high quality satellite images of 15 hurricanes which formed in the Atlantic Basin (includes Gulf of Mexico and Caribbean Sea) in the year 2005 which was the busiest season on record. The images show each storm near maximum intensity. Also, under each image there is additional information including, lowest pressure, maximum sustained winds, date range of the storm, highest category level reached on the Saffir-Simpson Hurricane Scale, and approximate position of each storm when the image was taken. Poster size is 35""x30""." proprietary
POSTER-2005 Sig Hurricanes_Not Applicable 2005 Significant U.S. Hurricane Strikes Poster NOAA_NCEI STAC Catalog 2005-07-10 2005-10-24 -102, 12, -69, 40.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093260-NOAA_NCEI.umm_json "The 2005 Significant U.S. Hurricane Strikes poster is one of two special edition posters for the Atlantic Hurricanes. This beautiful poster contains two sets of images of five hurricanes that impacted the United States in 2005, namely Katrina, Ophelia, Rita and Wilma. The images were created from NOAA's geostationary and polar-orbiting environmental satellites. In addition to the images, the poster has a map depicting the general track of each storm, a color temperature scale to read the hurricane cloud top temperatures, high level information on each storm, the category at time of landfall; as well as, a Saffir-Simpson Hurricane Scale. Poster size is 36""x32""." proprietary
POSTER-2005 Sig Hurricanes_Not Applicable 2005 Significant U.S. Hurricane Strikes Poster ALL STAC Catalog 2005-07-10 2005-10-24 -102, 12, -69, 40.5 https://cmr.earthdata.nasa.gov/search/concepts/C2107093260-NOAA_NCEI.umm_json "The 2005 Significant U.S. Hurricane Strikes poster is one of two special edition posters for the Atlantic Hurricanes. This beautiful poster contains two sets of images of five hurricanes that impacted the United States in 2005, namely Katrina, Ophelia, Rita and Wilma. The images were created from NOAA's geostationary and polar-orbiting environmental satellites. In addition to the images, the poster has a map depicting the general track of each storm, a color temperature scale to read the hurricane cloud top temperatures, high level information on each storm, the category at time of landfall; as well as, a Saffir-Simpson Hurricane Scale. Poster size is 36""x32""." proprietary
PRECIP_AMSR2_GCOMW1_1 NASA MEASURES Precipitation Ensemble based on AMSR2 GCOMW1 NASA PPS L1C V05 TBs 1-orbit L2 Swath 10x10km V1 (PRECIP_AMSR2_GCOMW1) at GES DISC GES_DISC STAC Catalog 2012-07-02 2021-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2368305620-GES_DISC.umm_json The data presented in this level 2 orbital product are rain rate estimates expressed as mm/hour determined from brightness temperatures (Tbs) obtained from the Advanced Microwave Scanning Radiometer-2 (AMSR-2) flown on the Global Climate Observing Mission-Water 1 (GCOM-W1). Most of the products generated in this data set are based upon the algorithms developed for the 3rd Algorithm Intercomparison Project (AIP-3) of the Global Precipitation Climatology Project (GPCP). Details of these 15 algorithms and development of a quality score which is a measure of confidence in the estimate, along with processing and algorithmic flags, can be found in the Algorithm Theoretical Basis Document (ATBD). The data in this product cover the period from 2012 to 2020 with one file per orbit. proprietary
@@ -13343,16 +13344,16 @@ Peatland_carbon_balance_1382_1 Global Peatland Carbon Balance and Land Use Chang
Pelican_PCO2_0 Partial pressure of carbon dioxide (PCO2) onboard the Pelican research vessel OB_DAAC STAC Catalog 2006-04-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360591-OB_DAAC.umm_json Measurements from the Pelican research vessel made off the southern coast of Louisiana in the Gulf of Mexico from 2006. proprietary
PenBaySurvey_0 Penobscot Bay Optical Survey OB_DAAC STAC Catalog 2007-11-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360592-OB_DAAC.umm_json Measurements made in the Penobscot Bay between 2007 and 2008. proprietary
PermafrostThaw_CarbonEmissions_1872_1 Projections of Permafrost Thaw and Carbon Release for RCP 4.5 and 8.5, 1901-2299 ORNL_CLOUD STAC Catalog 1901-01-01 2300-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2254686682-ORNL_CLOUD.umm_json This dataset consists of an ensemble of model projections from 1901 to 2299 for the northern hemisphere permafrost domain. The model projections include monthly average values for a common set of diagnostic outputs at a spatial resolution of 0.5 x 0.5 degrees latitude and longitude. The model simulations resulted from a synthesis effort organized by the Permafrost Carbon Network to evaluate the impacts of climate change on the carbon cycle in permafrost regions in the high northern latitudes. The model teams used different historical input weather data, but most used driver data developed by the Climate Research Unit - National Centers for Environmental Prediction (CRUNCEP) as modified for the Multiscale Terrestrial Model Intercomparison Project (MsTMIP). The teams scaled the driver data for the projections using output from global climate models from the fifth Coupled Model Intercomparison Project (CMIP5). The synthesis evaluated the terrestrial carbon cycle in the modern era and projected future emissions of carbon under two climate warming scenarios: Representative Concentration Pathways 4.5 and 8.5 (RCP45 and RCP85) from CMIP5. RCP45 represents emissions resulting in a global climate close to the target climate in the Paris Accord. RCP85 represents unconstrained greenhouse gas emissions. proprietary
-Permafrost_ActiveLayer_NSlope_1759_1 ABoVE: Active Layer Soil Characterization of Permafrost Sites, Northern Alaska, 2018 ORNL_CLOUD STAC Catalog 2018-08-22 2018-08-26 -149.31, 68.61, -148.56, 69.81 https://cmr.earthdata.nasa.gov/search/concepts/C2143402217-ORNL_CLOUD.umm_json This dataset provides in situ soil measurements including soil dielectric properties, temperature, and moisture profiles, active layer thickness (ALT), and measurements of soil organic matter, bulk density, porosity, texture, and coarse root biomass. Samples were collected from the surface to permafrost table in soil pits at selected sites along the Dalton Highway in Northern Alaska. From North to South, the study sites include Franklin Bluffs, Sagwon, Happy Valley, Ice Cut, and Imnavait Creek. Measurements were made from August 22 to August 26, 2018. The purpose of the field campaign was to characterize the dielectric properties of permafrost active layer soils in support of the NASA Arctic and Boreal Vulnerability Experiment (ABoVE) Airborne Campaign. proprietary
Permafrost_ActiveLayer_NSlope_1759_1 ABoVE: Active Layer Soil Characterization of Permafrost Sites, Northern Alaska, 2018 ALL STAC Catalog 2018-08-22 2018-08-26 -149.31, 68.61, -148.56, 69.81 https://cmr.earthdata.nasa.gov/search/concepts/C2143402217-ORNL_CLOUD.umm_json This dataset provides in situ soil measurements including soil dielectric properties, temperature, and moisture profiles, active layer thickness (ALT), and measurements of soil organic matter, bulk density, porosity, texture, and coarse root biomass. Samples were collected from the surface to permafrost table in soil pits at selected sites along the Dalton Highway in Northern Alaska. From North to South, the study sites include Franklin Bluffs, Sagwon, Happy Valley, Ice Cut, and Imnavait Creek. Measurements were made from August 22 to August 26, 2018. The purpose of the field campaign was to characterize the dielectric properties of permafrost active layer soils in support of the NASA Arctic and Boreal Vulnerability Experiment (ABoVE) Airborne Campaign. proprietary
-Permafrost_Thaw_Depth_YK_1598_1 ABoVE: Permafrost Measurements and Distribution Across the Y-K Delta, Alaska, 2016 ALL STAC Catalog 2009-06-27 2016-07-17 -165.69, 61.17, -165.03, 61.29 https://cmr.earthdata.nasa.gov/search/concepts/C2162142273-ORNL_CLOUD.umm_json This dataset provides field observations of thaw depth and dominant vegetation types, a LiDAR-derived elevation map, and permafrost distribution and probability maps for an area on the coastal plain of the Yukon-Kuskokwim Delta (YKD), in western Alaska, USA. Field data were collected during July 8-17, 2016 to parameterize and to validate the derived permafrost maps. The YKD is in the sporadic to isolated permafrost zone where permafrost forms extensive elevated plateaus on abandoned floodplains. The region is extremely flat and vulnerable to eustatic sea-level rise and inland storm surges. These high-resolution permafrost maps support landscape change analyses and assessments of the impacts of climate change on permafrost in this region of high biological productivity, critical wildlife habitats, and subsistence-based human economy. proprietary
+Permafrost_ActiveLayer_NSlope_1759_1 ABoVE: Active Layer Soil Characterization of Permafrost Sites, Northern Alaska, 2018 ORNL_CLOUD STAC Catalog 2018-08-22 2018-08-26 -149.31, 68.61, -148.56, 69.81 https://cmr.earthdata.nasa.gov/search/concepts/C2143402217-ORNL_CLOUD.umm_json This dataset provides in situ soil measurements including soil dielectric properties, temperature, and moisture profiles, active layer thickness (ALT), and measurements of soil organic matter, bulk density, porosity, texture, and coarse root biomass. Samples were collected from the surface to permafrost table in soil pits at selected sites along the Dalton Highway in Northern Alaska. From North to South, the study sites include Franklin Bluffs, Sagwon, Happy Valley, Ice Cut, and Imnavait Creek. Measurements were made from August 22 to August 26, 2018. The purpose of the field campaign was to characterize the dielectric properties of permafrost active layer soils in support of the NASA Arctic and Boreal Vulnerability Experiment (ABoVE) Airborne Campaign. proprietary
Permafrost_Thaw_Depth_YK_1598_1 ABoVE: Permafrost Measurements and Distribution Across the Y-K Delta, Alaska, 2016 ORNL_CLOUD STAC Catalog 2009-06-27 2016-07-17 -165.69, 61.17, -165.03, 61.29 https://cmr.earthdata.nasa.gov/search/concepts/C2162142273-ORNL_CLOUD.umm_json This dataset provides field observations of thaw depth and dominant vegetation types, a LiDAR-derived elevation map, and permafrost distribution and probability maps for an area on the coastal plain of the Yukon-Kuskokwim Delta (YKD), in western Alaska, USA. Field data were collected during July 8-17, 2016 to parameterize and to validate the derived permafrost maps. The YKD is in the sporadic to isolated permafrost zone where permafrost forms extensive elevated plateaus on abandoned floodplains. The region is extremely flat and vulnerable to eustatic sea-level rise and inland storm surges. These high-resolution permafrost maps support landscape change analyses and assessments of the impacts of climate change on permafrost in this region of high biological productivity, critical wildlife habitats, and subsistence-based human economy. proprietary
+Permafrost_Thaw_Depth_YK_1598_1 ABoVE: Permafrost Measurements and Distribution Across the Y-K Delta, Alaska, 2016 ALL STAC Catalog 2009-06-27 2016-07-17 -165.69, 61.17, -165.03, 61.29 https://cmr.earthdata.nasa.gov/search/concepts/C2162142273-ORNL_CLOUD.umm_json This dataset provides field observations of thaw depth and dominant vegetation types, a LiDAR-derived elevation map, and permafrost distribution and probability maps for an area on the coastal plain of the Yukon-Kuskokwim Delta (YKD), in western Alaska, USA. Field data were collected during July 8-17, 2016 to parameterize and to validate the derived permafrost maps. The YKD is in the sporadic to isolated permafrost zone where permafrost forms extensive elevated plateaus on abandoned floodplains. The region is extremely flat and vulnerable to eustatic sea-level rise and inland storm surges. These high-resolution permafrost maps support landscape change analyses and assessments of the impacts of climate change on permafrost in this region of high biological productivity, critical wildlife habitats, and subsistence-based human economy. proprietary
PhenoCam_V2_1674_2 PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018 ORNL_CLOUD STAC Catalog 1999-11-16 2018-12-31 -158.15, -22.97, 119.22, 71.28 https://cmr.earthdata.nasa.gov/search/concepts/C2764826583-ORNL_CLOUD.umm_json This data set provides a time series of vegetation phenological observations for 393 sites across diverse ecosystems of the world (mostly North America) from 2000-2018. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals. proprietary
Phenocam_Images_V2_1689_2 PhenoCam Dataset v2.0: Digital Camera Imagery from the PhenoCam Network, 2000-2018 ORNL_CLOUD STAC Catalog 1999-11-16 2018-12-31 -158.15, -22.97, 119.22, 71.28 https://cmr.earthdata.nasa.gov/search/concepts/C2764728896-ORNL_CLOUD.umm_json This dataset provides a time series of visible-wavelength digital camera imagery collected through the PhenoCam Network at each of 393 sites predominantly in North America from 2000-2018. The raw imagery was used to derive information on phenology, including time series of vegetation color, canopy greenness, and phenology transition dates for the PhenoCam Dataset v2.0. proprietary
Phenology_AmeriFlux_Neon_Sites_2033_1 Land Surface Phenology, Eddy Covariance Tower Sites, North America, 2017-2021 ORNL_CLOUD STAC Catalog 2017-01-01 2021-12-31 -176.13, 14.34, -57.3, 70.98 https://cmr.earthdata.nasa.gov/search/concepts/C2764693210-ORNL_CLOUD.umm_json This land surface phenology (LSP) dataset provides spatially explicit data related to the timing of phenological changes such as the start, peak, and end of vegetation activity, vegetation index metrics and associated quality assurance flags. The data are for the growing seasons of 2017-2021 for 10-km x 10-km windows centered over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. The dataset is derived at 3-m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. These LSP data can be used to assess satellite-based LSP products, to evaluate predictions from land surface models, and to analyze processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes. The data are provided in NetCDF format along with geospatial area-of-interest information and visualizations of the analysis window for each site in GeoJSON and HTML formats. proprietary
Phenology_Deciduous_Forest_1570_1 Landsat-derived Spring and Autumn Phenology, Eastern US - Canadian Forests, 1984-2013 ORNL_CLOUD STAC Catalog 1984-01-01 2013-12-31 -124.42, 29.63, -60.4, 62.04 https://cmr.earthdata.nasa.gov/search/concepts/C2764880255-ORNL_CLOUD.umm_json This dataset provides Landsat phenology algorithm (LPA) derived start and end of growing seasons (SOS and EOS) at 500-m resolution for deciduous and mixed forest areas of 75 selected Landsat sidelap regions across the Eastern United States and Canada. The data are a 30-year time series (1984-2013) of derived spring and autumn phenology for forested areas of the Eastern Temperate Forest, Northern Forest, and Taiga ecoregions. proprietary
-Photos_ThermokarstLakes_AK_1845_1 ABoVE: Aerial Photographs of Frozen Lakes near Fairbanks, Alaska, October 2014 ALL STAC Catalog 2014-10-08 2014-10-08 -147.95, 64.86, -147.76, 64.94 https://cmr.earthdata.nasa.gov/search/concepts/C2143401765-ORNL_CLOUD.umm_json This dataset includes high resolution orthophotographs of 21 lakes in the region of Fairbanks, Alaska, USA. Aerial photographs were taken on October 8, 2014, three days after lake-ice formation. These photographs were used to identify open holes in lake ice that indicate the location of hotspot seeps associated with the releases of methane from thawing permafrost. Aerial photography can be used to measure changes in lake areas and to observe patterns in the formation of lake ice and other early winter lake conditions. proprietary
Photos_ThermokarstLakes_AK_1845_1 ABoVE: Aerial Photographs of Frozen Lakes near Fairbanks, Alaska, October 2014 ORNL_CLOUD STAC Catalog 2014-10-08 2014-10-08 -147.95, 64.86, -147.76, 64.94 https://cmr.earthdata.nasa.gov/search/concepts/C2143401765-ORNL_CLOUD.umm_json This dataset includes high resolution orthophotographs of 21 lakes in the region of Fairbanks, Alaska, USA. Aerial photographs were taken on October 8, 2014, three days after lake-ice formation. These photographs were used to identify open holes in lake ice that indicate the location of hotspot seeps associated with the releases of methane from thawing permafrost. Aerial photography can be used to measure changes in lake areas and to observe patterns in the formation of lake ice and other early winter lake conditions. proprietary
+Photos_ThermokarstLakes_AK_1845_1 ABoVE: Aerial Photographs of Frozen Lakes near Fairbanks, Alaska, October 2014 ALL STAC Catalog 2014-10-08 2014-10-08 -147.95, 64.86, -147.76, 64.94 https://cmr.earthdata.nasa.gov/search/concepts/C2143401765-ORNL_CLOUD.umm_json This dataset includes high resolution orthophotographs of 21 lakes in the region of Fairbanks, Alaska, USA. Aerial photographs were taken on October 8, 2014, three days after lake-ice formation. These photographs were used to identify open holes in lake ice that indicate the location of hotspot seeps associated with the releases of methane from thawing permafrost. Aerial photography can be used to measure changes in lake areas and to observe patterns in the formation of lake ice and other early winter lake conditions. proprietary
Pingo_Veg_Plots_1507_1 Arctic Vegetation Plots from Pingo Communities, North Slope, Alaska, 1984-1986 ORNL_CLOUD STAC Catalog 1983-01-01 1983-12-31 -149.95, 69.71, -147.66, 70.5 https://cmr.earthdata.nasa.gov/search/concepts/C2170970856-ORNL_CLOUD.umm_json This data set provides vegetation species and vegetation plot data collected between 1983 and 1985 from 293 study plots on 41 pingos on the North Slope of Alaska. The pingos were located within the Arctic Coastal Plain in the Kuparuk, Prudhoe Bay, Kadleroshilik, and Toolik River areas. Specific attributes include dominant vegetation species, cover, soil pH, moisture, and physical characteristics of the plots. proprietary
PlanetScope.Full.Archive_7.0 PlanetScope Full Archive ESA STAC Catalog 2016-06-22 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336933-ESA.umm_json "The PlanetScope Level 1B Basic Scene and Level 3B Ortho Scene full archive products are available as part of Planet imagery offer. The Unrectified Asset: PlanetScope Basic Analytic Radiance (TOAR) product is a Scaled Top of Atmosphere Radiance (at sensor) and sensor corrected product, without correction for any geometric distortions inherent in the imaging processes and is not mapped to a cartographic projection. The imagery data is accompanied by Rational Polynomial Coefficients (RPCs) to enable orthorectification by the user. This kind of product is designed for users with advanced image processing and geometric correction capabilities. Basic Scene Product Components and Format Product Components Image File (GeoTIFF format) Metadata File (XML format) Rational Polynomial Coefficients (XML format) Thumbnail File (GeoTIFF format) Unusable Data Mask UDM File (GeoTIFF format) Usable Data Mask UDM2 File (GeoTIFF format) Bands 4-band multispectral image (blue, green, red, near-infrared) or 8-band (coastal-blue, blue, green I, green, yellow, red, Rededge, near-infrared) Ground Sampling Distance Approximate, satellite altitude dependent Dove-C: 3.0 m-4.1 m Dove-R: 3.0 m-4.1 m SuperDove: 3.7 m-4.2 m Accuracy <10 m RMSE The Rectified assets: The PlanetScope Ortho Scene product is radiometrically-, sensor- and geometrically- corrected and is projected to a UTM/WGS84 cartographic map projection. The geometric correction uses fine Digital Elevation Models (DEMs) with a post spacing of between 30 and 90 metres. Ortho Scene Product Components and Format Product Components Image File (GeoTIFF format) Metadata File (XML format) Thumbnail File (GeoTIFF format) Unusable Data Mask UDM File (GeoTIFF format) Usable Data Mask UDM2 File (GeoTIFF format) Bands 3-band natural colour (red, green, blue) or 4-band multispectral image (blue, green, red, near-infrared) or 8-band (coastal-blue, blue, green I, green, yellow, red, RedEdge, near-infrared) Ground Sampling Distance Approximate, satellite altitude dependent Dove-C: 3.0 m-4.1 m Dove-R: 3.0 m-4.1 m SuperDove: 3.7 m-4.2 m Projection UTM WGS84 Accuracy <10 m RMSE PlanetScope Ortho Scene product is available in the following: PlanetScope Visual Ortho Scene product is orthorectified and colour-corrected (using a colour curve) 3-band RGB Imagery. This correction attempts to optimise colours as seen by the human eye providing images as they would look if viewed from the perspective of the satellite. PlanetScope Surface Reflectance product is orthorectified, 4-band BGRN or 8-band Coastal Blue, Blue, Green I, Green, Yellow, Red, RedEdge, NIR Imagery with geometric, radiometric and corrected for surface reflection. This data is optimal for value-added image processing such as land cover classifications. PlanetScope Analytic Ortho Scene Surface Reflectance product is orthorectified, 4-band BGRN or 8-band Coastal Blue, Blue, Green I, Green, Yellow, Red, RedEdge, NIR Imagery with geometric, radiometric and calibrated to top of atmosphere radiance. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
PlanetScopeESAarchive_8.0 PlanetScope ESA archive ESA STAC Catalog 2018-11-15 2018-11-21 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C2547572362-ESA.umm_json "The PlanetScope ESA archive collection consists of PlanetScope products requested by ESA supported projects over their areas of interest around the world and that ESA collected over the years. The dataset regularly grows as ESA collects new products. Three product lines for PlanetScope imagery are offered, for all of them the Ground Sampling Distance at nadir is 3.7 m (at reference altitude 475 km). EO-SIP Product Type Product description Processing Level PSC_DEF_S3 3 bands – Analytic and Visual - Basic and Ortho Scene level 1B and 3B PSC_DEF_S4 4 bands – Analytic and Visual - Basic and Ortho Scene level 1B and 3B PSC_DEF_OT 3 bands, 4 bands and 5 bands – Analytic and Visual - Ortho Tile level 3A The Basic Scene product is a single-frame scaled Top of Atmosphere Radiance (at sensor) and sensor-corrected product. The product is not orthorectified or corrected for terrain distortions, radiometric and sensor corrections are applied to the data. The Ortho Scenes product is a single-frame scaled Top of Atmosphere Radiance (at sensor) or Surface Reflectance image product. The product is radiometrically, sensor and geometrically corrected and is projected to a cartographic map (UTM/WGS84). The Ortho Tiles are multiple orthorectified scenes in a single strip that have been merged and then divided according to a defined grid. Radiometric and sensor corrections are applied, the imagery is orthorectified and projected to a UTM projection. Spatial coverage: Check the spatial coverage of the collection on a _$$map$$ https://tpm-ds.eo.esa.int/socat/PlanetScope available on the Third Party Missions Dissemination Service. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
@@ -13372,8 +13373,8 @@ Polarimetric_CT_1601_1 AfriSAR: Canopy Structure Derived from PolInSAR and Coher
Polarimetric_height_profile_1577_1 AfriSAR: Polarimetric Height Profiles by TomoSAR, Lope and Rabi Forests, Gabon, 2016 ALL STAC Catalog 2016-02-25 2016-02-28 9.67, -2.08, 11.86, 0.1 https://cmr.earthdata.nasa.gov/search/concepts/C2734257089-ORNL_CLOUD.umm_json This dataset provides height profiles derived from UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar; JPL) data acquired over Lope National Park and Rabi Forest in Gabon as part of the AfriSAR campaign in 2016. These data were produced using synthetic aperture radar tomography (TomoSAR), a method that reveals three-dimensional forest structures by extending the conventional two-dimensional imaging capabilities of radars using multiple images acquired from slightly different antenna positions. AfriSAR was an airborne campaign that collected radar, lidar, and field measurements of forests in Gabon, West Africa, as part of a collaborative mission between NASA, the European Space Agency, and the Gabonese Space Agency. These data will help prepare for and calibrate current and upcoming spaceborne missions that aim to gauge the role of forests in Earth's carbon cycle, such as the Global Ecosystem Dynamics Investigation (GEDI). proprietary
Polarimetric_height_profile_1577_1 AfriSAR: Polarimetric Height Profiles by TomoSAR, Lope and Rabi Forests, Gabon, 2016 ORNL_CLOUD STAC Catalog 2016-02-25 2016-02-28 9.67, -2.08, 11.86, 0.1 https://cmr.earthdata.nasa.gov/search/concepts/C2734257089-ORNL_CLOUD.umm_json This dataset provides height profiles derived from UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar; JPL) data acquired over Lope National Park and Rabi Forest in Gabon as part of the AfriSAR campaign in 2016. These data were produced using synthetic aperture radar tomography (TomoSAR), a method that reveals three-dimensional forest structures by extending the conventional two-dimensional imaging capabilities of radars using multiple images acquired from slightly different antenna positions. AfriSAR was an airborne campaign that collected radar, lidar, and field measurements of forests in Gabon, West Africa, as part of a collaborative mission between NASA, the European Space Agency, and the Gabonese Space Agency. These data will help prepare for and calibrate current and upcoming spaceborne missions that aim to gauge the role of forests in Earth's carbon cycle, such as the Global Ecosystem Dynamics Investigation (GEDI). proprietary
Poplar_Veg_Plots_1376_1 Arctic Vegetation Plots, Poplars, Arctic and Interior AK and YT, Canada, 2003-2005 ORNL_CLOUD STAC Catalog 2003-06-18 2005-08-17 -162.74, 61.08, -135.22, 69.47 https://cmr.earthdata.nasa.gov/search/concepts/C2170969941-ORNL_CLOUD.umm_json This data set provides vegetation cover and environmental plot data collected from 32 balsam poplar (Populus balsamifera L., Salicaceae) vegetation plots located on the Arctic Slope of Alaska and in the interior boreal forests of Alaska and the Yukon from 2003 to 2005. The estimated percent land cover by species per plot are according to the older Braun-Blanquet cover-abundance scale. Plot data includes moisture, topographic position, slope, aspect, shape, and soil data. proprietary
-PostFire_Tree_Regeneration_1955_1.1 ABoVE: Synthesis of Post-Fire Regeneration Across Boreal North America ALL STAC Catalog 1989-01-01 2018-12-31 -152.2, 49.12, -71.01, 66.96 https://cmr.earthdata.nasa.gov/search/concepts/C2539840222-ORNL_CLOUD.umm_json This dataset is a synthesis of species-specific pre- and post-fire tree stem density estimates, field plot characterization data, and acquired climate moisture deficit data for sites from Alaska, USA eastward to Quebec, Canada in fires that burned between 1989 and 2014. Data are from 1,538 sites across 58 fire perimeters encompassing 4.52 Mha of forest and all major boreal ecozones in North America. To be included in this synthesis, a site had to contain information on species-specific post-fire seedling densities. This included sites where seedlings had been counted 2-13 years post-fire, a timeframe over which there was little change in relative dominance of species based on densities. Plot characterization data includes stand age, site drainage, disturbance history, crown combustion severity, seedbed conditions, and stand structural attributes. Gridded values of Hargreaves Climate Moisture Deficit (CMD) were obtained for each plot where plot coordinates were available. These values included 30-year normals (1981-2010) and CMD in the two years immediately following the fire year. CMD anomalies were calculated as the difference between the 30-year normal and the single year values for each of the first two years after a fire. These synthesis data are provided in comma-separated values (CSV) format. proprietary
PostFire_Tree_Regeneration_1955_1.1 ABoVE: Synthesis of Post-Fire Regeneration Across Boreal North America ORNL_CLOUD STAC Catalog 1989-01-01 2018-12-31 -152.2, 49.12, -71.01, 66.96 https://cmr.earthdata.nasa.gov/search/concepts/C2539840222-ORNL_CLOUD.umm_json This dataset is a synthesis of species-specific pre- and post-fire tree stem density estimates, field plot characterization data, and acquired climate moisture deficit data for sites from Alaska, USA eastward to Quebec, Canada in fires that burned between 1989 and 2014. Data are from 1,538 sites across 58 fire perimeters encompassing 4.52 Mha of forest and all major boreal ecozones in North America. To be included in this synthesis, a site had to contain information on species-specific post-fire seedling densities. This included sites where seedlings had been counted 2-13 years post-fire, a timeframe over which there was little change in relative dominance of species based on densities. Plot characterization data includes stand age, site drainage, disturbance history, crown combustion severity, seedbed conditions, and stand structural attributes. Gridded values of Hargreaves Climate Moisture Deficit (CMD) were obtained for each plot where plot coordinates were available. These values included 30-year normals (1981-2010) and CMD in the two years immediately following the fire year. CMD anomalies were calculated as the difference between the 30-year normal and the single year values for each of the first two years after a fire. These synthesis data are provided in comma-separated values (CSV) format. proprietary
+PostFire_Tree_Regeneration_1955_1.1 ABoVE: Synthesis of Post-Fire Regeneration Across Boreal North America ALL STAC Catalog 1989-01-01 2018-12-31 -152.2, 49.12, -71.01, 66.96 https://cmr.earthdata.nasa.gov/search/concepts/C2539840222-ORNL_CLOUD.umm_json This dataset is a synthesis of species-specific pre- and post-fire tree stem density estimates, field plot characterization data, and acquired climate moisture deficit data for sites from Alaska, USA eastward to Quebec, Canada in fires that burned between 1989 and 2014. Data are from 1,538 sites across 58 fire perimeters encompassing 4.52 Mha of forest and all major boreal ecozones in North America. To be included in this synthesis, a site had to contain information on species-specific post-fire seedling densities. This included sites where seedlings had been counted 2-13 years post-fire, a timeframe over which there was little change in relative dominance of species based on densities. Plot characterization data includes stand age, site drainage, disturbance history, crown combustion severity, seedbed conditions, and stand structural attributes. Gridded values of Hargreaves Climate Moisture Deficit (CMD) were obtained for each plot where plot coordinates were available. These values included 30-year normals (1981-2010) and CMD in the two years immediately following the fire year. CMD anomalies were calculated as the difference between the 30-year normal and the single year values for each of the first two years after a fire. These synthesis data are provided in comma-separated values (CSV) format. proprietary
Post_Fire_C_Emissions_1787_1 ABoVE: Spatial Estimates of Carbon Combustion from Wildfires across SK, Canada, 2015 ORNL_CLOUD STAC Catalog 2015-04-06 2015-08-11 -116.06, 51.19, -100.17, 61.24 https://cmr.earthdata.nasa.gov/search/concepts/C2143401918-ORNL_CLOUD.umm_json This dataset provides spatial estimates of carbon combustion from all 2015 wildfire burned areas across Saskatchewan, Canada, on a 30-m grid. Carbon combustion (kg C/m2) was derived from post-fire field measurements of carbon stocks completed in 2016 at 47 stands that burned during three 2015 Saskatchewan wildfires (Egg, Philion, and Brady) and at 32 unburned stands in adjacent areas. The study areas covered two ecozones (Boreal Plains and Boreal Shield), two stand-replacing history types (fire and timber harvest), three soil moisture classes (xeric, mesic, and subhygric), and three stand dominance classifications (coniferous, deciduous, and mixed). To spatially extrapolate estimates of combustion to all 2015 fires in Saskatchewan, a predictive radial support vector machine model was trained on the 47 burned stands with associated environmental variables and geospatial predictors and applied to historical fire areas. The dataset also includes uncertainty estimates represented as per pixel standard deviations of model estimates derived using a Monte Carlo analysis. proprietary
Post_Fire_C_Emissions_1787_1 ABoVE: Spatial Estimates of Carbon Combustion from Wildfires across SK, Canada, 2015 ALL STAC Catalog 2015-04-06 2015-08-11 -116.06, 51.19, -100.17, 61.24 https://cmr.earthdata.nasa.gov/search/concepts/C2143401918-ORNL_CLOUD.umm_json This dataset provides spatial estimates of carbon combustion from all 2015 wildfire burned areas across Saskatchewan, Canada, on a 30-m grid. Carbon combustion (kg C/m2) was derived from post-fire field measurements of carbon stocks completed in 2016 at 47 stands that burned during three 2015 Saskatchewan wildfires (Egg, Philion, and Brady) and at 32 unburned stands in adjacent areas. The study areas covered two ecozones (Boreal Plains and Boreal Shield), two stand-replacing history types (fire and timber harvest), three soil moisture classes (xeric, mesic, and subhygric), and three stand dominance classifications (coniferous, deciduous, and mixed). To spatially extrapolate estimates of combustion to all 2015 fires in Saskatchewan, a predictive radial support vector machine model was trained on the 47 burned stands with associated environmental variables and geospatial predictors and applied to historical fire areas. The dataset also includes uncertainty estimates represented as per pixel standard deviations of model estimates derived using a Monte Carlo analysis. proprietary
Post_Fire_SOC_NWT_2235_1 Post-fire Recovery of Soil Organic Layer Carbon in Canadian Boreal Forests, 2015-2018 ORNL_CLOUD STAC Catalog 2015-06-11 2018-08-24 -132.67, 59.79, -104.19, 68.33 https://cmr.earthdata.nasa.gov/search/concepts/C2854211353-ORNL_CLOUD.umm_json This dataset provides site moisture, soil organic layer thickness, soil organic carbon, nonvascular plant functional group, stand dominance, ecozone, time-after-fire, jack pine proportion, and deciduous proportion for 511 forested plots spanning ~140,000 km2 across two ecozones of the Northwest Territories, Canada (NWT). The plots were established during 2015-2018 across 41 wildfire scars and unburned areas (no burn history prior to 1965), with 317 plots in the Plains and 194 plots in the Shield regions. At each plot, two adjacent 30-m transects were established 2 m apart, running north from the plot origin. Soil organic layer (SOL) depth (cm) was measured every 3 m and the mean was taken from the 10 measurements to calculate a plot-level SOL thickness. Three soil organic layer profiles were destructively sampled at 0, 12, and 24 m using a corer that was custom designed for NWT soils. Within the transects, all stems taller than 1.37 m were identified to species to calculate tree density (stems / m2). Nonvascular plant percent cover was identified to functional group at five, 1-m2 quadrats spaced 6 m apart along the belt transect. A subset of 2,067 of 5,137 total increments from 1,803 profiles from 421 plots were analyzed for total percent C using a CHN analyzer. Time-after-fire was established using fire history records. For older plots where no known fire history is recorded, tree age was used. Data are for the period 2015-06-11 to 2018-08-24 and are provided in comma-separated values (CSV) format. proprietary
@@ -13395,8 +13396,8 @@ PreDeltaX_Vegetation_Structure_1805_1 Pre-Delta-X: Vegetation Species, Structure
PreDeltaX_Water_Level_Data_1801_1 Pre-Delta-X: Water Levels across Wax Lake Outlet, Atchafalaya Basin, LA, USA, 2016 ORNL_CLOUD STAC Catalog 2016-10-13 2016-10-20 -91.45, 29.51, -91.36, 29.74 https://cmr.earthdata.nasa.gov/search/concepts/C2025123345-ORNL_CLOUD.umm_json This dataset provides absolute water level elevations derived for 10 locations across the Wax Lake Delta, Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Field measurements were made during the Pre-Delta-X campaign on October 13-20, 2016. Relative water level measurements were recorded every five minutes during a one-week period using in situ pressure transducers (Solinst) to measure water surface elevation change with millimeter accuracy. The Solinst system combines a total pressure transducer (TPT) and a temperature detector. Once underwater, the TPT measures the sum of the atmosphere and water pressure above the sensor. Atmospheric pressure fluctuations must be accounted for to obtain the height of the water column above the TPT. An absolute elevation correction was applied to the water level data using an iterative approach with the USGS Calumet Station water level height and Airborne Snow Observatory (ASO) lidar water level profiles. These Pre-Delta-X water level measurements served to calibrate and validate the campaign's remote sensing observations and hydrodynamic models. proprietary
Pre_LBA_ABRACOS_899_1.1 Pre-LBA Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) Data ORNL_CLOUD STAC Catalog 1991-01-01 1996-12-31 -75, -18, -46, 5 https://cmr.earthdata.nasa.gov/search/concepts/C2762262185-ORNL_CLOUD.umm_json The data set presents the principal data from the Anglo-BRazilian Amazonian Climate Observation Study (ABRACOS) (Gash et al, 1996) and provides quality controlled information from five of the study topics considered by the project in five zipped files containing ASCII text data. The five study topics include Micrometeorology, Climate, Carbon Dioxide and Water Vapor, Plant Physiology, and Soil Moisture. The objectives of the ABRACOS were to monitor Amazonian climate and improve the understanding of the consequences of deforestation and to provide data for the calibration and validation of GCMs and GCM sub-models of Amazonian forest and post-deforestation pasture (Shuttleworth et al, 1991). Three areas were instrumented, each with different soils, dry season intensities and deforestation densities (Gash et al, 1996). In each area, an automatic weather station and soil moisture measurement equipment were installed: in a primary forest site and in nearby cattle pasture, for monitoring climate and soil status throughout the year. Additional intensive periods of study (or Missions), of varying duration, were operated at these sites: for calibration purposes, to understand the physical processes relevant to each site, and for detailed comparisons between sites. These data were collected under the ABRACOS project and made available by the UK Institute of Hydrology and the Instituto Nacional de Pesquisas Espaciais (Brazil). ABRACOS is a collaboration between the Agencia Brasileira de Cooperacao and the UK Overseas Development Administration. The processed, quality controlled and integrated data in the documented Pre-LBA data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually. proprietary
Proantar_0 Measurements off James Ross Island, Antarctica OB_DAAC STAC Catalog 2005-01-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360623-OB_DAAC.umm_json Measurements made off James Ross Island near Antarctica in 2005. proprietary
-Profile_based_PBL_heights_1706_1.1 ACT-America: Profile-based Planetary Boundary Layer Heights, Eastern USA ALL STAC Catalog 2016-07-18 2019-07-26 -106.36, 28.65, -73.13, 49.49 https://cmr.earthdata.nasa.gov/search/concepts/C2677222693-ORNL_CLOUD.umm_json This dataset provides profile-based estimates of the height to the top of the planetary boundary layer (PBL), also known as the atmospheric boundary layer (ABL), in meters above mean sea level estimated from meteorological measurements acquired during ascending or descending vertical profile flight segments during NASA's Atmospheric Carbon and Transport - America (ACT-America) airborne campaign. ACT-America flights sampled the atmosphere over the central and eastern United States seasonally from 2016 - 2019. Two aircraft platforms, the NASA Langley Beechcraft B-200 King Air and the NASA Goddard Space Flight Center's C-130 Hercules, were used to collect high-quality in situ measurements across a variety of continental surfaces and atmospheric conditions. proprietary
Profile_based_PBL_heights_1706_1.1 ACT-America: Profile-based Planetary Boundary Layer Heights, Eastern USA ORNL_CLOUD STAC Catalog 2016-07-18 2019-07-26 -106.36, 28.65, -73.13, 49.49 https://cmr.earthdata.nasa.gov/search/concepts/C2677222693-ORNL_CLOUD.umm_json This dataset provides profile-based estimates of the height to the top of the planetary boundary layer (PBL), also known as the atmospheric boundary layer (ABL), in meters above mean sea level estimated from meteorological measurements acquired during ascending or descending vertical profile flight segments during NASA's Atmospheric Carbon and Transport - America (ACT-America) airborne campaign. ACT-America flights sampled the atmosphere over the central and eastern United States seasonally from 2016 - 2019. Two aircraft platforms, the NASA Langley Beechcraft B-200 King Air and the NASA Goddard Space Flight Center's C-130 Hercules, were used to collect high-quality in situ measurements across a variety of continental surfaces and atmospheric conditions. proprietary
+Profile_based_PBL_heights_1706_1.1 ACT-America: Profile-based Planetary Boundary Layer Heights, Eastern USA ALL STAC Catalog 2016-07-18 2019-07-26 -106.36, 28.65, -73.13, 49.49 https://cmr.earthdata.nasa.gov/search/concepts/C2677222693-ORNL_CLOUD.umm_json This dataset provides profile-based estimates of the height to the top of the planetary boundary layer (PBL), also known as the atmospheric boundary layer (ABL), in meters above mean sea level estimated from meteorological measurements acquired during ascending or descending vertical profile flight segments during NASA's Atmospheric Carbon and Transport - America (ACT-America) airborne campaign. ACT-America flights sampled the atmosphere over the central and eastern United States seasonally from 2016 - 2019. Two aircraft platforms, the NASA Langley Beechcraft B-200 King Air and the NASA Goddard Space Flight Center's C-130 Hercules, were used to collect high-quality in situ measurements across a variety of continental surfaces and atmospheric conditions. proprietary
Prudhoe_Bay_ArcSEES_Veg_Plots_1555_1 Arctic Vegetation Plots, Prudhoe Bay ArcSEES Road Study, Lake Colleen, Alaska, 2014 ORNL_CLOUD STAC Catalog 2014-08-06 2014-08-13 -148.47, 70.22, -148.47, 70.22 https://cmr.earthdata.nasa.gov/search/concepts/C2162122325-ORNL_CLOUD.umm_json This dataset provides environmental, soil, and vegetation data collected from study plots in the vicinity of Lake Colleen off the Spine Road at Prudhoe Bay, Alaska, during August of 2014. Data include vegetation species, leaf area index (LAI), percent cover classes, soil moisture and color, and plot characteristics including geology, topographic position, slope, aspect, and plot disturbance. proprietary
Prudhoe_Bay_Veg_Maps_1387_1 Geobotanical and Impact Map Collection for Prudhoe Bay Oilfield, Alaska, 1972-2010 ORNL_CLOUD STAC Catalog 1949-01-01 2010-07-31 -150.17, 69.97, -146.97, 71.03 https://cmr.earthdata.nasa.gov/search/concepts/C2162616071-ORNL_CLOUD.umm_json This data set provides a collection of maps of geoecological characteristics of areas within the Beechey Point quadrangle near Prudhoe Bay on the North slope of Alaska: a geobotanical atlas of the Prudhoe Bay region, a land cover map of the Beechey Point quadrangle, and cumulative impact maps in the Prudhoe Bay Oilfield for ten dates from 1968 to 2010. The geobotanical atlas is based on aerial photographs and covers 145 square kilometers of the Prudhoe Bay Oilfield. The land cover map of the Beechey Point quadrangle was derived from the Landsat multispectral scanner, aerial photography, and other field and cartographic methods. The cumulative impact maps of the Prudhoe Bay Oilfield show historical infrastructure and natural changes digitized from aerial photos taken in each successive analysis year (1968, 1970, 1972, 1973, 1977, 1979, 1983, 1990, 2001, and 2010). Nine geoecological attributes are included: dominant vegetation, secondary vegetation, tertiary vegetation, percentage open water, landform, dominant surface form, secondary surface form, dominant soil, and secondary soil. These data document environmental changes in an Arctic region that is affected by both climate change and rapid industrial development. proprietary
Prudhoe_Bay_Veg_Plots_1360_1 Arctic Vegetation Plots at Prudhoe Bay, Alaska, 1973-1980 ORNL_CLOUD STAC Catalog 1973-01-01 1980-12-31 -148.95, 70.25, -148.29, 70.38 https://cmr.earthdata.nasa.gov/search/concepts/C2170969598-ORNL_CLOUD.umm_json This data set provides environmental, soil, and vegetation data collected between 1973 and 1980 from 89 study plots in the Prudhoe Bay region of Alaska. Data includes the baseline plot information for vegetation, soils, and site factors for study plots subjectively located in 43 plant communities and 4 broad habitat types across the glaciated landscape. Specific attributes include: dominant vegetation, species, and cover; soil chemistry, physical characteristics, moisture, and organic matter. This product brings together for easy reference all the available information collected from the plots that has been used for classification, mapping, and analysis of geobotanical factors in the Prudhoe Bay region and across Alaska. proprietary
@@ -13468,15 +13469,15 @@ RSCAT_LEVEL_2B_OWV_COMP_12_V1.1_1.1 RapidScat Level 2B Ocean Wind Vectors in 12.
RSCAT_LEVEL_2B_OWV_COMP_12_V1.2_1.2 RapidScat Level 2B Ocean Wind Vectors in 12.5km Slice Composites Version 1.2 POCLOUD STAC Catalog 2015-08-19 2016-08-19 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C2526576305-POCLOUD.umm_json "This dataset contains the RapidScat Level 2B 12.5km Version 1.2 science-quality ocean surface wind vectors, which are intended as a replacement and continuation of the Version 1.1 data forward from orbital revolution number 5127, corresponding to 19 August 2015; the overlapping time period starting on 19 August 2015 corresponds to the first time period of the recorded low signal-to-noise ratio (SNR). The Level 2B wind vectors are binned on a 12.5 km Wind Vector Cell (WVC) grid and processed using the Level 2A Sigma-0 dataset. RapidScat is a Ku-band dual beam circular rotating scatterometer retaining much of the same hardware and functionality of QuikSCAT, with exception of the antenna sub-system and digital interface to the International Space Station (ISS) Columbus module, which is where RapidScat is mounted. The NASA mission is officially referred to as ISS-RapidScat. Unlike QuikSCAT, ISS-RapidScat is not in sun-synchronous orbit, and flies at roughly half the altitude with a low inclination angle that restricts data coverage to the tropics and mid-latitude regions; the extent of latitudinal coverage stretches from approximately 61 degrees North to 61 degrees South. Furthermore, there is no consistent local time of day retrieval. This dataset is provided in a netCDF-3 file format that follows the netCDF-4 classic model (i.e., generated by the netCDF-4 API) and made available via FTP and OPeNDAP. For data access, please click on the ""Data Access"" tab above. This Version 1.2 dataset differs from the previous Version 1.1 dataset as follows: 1) L1B sigma-0 has been re-calibrated during the periods of low signal-to-noise ratio (SNR) and 2) during low SNR periods the L1B sigma-0 calibration is determined using re-pointed L1B QuikSCAT data. It is advised for users to avoid using the ""wind_obj"" variable in this dataset since it is minimally applicable and meant primarily for quality assurance; for users who wish to access the objective function values for each ambiguity, it is suggested to use only the ""ambiguity_obj"" variable. The ""wind_obj"" variable contains DIRTH probabilities (which are derived form the ""ambiguity_obj"" objective function values) in the range of 0 to 1 indicating the conditional probability that the true direction is within + or - 2.5 degrees of the retrieved wind direction given the observed backscatter measurements in the cell. If you have any questions or concerns, please visit our Forum at https://podaac.jpl.nasa.gov/forum/." proprietary
RSCAT_LEVEL_2B_OWV_COMP_12_V1.3_1.3 RapidScat Level 2B Ocean Wind Vectors in 12.5km Slice Composites Version 1.3 POCLOUD STAC Catalog 2016-02-11 2016-08-19 -180, -61, 180, 61 https://cmr.earthdata.nasa.gov/search/concepts/C2526576326-POCLOUD.umm_json "This dataset contains the RapidScat Level 2B 12.5km Version 1.3 science-quality ocean surface wind vectors, which are intended as a replacement and continuation of the Version 1.1 and 1.2 data forward from orbital revolution number 7873, corresponding to 11 February 2016; on 11 Feb 2016, RapidScat entered it's 3rd low signal to noise ratio (SNR) state and the initial calibration of low SNR 3 was preliminary during the Version 1.2 release. The fundamental difference between Version 1.3 and the previous Version 1.2 datasets is that the L1B sigma-0 has been re-calibrated during the periods of low SNR states 3 and 4 using re-pointed QuikSCAT data. The Version 1.1 should still be considered valid up to the first rev of version 1.2 (5127), and similarly version 1.2 shall be considered valid up to the first rev of version 1.3 (7873). The Level 2B wind vectors are binned on a 12.5 km Wind Vector Cell (WVC) grid and processed using the Level 2A Sigma-0 dataset. RapidScat is a Ku-band dual beam circular rotating scatterometer retaining much of the same hardware and functionality of QuikSCAT, with exception of the antenna sub-system and digital interface to the International Space Station (ISS) Columbus module, which is where RapidScat is mounted. The NASA mission is officially referred to as ISS-RapidScat. Unlike QuikSCAT, ISS-RapidScat is not in sun-synchronous orbit, and flies at roughly half the altitude with a low inclination angle that restricts data coverage to the tropics and mid-latitude regions; the extent of latitudinal coverage stretches from approximately 61 degrees North to 61 degrees South. Furthermore, there is no consistent local time of day retrieval. This dataset is provided in a netCDF-3 file format that follows the netCDF-4 classic model (i.e., generated by the netCDF-4 API) and made available via FTP and OPeNDAP. For data access, please click on the ""Data Access"" tab above. It is advised for users to avoid using the ""wind_obj"" variable in this dataset since it is minimally applicable and meant primarily for quality assurance; for users who wish to access the objective function values for each ambiguity, it is suggested to use only the ""ambiguity_obj"" variable. The ""wind_obj"" variable contains DIRTH probabilities (which are derived form the ""ambiguity_obj"" objective function values) in the range of 0 to 1 indicating the conditional probability that the true direction is within + or - 2.5 degrees of the retrieved wind direction given the observed backscatter measurements in the cell. If you have any questions or concerns, please visit our Forum at https://podaac.jpl.nasa.gov/forum/." proprietary
RSES_PCM_1 Cosmogenic dating AU_AADC STAC Catalog 2001-12-20 63.6203, -75.2756, 73.7101, -69.7425 https://cmr.earthdata.nasa.gov/search/concepts/C1214313722-AU_AADC.umm_json The data set consists of cosmogenic exposure ages for samples collected by Research School of Earth Sciences in the Prince Charles Mountains and vicinity. Thus far work has been carried out in the 2001/2002, 2002/2003, 2003/2004 and 2004/2005 field seasons. Currently, the only data publicly available is an excel spreadsheet detailing sampling locations. The objectives of this project were: To develop a comprehensive understanding of the Lambert Glacier of East Antarctica, from the time of the last maximum glaciation to the present, through an integrated and interdisciplinary study combining new field evidence - ice retreat history from cosmogenic exposure dating, geodetic measurements of crustal rebound, satellite measurements of present ice heights and changes therein - with other geological and glaciological data and numerical geophysical modelling advances. The project contributes to the quantitative characterisation of the complex interactions between ice-sheets, oceans and solid earth within the climate system. Outcomes have implications for geophysics, glaciology, geomorphology, climate, and past and future sea-level change. This work was completed as part of ASAC projects 2502 and 2516 (ASAC_2502 and ASAC_2516). The fields in this dataset are: Sample Date Collector Type Lithology Location Elevation Latitude Longitude proprietary
-RSFDCE_KLIM4 Absolute Minimum of Air Temperature. Year By Year Data ALL STAC Catalog 1881-01-01 1965-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608674-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by West Sybiria Computer Centre in 1977 and containes data from 1078 stations of the USSR. Data is currently stored on magnetic tape (800 bit/inch). proprietary
RSFDCE_KLIM4 Absolute Minimum of Air Temperature. Year By Year Data SCIOPS STAC Catalog 1881-01-01 1965-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608674-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by West Sybiria Computer Centre in 1977 and containes data from 1078 stations of the USSR. Data is currently stored on magnetic tape (800 bit/inch). proprietary
+RSFDCE_KLIM4 Absolute Minimum of Air Temperature. Year By Year Data ALL STAC Catalog 1881-01-01 1965-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608674-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by West Sybiria Computer Centre in 1977 and containes data from 1078 stations of the USSR. Data is currently stored on magnetic tape (800 bit/inch). proprietary
RSFDCE_KLIM5 Air Temperature 01.00 P.M. Year By Year Date SCIOPS STAC Catalog 1881-01-01 1965-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608673-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by West Subiria Computer Centre in 1977 and containes data from 1078 stations of the USSR. Data is currently stored on magnetic tape (800 bit/inch). proprietary
RSFDCE_KLIM5 Air Temperature 01.00 P.M. Year By Year Date ALL STAC Catalog 1881-01-01 1965-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608673-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by West Subiria Computer Centre in 1977 and containes data from 1078 stations of the USSR. Data is currently stored on magnetic tape (800 bit/inch). proprietary
RSS18_AVIRIS_L1B_449_1 BOREAS RSS-18 Level 1B AVIRIS At-Sensor Radiance Imagery ORNL_CLOUD STAC Catalog 1996-08-14 1996-08-14 -106.49, 53.45, -105.03, 54.32 https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.umm_json This dataset holds Level 1B (L1B) radiance data collected by the AVIRIS-Classic instrument near Prince Albert, Saskatchewan, Canada, on August 14, 1996. This imagery was acquired for the Boreal Ecosystem-Atmosphere Study (BOREAS) project in the boreal forests of central Canada. BOREAS focused on improving the understanding of exchanges of radiative energy, sensible heat, water, CO2 and trace gases between the boreal forest and the lower atmosphere. NASA's AVIRIS-Classic is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-Classic measures reflected radiance in 224 contiguous bands at approximately 10-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 400-2500 nm. The AVIRIS-Classic sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub meter range. For these data, AVIRIS-Classic was deployed on NASA's ER-2 high altitude aircraft. These spectra are acquired as images with 20-meter spatial resolution, 11 km swath width, and flight lines up to 800 km in length. The measurements are spectrally, radiometrically, and geometrically calibrated. There are seven flight lines subdivided into 66 scenes. The dataset includes the radiance imagery cube for each scene along with calibration and navigation information. The radiance data are in instrument coordinates, georeferenced by center of each scan line, and provided in a binary file. Metadata are included in a mixture of binary and text file formats. proprietary
RSS_WindSat_L1C_TB_V08.0_8.0 RSS WindSat L1C Calibrated TB Version 8 POCLOUD STAC Catalog 2003-02-01 2020-10-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2559430954-POCLOUD.umm_json The WindSat Polarimetric Radiometer, launched on January 6, 2003 aboard the Department of Defense Coriolis satellite, was designed to measure the ocean surface wind vector from space. It developed by the Naval Research Laboratory (NRL) Remote Sensing Division and the Naval Center for Space Technology for the U.S. Navy and the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Integrated Program Office (IPO). The dataset contains the Level 1C WindSat Top of the Atmosphere (TOA) TB processed by RSS. The WindSat radiances are turned into TOA TB after correction for hot and cold calibration anomalies, receiver non-linearities, sensor pointing errors, antenna cross-polarization contamination, spillover, Faraday rotation and polarization alignment. The data are resampled on a fixed regular 0.125 deg Earth grid using Backus-Gilbert Optimum Interpolation. The sampling is done separately for fore and aft looks. The 10.7, 18.7, 23.8, 37.0 GHz channels are resampled to the 10.7 GHz spatial resolution. The 6.8 GHz channels are given at their native spatial resolution. The 10.7, 18.7, 23.8, 37.0 GHz channels are absolutely calibrated using the GMI sensor as calibration reference. The 6.8 GHz channels are calibrated using the open ocean with the RSS ocean emission model and the Amazon rain forest as calibration targets. The Faraday rotation angle (FRA) and geometric polarization basis rotation angle (PRA) were added in the last run. proprietary
Radarsat-2_8.0 RADARSAT-2 ESA Archive ESA STAC Catalog 2008-07-27 2021-04-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689631-ESA.umm_json The RADARSAT-2 ESA archive collection consists of RADARSAT-2 products requested by ESA supported projects over their areas of interest around the world. The dataset regularly grows as ESA collects new products over the years. Following Beam modes are available: Standard, Wide Swath, Fine Resolution, Extended Low Incidence, Extended High Incidence, ScanSAR Narrow and ScanSAR Wide. Standard Beam Mode allows imaging over a wide range of incidence angles with a set of image quality characteristics which provides a balance between fine resolution and wide coverage, and between spatial and radiometric resolutions. Standard Beam Mode operates with any one of eight beams, referred to as S1 to S8, in single and dual polarisation . The nominal incidence angle range covered by the full set of beams is 20 degrees (at the inner edge of S1) to 52 degrees (at the outer edge of S8). Each individual beam covers a nominal ground swath of 100 km within the total standard beam accessibility swath of more than 500 km. BEAM MODE: Standard PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 8.0 or 11.8 x 5.1 (SLC), 8.0 x 8.0 (SGX), 12.5 x 12.5 (SSG, SPG) Resolution - Range x Azimuth (m): 9.0 or 13.5 x 7.7 (SLC), 26.8 - 17.3 x 24.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 100 x 100 Range of Angle of Incidence (deg): 20 - 52 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: • Single: HH or VV or HV or VH • Dual: HH + HV or VV + VH Wide Swath Beam Mode allows imaging of wider swaths than Standard Beam Mode, but at the expense of slightly coarser spatial resolution. The three Wide Swath beams, W1, W2 and W3, provide coverage of swaths of approximately 170 km, 150 km and 130 km in width respectively, and collectively span a total incidence angle range from 20 degrees to 45 degrees. Polarisation can be single and dual. BEAM MODE: Wide PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 11.8 x 5.1 (SLC), 10 x 10 (SGX), 12.5 x 12.5 (SSG, SPG) Resolution - Range x Azimuth (m): 13.5 x 7.7 (SLC), 40.0 - 19.2 x 24.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 150 x 150 Range of Angle of Incidence (deg): 20 - 45 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: • Single: HH or VV or HV or VH • Dual: HH + HV or VV + VH Fine Resolution Beam Mode is intended for applications which require finer spatial resolution. Products from this beam mode have a nominal ground swath of 50 km. Nine Fine Resolution physical beams, F23 to F21, and F1 to F6 are available to cover the incidence angle range from 30 to 50 degrees. For each of these beams, the swath can optionally be centred with respect to the physical beam or it can be shifted slightly to the near or far range side. Thanks to these additional swath positioning choices, overlaps of more than 50% are provided between adjacent swaths. RADARSAT-2 can operate in single and dual polarisation for this beam mode. BEAM MODE: Fine PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 4.7 x 5.1 (SLC), 3.13 x 3.13 (SGX), 6.25 x 6.25 (SSG, SPG) Resolution - Range x Azimuth (m): 5.2 x 7.7 (SLC), 10.4 - 6.8 x 7.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 50 x 50 Range of Angle of Incidence (deg): 30 - 50 No. of Looks - Range x Azimuth: 1 x 1 (SLC,SGX, SGF, SSG, SPG) Polarisations - Options: • Single: HH or VV or HV or VH • Dual: HH + HV or VV + VH In the Extended Low Incidence Beam Mode, a single Extended Low Incidence Beam, EL1, is provided for imaging in the incidence angle range from 10 to 23 degrees with a nominal ground swath coverage of 170 km. Some minor degradation of image quality can be expected due to operation of the antenna beyond its optimum scan angle range. Only single polarisation is available. BEAM MODE: Extended Low PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 8.0 x 5.1 (SLC), 10.0 x 10.0 (SGX), 12.5 x 12.5 (SSG, SPG) Nominal Resolution - Range x Azimuth (m): 9.0 x 7.7 (SLC), 52.7 - 23.3 x 24.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 170 x 170 Range of Angle of Incidence (deg): 10 - 23 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: Single Pol HH In the Extended High Incidence Beam Mode, six Extended High Incidence Beams, EH1 to EH6, are available for imaging in the 49 to 60 degree incidence angle range. Since these beams operate outside the optimum scan angle range of the SAR antenna, some degradation of image quality, becoming progressively more severe with increasing incidence angle, can be expected when compared with the Standard Beams. Swath widths are restricted to a nominal 80 km for the inner three beams, and 70 km for the outer beams. Only single polarisation available. BEAM MODE: Extended High PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 11.8 x 5.1 (SLC), 8.0 x 8.0 (SGX), 12.5 x 12.5 (SSG, SPG) Resolution - Range x Azimuth (m): 13.5 x 7.7 (SLC), 18.2 - 15.9 x 24.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 75 x 75 Range of Angle of Incidence (deg): 49 - 60 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: Single Pol HH ScanSAR Narrow Beam Mode provides coverage of a ground swath approximately double the width of the Wide Swath Beam Mode swaths. Two swath positions with different combinations of physical beams can be used: SCNA, which uses physical beams W1 and W2, and SCNB, which uses physical beams W2, S5, and S6. Both options provide coverage of swath widths of about 300 km. The SCNA combination provides coverage over the incidence angle range from 20 to 39 degrees. The SCNB combination provides coverage over the incidence angle range 31 to 47 degrees. RADARSAT-2 can operate in single and dual polarisation for this beam mode. BEAM MODE: ScanSAR Narrow PRODUCT: SCN, SCF, SCS Nominal Pixel Spacing - Range x Azimuth (m) : 25 x 25 Nominal Resolution - Range x Azimuth (m):81-38 x 40-70 Nominal Scene Size - Range x Azimuth (km): 300 x 300 Range of Angle of Incidence (deg): 20 - 46 No. of Looks - Range x Azimuth: 2 x 2 Polarisations - Options: • Single Co or Cross: HH or VV or HV or VH • Dual: HH + HV or VV + VH ScanSAR Wide Beam Mode provides coverage of a ground swath approximately triple the width of the Wide Swath Beam Mode swaths. Two swath positions with different combinations of physical beams can be used: SCWA, which uses physical beams W1, W2, W3, and S7, and SCWB, which uses physical beams W1, W2, S5 and S6. The SCWA combination allows imaging of a swath of more than 500 km covering an incidence angle range of 20 to 49 degrees. The SCWB combination allows imaging of a swath of more than 450 km covering the incidence angle. Polarisation can be single and dual. BEAM MODE: ScanSAR Wide PRODUCT: SCW, SCF, SCS Nominal Pixel Spacing - Range x Azimuth (m) : 50 x 50 Resolution - Range x Azimuth (m): 163.0 - 73 x 78-106 Nominal Scene Size - Range x Azimuth (km): 500 x 500 Range of Angle of Incidence (deg): 20 - 49 No. of Looks - Range x Azimuth: 4 x 2 Polarisations - Options: • Single Co or Cross: HH or VV or HV or VH • Dual: HH + HV or VV + VH These are the different products : SLC (Single Look Complex): Amplitude and phase information is preserved. Data is in slant range. Georeferenced and aligned with the satellite track SGF (Path Image): Data is converted to ground range and may be multi-look processed. Scene is oriented in direction of orbit path. Georeferenced and aligned with the satellite track. SGX (Path Image Plus): Same as SGF except processed with refined pixel spacing as needed to fully encompass the image data bandwidths. Georeferenced and aligned with the satellite track SSG(Map Image): Image is geocorrected to a map projection. SPG (Precision Map Image): Image is geocorrected to a map projection. Ground control points (GCP) are used to improve positional accuracy. SCN(ScanSAR Narrow)/SCF(ScanSAR Wide) : ScanSAR Narrow/Wide beam mode product with original processing options and metadata fields (for backwards compatibility only). Georeferenced and aligned with the satellite track SCF (ScanSAR Fine): ScanSAR product equivalent to SGF with additional processing options and metadata fields. Georeferenced and aligned with the satellite track SCS(ScanSAR Sampled) : Same as SCF except with finer sampling. Georeferenced and aligned with the satellite track proprietary
-Radial_Growth_PRI_1781_1 ABoVE: Photochemical Reflectance and Tree Growth, Brooks Range, Alaska, 2018-2019 ORNL_CLOUD STAC Catalog 2018-05-01 2019-09-13 -149.76, 67.97, -149.72, 68.02 https://cmr.earthdata.nasa.gov/search/concepts/C2143401854-ORNL_CLOUD.umm_json This dataset provides simultaneous in-situ measurements of the photochemical reflectance index (PRI) and radial tree growth of selected white spruce trees (Picea glauca (Moench) Voss) at the northern treeline in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. PRI and dendrometer measurements were simultaneously collected on 29 trees from six plots spaced along a 5.5 km transect from south to north where tree density becomes increasingly sparse. Measurements were made throughout the 2018 and 2019 growing seasons (May 1 to September 15) with a sampling interval of 5 minutes. The data were collected to better understand the suitability of the PRI to remotely track radial tree growth dynamics. proprietary
Radial_Growth_PRI_1781_1 ABoVE: Photochemical Reflectance and Tree Growth, Brooks Range, Alaska, 2018-2019 ALL STAC Catalog 2018-05-01 2019-09-13 -149.76, 67.97, -149.72, 68.02 https://cmr.earthdata.nasa.gov/search/concepts/C2143401854-ORNL_CLOUD.umm_json This dataset provides simultaneous in-situ measurements of the photochemical reflectance index (PRI) and radial tree growth of selected white spruce trees (Picea glauca (Moench) Voss) at the northern treeline in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. PRI and dendrometer measurements were simultaneously collected on 29 trees from six plots spaced along a 5.5 km transect from south to north where tree density becomes increasingly sparse. Measurements were made throughout the 2018 and 2019 growing seasons (May 1 to September 15) with a sampling interval of 5 minutes. The data were collected to better understand the suitability of the PRI to remotely track radial tree growth dynamics. proprietary
+Radial_Growth_PRI_1781_1 ABoVE: Photochemical Reflectance and Tree Growth, Brooks Range, Alaska, 2018-2019 ORNL_CLOUD STAC Catalog 2018-05-01 2019-09-13 -149.76, 67.97, -149.72, 68.02 https://cmr.earthdata.nasa.gov/search/concepts/C2143401854-ORNL_CLOUD.umm_json This dataset provides simultaneous in-situ measurements of the photochemical reflectance index (PRI) and radial tree growth of selected white spruce trees (Picea glauca (Moench) Voss) at the northern treeline in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. PRI and dendrometer measurements were simultaneously collected on 29 trees from six plots spaced along a 5.5 km transect from south to north where tree density becomes increasingly sparse. Measurements were made throughout the 2018 and 2019 growing seasons (May 1 to September 15) with a sampling interval of 5 minutes. The data were collected to better understand the suitability of the PRI to remotely track radial tree growth dynamics. proprietary
Rain-on-Snow_Data_1611_1 ABoVE: Rain-on-Snow Frequency and Distribution during Cold Seasons, Alaska, 2003-2016 ALL STAC Catalog 2002-11-01 2016-12-31 -175.4, 48.62, -111.54, 73.85 https://cmr.earthdata.nasa.gov/search/concepts/C2162145449-ORNL_CLOUD.umm_json This dataset provides maps of rain-on-snow (ROS) events across Alaska for the individual months of November to March 2002-2011 and November to March 2012-2016, and annual water year summary maps for 2003-2011 and 2013-2016. ROS events were defined as changes in passive microwave (PM) detection in surface snow wetness and isothermal states induced by atmospheric processes often associated with winter rainfall. The data are summations of the number of days with ROS events per pixel at 6-km spatial resolution per month or per 5-month water year. The daily ROS record encompassed the months when snowmelt from solar irradiance is minimal and snow cover is widespread and relatively consistent throughout the region. Daily ROS geospatial classification across Alaska was derived by combining snow cover and daily microwave brightness temperature retrievals sensitive to landscape freeze-thaw dynamics from overlapping (1) Moderate Resolution Imaging Spectroradiometer (MODIS) MOD10A2 eight-day maximum snow cover extent (SCE) product and (2) Advanced Microwave Scanning Radiometer for EOS (AMSR-E) (2002-2011) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) (2012-to present) Microwave Radiation Imager (MWRI) observations at 19 GHz and 37 GHz. proprietary
Rain-on-Snow_Data_1611_1 ABoVE: Rain-on-Snow Frequency and Distribution during Cold Seasons, Alaska, 2003-2016 ORNL_CLOUD STAC Catalog 2002-11-01 2016-12-31 -175.4, 48.62, -111.54, 73.85 https://cmr.earthdata.nasa.gov/search/concepts/C2162145449-ORNL_CLOUD.umm_json This dataset provides maps of rain-on-snow (ROS) events across Alaska for the individual months of November to March 2002-2011 and November to March 2012-2016, and annual water year summary maps for 2003-2011 and 2013-2016. ROS events were defined as changes in passive microwave (PM) detection in surface snow wetness and isothermal states induced by atmospheric processes often associated with winter rainfall. The data are summations of the number of days with ROS events per pixel at 6-km spatial resolution per month or per 5-month water year. The daily ROS record encompassed the months when snowmelt from solar irradiance is minimal and snow cover is widespread and relatively consistent throughout the region. Daily ROS geospatial classification across Alaska was derived by combining snow cover and daily microwave brightness temperature retrievals sensitive to landscape freeze-thaw dynamics from overlapping (1) Moderate Resolution Imaging Spectroradiometer (MODIS) MOD10A2 eight-day maximum snow cover extent (SCE) product and (2) Advanced Microwave Scanning Radiometer for EOS (AMSR-E) (2002-2011) and the Advanced Microwave Scanning Radiometer 2 (AMSR2) (2012-to present) Microwave Radiation Imager (MWRI) observations at 19 GHz and 37 GHz. proprietary
RapidEye.ESA.archive_7.0 RapidEye ESA archive ESA STAC Catalog 2009-02-22 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C1965336937-ESA.umm_json The RapidEye ESA archive is a subset of the RapidEye Full archive that ESA collected over the years. The dataset regularly grows as ESA collects new RapidEye products. proprietary
@@ -13493,12 +13494,12 @@ RemSensPOC_0 Remote-sensing-derived particulate organic carbon (POC) validation
ResourceSat-1-IRS-P6.archive_6.0 ResourceSat-1/IRS-P6 full archive ESA STAC Catalog 2003-11-01 2013-09-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336942-ESA.umm_json ResourceSat-1 (also known as IRS-P6) archive products are available as below. • LISS-IV MN: Mono-Chromatic, Resolution 5 m, Coverage 70 km x 70 km, Radiometrically and Ortho (DN) corrected, Acquisition in Neustrelitz 2004 - 2010, Global Archive 2003 - 2013 • LISS-III: Multi-spectral, Resolution 20 m, Coverage 140 km x 140 km, Radiometrically and Ortho (DN) corrected (ortho delivered without Band 5), Acquisition in Neustrelitz 2004 - 2013, Global Archive 2003 - 2013 • AWiFS: Multi-spectral, Resolution 60 m, Coverage 370 km x 370 km, Radiometrically and Ortho (DN) corrected, Acquisition in Neustrelitz 2004 - 2013, Global Archive 2003 - 2013 Note: • LISS-IV: Mono-Chromatic, the band is selectable. In practice the red is used. • For LISS-IV MN and LISS-III ortho corrected: If unavailable, user has to supply ground control information and DEM in suitable qualityFor AWiFS ortho corrected: service based on in house available ground control information and DEM The products are available as part of the GAF Imagery products from the Indian missions: IRS-1C, IRS-1D, CartoSat-1 (IRS-P5), ResourceSat-1 (IRS-P6) and ResourceSat-2 (IRS-R2) missions. ‘ResourceSat-1 archive’ collection has worldwide coverage: for data acquired over Neustrelitz footprint, the users can browse the EOWEB GeoPortal catalogue (http://www.euromap.de/products/serv_003.html) to search archived products; worldwide data (out the Neustrelitz footprint) can be requested by contacting GAF user support to check the readiness since no catalogue is not available. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability (https://earth.esa.int/eogateway/documents/20142/37627/Indian-Data-Terms-Of-Applicability.pdf). proprietary
ResourceSat-2.archive.and.tasking_6.0 ResourceSat-2 full archive and tasking ESA STAC Catalog 2011-05-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336944-ESA.umm_json ResourceSat-2 (also known as IRS-R2) archive and tasking products are available as below: Sensor: LISS-IV Type: Mono-Chromatic Resolution (m): 5 Coverage (km x km): 70 x 70 System or radiometrically corrected and Ortho corrected (DN) Neustralitz archive: 2014 Global archive: 2011 Sensor: LISS-III Type: Multi-spectral Resolution (m): 20 Coverage (km x km): 140 x 140 System or radiometrically corrected, Ortho corrected (DN) and Ortho corrected (TOA reflectance) Neustralitz archive: 2014 Global archive: 2011 Sensor: AWiFS Type: Multi-spectral Resolution (m): 60 Coverage (km x km): 370 x 370 System or radiometrically corrected, Ortho corrected (DN) and Ortho corrected (TOA reflectance) Neustralitz archive: 2014 Global archive: 2011 Note: • LISS-IV: Mono-Chromatic, the band is selectable. In practice the red is used.For LISS-IV MN and LISS-III ortho corrected: If unavailable, user has to supply ground control information and DEM in suitable qualityFor AWiFS ortho corrected: service based on in house available ground control information and DEM The products are available as part of the GAF Imagery products from the Indian missions: IRS-1C, IRS-1D, CartoSat-1 (IRS-P5), ResourceSat-1 (IRS-P6) and ResourceSat-2 (IRS-R2) missions. ‘ResourceSat-2 archive and tasking’ collection has worldwide coverage: for data acquired over Neustrelitz footprint, the users can browse the EOWEB GeoPortal catalogue (http://www.euromap.de/products/serv_003.html) to search archived products; worldwide data (out the Neustrelitz footprint) can be requested by contacting GAF user support to check the readiness since no catalogue is not available. All details about the data provision, data access conditions and quota assignment procedure are described in the Terms of Applicability (https://earth.esa.int/eogateway/documents/20142/37627/Indian-Data-Terms-Of-Applicability.pdf). proprietary
Respiration_622_1 Global Annual Soil Respiration Data (Raich and Schlesinger 1992) ORNL_CLOUD STAC Catalog 1963-01-01 1992-01-01 -156.4, -37.5, 146.5, 71.18 https://cmr.earthdata.nasa.gov/search/concepts/C2216863171-ORNL_CLOUD.umm_json This data set is a compilation of soil respiration rates (g C m-2 yr-1) from terrestrial and wetland ecosystems reported in the literature prior to 1992. These rates were measured in a variety of ecosystems to examine rates of microbial activity, nutrient turnover, carbon cycling, root dynamics, and a variety of other soil processes. Also included in the data set are biome type, vegetation type, locality, and geographic coordinates. proprietary
-RiSCC_Outcomes_Bibliography_1 A bibliography containing references to the outcomes of the RiSCC project from the Antarctic and subantarctic regions AU_AADC STAC Catalog 1994-01-01 2006-12-31 -180, -70, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214311230-AU_AADC.umm_json A bibliography of references relating to the outcomes of the RiSCC project (Regional Sensitivity to Climate Change in Antarctic Terrestrial Ecosystems) from the Antarctic and subantarctic regions, dating from 1994 to 2006. The bibliography was compiled by Dana Bergstrom, and contains 162 references. proprietary
RiSCC_Outcomes_Bibliography_1 A bibliography containing references to the outcomes of the RiSCC project from the Antarctic and subantarctic regions ALL STAC Catalog 1994-01-01 2006-12-31 -180, -70, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214311230-AU_AADC.umm_json A bibliography of references relating to the outcomes of the RiSCC project (Regional Sensitivity to Climate Change in Antarctic Terrestrial Ecosystems) from the Antarctic and subantarctic regions, dating from 1994 to 2006. The bibliography was compiled by Dana Bergstrom, and contains 162 references. proprietary
-RiSCC_Research_Support_Bibliography_1 A bibliography containing references to the research support of the RiSCC project from the Antarctic and subantarctic regions ALL STAC Catalog 1875-01-01 2004-12-31 -180, -70, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214311231-AU_AADC.umm_json A bibliography of references relating to the research support of the RiSCC project (Regional Sensitivity to Climate Change in Antarctic Terrestrial Ecosystems) from the Antarctic and subantarctic regions, dating from 1875 to 2004. The bibliography was compiled by Dana Bergstrom, and contains 76 references. proprietary
+RiSCC_Outcomes_Bibliography_1 A bibliography containing references to the outcomes of the RiSCC project from the Antarctic and subantarctic regions AU_AADC STAC Catalog 1994-01-01 2006-12-31 -180, -70, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214311230-AU_AADC.umm_json A bibliography of references relating to the outcomes of the RiSCC project (Regional Sensitivity to Climate Change in Antarctic Terrestrial Ecosystems) from the Antarctic and subantarctic regions, dating from 1994 to 2006. The bibliography was compiled by Dana Bergstrom, and contains 162 references. proprietary
RiSCC_Research_Support_Bibliography_1 A bibliography containing references to the research support of the RiSCC project from the Antarctic and subantarctic regions AU_AADC STAC Catalog 1875-01-01 2004-12-31 -180, -70, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214311231-AU_AADC.umm_json A bibliography of references relating to the research support of the RiSCC project (Regional Sensitivity to Climate Change in Antarctic Terrestrial Ecosystems) from the Antarctic and subantarctic regions, dating from 1875 to 2004. The bibliography was compiled by Dana Bergstrom, and contains 76 references. proprietary
-River_Ice_Breakup_Freezeup_1697_1 ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016 ORNL_CLOUD STAC Catalog 1972-11-04 2016-11-30 -160.07, 62.9, -142.99, 66.36 https://cmr.earthdata.nasa.gov/search/concepts/C2143403517-ORNL_CLOUD.umm_json This dataset provides estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue. proprietary
+RiSCC_Research_Support_Bibliography_1 A bibliography containing references to the research support of the RiSCC project from the Antarctic and subantarctic regions ALL STAC Catalog 1875-01-01 2004-12-31 -180, -70, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214311231-AU_AADC.umm_json A bibliography of references relating to the research support of the RiSCC project (Regional Sensitivity to Climate Change in Antarctic Terrestrial Ecosystems) from the Antarctic and subantarctic regions, dating from 1875 to 2004. The bibliography was compiled by Dana Bergstrom, and contains 76 references. proprietary
River_Ice_Breakup_Freezeup_1697_1 ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016 ALL STAC Catalog 1972-11-04 2016-11-30 -160.07, 62.9, -142.99, 66.36 https://cmr.earthdata.nasa.gov/search/concepts/C2143403517-ORNL_CLOUD.umm_json This dataset provides estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue. proprietary
+River_Ice_Breakup_Freezeup_1697_1 ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016 ORNL_CLOUD STAC Catalog 1972-11-04 2016-11-30 -160.07, 62.9, -142.99, 66.36 https://cmr.earthdata.nasa.gov/search/concepts/C2143403517-ORNL_CLOUD.umm_json This dataset provides estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue. proprietary
RoyalPenguin1955-1969_1 Breeding biology of the Royal Penguin (Eudypted chrysolophus)at Macquarie Island 1955-1969 AU_AADC STAC Catalog 1955-01-01 1969-12-31 158.76892, -54.78247, 158.95569, -54.48201 https://cmr.earthdata.nasa.gov/search/concepts/C1214313721-AU_AADC.umm_json The data are contained in a number of log books in hand written form (now scanned onto CD ROM. They were gathered according to a protocol updated annually by the Principal Investigator, DR Robert Carrick (now deceased). Details are contained in the paper Carrick R (1972) Population ecology of the Australian black-backed magpie, royal penguin, and silver gull. in: Population ecology of migratory birds - A symposium. US Dept of the Interior, Fish and wildlife service. Wildlife Research Report 2. pp 41-99. The only other information on the Royal penguin population to come from these investigations is the PhD Thesis of G.T. Smith, Studies on the behaviour and reproduction of the Royal penguin Eudyptes chrysolophus schlegeli. Australian National University April 1970. The log books contain a vast array of observations on the Royal penguin. Major observations/studies include banding of chicks and adults, breeding chronology, egg laying, breeding success, arrival weights, movements within and between colonies. The protocols for the collection of the data are missing although some instructions and notes are included in the volumes. Some data have also been entered into an excel spreadsheet. proprietary
Ruker_rymill_sat_1 Mount Ruker and Mount Rymill Satellite Image Maps 1:100 000 AU_AADC STAC Catalog 1989-03-18 1989-11-29 63, -74, 66.67, -72.67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311244-AU_AADC.umm_json Two satellite images maps of Mt Ruker and Mt Rymill in the Australian Antarctic Territory were produced by the Australian Antarctic Division in 1998. Both maps are at a scale of 1:100 000 using Landsat TM imagery. Data source: Mount Ruker - Landsat TM imagery, scenes 128/112, acquired 29 November 1989. Mount Rymill - Landsat TM imagery, scenes 128/111 and 128/112, acquired 18 March 1989 and 29 November 1989 respectively. Nomenclature: Names have been approved by the Antarctic Names Committee of Australia. Please see the URL link for details on the images and processes used to produce these maps. proprietary
Russian_Forest_Disturbance_1294_1 Russian Boreal Forest Disturbance Maps Derived from Landsat Imagery, 1984-2000 ORNL_CLOUD STAC Catalog 1984-06-01 2000-08-31 30.98, 43.76, 138.63, 65.32 https://cmr.earthdata.nasa.gov/search/concepts/C2773247983-ORNL_CLOUD.umm_json This data set provides Boreal forest disturbance maps at 30-m resolution for 55 selected sites across Northern Eurasia within the Russian Federation. Disturbance events were derived from selected high-quality multi-year time series of Landsat Thematic Mapper and Enhanced Thematic Mapper Plus images (stacks) over the 1984 to 2000 time period. Forest pixels were classified by year of latest disturbance or as undisturbed. proprietary
@@ -13611,8 +13612,8 @@ SAR_IMM_1P_10.0 ERS-1/2 SAR IM Medium Resolution L1 [SAR_IMM_1P] ESA STAC Catalo
SAR_IMP_1P_8.0 ERS-1/2 SAR IM Precision L1 [SAR_IMP_1P] ESA STAC Catalog 1991-07-27 2011-07-04 -180, -82, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1532648151-ESA.umm_json The SAR Precision product is a multi-look (speckle-reduced), ground range image acquired in Image Mode. This product type is most applicable to users interested in remote sensing applications, but is also suitable for calibration purposes. The products are calibrated and corrected for the SAR antenna pattern and range-spreading loss. Radar backscatter can be derived from the products for geophysical modelling, but no correction is applied for terrain-induced radiometric effects. The images are not geocoded, and terrain distortion (foreshortening and layover) has not been removed. The numbering sequence relates to the satellite position and therefore differs between Ascending and Descending scenes. Product characteristics: - Pixel size: 12.5 m (range - across track) x 12.5 m (azimuth - along track) - Scene area: 100 km (range) x at least 102.5 km (azimuth) - Scene size: 8000 pixels range x at least 8200 lines (azimuth) - Pixel depth: 16 bits unsigned integer - Total product volume: 125 MBs - Projection: Ground-range - Number of looks: 3 proprietary
SAR_IMS_1P_8.0 ERS-1/2 SAR IM Single Look Complex L1 [SAR_IMS_1P] ESA STAC Catalog 1991-07-27 2011-07-04 -180, -82, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1532648152-ESA.umm_json The SAR SLC product is a single look complex acquired in Image Mode. It is a digital image, with slant range and phase preserved, generated from raw SAR data using up-to-date auxiliary parameters. The products are intended for use in SAR quality assessment, calibration and interferometric applications. A minimum number of corrections and interpolations are performed on the data. Absolute calibration parameters (when available) are provided in the product annotation. Product characteristics: - Pixel size: 8 m (range - across track) x 4 m (azimuth - along track – varying slightly depending on acquisition Pulse Repetition Frequency) - Scene area: 100 km (range) x at least 102.5 km (azimuth) - Scene size: 5000 samples (range) x at least 30000 lines (azimuth) - Pixel depth: 32 bits signed integer (16 bits I, 16 bits Q) - Total product volume: 575 MB - Projection: Slant range - Number of looks: 1 proprietary
SAR_IM_0P_9.0 ERS-1/2 SAR IM L0 [SAR_IM__0P] ESA STAC Catalog 1991-07-27 2011-07-04 -180, -82, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1965336946-ESA.umm_json This SAR Level 0 product is acquired in Image Mode. The products consist of the SAR telemetry data and are supplied as standard scenes. It also contains all the required auxiliary data necessary for data processing. The product serves two main purposes: For testing ERS SAR processors independently from the HDDR system For users interested in full SAR data processing. Product characteristics: - Scene area: 100 km (range - across track) x full segment length (azimuth - along track) - Scene size: 5616 samples (range) x full segment length (azimuth) - Pixel depth: 10 bits signed integer (5 bits I, 5 bits Q) - Projection: Slant range proprietary
-SAR_Methane_Ebullition_AK_1790_1 ABoVE: SAR-based Methane Ebullition Flux from Lakes, Five Regions, Alaska, 2007-2010 ALL STAC Catalog 2007-11-13 2010-11-11 -165.17, 64.44, -147.37, 71.35 https://cmr.earthdata.nasa.gov/search/concepts/C2143401901-ORNL_CLOUD.umm_json This dataset provides Synthetic Aperture Radar (SAR) estimates of lake-source methane ebullition flux in mg CH4/m2/d for thousands of lakes in five regions across Alaska. The study regions include the Atqasuk, Barrow Peninsula, Fairbanks, northern Seward Peninsula, and Toolik. L-band SAR backscatter values for early winter lake ice scenes were collected from 2007 to 2010 over 5,143 lakes using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) instrument on the Advanced Land Observing Satellite (ALOS-1) satellite. The backscatter data were combined with field measurements of methane ebullition from 48 study lakes across the five regions to obtain a volumetric flux estimate for each lake. Mean methane gas-fractions from each region were applied to the SAR-based volumetric fluxes to obtain an estimate of methane ebullition mass flux per lake. The data files contain lake perimeters and the lake-specific attributes of lake area, SAR backscatter values and standard errors, volumetric flux with standard errors, mean percent of methane from gas samples, and methane ebullition mass flux. proprietary
SAR_Methane_Ebullition_AK_1790_1 ABoVE: SAR-based Methane Ebullition Flux from Lakes, Five Regions, Alaska, 2007-2010 ORNL_CLOUD STAC Catalog 2007-11-13 2010-11-11 -165.17, 64.44, -147.37, 71.35 https://cmr.earthdata.nasa.gov/search/concepts/C2143401901-ORNL_CLOUD.umm_json This dataset provides Synthetic Aperture Radar (SAR) estimates of lake-source methane ebullition flux in mg CH4/m2/d for thousands of lakes in five regions across Alaska. The study regions include the Atqasuk, Barrow Peninsula, Fairbanks, northern Seward Peninsula, and Toolik. L-band SAR backscatter values for early winter lake ice scenes were collected from 2007 to 2010 over 5,143 lakes using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) instrument on the Advanced Land Observing Satellite (ALOS-1) satellite. The backscatter data were combined with field measurements of methane ebullition from 48 study lakes across the five regions to obtain a volumetric flux estimate for each lake. Mean methane gas-fractions from each region were applied to the SAR-based volumetric fluxes to obtain an estimate of methane ebullition mass flux per lake. The data files contain lake perimeters and the lake-specific attributes of lake area, SAR backscatter values and standard errors, volumetric flux with standard errors, mean percent of methane from gas samples, and methane ebullition mass flux. proprietary
+SAR_Methane_Ebullition_AK_1790_1 ABoVE: SAR-based Methane Ebullition Flux from Lakes, Five Regions, Alaska, 2007-2010 ALL STAC Catalog 2007-11-13 2010-11-11 -165.17, 64.44, -147.37, 71.35 https://cmr.earthdata.nasa.gov/search/concepts/C2143401901-ORNL_CLOUD.umm_json This dataset provides Synthetic Aperture Radar (SAR) estimates of lake-source methane ebullition flux in mg CH4/m2/d for thousands of lakes in five regions across Alaska. The study regions include the Atqasuk, Barrow Peninsula, Fairbanks, northern Seward Peninsula, and Toolik. L-band SAR backscatter values for early winter lake ice scenes were collected from 2007 to 2010 over 5,143 lakes using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) instrument on the Advanced Land Observing Satellite (ALOS-1) satellite. The backscatter data were combined with field measurements of methane ebullition from 48 study lakes across the five regions to obtain a volumetric flux estimate for each lake. Mean methane gas-fractions from each region were applied to the SAR-based volumetric fluxes to obtain an estimate of methane ebullition mass flux per lake. The data files contain lake perimeters and the lake-specific attributes of lake area, SAR backscatter values and standard errors, volumetric flux with standard errors, mean percent of methane from gas samples, and methane ebullition mass flux. proprietary
SASSIE_L1_SWIFT_V1_1 SASSIE Arctic Field Campaign L1 SWIFT Data Fall 2022 POCLOUD STAC Catalog 2022-08-01 2022-10-31 -153.6, 72, -145.5, 73.5 https://cmr.earthdata.nasa.gov/search/concepts/C2580152405-POCLOUD.umm_json The Salinity and Stratification at the Sea Ice Edge (SASSIE) project is a NASA experiment that aims to understand how salinity anomalies in the upper ocean generated by melting sea ice affect sea surface temperature (SST), stratification, and subsequent sea-ice growth. SASSIE involved a field campaign that sampled the transition from summer melt to autumn ice advance in the Beaufort Sea during August-October 2022, making intensive in situ and remote sensing observations within ~200km of the sea ice edge. The Surface Wave Instrument Float with Tracking (SWIFT) drifter is a passive Lagrangian wave-following sensor platform. During the SASSIE deployment, five SWIFT drifters were deployed in September 2022, collecting measurements of salinity, sea surface temperature, waves, and meteorological data. SWIFT drifter buoys contain GPS, a pulse-coherent Doppler velocity profiler, an autonomous meteorological station, and a digital video recorder. Level 1 data are available as compressed files containing graphics of the measurements alongside MATLAB and NetCDF files. proprietary
SASSIE_L1_WAVEGLIDER_V1_1 SASSIE Arctic Field Campaign L1 Wave Glider Data Fall 2022 POCLOUD STAC Catalog 2022-08-01 2022-10-31 -170.5, 67.46, -138, 75.75 https://cmr.earthdata.nasa.gov/search/concepts/C2580179397-POCLOUD.umm_json The Salinity and Stratification at the Sea Ice Edge (SASSIE) project is a NASA experiment that aims to understand how salinity anomalies in the upper ocean generated by melting sea ice affect sea surface temperature (SST), stratification, and subsequent sea-ice growth. SASSIE involved a field campaign that sampled the transition from summer melt to autumn ice advance in the Beaufort Sea during August-October 2022, making intensive in situ and remote sensing observations within ~200km of the sea ice edge. A waveglider is an autonomous platform propelled by the conversion of ocean wave energy into forward thrust and employing solar panels to power instrumentation. During the SASSIE deployment, four wavegliders were deployed near Prudhoe Bay on 12-14 August 2022. The wavegliders collect measurements of ocean surface salinity, temperature, currents, waves, and meteorological data. Custom integrated Casting CTDs provide additional profiles of salinity and temperature to a depth of 150m below the surface. L1 data are available as a compressed file containing graphics of the measurements alongside MATLAB data files. proprietary
SASSIE_L2_ALTO_ALAMO_FLOATS_V1_1 SASSIE Arctic Field Campaign ALTO/ALAMO Profiling Float Data Fall 2022 Version 1 POCLOUD STAC Catalog 2022-09-08 2022-10-15 -156, 71, -145, 73.5 https://cmr.earthdata.nasa.gov/search/concepts/C2638311700-POCLOUD.umm_json The Salinity and Stratification at the Sea Ice Edge (SASSIE) project is a NASA experiment that aims to understand how salinity anomalies in the upper ocean generated by melting sea ice affect sea surface temperature (SST), stratification, and subsequent sea-ice growth. SASSIE involved a field campaign that sampled the transition from summer melt to autumn ice advance in the Beaufort Sea during August-October 2022, making intensive in situ and remote sensing observations within ~200 km of the sea ice edge. This dataset contains temperature and salinity measurements collected by ALTO and Air Launched Autonomous Micro Observer (ALAMO) profiling floats deployed in the Beaufort Sea. ALTO floats had ice-avoidance firmware, meaning that they stopped surfacing and transmitting data once surface temperatures dropped to near-freezing values (indicating the presence of sea ice). They will hopefully reappear in summer 2023 to report data from the previous ice-covered season. ALAMO floats did not have ice-avoidance, in order to ensure that they reported data as long as possible during ice freeze-up. As a result, they will likely not survive over the winter. Future versions if this dataset may include data collected after Fall 2022. Data are available in netCDF format. proprietary
@@ -13704,8 +13705,8 @@ SEAC4RS_Sondes_Data_1 SEAC4RS Radiosonde/Ozonesonde Data LARC_ASDC STAC Catalog
SEAC4RS_TraceGas_AircraftInSitu_DC8_Data_1 SEAC4RS DC-8 Aircraft In-Situ Trace Gas Data LARC_ASDC STAC Catalog 2013-08-02 2013-09-24 -127, 19, -79, 51 https://cmr.earthdata.nasa.gov/search/concepts/C2119341669-LARC_ASDC.umm_json SEAC4RS_TraceGas_AircraftInSitu_DC8_Data are in-situ trace gas data collected onboard the DC8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEA4CRS) airborne field study. Data collection for this product is complete. Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) airborne field study was conducted in August and September of 2013. The field operation was based in Houston, Texas. The primary SEAC4RS science objectives are: to determine how pollutant emissions are redistributed via deep convection throughout the troposphere; to determine the evolution of gases and aerosols in deep convective outflow and the implications for UT/LS chemistry; to identify the influences and feedbacks of aerosol particles from anthropogenic pollution and biomass burning on meteorology and climate through changes in the atmospheric heat budget (i.e., semi-direct effect) or through microphysical changes in clouds (i.e., indirect effects); and lastly, to serve as a calibration and validation test bed for future satellite instruments and missions. The airborne observational data were collected from three aircraft platforms: the NASA DC-8, ER-2, and SPEC LearJet. Both the NASA DC-8 and ER-2 aircraft were instrumented for comprehensive in-situ and remote sensing measurements of the trace gas, aerosol properties, and cloud properties. In addition, radiative fluxes and meteorological parameters were also recorded. The NASA DC-8 was mostly responsible for tropospheric sampling, while the NASA ER-2 was operating in the lower stratospheric regime. The SPEC LearJet was dedicated to in-situ cloud characterizations. To accomplish the science objectives, the flight plans were designed to investigate the influence of biomass burning and pollution, their temporal evolution, and ultimately, impacts on meteorological processes which can, in turn, feedback on regional air quality. With respect to meteorological feedbacks, the opportunity to examine the impact of polluting aerosols on cloud properties and dynamics was of particular interest. proprietary
SEAC4RS_TraceGas_AircraftInSitu_ER2_Data_1 SEAC4RS ER-2 Aircraft In-Situ Trace Gas Data LARC_ASDC STAC Catalog 2013-08-01 2013-09-23 -128, 15, -82, 53 https://cmr.earthdata.nasa.gov/search/concepts/C2119341690-LARC_ASDC.umm_json SEAC4RS_TraceGas_AircraftInSitu_ER2_Data are in-situ trace gas data collected onboard the ER-2 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEA4CRS) airborne field study. Data collection for this product is complete. Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) airborne field study was conducted in August and September of 2013. The field operation was based in Houston, Texas. The primary SEAC4RS science objectives are: to determine how pollutant emissions are redistributed via deep convection throughout the troposphere; to determine the evolution of gases and aerosols in deep convective outflow and the implications for UT/LS chemistry; to identify the influences and feedbacks of aerosol particles from anthropogenic pollution and biomass burning on meteorology and climate through changes in the atmospheric heat budget (i.e., semi-direct effect) or through microphysical changes in clouds (i.e., indirect effects); and lastly, to serve as a calibration and validation test bed for future satellite instruments and missions. The airborne observational data were collected from three aircraft platforms: the NASA DC-8, ER-2, and SPEC LearJet. Both the NASA DC-8 and ER-2 aircraft were instrumented for comprehensive in-situ and remote sensing measurements of the trace gas, aerosol properties, and cloud properties. In addition, radiative fluxes and meteorological parameters were also recorded. The NASA DC-8 was mostly responsible for tropospheric sampling, while the NASA ER-2 was operating in the lower stratospheric regime. The SPEC LearJet was dedicated to in-situ cloud characterizations. To accomplish the science objectives, the flight plans were designed to investigate the influence of biomass burning and pollution, their temporal evolution, and ultimately, impacts on meteorological processes which can, in turn, feedback on regional air quality. With respect to meteorological feedbacks, the opportunity to examine the impact of polluting aerosols on cloud properties and dynamics was of particular interest. proprietary
SEAC4RS_jValue_AircraftInSitu_DC8_Data_1 SEAC4RS DC-8 Aircraft In-Situ Photolysis Rate Data LARC_ASDC STAC Catalog 2013-08-02 2013-09-24 -127, 19, -80, 51 https://cmr.earthdata.nasa.gov/search/concepts/C2119341667-LARC_ASDC.umm_json SEAC4RS_jValue_AircraftInSitu_DC8_Data are in-situ photolysis rate (j value) data collected onboard the DC8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEA4CRS) airborne field study. Data collection for this product is complete. Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) airborne field study was conducted in August and September of 2013. The field operation was based in Houston, Texas. The primary SEAC4RS science objectives are: to determine how pollutant emissions are redistributed via deep convection throughout the troposphere; to determine the evolution of gases and aerosols in deep convective outflow and the implications for UT/LS chemistry; to identify the influences and feedbacks of aerosol particles from anthropogenic pollution and biomass burning on meteorology and climate through changes in the atmospheric heat budget (i.e., semi-direct effect) or through microphysical changes in clouds (i.e., indirect effects); and lastly, to serve as a calibration and validation test bed for future satellite instruments and missions. The airborne observational data were collected from three aircraft platforms: the NASA DC-8, ER-2, and SPEC LearJet. Both the NASA DC-8 and ER-2 aircraft were instrumented for comprehensive in-situ and remote sensing measurements of the trace gas, aerosol properties, and cloud properties. In addition, radiative fluxes and meteorological parameters were also recorded. The NASA DC-8 was mostly responsible for tropospheric sampling, while the NASA ER-2 was operating in the lower stratospheric regime. The SPEC LearJet was dedicated to in-situ cloud characterizations. To accomplish the science objectives, the flight plans were designed to investigate the influence of biomass burning and pollution, their temporal evolution, and ultimately, impacts on meteorological processes which can, in turn, feedback on regional air quality. With respect to meteorological feedbacks, the opportunity to examine the impact of polluting aerosols on cloud properties and dynamics was of particular interest. proprietary
-SEAGLIDER_GUAM_2019_V1 Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020) POCLOUD STAC Catalog 2019-10-03 2020-01-15 143.63035, 13.39476, 144.613, 14.71229 https://cmr.earthdata.nasa.gov/search/concepts/C2151536874-POCLOUD.umm_json This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14°N 144°E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington. proprietary
SEAGLIDER_GUAM_2019_V1 Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020) ALL STAC Catalog 2019-10-03 2020-01-15 143.63035, 13.39476, 144.613, 14.71229 https://cmr.earthdata.nasa.gov/search/concepts/C2151536874-POCLOUD.umm_json This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14°N 144°E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington. proprietary
+SEAGLIDER_GUAM_2019_V1 Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020) POCLOUD STAC Catalog 2019-10-03 2020-01-15 143.63035, 13.39476, 144.613, 14.71229 https://cmr.earthdata.nasa.gov/search/concepts/C2151536874-POCLOUD.umm_json This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14°N 144°E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington. proprietary
SEAHAWK_VALIDATION_0 Continuing the Mission: SeaHawk-1 Ocean Color CubeSat Nanosatellite OB_DAAC STAC Catalog 2022-05-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2639478178-OB_DAAC.umm_json Satellite validation work related to the SeaHawk Ocean Color CubeSat mission. This is a partnership between NASA, UNCW, UGA, ACC Clyde Space and Cloudland instruments. The project was funded by the Gordon and Betty Moore Foundation (grant number 11171) for years 2022-2025. proprietary
SEASAT_SAR_L1_HDF5_1 SEASAT_SAR_LEVEL1_HDF5 ASF STAC Catalog 1978-07-04 1978-10-11 164.882812, 2.811371, 163.125, 77.235074 https://cmr.earthdata.nasa.gov/search/concepts/C1206500991-ASF.umm_json SEASAT Image Level 1 proprietary
SEASAT_SAR_L1_TIFF_1 SEASAT_SAR_LEVEL1_GEOTIFF ASF STAC Catalog 1978-07-04 1978-10-11 164.882812, 2.811371, 163.125, 77.235074 https://cmr.earthdata.nasa.gov/search/concepts/C1206500826-ASF.umm_json SEASAT Image GeoTIFF proprietary
@@ -13780,8 +13781,8 @@ SIMBAD_DESCHAMPS_LOA_0 Measurements using the SIMBAD radiometer by the Laboratoi
SIO-Pier_0 Scripps Ocean Institute (SOI) pier measurements OB_DAAC STAC Catalog 2007-04-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360662-OB_DAAC.umm_json Measurements made from the Scripps Ocean Institute pier in 2007. proprietary
SIPEX_ASPECT_1 ASPeCt Sea Ice Data from the SIPEX Voyage of the Aurora Australis in 2007-2008 AU_AADC STAC Catalog 2007-09-09 2007-10-11 116.43, -65.6, 129.133, -61.9 https://cmr.earthdata.nasa.gov/search/concepts/C1214311291-AU_AADC.umm_json ASPeCt is an expert group on multi-disciplinary Antarctic sea ice zone research within the SCAR Physical Sciences program. Established in 1996, ASPeCt has the key objective of improving our understanding of the Antarctic sea ice zone through focussed and ongoing field programs, remote sensing and numerical modelling. The program is designed to complement, and contribute to, other international science programs in Antarctica as well as existing and proposed research programs within national Antarctic programs. ASPeCt also includes a component of data rescue of valuable historical sea ice zone information. The overall aim of ASPeCt is to understand and model the role of Antarctic sea ice in the coupled atmosphere-ice-ocean system. This requires an understanding of key processes, and the determination of physical, chemical, and biological properties of the sea ice zone. These are addressed by objectives which are: 1) To establish the distribution of the basic physical properties of sea ice that are important to air-sea interaction and to biological processes within the Antarctic sea-ice zone (ice and snow cover thickness distributions; structural, chemical and thermal properties of the snow and ice; upper ocean hydrography; floe size and lead distribution). These data are required to derive forcing and validation fields for climate models and to determine factors controlling the biology and ecology of the sea ice-associated biota. 2) To understand the key sea-ice zone processes necessary for improved parameterization of these processes in coupled models. These ASPeCt measurements were taken onboard the Aurora Australis during the SIPEX voyage in the 2007-2008 summer season. proprietary
SIPEX_II_ASPECT_1 ASPeCt ship-based observations during the SIPEX II voyage of the Aurora Australis, 2012 AU_AADC STAC Catalog 2012-09-22 2012-11-11 113, -66, 125, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214311294-AU_AADC.umm_json This dataset contains observations of ice conditions taken from the bridge of the RV Aurora Australis during SIPEX 2012, following the Scientific Committee on Antarctic Research/CliC Antarctic Sea Ice Processes and Climate [ASPeCt] protocols. See aspect.antarctica.gov.au Observations include total and partial concentration, ice type, thickness, floe size, topography, and snow cover in each of three primary ice categories; open water characteristics, and weather summary. The dataset is comprised of the scanned pages of a single logbook, which holds hourly observations taken by observers while the ship was moving through sea-ice zone. The following persons assisted in the collection of these data: Dr R. Massom, AAD, Member of observation team Mr A. Steer, AAD, Member of observation team Prof S. Warren, UW(Seattle), USA, Member of observation team Dr J. Hutchings, IARC, UAF, USA, Member of observation team Dr T. Toyota, Inst Low Temp Science, Japan, Member of observation team Dr T. Tamura, NIPR, Japan, Member of EM observation team Dr G. Dieckmann, AWI, Germany, Member of observation team Dr E. Maksym, WHOI, USA, Member of observation team Mr R. Stevens, IMAS, Trainee on observation team Dr J. Melbourne-Thomas, ACE CRC, Trainee on observation team Dr A. Giles, ACE CRC, Trainee on observation team Ms M. Zhia, IMAS, Trainee on observation team Ms J. Jansens, IMAS, Trainee on observation team Mr R. Humphries, Univ Wollengong, Trainee on observation team Mr C. Sampson, Univ Utah, USA, Trainee on observation team Mr Olivier Lecomte, Univ Catholique, Louvain-la-Neuve, Belgium, Trainee on observation team Mr D. Lubbers, Univ Utah, USA, Trainee on observation team Ms M. Zatko, UW(Seattle), USA, Trainee on observation team Ms C. Gionfriddo, Uni Melbourne, Trainee on observation team Mr K. Nakata, EES, Japan, Trainee on observation team proprietary
-SIPEX_II_AUV_1 3-D mapping of sea ice draft with an autonomous underwater vehicle AU_AADC STAC Catalog 2012-09-28 2012-10-13 115, -65, 125, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214311295-AU_AADC.umm_json We set out to achieve floe-scale 3-D mapping of sea ice draft and bio-optical parameters using a Multibeam SONAR and Hyperspectral radiometer mounted to an Autonomous Underwater Vehicle (AUV). The AUV utilised was the 'JAGUAR' Seabed-class vehicle from the Deep Submergence Laboratory at the WoodsHole Oceanographic Institution. The AUV comes with a CTD and ADCP. However these are not deployed as scientific sensors and therefore are unsupported in terms of metadata. In particular the CTD was not calibrated before or during the voyage. The AUV used a LongBaseLine system formed by three transponders to navigate to and from the survey grid. Two were located on the ice and the third was deployed from the back of the ship with an acoustic communications modem. Once at the survey grid beneath the sea ice, the AUV used the DVL to navigate using bottom-tracking of the underside of the sea ice. We conducted 4 missions beneath sea-ice during the SIPEX-II voyage. The current status of the data is that is in un-processed and unavailable until final processing is completed in 2013. Persons interested in the data should contact Dr Guy Williams directly for further information and preliminary figures relating to the AUV missions. The files currently in the archive are in raw form. Some preliminary data is provided for stations 2, 3, 4 and 6 as: floe-2-20120926.mat floe-3-20121003.mat floe-4-20121006.mat floe-6-20121013.mat These can be accessed using the Seabed_plot routines (MATLAB) in this folder. There is a readme file provided called what-is-this.txt Also included is the video footage taken from the AUV using a GoPro HD Hero. Video Codec: avc1 Resolution: 1920x1080 pixels Frame Rate: 29.970030 f/s Audio Codec: mp4a Audio Bitrate: 1536 kb/s Finally, plots of the data for ice stations 2,3,4 and 6 are included in the preliminary figures folder. The file names indicate which ice station the plots are from. proprietary
SIPEX_II_AUV_1 3-D mapping of sea ice draft with an autonomous underwater vehicle ALL STAC Catalog 2012-09-28 2012-10-13 115, -65, 125, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214311295-AU_AADC.umm_json We set out to achieve floe-scale 3-D mapping of sea ice draft and bio-optical parameters using a Multibeam SONAR and Hyperspectral radiometer mounted to an Autonomous Underwater Vehicle (AUV). The AUV utilised was the 'JAGUAR' Seabed-class vehicle from the Deep Submergence Laboratory at the WoodsHole Oceanographic Institution. The AUV comes with a CTD and ADCP. However these are not deployed as scientific sensors and therefore are unsupported in terms of metadata. In particular the CTD was not calibrated before or during the voyage. The AUV used a LongBaseLine system formed by three transponders to navigate to and from the survey grid. Two were located on the ice and the third was deployed from the back of the ship with an acoustic communications modem. Once at the survey grid beneath the sea ice, the AUV used the DVL to navigate using bottom-tracking of the underside of the sea ice. We conducted 4 missions beneath sea-ice during the SIPEX-II voyage. The current status of the data is that is in un-processed and unavailable until final processing is completed in 2013. Persons interested in the data should contact Dr Guy Williams directly for further information and preliminary figures relating to the AUV missions. The files currently in the archive are in raw form. Some preliminary data is provided for stations 2, 3, 4 and 6 as: floe-2-20120926.mat floe-3-20121003.mat floe-4-20121006.mat floe-6-20121013.mat These can be accessed using the Seabed_plot routines (MATLAB) in this folder. There is a readme file provided called what-is-this.txt Also included is the video footage taken from the AUV using a GoPro HD Hero. Video Codec: avc1 Resolution: 1920x1080 pixels Frame Rate: 29.970030 f/s Audio Codec: mp4a Audio Bitrate: 1536 kb/s Finally, plots of the data for ice stations 2,3,4 and 6 are included in the preliminary figures folder. The file names indicate which ice station the plots are from. proprietary
+SIPEX_II_AUV_1 3-D mapping of sea ice draft with an autonomous underwater vehicle AU_AADC STAC Catalog 2012-09-28 2012-10-13 115, -65, 125, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214311295-AU_AADC.umm_json We set out to achieve floe-scale 3-D mapping of sea ice draft and bio-optical parameters using a Multibeam SONAR and Hyperspectral radiometer mounted to an Autonomous Underwater Vehicle (AUV). The AUV utilised was the 'JAGUAR' Seabed-class vehicle from the Deep Submergence Laboratory at the WoodsHole Oceanographic Institution. The AUV comes with a CTD and ADCP. However these are not deployed as scientific sensors and therefore are unsupported in terms of metadata. In particular the CTD was not calibrated before or during the voyage. The AUV used a LongBaseLine system formed by three transponders to navigate to and from the survey grid. Two were located on the ice and the third was deployed from the back of the ship with an acoustic communications modem. Once at the survey grid beneath the sea ice, the AUV used the DVL to navigate using bottom-tracking of the underside of the sea ice. We conducted 4 missions beneath sea-ice during the SIPEX-II voyage. The current status of the data is that is in un-processed and unavailable until final processing is completed in 2013. Persons interested in the data should contact Dr Guy Williams directly for further information and preliminary figures relating to the AUV missions. The files currently in the archive are in raw form. Some preliminary data is provided for stations 2, 3, 4 and 6 as: floe-2-20120926.mat floe-3-20121003.mat floe-4-20121006.mat floe-6-20121013.mat These can be accessed using the Seabed_plot routines (MATLAB) in this folder. There is a readme file provided called what-is-this.txt Also included is the video footage taken from the AUV using a GoPro HD Hero. Video Codec: avc1 Resolution: 1920x1080 pixels Frame Rate: 29.970030 f/s Audio Codec: mp4a Audio Bitrate: 1536 kb/s Finally, plots of the data for ice stations 2,3,4 and 6 are included in the preliminary figures folder. The file names indicate which ice station the plots are from. proprietary
SIPEX_II_Aerosols_1 In-situ total aerosol number using condensation particle counters as observed during the SIPEX II voyage of the Aurora Australis, 2012 AU_AADC STAC Catalog 2012-09-23 2012-10-24 119, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214311293-AU_AADC.umm_json "The current dataset includes total aerosol count from two different Condensation Particle Counters (CPCs). The two CPCs measure total aerosol number in two different size ranges: - TSI Model 3025A measures particles with diameters larger than 3 nm (files are in the 3025_3nm folder) - TSI Model 3772 measures particles with diameters larger than 10 nm (files are in the 3772_10nm folder) The two CPCs are measuring from the same sample air and as such, the difference between the two measurements gives a measurement of total aerosol concentration in the 3-10 nm size range, known as the nucleation mode. Instrument setup: The instruments are setup inside an insulated shipping container mounted on the hatch covers directly aft of the forecastle. A 100 L pump is used to pull sample air from a 3 m high mast located on the starboard side of the forecastle. The air is pulled through 17 m of 50 mm antistatic (copper coil) polyurethane tubing and 2 m of 50 mm stainless steel pipe for connection and extensions. A 1 m length of one quarter inch stainless steel tubing penetrates into the container and directly through the wall of the polyurethane tubing for sampling off the primary flow to the CPCs. The inserted stainless steel tubing is oriented in such a way that sampled aerosol experience minimal turns to avoid sample loss. Approximately 1.7 m of flexible conductive tubing extends to a Y-piece which directs flow into each CPC. Butanol contaminated exhaust from the CPCs is pushed out of the container by two 10 LPM pumps. Data Processing: Raw data is calibrated for each instrument's recorded flow rate, and an inlet efficiency to correct for losses in the long inlet. Data is then resampled to minute time resolution, and filtered for logged events, wind directions which sampled ship exhaust, and outliers in the dataset. This produced a dataset which represented the sampling of clean Antarctic background atmosphere. The dataset includes both aerosol number concentrations from each instrument giving total number of particles above 3 nm and 10 nm respectively, as well as the different between these values, which gives a measure of newly formed particles in the nucleation mode between 3-10 nm (New Particle Formation, NPF). Associated uncertainties are included in the dataset." proprietary
SIPEX_II_Albedo_1 Albedos for 300-2500nm for thin sea ice covered with frost flowers, nilas, snow, and slush collected during SIPEX II ALL STAC Catalog 2012-09-14 2012-11-04 113, -66, 147, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214311265-AU_AADC.umm_json This dataset contains albedo data for several varieties of sea ice and snow from 300-2500 nm measured during the SIPEX II voyage (2012). An Analytical Spectral Device (ASD) spectrophotometer records the amount of radiation impingent on a cosine collector, which contains a spectralon diffuser plate. The radiation that hits the diffuser plate is scattered equally in all directions (isotropically). A portion of the radiation incident on the plate is scattered in the direction of a fiber optic cable, which is connected to the ASD. The ASD separates the incoming radiation into 3-10 nm wavelength bins, thus creating a radiation spectrum spanning 300-2500 nm. The cosine collector can be oriented both upwards towards the sky and downward towards the snow and/or sea ice to measure the spectral signature of both the downwelling (from the sky) and upwelling (from the snow/ice) radiation. For each site, we record 5 upwelling and 5 downwelling spectral signatures. MATLAB or a similar analysis package is required to open the spectrum files that are created by the ASD. The ASD files are raw files and named in a sequence, starting with 'spectrum.000'. MATLAB or similar scripts can been written to convert the ASD spectrum data to .mat files. The spectra in the processed files are used to calculate the albedos for various snow and ice types when the ratio of upwelling to downwelling radiation is computed. We use two upwelling scans per one downwelling scan to compute the albedo. Also included is some photography of frost flowers and other examples of ice that was observed. proprietary
SIPEX_II_Albedo_1 Albedos for 300-2500nm for thin sea ice covered with frost flowers, nilas, snow, and slush collected during SIPEX II AU_AADC STAC Catalog 2012-09-14 2012-11-04 113, -66, 147, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214311265-AU_AADC.umm_json This dataset contains albedo data for several varieties of sea ice and snow from 300-2500 nm measured during the SIPEX II voyage (2012). An Analytical Spectral Device (ASD) spectrophotometer records the amount of radiation impingent on a cosine collector, which contains a spectralon diffuser plate. The radiation that hits the diffuser plate is scattered equally in all directions (isotropically). A portion of the radiation incident on the plate is scattered in the direction of a fiber optic cable, which is connected to the ASD. The ASD separates the incoming radiation into 3-10 nm wavelength bins, thus creating a radiation spectrum spanning 300-2500 nm. The cosine collector can be oriented both upwards towards the sky and downward towards the snow and/or sea ice to measure the spectral signature of both the downwelling (from the sky) and upwelling (from the snow/ice) radiation. For each site, we record 5 upwelling and 5 downwelling spectral signatures. MATLAB or a similar analysis package is required to open the spectrum files that are created by the ASD. The ASD files are raw files and named in a sequence, starting with 'spectrum.000'. MATLAB or similar scripts can been written to convert the ASD spectrum data to .mat files. The spectra in the processed files are used to calculate the albedos for various snow and ice types when the ratio of upwelling to downwelling radiation is computed. We use two upwelling scans per one downwelling scan to compute the albedo. Also included is some photography of frost flowers and other examples of ice that was observed. proprietary
@@ -13825,8 +13826,8 @@ SIR-C_PRECISION Spaceborne Imaging Radar-C Precision USGS_LTA STAC Catalog 1994-
SIRSN3L1_001 SIRS/Nimbus-3 Level 1 Radiance Data V001 (SIRSN3L1) at GES DISC GES_DISC STAC Catalog 1969-04-14 1970-06-19 -180, -80.15, 180, 80.15 https://cmr.earthdata.nasa.gov/search/concepts/C1622768257-GES_DISC.umm_json SIRSN3L1 is the Nimbus-3 Satellite Infrared Spectrometer (SIRS) Level 1 Radiance Data product. SIRS measured infrared radiation (11 to 36 micrometers) emitted from the earth and its atmosphere in 13 selected spectral intervals in the carbon dioxide and water vapor bands plus one channel in the 11-micrometer atmospheric window. The radiances were used to determine the vertical temperature and water vapor profiles of the atmosphere. The data were recovered from the original 6250 tapes, and are now stored online as daily files in their original proprietary binary format each with about 14 orbits per day. The Nimbus-3 SIRS only viewed the nadir of the subsatellite track. Spatial coverage is near global from about latitude -80 to +80 degrees. The data are available from 08 April 1970 (day of year 98) to 08 April 1971. The principal investigator for the SIRS experiment was Dr. David Q. Wark from the NOAA National Environmental Satellite Data and Information Service. This product was previously available from the NSSDC with the identifier ESAD-00130 (old ID 70-025A-04A). proprietary
SIRSN4L1_001 SIRS/Nimbus-4 Level 1 Radiance Data V001 (SIRSN4L1) at GES DISC GES_DISC STAC Catalog 1970-04-08 1971-04-08 -180, -85, 180, 85 https://cmr.earthdata.nasa.gov/search/concepts/C1622768259-GES_DISC.umm_json SIRSN4L1 is the Nimbus-4 Satellite Infrared Spectrometer (SIRS) Level 1 Radiance Data product. SIRS measured infrared radiation (11 to 36 micrometers) emitted from the earth and its atmosphere in 13 selected spectral intervals in the carbon dioxide and water vapor bands plus one channel in the 11-micrometer atmospheric window. The radiances were used to determine the vertical temperature and water vapor profiles of the atmosphere. The data were recovered from the original 6250 tapes, and are now stored online as daily files in their original proprietary binary format each with about 14 orbits per day. The Nimbus-4 SIRS used a scan mirror to observe 12.5 deg to either side of the subsatellite track. Spatial coverage is near global from latitude -85 to +85 degrees. The data are available from 08 April 1970 (day of year 98) to 08 April 1971. The principal investigator for the SIRS experiment was Dr. David Q. Wark from the NOAA National Environmental Satellite Data and Information Service. This product was previously available from the NSSDC with the identifier ESAD-00130 (old ID 70-025A-04A). proprietary
SISTER_Workflow_V004_2335_4 SISTER: Experimental Workflows, Product Generation Environment, and Sample Data, V004 ORNL_CLOUD STAC Catalog 2011-05-13 2018-01-26 -158.05, 21.2, -107.96, 39.08 https://cmr.earthdata.nasa.gov/search/concepts/C3114843226-ORNL_CLOUD.umm_json The Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) activity originated in support of the NASA Earth System Observatory's Surface Biology and Geology (SBG) mission to develop prototype workflows with community algorithms and generate prototype data products envisioned for SBG. SISTER focused on developing a data system that is open, portable, scalable, standards-compliant, and reproducible. This collection contains EXPERIMENTAL workflows and sample data products, including (a) the Common Workflow Language (CWL) process file and a Jupyter Notebook that run the entire SISTER workflow capable of generating experimental sample data products spanning terrestrial ecosystems, inland and coastal aquatic ecosystems, and snow, (b) the archived algorithm steps (as OGC Application Packages) used to generate products at each step of the workflow, (c) a small number of experimental sample data products produced by the workflow which are based on the Airborne Visible/Infrared Imaging Spectrometer-Classic (AVIRIS or AVIRIS-CL) instrument, and (d) instructions for reproducing the sample products included in this dataset. DISCLAIMER: This collection contains experimental workflows, experimental community algorithms, and experimental sample data products to demonstrate the capabilities of an end-to-end processing system. The experimental sample data products provided have not been fully validated and are not intended for scientific use. The community algorithms provided are placeholders which can be replaced by any user's algorithms for their own science and application interests. These algorithms should not in any capacity be considered the algorithms that will be implemented in the upcoming Surface Biology and Geology mission. proprietary
-SIZEX-89-SAR Airborne X- and C-band SAR Images of Sea Ice in the Barents Sea SCIOPS STAC Catalog 1989-02-15 1989-02-27 15, 74, 25, 77 https://cmr.earthdata.nasa.gov/search/concepts/C1214584391-SCIOPS.umm_json SIZEX-89 was an official pre-launch ERS-1 program where the main objectives were to perform ERS-1 type sensors signature studies of different ice types in order to develop SAR algorithms for ice variables such as ice types, ice concentrations and ice kinematics. SIZEX-89 was a multidisciplinary, international winter experiment carried out in the Barents and the Greenland Seas during February and March 1989. During the experiment, 130 CCT tape of airborne X-band and C-band SAR data were obtained by the CCRS CV-580 in the Barents Sea, in February 1989. Remote Sensing, oceanographical, ocean acoustical, meteorological and sea ice data were collected. Several platforms were used: one ice-strengthened vessel (R/V Polarbjorn), one open ocean ship (R/V Hakon Mosby), helicopter drifting buoys, bottom-moored buoys, aircraft and satellites (NOAA, DMSP). In addition to data collection, an ice-forecasting model was run operationally to predict ice motion, ice thickness and ice concentration. The integrated data set obtained in SIZEX-89 is a pilot data set suitable to develop and improve methods for ice monitoring and prediction. proprietary
SIZEX-89-SAR Airborne X- and C-band SAR Images of Sea Ice in the Barents Sea ALL STAC Catalog 1989-02-15 1989-02-27 15, 74, 25, 77 https://cmr.earthdata.nasa.gov/search/concepts/C1214584391-SCIOPS.umm_json SIZEX-89 was an official pre-launch ERS-1 program where the main objectives were to perform ERS-1 type sensors signature studies of different ice types in order to develop SAR algorithms for ice variables such as ice types, ice concentrations and ice kinematics. SIZEX-89 was a multidisciplinary, international winter experiment carried out in the Barents and the Greenland Seas during February and March 1989. During the experiment, 130 CCT tape of airborne X-band and C-band SAR data were obtained by the CCRS CV-580 in the Barents Sea, in February 1989. Remote Sensing, oceanographical, ocean acoustical, meteorological and sea ice data were collected. Several platforms were used: one ice-strengthened vessel (R/V Polarbjorn), one open ocean ship (R/V Hakon Mosby), helicopter drifting buoys, bottom-moored buoys, aircraft and satellites (NOAA, DMSP). In addition to data collection, an ice-forecasting model was run operationally to predict ice motion, ice thickness and ice concentration. The integrated data set obtained in SIZEX-89 is a pilot data set suitable to develop and improve methods for ice monitoring and prediction. proprietary
+SIZEX-89-SAR Airborne X- and C-band SAR Images of Sea Ice in the Barents Sea SCIOPS STAC Catalog 1989-02-15 1989-02-27 15, 74, 25, 77 https://cmr.earthdata.nasa.gov/search/concepts/C1214584391-SCIOPS.umm_json SIZEX-89 was an official pre-launch ERS-1 program where the main objectives were to perform ERS-1 type sensors signature studies of different ice types in order to develop SAR algorithms for ice variables such as ice types, ice concentrations and ice kinematics. SIZEX-89 was a multidisciplinary, international winter experiment carried out in the Barents and the Greenland Seas during February and March 1989. During the experiment, 130 CCT tape of airborne X-band and C-band SAR data were obtained by the CCRS CV-580 in the Barents Sea, in February 1989. Remote Sensing, oceanographical, ocean acoustical, meteorological and sea ice data were collected. Several platforms were used: one ice-strengthened vessel (R/V Polarbjorn), one open ocean ship (R/V Hakon Mosby), helicopter drifting buoys, bottom-moored buoys, aircraft and satellites (NOAA, DMSP). In addition to data collection, an ice-forecasting model was run operationally to predict ice motion, ice thickness and ice concentration. The integrated data set obtained in SIZEX-89 is a pilot data set suitable to develop and improve methods for ice monitoring and prediction. proprietary
SLAR Side Looking Airborne Radar (SLAR) Imagery USGS_LTA STAC Catalog 1980-07-18 1993-11-30 -180, 24, -60, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1220566112-USGS_LTA.umm_json Side-Looking Airborne Radar (SLAR) imagery is available from the U.S. Geological Survey (USGS) for selected project areas in the conterminous United States and Alaska. Data are X-band synthetic aperture radar (horizontally transmitted, horizontally received) with the exception of some test sites. Coverage was contracted on a yearly basis. The USGS SLAR images most often consist of contact strip images and 1:250,000-scale, map-controlled mosaics. Greater than half of the available SLAR image strips are distributed on 8-mm cassettes, while some image strips are distributed on CD-ROM. In addition, ancillary products such as indexes (on paper, film, or microfiche) and custom photographic products may also be available. Due to the geographically non-searchable nature of the SLAR inventory, customer assistance may be obtained to determine availability of SLAR data over the user's area of interest. Customer knowledge of USGS 1:250,000-scale map names is beneficial in expediting orders. A scale of 1:50,000 only applies to Alaska coverage. proprietary
SLOPE_GPP_CONUS_1786_1 MODIS-based GPP, PAR, fC4, and SANIRv estimates from SLOPE for CONUS, 2000-2019 ORNL_CLOUD STAC Catalog 2000-01-01 2020-01-01 -155.57, 19.99, -52.22, 50.01 https://cmr.earthdata.nasa.gov/search/concepts/C2266194621-ORNL_CLOUD.umm_json This dataset contains estimated gross primary productivity (GPP), photosynthetically active radiation (PAR), soil adjusted near infrared reflectance of vegetation (SANIRv), the fraction of C4 crops in vegetation (fC4), and their uncertainties for the conterminous United States (CONUS) from 2000 to 2019. The daily estimates are SatelLite Only Photosynthesis Estimation (SLOPE) products at 250-m resolution. There are three distinct features of the GPP estimation algorithm: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR, (2) SLOPE couples gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRv (SANIRv) dataset, and (3) SLOPE couples a temporal pattern recognition approach with a long-term Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two parameters to estimate GPP, along with a quantitative uncertainty, on a per-pixel and daily basis. The slope GPP product has an R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1. proprietary
SMAP_JPL_L2B_NRT2_SSS_CAP_V5_5.0 JPL SMAP Level 2B Near Real-time CAP Sea Surface Salinity V5.0 Validated Dataset (2 hour latency) POCLOUD STAC Catalog 2015-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2681262364-POCLOUD.umm_json The SMAP-SSS V5.0, level 2B (NRT CAP) dataset produced by the Jet Propulsion Laboratory Combined Active-Passive (CAP) project , is a validated product that provides near real-time orbital/swath data on sea surface salinity (SSS) and extreme winds, derived from the NASA's Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015. This mission, initially designed to measure and map Earth's soil moisture and freeze/thaw state to better understand terrestrial water, carbon and energy cycles has been adapted to measure ocean SSS and ocean wind speed using its passive microwave instrument. The SMAP instrument is in a near polar orbiting, sun synchronous orbit with a nominal 8 day repeat cycle.
The dataset includes derived SMAP SSS, SSS uncertainty, wind speed and direction data for extreme winds, as well as brightness temperatures for each radiometer polarization. Furthermore, it contains ancillary reference surface salinity, ice concentration, wind and wave height data, quality flags, and navigation data. This broad range of parameters stems from the observatory's version 5.0 (V5) CAP retrieval algorithm, initially developed for the Aquarius/SAC-D mission and subsequently extended to SMAP. Datafrom April 1, 2015 to present, is available with a latency of about 6 hours. The observations are global, provided on a 25km swath grid with an approximate spatial resolution of 60 km. Each data file covers one 98-minute orbit, with 15 files generated per day. The data are based on the near-real-time SMAP V5 Level-1 Brightness Temperatures (TB) and benefits from an enhanced calibration methodology, which improves the absolute radiometric calibration and minimizes biases between ascending and descending passes. These improvements also enrich the applicability of SMAP Level-1 data for other uses, such as further sea surface salinity and wind assessments. Due to a malfunction of the SMAP scatterometer on July 7, 2015, collocated wind speed data has been utilized for the necessary surface roughness correction for salinity retrieval.
This JPL SMAP-SSS V5.0 dataset holds tremendous potential for scientific research and various applications. Given the SMAP satellite's near-polar orbit and sun-synchronous nature, it achieves global coverage in approximately three days , enabling researchers to monitor and model global oceanic and climatic phenomena with unprecedented detail and timeliness. These data can inform and enhance understanding of global weather patterns, the Earth’s hydrological cycle, ocean circulation, and climate change. proprietary
@@ -13869,8 +13870,8 @@ SMAP_RSS_L3_SSS_SMI_MONTHLY_V6_6.0 RSS SMAP Level 3 Sea Surface Salinity Standar
SMERGE_RZSM0_40CM_2.0 Smerge-Noah-CCI root zone soil moisture 0-40 cm L4 daily 0.125 x 0.125 degree V2.0 (SMERGE_RZSM0_40CM) at GES DISC GES_DISC STAC Catalog 1979-01-02 2019-05-10 -125, 25, -67, 53 https://cmr.earthdata.nasa.gov/search/concepts/C1569839798-GES_DISC.umm_json Smerge-Noah-CCI root zone soil moisture 0-40 cm L4 daily 0.125 x 0.125 degree V2.0 is a multi-decadal root-zone soil moisture product. Smerge is developed by merging the North American Land Data Assimilation System (NLDAS) land surface model output with surface satellite retrievals from the European Space Agency Climate Change Initiative. The data have a 0.125 degree resolution at a daily time-step, covering the entire continental United States and spanning nearly four decades (January 1979 to May 2019). This data product contains root-zone soil moisture of 0 - 40 cm layer, Climate Change Initiative (CCI) derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag. This data product is the recommended replacement for the AMSR-E/Aqua root zone soil moisture L3 1 day 25 km x 25 km descending and 2-Layer Palmer Water Balance Model V001 product (LPRM_AMSRE_D_RZSM3), which will be removed from archive on June 27, 2022. Smerge provides a better root zone soil moisture estimation because it has higher data quality and longer temporal coverage. proprietary
SMHI_IPY_ACEX-2004-ODEN-TRACK_1.0 ACEX 2004 ODEN TRACK ALL STAC Catalog 2004-08-08 2004-09-13 19.045, 69.727, 175.94, 89.999 https://cmr.earthdata.nasa.gov/search/concepts/C1214595274-SCIOPS.umm_json Icebreaker Oden\\\\\\\\\\\\\\\'s trackline during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
SMHI_IPY_ACEX-2004-ODEN-TRACK_1.0 ACEX 2004 ODEN TRACK SCIOPS STAC Catalog 2004-08-08 2004-09-13 19.045, 69.727, 175.94, 89.999 https://cmr.earthdata.nasa.gov/search/concepts/C1214595274-SCIOPS.umm_json Icebreaker Oden\\\\\\\\\\\\\\\'s trackline during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
-SMHI_IPY_ACEX-2004-Seismic ACEX 2004 Seismic ALL STAC Catalog 2004-08-08 2004-09-13 139.0632, 87.917, 140.31, 87.977 https://cmr.earthdata.nasa.gov/search/concepts/C1214595276-SCIOPS.umm_json Reflection seismic profiles aquired during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
SMHI_IPY_ACEX-2004-Seismic ACEX 2004 Seismic SCIOPS STAC Catalog 2004-08-08 2004-09-13 139.0632, 87.917, 140.31, 87.977 https://cmr.earthdata.nasa.gov/search/concepts/C1214595276-SCIOPS.umm_json Reflection seismic profiles aquired during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
+SMHI_IPY_ACEX-2004-Seismic ACEX 2004 Seismic ALL STAC Catalog 2004-08-08 2004-09-13 139.0632, 87.917, 140.31, 87.977 https://cmr.earthdata.nasa.gov/search/concepts/C1214595276-SCIOPS.umm_json Reflection seismic profiles aquired during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
SMHI_IPY_ACEX-2004-Sites_1.0 ACEX 2004 Sites SCIOPS STAC Catalog 2004-08-08 2004-09-13 -4.05029, 69.727, 19.045, 89.999 https://cmr.earthdata.nasa.gov/search/concepts/C1214595252-SCIOPS.umm_json The site location for the cores retrieved during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
SMHI_IPY_ACEX-2004-Sites_1.0 ACEX 2004 Sites ALL STAC Catalog 2004-08-08 2004-09-13 -4.05029, 69.727, 19.045, 89.999 https://cmr.earthdata.nasa.gov/search/concepts/C1214595252-SCIOPS.umm_json The site location for the cores retrieved during the International Ocean Drilling Program (IODP) Leg 302, also known as Arctic Coring Expedition (ACEX). proprietary
SMHI_IPY_AGAVE2007-track_1.0 AGAVE2007 track SCIOPS STAC Catalog 2007-07-01 2007-08-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214595299-SCIOPS.umm_json Icebreaker Oden\\\\\\\\\\\\\\\'s trackline during the Arctic Gakkel Vents Expedition (AGAVE) 2007. proprietary
@@ -14166,8 +14167,8 @@ SOE_elephant_seals_4 Annual population estimates of Southern Elephant Seals at M
SOE_fast_ice_thickness_1 Fast ice thickness at Davis, Mawson and Casey AU_AADC STAC Catalog 1954-01-01 1992-10-21 62.8738, -68.5766, 110.5276, -66.2818 https://cmr.earthdata.nasa.gov/search/concepts/C1214311316-AU_AADC.umm_json This indicator is no longer maintained, and is considered OBSOLETE. INDICATOR DEFINITION Regular measurements of the thickness of the fast ice, and of the snow cover that forms on it, are made through drilled holes at several sites near both Mawson and Davis. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Each season around the end of March, the ocean surface around Antarctica freezes to form sea ice. Close to the coast in some regions (e.g. near Mawson and Davis stations) this ice remains fastened to the land throughout the winter and is called fast ice. The thickness and growth rate of fast ice are determined purely by energy exchanges at the air-ice and ice-water interfaces. This contrasts with moving pack ice where deformational processes of rafting and ridging also determine the ice thickness. The maximum thickness that the fast ice reaches, and the date on which it reaches that maximum, represent an integration of the atmospheric and oceanic conditions. Changes in ice thickness represent changes in either oceanic or atmospheric heat transfer. Thicker fast ice reflects either a decrease in air temperature or decreasing oceanic heat flux. These effects can be extrapolated to encompass large-scale ocean-atmosphere processes and potentially, global climate change. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: At sites near Australian Antarctic continental stations: Davis; Mawson. Frequency: at least weekly, reported annually Measurement Technique: Tape measurements through freshly drilled 5 cm diameter holes in the ice at marked sites. RESEARCH ISSUES To more effectively analyse the changes in Antarctic fast ice a detailed long-term dataset of sea ice conditions needs to be established. This would provide a baseline for future comparisons and contribute important data for climate modelling and aid the detection of changes that may occur due to climate or environmental change. LINKS TO OTHER INDICATORS SOE Indicator 1 - Monthly mean air temperatures at Australian Antarctic stations SOE Indicator 40 - Average sea surface temperatures in latitude bands 40-50oS, 50-60oS, 60oS-continent SOE Indicator 41 - Average sea surface salinity in latitude bands: 40-50oS, 50-60oS, 60oS-continent SOE Indicator 42 - Antarctic sea ice extent and concentration The fast ice data are also available as a direct download via the url given below. The data are in word documents, and are divided up by year and site (there are three sites (a,b,c) at each station). Snow thickness data have also been included. A pdf document detailing how the observations are collected is also available for download. proprietary
SOE_fur_seals_1 Environmental determinants of fecundity and pup growth in fur seals AU_AADC STAC Catalog 1990-01-01 1999-12-31 158.76343, -54.78327, 158.9653, -54.47882 https://cmr.earthdata.nasa.gov/search/concepts/C1214313694-AU_AADC.umm_json This indicator is no longer maintained, and is considered OBSOLETE. INDICATOR DEFINITION The fecundity (pupping rates) of female fur seals and the growth rates of their pups relative to changes in sea surface temperatures (local primary production) in the vicinity of Macquarie Island. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION A highly negative correlation has been detected between sea surface temperatures in the vicinity of Macquarie Island and fur seal fecundity and pup growth. A dataset of over ten years has shown that autumn sea-surface temperatures are highly negatively correlated with female fecundity in the following breeding season. Rather than the reproductive success in terms of fecundity and pup growth being seen simply as a correlate of SST and presumably ocean productivity, the measure is much more than this. What the dataset from the Macquarie Island fur seal populations is rather more unique, in that they indicate how environmental variability effects the reproductive success of animals at annual and lifetime scales. This is especially important as we can now show what impacts environmental/climatic phenomena such as the Antarctic Circumpolar Wave, and global warming will have on fur seals, and how changes in the environment may impact on the viability of populations. In this situation, the data clearly suggest that warmer ocean temperatures significantly effect the reproductive success of fur seals. Sustained warmer temperatures would therefore impose demographic constraints on populations. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial scale: SST data are obtained from a 1 degree square just north of the island that represents the region in which most females obtain food throughout their lactation period. Frequency: Data on the reproductive success of fur seals is to be collected annually. Measurement technique: Each breeding season (November-January), the reproductive success of tagged females is monitored, including their pupping success, and the growth rates of their pups. RESEARCH ISSUES LINKS TO OTHER INDICATORS proprietary
SOE_generator_boiler_fuel_usage_1 Monthly fuel usage of the generator sets and boilers at Australian Antarctic Stations AU_AADC STAC Catalog 1990-01-01 2016-02-29 62.8738, -68.5766, 158.8609, -54.6198 https://cmr.earthdata.nasa.gov/search/concepts/C1214311317-AU_AADC.umm_json INDICATOR DEFINITION The quantity of fuel used by generator sets and boilers at Casey, Davis, Mawson and Macquarie Island stations as measured on a monthly basis and reported in the monthly reports from the Station Plant Inspectors to the Kingston (Head Office) Mechanical Supervisor. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: PRESSURE RATIONALE FOR INDICATOR SELECTION The amount of fuel used in Antarctica for power generation and heating is proportional to environmental impact due to the emissions released. Special Antarctic Blend (SAB), a light diesel like fuel, is used at the stations to power the station generator sets, to provide heat through boilers, and to run plant and equipment including the station incinerator and vehicles. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial scale: Australian Antarctic stations: Casey (lat 66 deg 16' 54.5& S, long 110 deg 31' 39.4& E), Davis (lat 68 deg 34' 35.8& S, long 77 deg 58' 02.6& E), Mawson (lat 67 deg 36' 09.7& S, long 62 deg 52' 25.7& E) and Macquarie Island (lat 54 deg 37' 59.9& S, long 158 deg 52' 59.9& E). Frequency: Monthly reports Measurement technique: The figures are obtained by direct reading of gauges on the stations on a regular basis. The data are recorded in the Plant Inspectors monthly reports. RESEARCH ISSUES In the future, it is planned to automate the collection of most of this data. LINKS TO OTHER INDICATORS SOE Indicator 1 - Monthly mean air temperatures at Australian Antarctic stations. SOE Indicator 2 - Highest monthly air temperatures at Australian Antarctic Stations SOE Indicator 3 - Lowest monthly air temperatures at Australian Antarctic Stations SOE Indicator 4 - Monthly mean lower stratospheric temperatures above Australian Antarctic Stations SOE Indicator 7 - Monthly mean of three-hourly wind speeds (m/s) SOE Indicator 48 - Station and ship person days SOE Indicator 57 - Monthly total of fuel used by station incinerators SOE Indicator 58 - Monthly total of fuel used by station vehicles SOE Indicator 59 - Monthly electricity usage SOE Indicator 60 - Total helicopter hours SOE Indicator 61 - Total potable water consumption SOE Indicator 65 - Station footprint for Australian Antarctic stations proprietary
-SOE_greenhouse_gas_1 Air sampling for greenhouse gas concentrations and associated species AU_AADC STAC Catalog 1984-11-01 62, -90, 159, -41 https://cmr.earthdata.nasa.gov/search/concepts/C1214311318-AU_AADC.umm_json INDICATOR DEFINITION Measurement of air samples for values of the primary greenhouse gases (carbon dioxide, methane and nitrous oxide) and associated species (carbon monoxide, hydrogen and isotopes of carbon dioxide) in the Southern Hemisphere atmosphere. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Over the last century the concentration of greenhouse gases has risen in the atmosphere. The average rise is about half that expected from human activities, predominantly the burning of fossil fuel. Thus observations of the concentration of these gases provides a measure of anthropogenic greenhouse forcing in the atmosphere, and for example, monitors the effectiveness of oceans and terrestrial biomes in removing the excess CO2. Measurements of long-lived trace gas levels in Antarctic air generally provide an accurate integration of global exchanges between the surface and the atmosphere. The climate-influencing gases of main interest are gases released as a result of human activity, as well as from (climate-driven) physical, chemical and biological processes in both land and oceans. The Antarctic monitoring, in concert with other global network results, exploits trace gas ratios to identify and locate globally significant exchanges. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: High latitude Southern Hemisphere air samples are collected from AAD sites by BoM personnel at Mawson station, Casey station and Macquarie Island, and by NOAA staff at South Pole. These complement CSIRO supervised sites at Cape Grim, Tasmania and ~7 other globally distributed locations. Frequency: Typical sites collect ~4 flasks of air per month for subsequent analysis at CSIRO. Measurement Technique: Various chemical analysis techniques (Francey et al. 1996). RESEARCH ISSUES For global trace gas monitoring, improvements are sought in network intercalibration and in increased sampling, e.g. continuous CO2 monitoring, vertical profiles, continental sites. More generally, improved coordination of atmospheric composition modeling, surface flux measurements and atmospheric transport representations are sought to serve new 'multiple-constraint modeling frameworks'. LINKS TO OTHER INDICATORS Monthly averages of daily maximum and minimum temperatures for Australian Antarctic Stations Mean sea level Average Summer chlorophyll concentrations in the Southern Ocean, from latitude bands 40-50 deg S, 50-60 deg S, 60 deg S-continent Average sea surface temperatures in latitude bands 40-50 deg S, 50-60 deg S, 60 deg S-continent Antarctic sea ice extent and concentration proprietary
SOE_greenhouse_gas_1 Air sampling for greenhouse gas concentrations and associated species ALL STAC Catalog 1984-11-01 62, -90, 159, -41 https://cmr.earthdata.nasa.gov/search/concepts/C1214311318-AU_AADC.umm_json INDICATOR DEFINITION Measurement of air samples for values of the primary greenhouse gases (carbon dioxide, methane and nitrous oxide) and associated species (carbon monoxide, hydrogen and isotopes of carbon dioxide) in the Southern Hemisphere atmosphere. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Over the last century the concentration of greenhouse gases has risen in the atmosphere. The average rise is about half that expected from human activities, predominantly the burning of fossil fuel. Thus observations of the concentration of these gases provides a measure of anthropogenic greenhouse forcing in the atmosphere, and for example, monitors the effectiveness of oceans and terrestrial biomes in removing the excess CO2. Measurements of long-lived trace gas levels in Antarctic air generally provide an accurate integration of global exchanges between the surface and the atmosphere. The climate-influencing gases of main interest are gases released as a result of human activity, as well as from (climate-driven) physical, chemical and biological processes in both land and oceans. The Antarctic monitoring, in concert with other global network results, exploits trace gas ratios to identify and locate globally significant exchanges. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: High latitude Southern Hemisphere air samples are collected from AAD sites by BoM personnel at Mawson station, Casey station and Macquarie Island, and by NOAA staff at South Pole. These complement CSIRO supervised sites at Cape Grim, Tasmania and ~7 other globally distributed locations. Frequency: Typical sites collect ~4 flasks of air per month for subsequent analysis at CSIRO. Measurement Technique: Various chemical analysis techniques (Francey et al. 1996). RESEARCH ISSUES For global trace gas monitoring, improvements are sought in network intercalibration and in increased sampling, e.g. continuous CO2 monitoring, vertical profiles, continental sites. More generally, improved coordination of atmospheric composition modeling, surface flux measurements and atmospheric transport representations are sought to serve new 'multiple-constraint modeling frameworks'. LINKS TO OTHER INDICATORS Monthly averages of daily maximum and minimum temperatures for Australian Antarctic Stations Mean sea level Average Summer chlorophyll concentrations in the Southern Ocean, from latitude bands 40-50 deg S, 50-60 deg S, 60 deg S-continent Average sea surface temperatures in latitude bands 40-50 deg S, 50-60 deg S, 60 deg S-continent Antarctic sea ice extent and concentration proprietary
+SOE_greenhouse_gas_1 Air sampling for greenhouse gas concentrations and associated species AU_AADC STAC Catalog 1984-11-01 62, -90, 159, -41 https://cmr.earthdata.nasa.gov/search/concepts/C1214311318-AU_AADC.umm_json INDICATOR DEFINITION Measurement of air samples for values of the primary greenhouse gases (carbon dioxide, methane and nitrous oxide) and associated species (carbon monoxide, hydrogen and isotopes of carbon dioxide) in the Southern Hemisphere atmosphere. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Over the last century the concentration of greenhouse gases has risen in the atmosphere. The average rise is about half that expected from human activities, predominantly the burning of fossil fuel. Thus observations of the concentration of these gases provides a measure of anthropogenic greenhouse forcing in the atmosphere, and for example, monitors the effectiveness of oceans and terrestrial biomes in removing the excess CO2. Measurements of long-lived trace gas levels in Antarctic air generally provide an accurate integration of global exchanges between the surface and the atmosphere. The climate-influencing gases of main interest are gases released as a result of human activity, as well as from (climate-driven) physical, chemical and biological processes in both land and oceans. The Antarctic monitoring, in concert with other global network results, exploits trace gas ratios to identify and locate globally significant exchanges. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: High latitude Southern Hemisphere air samples are collected from AAD sites by BoM personnel at Mawson station, Casey station and Macquarie Island, and by NOAA staff at South Pole. These complement CSIRO supervised sites at Cape Grim, Tasmania and ~7 other globally distributed locations. Frequency: Typical sites collect ~4 flasks of air per month for subsequent analysis at CSIRO. Measurement Technique: Various chemical analysis techniques (Francey et al. 1996). RESEARCH ISSUES For global trace gas monitoring, improvements are sought in network intercalibration and in increased sampling, e.g. continuous CO2 monitoring, vertical profiles, continental sites. More generally, improved coordination of atmospheric composition modeling, surface flux measurements and atmospheric transport representations are sought to serve new 'multiple-constraint modeling frameworks'. LINKS TO OTHER INDICATORS Monthly averages of daily maximum and minimum temperatures for Australian Antarctic Stations Mean sea level Average Summer chlorophyll concentrations in the Southern Ocean, from latitude bands 40-50 deg S, 50-60 deg S, 60 deg S-continent Average sea surface temperatures in latitude bands 40-50 deg S, 50-60 deg S, 60 deg S-continent Antarctic sea ice extent and concentration proprietary
SOE_incinerated_waste_1 Amount of incinerated waste from Australian Antarctic Stations AU_AADC STAC Catalog 1999-01-01 62.8738, -68.5766, 158.8609, -54.6198 https://cmr.earthdata.nasa.gov/search/concepts/C1214311277-AU_AADC.umm_json INDICATOR DEFINITION This indicator identifies the total weight of material incinerated, and the weights of the major components on Casey, Davis, Mawson and Macquarie Island stations. The figures are reported monthly, in the station plumbers' reports to the Building Services Supervisor in Kingston, and to the Operations Environment Officer. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: PRESSURE RATIONALE FOR INDICATOR SELECTION Waste minimization is an important element of Australia's Antarctic program, so the total weight of waste produced, and any trends, provide an important management tool. Approximately 10% of waste is incinerated, so incineration statistics are an important part of this assessment. A separate aim of Australia's program is reduction in the amount of material incinerated on the stations, either reduction in the amounts of certain materials sent to the stations or by diverting materials from incineration to reuse or recycling. In either case it will be necessary to target individual materials incinerated, as different materials are likely to respond to different management practices. To properly target these materials it is important to know the amounts of each of the materials incinerated, and trends over time. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial scale: Australian Antarctic continental stations and Macquarie Island station. Frequency: Weights are recorded each time materials are incinerated, which is every few days in winter and daily in summer and reported monthly. Measurement technique: Weights are recorded for the following categories: (1) food scraps, (2) spoiled fruit and vegetables, (3) wood and wood products (not treated wood), (4) cardboard, (5) paper products (poor quality paper, books and magazines), (6) medical waste, (7) science waste, (8) hydroponics waste, (9) human waste from the field and (10) miscellaneous. In addition, weights of specific materials may be recorded separately, if burnt in unusually large amounts, for example if large amounts of particular types of fruit and vegetables have been spoiled. RESEARCH ISSUES Chemical analysis of emissions as a pollution index and also to assess the efficiency of the burn. This information could be used to indicate the need to change the components of burns or to adjust the equipment. It may also highlight the release of toxic materials into the atmosphere which may be overcome by eliminating certain materials from incineration. A major audit of total waste production, leading to recommendations on how to achieve maximum waste reduction. LINKS TO OTHER INDICATORS SOE Indicator 47 - Number and nature of incidents resulting in environmental impact SOE Indicator 48 - Station and ship person days SOE Indicator 49 - Medical consultations per 1000 person years SOE Indicator 53 - Recycled and quarantine waste returned to Australia SOE Indicator 57 - Monthly total of fuel used by station incinerators SOE Indicator 69 - Resources committed to environmental issues proprietary
SOE_incinerator_fuel_usage_1 Monthly incinerator fuel usage of Australian Antarctic Stations AU_AADC STAC Catalog 1995-01-01 2016-02-29 62.8738, -68.5766, 158.8609, -54.6198 https://cmr.earthdata.nasa.gov/search/concepts/C1214311321-AU_AADC.umm_json INDICATOR DEFINITION The quantity of fuel used for incinerators at Casey, Davis, Mawson and Macquarie Island stations as measured on a monthly basis and reported in the monthly reports from the Station Plant Inspectors to the Kingston (Head Office) Mechanical Supervisor. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: PRESSURE RATIONALE FOR INDICATOR SELECTION The amount of fuel used in Antarctica for waste incineration contributes to environmental impact due to the emissions released. Special Antarctic Blend (SAB), a light diesel like fuel, is used at the stations for the incinerators. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial scale: Australian Antarctic stations: Casey (lat 66 deg 16' 54.5& S, long 110 deg 31' 39.4& E), Davis (lat 68 deg 34' 35.8& S, long 77 deg 58' 02.6& E), Mawson (lat 67 deg 36' 09.7& S, long 62 deg 52' 25.7& E) and Macquarie Island (lat 54 deg 37' 59.9& S, long 158 deg 52' 59.9& E). Frequency: Monthly reports Measurement technique: The figures are obtained by direct reading of gauges on the stations on a regular basis. The data are recorded in the Plant Inspectors monthly reports. RESEARCH ISSUES In the future, it is planned to automate the collection of most of this data. LINKS TO OTHER INDICATORS SOE Indicator 47 - Number and nature of incidents resulting in environmental impact SOE Indicator 48 - Station and ship person days SOE Indicator 53 - Recycled and quarantine waste returned to Australia SOE Indicator 54 - Amount of waste incinerated at Australian stations SOE Indicator 56 - Monthly fuel usage of the generator sets and boilers SOE Indicator 58 - Monthly total of fuel used by station vehicles SOE Indicator 60 - Total helicopter hours proprietary
SOE_low_strato_1 Monthly mean lower stratospheric temperatures above Australian Antarctic stations. AU_AADC STAC Catalog 1948-04-01 2019-02-01 61, -69, 159, -54 https://cmr.earthdata.nasa.gov/search/concepts/C1214313695-AU_AADC.umm_json "INDICATOR DEFINITION Monthly means of daily temperatures at the 100hPa level (lower stratosphere), from radiosonde soundings above Australian Antarctic stations Casey, Davis, Mawson and Macquarie Island. TYPE OF INDICATOR There are three types of indicators used in this report: 1.Describes the CONDITION of important elements of a system; 2.Show the extent of the major PRESSURES exerted on a system; 3.Determine RESPONSES to either condition or changes in the condition of a system. This indicator is one of: CONDITION RATIONALE FOR INDICATOR SELECTION Global climate models show warming in response to increased greenhouse gas (carbon dioxide, methane etc) concentrations in the atmosphere; this is called the 'enhanced greenhouse effect'. There is interest in climate variability and change not just at the surface, but extending up into the atmosphere. There is evidence of warming in the lower troposphere, but cooling in the lower stratosphere. Ozone depletion processes are also closely linked to stratospheric temperatures. DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM Spatial Scale: Australian Antarctic stations: Casey (lat 66 degrees 16' 54.5"" S, long 110 degrees 31' 39.4"" E), Davis (lat 68 degrees 34' 35.8"" S, long 77 degrees 58' 02.6"" E), Mawson (lat 67 degrees 36' 09.7"" S, long 62 degrees 52' 25.7"" E) and Macquarie Island (lat 54 degrees 37' 59.9"" S, long 158 degrees 52' 59.9"" E). Temporal scale: Monthly. Measurement technique: Radiosonde. RESEARCH ISSUES There is need to develop a high-quality data set from the available data, correcting erroneous data and estimating missing data. Adjustment may be necessary for changes in instrumentation or observing practices. Some of these changes are documented in the station history files held by the Regional Observations Section. These history files are currently held as paper records, although more recent information is held electronically and there is an effort to digitise the older records. Before the data can be used for the detection of change, a concerted effort will need to be made to identify deficiencies in the data, and then make compensations where possible. This is made more difficult by the lack of suitable comparison sites. Over recent years satellite data exist, which could be used in conjunction with radiosonde data. Satellite data and radiosonde data from other nations should lead to a greater coverage. LINKS TO OTHER INDICATORS SOE Indicators 1 - Monthly mean air temperatures for Australian Antarctic Stations SOE Indicators 2 - Monthly highest air temperatures for Australian Antarctic Stations SOE Indicators 3 - Monthly lowest air temperatures for Australian Antarctic Stations SOE Indicators 5 - Monthly mean mid-tropospheric temperature above Australian Antarctic stations SOE Indicators 6 - Daily mean 10m Firn Temperatures at AWS sites in the AAT (deg C) SOE Indicators 8 - Monthly mean of three-hourly mean sea level pressures (hPa) SOE Indicators 11 - Atmospheric concentrations of greenhouse gas species SOE Indicators 12 - Noctilucent cloud observations at Davis SOE Indicators 13 - Polar stratospheric cloud observations at Davis SOE Indicators 14 - Midwinter atmospheric temperature at altitude 87km SOE Indicators 16 - Extent of summer surface glacial melt (sq km) SOE Indicators 42 - Antarctic sea ice extent and concentration SOE Indicators 43 - Fast ice thickness at Davis and Mawson SOE Indicators 56 - Monthly fuel usage of the generator sets and boilers SOE Indicators 59 - Monthly electricity usage Note - Station codes in the data are as follows: 300000 - Davis 300001 - Mawson 300004 - Macquarie Island 300017 - Casey The fields in this dataset are: Mean 100hPa Temperature Year Month Station Station Code Value Enough Observations Number Observations" proprietary
@@ -14247,8 +14248,8 @@ SOR4XPSD_LOW_012 SORCE XPS Level 4 Solar Spectral Irradiance 1.0nm Res 24-Hour M
SORTIE_0 Spectral Ocean Radiance Transfer Investigation and Experiment (SORTIE) program OB_DAAC STAC Catalog 2007-03-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360665-OB_DAAC.umm_json Measurements made under the SORTIE (Spectral Ocean Radiance Transfer Investigation and Experiment) program between 2007 and 2009. proprietary
SPACE_PHOTOS Space Acquired Photography USGS_LTA STAC Catalog 1965-03-23 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566702-USGS_LTA.umm_json Gemini photography was acquired between March 23, 1965 and November 15, 1966. The images were collected as part of the Synoptic Terrain Photography and the Synoptic Weather Photography experiments during Gemini Missions III through XII. Hand-held cameras were used to obtain photographs of geologic, oceanic, and meteorologic targets. The Gemini archive consists primarily of 70-mm black and white (B/W), color, and color-infrared (CIR) film. All Gemini photographs are distributed by the USGS Earth Resources Observation and Science (EROS) Center as digital products only. Skylab photography was acquired between May 22, 1973 and February 8, 1974 during three manned flights. The Skylab Earth Resources Experiment Package used two photographic remote sensing systems. The Multispectral Photographic Camera (S190A), was a six-camera array, in which each camera used 70-mm film and a six-inch focal length lens. The acquired film ranges from narrow-band B/W to broad-band color and CIR. The Earth Terrain Camera (S190B) consisted of a single high-resolution camera which used five-inch film and an 18-inch focal length lens. The acquired film includes B/W, black and white infrared (BIR), color, and CIR. All Skylab photographs are distributed by the USGS EDC as digital products only. Shuttle Large Format Camera (LFC) images were acquired from the Space Shuttle Challenger Mission on October 5-13, 1984. The LFC was mounted in the cargo bay, and was operated via signals from ground controllers. The archived imagery includes 9 x 18 inch B/W, natural color, and CIR film. Shuttle LFC photographs are distributed by the USGS EDC as digital products only. proprietary
SPANBR Automatic Atmospheric Sun Photometer Data for Brazil CEOS_EXTRA STAC Catalog 1992-06-01 -65, -28, -45, -2 https://cmr.earthdata.nasa.gov/search/concepts/C2227456147-CEOS_EXTRA.umm_json A network of 9 automatic sunphotometers operates in Brazil. Direct sun and sky radiances are acquired every hour by a weather resistant Cimel spectral radiometer in the wavelengths of 340, 440, 670,870, 940, and 1020 nm and transmitted automatically through the NOAA data collection system geostationary link for near real-time processing into spectral aerosol optical thickness, wavelength exponent and precipitable water. Evaluation of the atmospheric effects of biomass burning emissions from June-November are among the primary targets of the measurements. ftp://ftp.pmel.noaa.gov proprietary
-SPL1AP_002 SMAP L1A Radiometer Time-Ordered Parsed Telemetry V002 NSIDC_ECS STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C1000001801-NSIDC_ECS.umm_json Each Level-1A (L1A) granule incorporates all radiometer data downlinked from the Soil Moisture Active Passive (SMAP) spacecraft for one specific half orbit. The data are scaled instrument counts of the following:
- The first four raw moments of the fullband channel for both vertical and horizontal polarizations
- The complex cross-correlations of the fullband channel
- The 16 subband channels for both vertical and horizontal polarizations
proprietary
SPL1AP_002 SMAP L1A Radiometer Time-Ordered Parsed Telemetry V002 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2938661641-NSIDC_CPRD.umm_json Each Level-1A (L1A) granule incorporates all radiometer data downlinked from the Soil Moisture Active Passive (SMAP) spacecraft for one specific half orbit. The data are scaled instrument counts of the following:
- The first four raw moments of the fullband channel for both vertical and horizontal polarizations
- The complex cross-correlations of the fullband channel
- The 16 subband channels for both vertical and horizontal polarizations
proprietary
+SPL1AP_002 SMAP L1A Radiometer Time-Ordered Parsed Telemetry V002 NSIDC_ECS STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C1000001801-NSIDC_ECS.umm_json Each Level-1A (L1A) granule incorporates all radiometer data downlinked from the Soil Moisture Active Passive (SMAP) spacecraft for one specific half orbit. The data are scaled instrument counts of the following:
- The first four raw moments of the fullband channel for both vertical and horizontal polarizations
- The complex cross-correlations of the fullband channel
- The 16 subband channels for both vertical and horizontal polarizations
proprietary
SPL1A_001_1 SMAP_L1A_RADAR_V001 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214473171-ASF.umm_json SMAP Level 1A Radar Product proprietary
SPL1A_002_2 SMAP_L1A_RADAR_V002 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243149604-ASF.umm_json SMAP Level 1A Radar Product Version 2 proprietary
SPL1A_METADATA_001_1 SMAP_L1A_RADAR_METADATA_V001 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214473426-ASF.umm_json SMAP Level 1A Radar Product Metadata proprietary
@@ -14264,8 +14265,8 @@ SPL1A_RO_METADATA_003_3 SMAP_L1A_RADAR_RECEIVE_ONLY_METADATA_V003 ASF STAC Catal
SPL1A_RO_QA_001_1 SMAP_L1A_RADAR_RECEIVE_ONLY_QA_V001 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243168733-ASF.umm_json SMAP Level 1A Radar Receive Only Data Quality Information Version 1 proprietary
SPL1A_RO_QA_002_2 SMAP_L1A_RADAR_RECEIVE_ONLY_QA_V002 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243168866-ASF.umm_json SMAP Level 1A Radar Receive Only Data Quality Information Version 2 proprietary
SPL1A_RO_QA_003_3 SMAP_L1A_RADAR_RECEIVE_ONLY_QA_V003 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243124139-ASF.umm_json SMAP Level 1A Radar Receive Only Data Quality Information Version 3 proprietary
-SPL1BTB_006 SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V006 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2938661904-NSIDC_CPRD.umm_json This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed. proprietary
SPL1BTB_006 SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2776463679-NSIDC_ECS.umm_json This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed. proprietary
+SPL1BTB_006 SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V006 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2938661904-NSIDC_CPRD.umm_json This Level-1B (L1B) product provides calibrated estimates of time-ordered geolocated brightness temperatures measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band brightness temperatures are referenced to the Earth's surface with undesired and erroneous radiometric sources removed. proprietary
SPL1BTB_NRT_105 Near Real-time SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures V105 NSIDC_ECS STAC Catalog 2025-01-08 -180, -86.4, 180, 86.4 https://cmr.earthdata.nasa.gov/search/concepts/C2257958430-NSIDC_ECS.umm_json "This Near Real-Time (NRT) data set corresponds to the standard SMAP L1B Radiometer Half-Orbit Time-Ordered Brightness Temperatures (SPL1BTB) product. The data provide calibrated estimates of time-ordered geolocated brightness temperature data measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product, SPL1BTB (https://doi.org/10.5067/ZHHBN1KQLI20)." proprietary
SPL1B_SO_LoRes_001_1 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_V001 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214473308-ASF.umm_json SMAP Level 1B Sigma Naught Low Res Product proprietary
SPL1B_SO_LoRes_002_2 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_V002 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243253631-ASF.umm_json SMAP Level 1B Sigma Naught Low Res Product Version 2 proprietary
@@ -14278,8 +14279,8 @@ SPL1B_SO_LoRes_QA_002_2 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_QA_V002 ASF STAC Catalog 2
SPL1B_SO_LoRes_QA_003_3 SMAP_L1B_SIGMA_NAUGHT_LOW_RES_QA_V003 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243129847-ASF.umm_json SMAP Level 1B Sigma Naught Low Res Data Quality Info Version 3 proprietary
SPL1CTB_006 SMAP L1C Radiometer Half-Orbit 36 km EASE-Grid Brightness Temperatures V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463699-NSIDC_ECS.umm_json This Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP L-band Level-1B time-ordered brightness temperatures resampled to an Earth-fixed, 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal. This L1C product is a gridded version of the SMAP time-ordered Level-1B radiometer brightness temperature product. proprietary
SPL1CTB_006 SMAP L1C Radiometer Half-Orbit 36 km EASE-Grid Brightness Temperatures V006 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938663268-NSIDC_CPRD.umm_json This Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP L-band Level-1B time-ordered brightness temperatures resampled to an Earth-fixed, 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal. This L1C product is a gridded version of the SMAP time-ordered Level-1B radiometer brightness temperature product. proprietary
-SPL1CTB_E_004 SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures V004 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938663435-NSIDC_CPRD.umm_json This enhanced Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract enhanced information from SMAP antenna temperatures before they are converted to brightness temperatures. The resulting brightness temperatures are posted to an Earth-fixed, 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal. proprietary
SPL1CTB_E_004 SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures V004 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463717-NSIDC_ECS.umm_json This enhanced Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract enhanced information from SMAP antenna temperatures before they are converted to brightness temperatures. The resulting brightness temperatures are posted to an Earth-fixed, 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal. proprietary
+SPL1CTB_E_004 SMAP Enhanced L1C Radiometer Half-Orbit 9 km EASE-Grid Brightness Temperatures V004 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938663435-NSIDC_CPRD.umm_json This enhanced Level-1C (L1C) product contains calibrated and geolocated brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract enhanced information from SMAP antenna temperatures before they are converted to brightness temperatures. The resulting brightness temperatures are posted to an Earth-fixed, 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in three projections: global cylindrical, Northern Hemisphere azimuthal, and Southern Hemisphere azimuthal. proprietary
SPL1C_S0_HiRes_001_1 SMAP_L1C_SIGMA_NAUGHT_HIGH_RES_V001 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214473367-ASF.umm_json SMAP Level 1C Sigma Naught High Res Product proprietary
SPL1C_S0_HiRes_002_2 SMAP_L1C_SIGMA_NAUGHT_HIGH_RES_V002 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243268956-ASF.umm_json SMAP Level 1C Sigma Naught High Res Product Version 2 proprietary
SPL1C_S0_HiRes_003_3 SMAP_L1C_SIGMA_NAUGHT_HIGH_RES_V003 ASF STAC Catalog 2015-02-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243144528-ASF.umm_json SMAP Level 1C Sigma Naught High Res Product Version 3 proprietary
@@ -14293,35 +14294,35 @@ SPL2SMAP_003 SMAP L2 Radar/Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V0
SPL2SMAP_003 SMAP L2 Radar/Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303829-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radar and radiometer during 6:00 a.m. descending half-orbit passes. SMAP L-band backscatter and brightness temperatures are used to derive soil moisture data, which are then resampled to an Earth-fixed, global, cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL2SMAP_S_003 SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 km EASE-Grid Soil Moisture V003 NSIDC_ECS STAC Catalog 2015-03-31 -180, -60, 180, 60 https://cmr.earthdata.nasa.gov/search/concepts/C1931663473-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes and the Sentinel-1A and -1B radar. SMAP L-band brightness temperatures and Copernicus Sentinel-1 C-band backscatter coefficients are used to derive soil moisture data, which are then resampled to an Earth-fixed, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). While the 3 km data product has undergone validation, the 1 km product has not and should be used with caution. proprietary
SPL2SMAP_S_003 SMAP/Sentinel-1 L2 Radiometer/Radar 30-Second Scene 3 km EASE-Grid Soil Moisture V003 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -60, 180, 60 https://cmr.earthdata.nasa.gov/search/concepts/C2938663471-NSIDC_CPRD.umm_json This Level-2 (L2) soil moisture product provides estimates of land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes and the Sentinel-1A and -1B radar. SMAP L-band brightness temperatures and Copernicus Sentinel-1 C-band backscatter coefficients are used to derive soil moisture data, which are then resampled to an Earth-fixed, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). While the 3 km data product has undergone validation, the 1 km product has not and should be used with caution. proprietary
-SPL2SMA_003 SMAP L2 Radar Half-Orbit 3 km EASE-Grid Soil Moisture V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303826-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) active radar during 6:00 a.m. descending half-orbit passes, as well as ancillary data such as surface temperature and vegetation water content. Input backscatter data used to derive soil moisture are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL2SMA_003 SMAP L2 Radar Half-Orbit 3 km EASE-Grid Soil Moisture V003 NSIDC_CPRD STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2812935277-NSIDC_CPRD.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) active radar during 6:00 a.m. descending half-orbit passes, as well as ancillary data such as surface temperature and vegetation water content. Input backscatter data used to derive soil moisture are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
-SPL2SMP_009 SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V009 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) [and made available as the SPL1CTB product], and the gridded brightness temperatures are then used to derive gridded soil moisture data. proprietary
+SPL2SMA_003 SMAP L2 Radar Half-Orbit 3 km EASE-Grid Soil Moisture V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303826-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) active radar during 6:00 a.m. descending half-orbit passes, as well as ancillary data such as surface temperature and vegetation water content. Input backscatter data used to derive soil moisture are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL2SMP_009 SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V009 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938663609-NSIDC_CPRD.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) [and made available as the SPL1CTB product], and the gridded brightness temperatures are then used to derive gridded soil moisture data. proprietary
-SPL2SMP_E_006 SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.umm_json This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product]. proprietary
+SPL2SMP_009 SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V009 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463734-NSIDC_ECS.umm_json This Level-2 (L2) soil moisture product provides estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are resampled to an Earth-fixed, global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) [and made available as the SPL1CTB product], and the gridded brightness temperatures are then used to derive gridded soil moisture data. proprietary
SPL2SMP_E_006 SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V006 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2938663676-NSIDC_CPRD.umm_json This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product]. proprietary
+SPL2SMP_E_006 SMAP Enhanced L2 Radiometer Half-Orbit 9 km EASE-Grid Soil Moisture V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776463773-NSIDC_ECS.umm_json This enhanced Level-2 (L2) product contains calibrated, geolocated, brightness temperatures acquired by the Soil Moisture Active Passive (SMAP) radiometer during 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP Level-1B (L1B) interpolated antenna temperatures. Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection [available as the SPl1CTB_E product]. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. These 9-km brightness temperatures are then used to retrieve surface soil moisture posted on the 9-km grid [this SPL2SMP_E product]. proprietary
SPL2SMP_NRT_107 Near Real-time SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture V107 NSIDC_ECS STAC Catalog 2025-01-08 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2312096175-NSIDC_ECS.umm_json "This Near Real-Time (NRT) data set corresponds to the standard SMAP L2 Radiometer Half-Orbit 36 km EASE-Grid Soil Moisture (SPL2SMP) product. The data provide estimates of global land surface conditions measured by the Soil Moisture Active Passive (SMAP) passive microwave radiometer, the SMAP L-band radiometer. These Near Real-Time data are available within three hours of satellite observation. The data are created using the latest available ancillary data and spacecraft and antenna attitude data to reduce latency. The SMAP satellite orbits Earth every two to three days, providing half-orbit, ascending and descending, coverage from 86.4°S to 86.4°N in swaths 1000 km across. Data are stored for approximately two to three weeks. Thus, at any given time, users have access to at least fourteen consecutive days of Near Real-Time data through the NSIDC DAAC. Users deciding between the NRT and standard SMAP products should consider the immediacy of their needs versus the quality of the data required. Near real-time data are provided for operational needs whereas standard products meet the quality needs of scientific research. If latency is not a primary concern, users are encouraged to use the standard science product SPL2SMP (https://doi.org/10.5067/LPJ8F0TAK6E0)." proprietary
SPL3FTA_003 SMAP L3 Radar Northern Hemisphere Daily 3 km EASE-Grid Freeze/Thaw State V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, 45, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303849-NSIDC_ECS.umm_json This Level-3 (L3) product provides a daily composite of Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radar from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band backscatter data are used to derive freeze/thaw data, which are then resampled to an Earth-fixed, Northern Hemisphere azimuthal 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL3FTA_003 SMAP L3 Radar Northern Hemisphere Daily 3 km EASE-Grid Freeze/Thaw State V003 NSIDC_CPRD STAC Catalog 2015-04-13 2015-07-07 -180, 45, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2872766057-NSIDC_CPRD.umm_json This Level-3 (L3) product provides a daily composite of Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radar from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band backscatter data are used to derive freeze/thaw data, which are then resampled to an Earth-fixed, Northern Hemisphere azimuthal 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL3FTP_004 SMAP L3 Radiometer Global and Northern Hemisphere Daily 36 km EASE-Grid Freeze/Thaw State V004 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463838-NSIDC_ECS.umm_json This Level-3 (L3) product provides a daily composite of landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are used to derive freeze/thaw state and transition data, which are then resampled to both an Earth-fixed, Northern Hemisphere azimuthal 36 km Equal-Area Scalable Earth Grid (EASE-Grid 2.0), and to an Earth-fixed global 36 km EASE-Grid 2.0. proprietary
SPL3FTP_004 SMAP L3 Radiometer Global and Northern Hemisphere Daily 36 km EASE-Grid Freeze/Thaw State V004 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938664170-NSIDC_CPRD.umm_json This Level-3 (L3) product provides a daily composite of landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. SMAP L-band brightness temperatures are used to derive freeze/thaw state and transition data, which are then resampled to both an Earth-fixed, Northern Hemisphere azimuthal 36 km Equal-Area Scalable Earth Grid (EASE-Grid 2.0), and to an Earth-fixed global 36 km EASE-Grid 2.0. proprietary
-SPL3FTP_E_004 SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State V004 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938664439-NSIDC_CPRD.umm_json This enhanced Level-3 (L3) product provides a daily composite of global and Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP enhanced Level-1C brightness temperatures (SPL1CTB_E). Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures. The data are then posted to two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal. proprietary
SPL3FTP_E_004 SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State V004 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463920-NSIDC_ECS.umm_json This enhanced Level-3 (L3) product provides a daily composite of global and Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP enhanced Level-1C brightness temperatures (SPL1CTB_E). Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures. The data are then posted to two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal. proprietary
-SPL3SMAP_003 SMAP L3 Radar/Radiometer Global Daily 9 km EASE-Grid Soil Moisture V003 NSIDC_CPRD STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2872767144-NSIDC_CPRD.umm_json This Level-3 (L3) soil moisture product provides a daily composite of global land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radar and radiometer. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
+SPL3FTP_E_004 SMAP Enhanced L3 Radiometer Global and Northern Hemisphere Daily 9 km EASE-Grid Freeze/Thaw State V004 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938664439-NSIDC_CPRD.umm_json This enhanced Level-3 (L3) product provides a daily composite of global and Northern Hemisphere landscape freeze/thaw conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer from 6:00 a.m. descending and 6:00 p.m. ascending half-orbit passes. This product is derived from SMAP enhanced Level-1C brightness temperatures (SPL1CTB_E). Backus-Gilbert optimal interpolation techniques are used to extract maximum information from SMAP antenna temperatures and convert them to brightness temperatures. The data are then posted to two 9 km Earth-fixed, Equal-Area Scalable Earth Grids, Version 2.0 (EASE-Grid 2.0): a global cylindrical and a Northern Hemisphere azimuthal. proprietary
SPL3SMAP_003 SMAP L3 Radar/Radiometer Global Daily 9 km EASE-Grid Soil Moisture V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303847-NSIDC_ECS.umm_json This Level-3 (L3) soil moisture product provides a daily composite of global land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radar and radiometer. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
+SPL3SMAP_003 SMAP L3 Radar/Radiometer Global Daily 9 km EASE-Grid Soil Moisture V003 NSIDC_CPRD STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2872767144-NSIDC_CPRD.umm_json This Level-3 (L3) soil moisture product provides a daily composite of global land surface conditions retrieved by both the Soil Moisture Active Passive (SMAP) radar and radiometer. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL3SMA_003 SMAP L3 Radar Global Daily 3 km EASE-Grid Soil Moisture V003 NSIDC_ECS STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C1236303828-NSIDC_ECS.umm_json This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) radar as well as a variety of ancillary data sources. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL3SMA_003 SMAP L3 Radar Global Daily 3 km EASE-Grid Soil Moisture V003 NSIDC_CPRD STAC Catalog 2015-04-13 2015-07-07 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2872766452-NSIDC_CPRD.umm_json This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) radar as well as a variety of ancillary data sources. SMAP L-band soil moisture data are resampled to an Earth-fixed, global, cylindrical 3 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
-SPL3SMP_009 SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture V009 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938664585-NSIDC_CPRD.umm_json This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band soil moisture data are resampled to a global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL3SMP_009 SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture V009 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2776463935-NSIDC_ECS.umm_json This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band soil moisture data are resampled to a global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
+SPL3SMP_009 SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture V009 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938664585-NSIDC_CPRD.umm_json This Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) passive microwave radiometer. SMAP L-band soil moisture data are resampled to a global, cylindrical 36 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0). proprietary
SPL3SMP_E_006 SMAP Enhanced L3 Radiometer Global and Polar Grid Daily 9 km EASE-Grid Soil Moisture V006 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2776463943-NSIDC_ECS.umm_json This enhanced Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer. This product is a daily composite of SMAP Level-2 (L2) soil moisture which is derived from SMAP Level-1C (L1C) interpolated brightness temperatures. Backus-Gilbert optimal interpolation techniques are used to extract information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. proprietary
SPL3SMP_E_006 SMAP Enhanced L3 Radiometer Global and Polar Grid Daily 9 km EASE-Grid Soil Moisture V006 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2938664763-NSIDC_CPRD.umm_json This enhanced Level-3 (L3) soil moisture product provides a composite of daily estimates of global land surface conditions retrieved by the Soil Moisture Active Passive (SMAP) radiometer. This product is a daily composite of SMAP Level-2 (L2) soil moisture which is derived from SMAP Level-1C (L1C) interpolated brightness temperatures. Backus-Gilbert optimal interpolation techniques are used to extract information from SMAP antenna temperatures and convert them to brightness temperatures, which are posted to the 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) in a global cylindrical projection. As of 2021, the data are also posted to the Northern Hemisphere EASE-Grid 2.0, an azimuthal equal-area projection. proprietary
SPL4CMDL_007 SMAP L4 Global Daily 9 km EASE-Grid Carbon Net Ecosystem Exchange V007 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2534576405-NSIDC_ECS.umm_json The Level-4 (L4) carbon product (SPL4CMDL) provides global gridded daily estimates of net ecosystem carbon (CO2) exchange derived using a satellite data based terrestrial carbon flux model informed by the following: Soil Moisture Active Passive (SMAP) L-band microwave observations, land cover and vegetation inputs from the Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and the Goddard Earth Observing System Model, Version 5 (GEOS-5) land model assimilation system. Parameters are computed using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
SPL4CMDL_007 SMAP L4 Global Daily 9 km EASE-Grid Carbon Net Ecosystem Exchange V007 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938665243-NSIDC_CPRD.umm_json The Level-4 (L4) carbon product (SPL4CMDL) provides global gridded daily estimates of net ecosystem carbon (CO2) exchange derived using a satellite data based terrestrial carbon flux model informed by the following: Soil Moisture Active Passive (SMAP) L-band microwave observations, land cover and vegetation inputs from the Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and the Goddard Earth Observing System Model, Version 5 (GEOS-5) land model assimilation system. Parameters are computed using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
-SPL4SMAU_007 SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update V007 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938665508-NSIDC_CPRD.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: - SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D)
- SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3)
- SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG).
For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
SPL4SMAU_007 SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update V007 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2537927247-NSIDC_ECS.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: - SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D)
- SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3)
- SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG).
For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
-SPL4SMGP_007 SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V007 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2531308461-NSIDC_ECS.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
+SPL4SMAU_007 SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update V007 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938665508-NSIDC_CPRD.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: - SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D)
- SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3)
- SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG).
For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
SPL4SMGP_007 SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V007 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938665761-NSIDC_CPRD.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
-SPL4SMLM_007 SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants V007 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2537926833-NSIDC_ECS.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
+SPL4SMGP_007 SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V007 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2531308461-NSIDC_ECS.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
SPL4SMLM_007 SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants V007 NSIDC_CPRD STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2938666109-NSIDC_CPRD.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
+SPL4SMLM_007 SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants V007 NSIDC_ECS STAC Catalog 2015-03-31 -180, -85.044, 180, 85.044 https://cmr.earthdata.nasa.gov/search/concepts/C2537926833-NSIDC_ECS.umm_json SMAP Level-4 (L4) surface and root zone soil moisture data are provided in three products: * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data (SPL4SMGP, DOI: 10.5067/EVKPQZ4AFC4D) * SMAP L4 Global 3-hourly 9 km EASE-Grid Surface and Root Zone Soil Moisture Analysis Update (SPL4SMAU, DOI: 10.5067/LWJ6TF5SZRG3) * SMAP L4 Global 9 km EASE-Grid Surface and Root Zone Soil Moisture Land Model Constants (SPL4SMLM, DOI: 10.5067/KN96XNPZM4EG). For each product, SMAP L-band brightness temperature data from descending and ascending half-orbit satellite passes (approximately 6:00 a.m. and 6:00 p.m. local solar time, respectively) are assimilated into a land surface model that is gridded using an Earth-fixed, global cylindrical 9 km Equal-Area Scalable Earth Grid, Version 2.0 (EASE-Grid 2.0) projection. proprietary
SPOT-6.and.7.ESA.archive_9.0 SPOT-6 and 7 ESA archive ESA STAC Catalog 2012-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336951-ESA.umm_json The SPOT 6 and 7 ESA archive is a dataset of SPOT 6 and SPOT 7 products that ESA collected over the years. The dataset regularly grows as ESA collects new SPOT 6 and 7 products. SPOT 6 and 7 Primary and Ortho products can be available in the following modes: Panchromatic image at 1.5m resolution Pansharpened colour image at 1.5m resolution Multispectral image in 4 spectral bands at 6m resolution Bundle (1.5m panchromatic image + 6m multispectral image) Spatial coverage: Check the spatial coverage of the collection on a _$$map$$ https://tpm-ds.eo.esa.int/socat/SPOT6-7 available on the Third Party Missions Dissemination Service. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided. proprietary
SPOT1-5_8.0 SPOT1-5 ESA archive ESA STAC Catalog 1986-04-01 2015-09-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1532648155-ESA.umm_json The ESA SPOT1-5 collection is a dataset of SPOT-1 to 5 Panchromatic and Multispectral products that ESA collected over the years. The HRV(IR) sensor onboard SPOT 1-4 provides data at 10 m spatial resolution Panchromatic mode (-1 band) and 20 m (Multispectral mode -3 or 4 bands). The HRG sensor on board of SPOT-5 provides spatial resolution of the imagery to < 3 m in the panchromatic band and to 10 m in the multispectral mode (3 bands). The SWIR band imagery remains at 20 m. The dataset mainly focuses on European and African sites but some American, Asian and Greenland areas are also covered. proprietary
SPOT4-5_Take5.ESAarchive_7.0 SPOT 4-5 Take5 ESA archive ESA STAC Catalog 2013-01-31 2015-09-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336953-ESA.umm_json At the end of SPOT-4 life, the Take5 experiment was launched and the satellite was moved to a lower orbit to obtain a 5 day repeat cycle, same repetition of Sentinel-2. Thanks to this orbit, from 1st of Feb to 19th of June 2013 a time series of images acquired every 5 days with constant angle and over 45 different sites were observed. In analogy to the previous SPOT-4 Take-5 experiment, also SPOT-5 was placed in a 5 days cycle orbit and 145 selected sites were acquired every 5 days under constant angles from 8th of April to 31st of August 2015. With a resolution of 10 m, the following processing levels are available: Level 1A: reflectance at the top of atmosphere (TOA), not orthorectified products Level 1C: data orthorectified reflectance at the top of atmosphere (TOA) Level 2A: data orthorectified surface reflectance after atmospheric correction (BOA), along with clouds mask and their shadow, and mask of water and snow. proprietary
@@ -14393,8 +14394,8 @@ SRTMSWBD_003 NASA Shuttle Radar Topography Mission Water Body Data Shapefiles &
SSBUVIRR_008 Shuttle SBUV (SSBUV) Solar Spectral Irradiance V008 (SSBUVIRR) at GES DISC GES_DISC STAC Catalog 1989-10-19 1996-01-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1273652226-GES_DISC.umm_json The Shuttle Solar Backscatter Ultraviolet (SSBUV) level-2 irradiance data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flown on the NOAA polar orbiting satellites. Data are available in an ASCII text format. UV irradiance data are available for the following days from the eight missions: Flight #1: 1989 October 19, 20, 21 Flight #2: 1990 October 7, 8, 9 Flight #3: 1991 August 3, 4, 5, 6 Flight #4: 1992 March 29, 30 Flight #5: 1993 April 9, 11, 13, 15, 16 Flight #6: 1994 March 14, 15, 17 Flight #7: 1994 November 5, 7, 10, 13 Flight #8: 1996 January 12, 16, 18 The Shuttle SBUV (SSBUV) instrument measured solar spectral UV irradiance during the maximum and declining phase of solar cycle 22. The SSBUV data accurately represent the absolute solar UV irradiance between 200-405 nm, and also show the long-term variations during eight flights between October 1989 and January 1996. These data have been used to correct long-term sensitivity changes in the NOAA-11 SBUV/2 data, which provide a near-daily record of solar UV variations over the 170-400 nm region between December 1988 and October 1994. These data demonstrate the evolution of short-term solar UV activity during solar cycle 22. proprietary
SSBUVO3_008 Shuttle SBUV (SSBUV) Level 2 Ozone Profile and Total Column, Aerosol Index, and UV-Reflectivity V008 (SSBUVO3) at GES DISC GES_DISC STAC Catalog 1989-10-19 1996-01-18 -180, -57, 180, 58 https://cmr.earthdata.nasa.gov/search/concepts/C1273652228-GES_DISC.umm_json The Shuttle Solar Backscatter Ultraviolet (SSBUV) Level-2 Ozone data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flying on the NOAA satellites. Data are available in the ASCII AMES text format. Ozone profiles of the upper atmosphere and total column ozone values are available for the following time periods: Flight #1: 1989 October 19, 20, 21. Flight #2: 1990 October 7, 8, 9. Flight #3: 1991 August 3, 4, 5, 6. Flight #4: 1992 March 29, 31. Flight #5: 1993 April 9, 11, 13, 15, 16. Flight #6: 1994 March 14, 15, 17. Flight #7: 1994 November 5, 7, 10, 13. Flight #8: 1996 January 12, 16, 18. SSBUV measures spectral ultraviolet radiances backscattered by the earth's atmosphere. For the ozone measurements the instrument steps over wavelengths between 252.2 and 339.99 nm while viewing the earth in the nadir position (50 km x 50 km footprint at nadir) at 19 pressure levels between 0.3 mb and 100 mb. proprietary
SSDP_HAZARD_EARTHQUAKE Earthquakes and Planning for Ground Rupture Hazards CEOS_EXTRA STAC Catalog 1970-01-01 -116, 33, -115.5, 33.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231553786-CEOS_EXTRA.umm_json Detailed maps bring a greater resolution to the number and locations of active faults. Preparing maps at a higher resolution requires extensive field study, and with a GIS, information, such as tract and parcel data, utility corridors, and flood hazard zones, can be incorporated to help decision makers in locating remediation facilities. After the Sylmar earthquake in 1972, building codes were strengthened, and the Alquist-Priolo Special Studies Zone Act was passed. Its purpose is to mitigate the hazard of fault rupture by prohibiting the location of most human occupancy structures across the traces of active faults. Earthquake fault zones are regulatory zones that encompass surface traces of active faults with a potential for future surface fault rupture. The zones are generally established about 500 feet on either side of the surface trace of active faults. Active faults and strips of state-mandated zoning along faults (Alquist-Priolo zones) riddle the Salton Sea Basin. The primary fault, the San Andreas, steps from the northeast side of the Salton Sea across the southern end, along a series of poorly understood faults, to the Brawley and Imperial fault systems. This stepover region has not had a historic ground-rupturing earthquake. Alquist-Priolo zones could not be defined because the faults are not well-located. Faults parallel to, and splaying from, the San Andreas are also capable of major earthquakes. Initial plans for remediation facilities take into account the generalized information (at 1:750,000 scale) on active faults, and the fault maps do not provide information on strong ground shaking. The shaking can damage facilities that lie far from an earthquake epicenter and far from active faults. Information on near-surface materials is required to estimate the ground-shaking hazards. proprietary
-SSEC-AMRC-AIRCRAFT Aircraft meteorological reports over Antarctica SCIOPS STAC Catalog 2004-04-04 2015-08-31 -180, -90, 180, 0 https://cmr.earthdata.nasa.gov/search/concepts/C1214605495-SCIOPS.umm_json The AMRC has been archiving the Aircraft data since the 2000's in the ftp archive. Products used to be made in real-time, but data collection has ended starting 31 August, 2015. proprietary
SSEC-AMRC-AIRCRAFT Aircraft meteorological reports over Antarctica ALL STAC Catalog 2004-04-04 2015-08-31 -180, -90, 180, 0 https://cmr.earthdata.nasa.gov/search/concepts/C1214605495-SCIOPS.umm_json The AMRC has been archiving the Aircraft data since the 2000's in the ftp archive. Products used to be made in real-time, but data collection has ended starting 31 August, 2015. proprietary
+SSEC-AMRC-AIRCRAFT Aircraft meteorological reports over Antarctica SCIOPS STAC Catalog 2004-04-04 2015-08-31 -180, -90, 180, 0 https://cmr.earthdata.nasa.gov/search/concepts/C1214605495-SCIOPS.umm_json The AMRC has been archiving the Aircraft data since the 2000's in the ftp archive. Products used to be made in real-time, but data collection has ended starting 31 August, 2015. proprietary
SSFR_irradiance_841_1 SAFARI 2000 Solar Spectral Flux Radiometer Data, Southern Africa, Dry Season 2000 ORNL_CLOUD STAC Catalog 2000-08-17 2000-09-16 5, -35, 60, 5 https://cmr.earthdata.nasa.gov/search/concepts/C2788411266-ORNL_CLOUD.umm_json The Solar Spectral Flux Radiometer (SSFR) was deployed on the University of Washington CV-580 during the dry season component of the Southern African Regional Science Initiative, August 1 - September 20, 2000. The SSFR made simultaneous measurements of both downwelling and upwelling net solar spectral irradiance at varying flight levels. Data have been provided for twenty flights in netcdf format for the period August 17 - September 16, 2000.For a complete detailed guide to the extensive measurements obtained aboard the UW Convair-580 aircraft in support of SAFARI 2000, see the UW Technical Report for the SAFARI 2000 Project. proprietary
STAQS_AircraftRemoteSensing_JSC-GV_GCAS_Data_1 STAQS JSC GV GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator Data LARC_CLOUD STAC Catalog 2023-06-26 2023-08-17 -120.3, 33.36, -72, 44.56 https://cmr.earthdata.nasa.gov/search/concepts/C2862468660-LARC_CLOUD.umm_json STAQS_AircraftRemoteSensing_JSC-GV_GCAS_Data is the remotely sensed trace gas data for the JSC Gulfstream V aircraft taken by the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) instrument as part of the Synergistic TEMPO Air Quality Science (STAQS) mission. Data collection for this product is complete. Launched in April 2023, NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite monitors major air pollutants across North America every daylight hour at high spatial resolution at a geostationary orbit (GEO). With these measurements, NASA’s STAQS mission seeks to integrate TEMPO satellite observations with traditional air quality monitoring to improve understanding of air quality science. STAQS is being conducted during summer 2023, targeting urban areas, including Los Angeles, New York City, and Chicago. As part of the mission two aircraft will be outfitted with various remote sensing payloads. The Johnson Space Center (JSC) Gulfstream-V (G-V) aircraft will feature the GeoCAPE Airborne Simulator (GCAS) and combined High Spectral Resolution Lidar-2 (HSRL-2) and Ozone Differential Absorption Lidar (DIAL). This payload provides repeated high-resolution mapping of NO2, HCHO, ozone, and aerosols up to 3x per day over targeted cities. NASA Langley Research Center’s (LaRC’s) Gulfstream-III will measure city-scale emissions 2x per day over the targeted cities with the High-Altitude Lidar Observatory (HALO) and Airborne Visible InfraRed Imaging Spectrometer – Next Generation (AVIRS-NG). STAQS will also incorporate ground-based tropospheric ozone profiles from the NASA Tropospheric Ozone Lidar Network (TOLNet), NO2, HCHO, and ozone measurements from Pandora spectrometers, and will leverage existing networks operated by the EPA and state air quality agencies. The primary goal of STAQS is to improve our current understanding of air quality science under the TEMPO field of regard. Further goals include evaluating TEMPO level 2 data products, interpreting the temporal and spatial evolution of air quality events tracked by TEMPO, improving temporal estimates of anthropogenic, biogenic, and greenhouse gas emissions, and assessing the benefit of assimilating TEMPO data into chemical transport models. proprietary
STAQS_AircraftRemoteSensing_JSC-GV_HSRL2_Data_1 STAQS JSC GV High Spectral Resolution Lidar-2 Data LARC_CLOUD STAC Catalog 2023-06-24 2023-08-16 -119.8, 29.25, -72.1, 44.22 https://cmr.earthdata.nasa.gov/search/concepts/C2862479332-LARC_CLOUD.umm_json STAQS_AircraftRemoteSensing_JSC-GV_HSRL2_Data is the remotely sensed trace gas data for the JSC Gulfstream V aircraft taken by the High Spectral Resolution Lidar-2 (HSRL-2) as part of the Synergistic TEMPO Air Quality Science (STAQS) mission. Data collection for this product is complete. Launched in April 2023, NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite monitors major air pollutants across North America every daylight hour at high spatial resolution at a geostationary orbit (GEO). With these measurements, NASA’s STAQS mission seeks to integrate TEMPO satellite observations with traditional air quality monitoring to improve understanding of air quality science. STAQS is being conducted during summer 2023, targeting urban areas, including Los Angeles, New York City, and Chicago. As part of the mission two aircraft will be outfitted with various remote sensing payloads. The Johnson Space Center (JSC) Gulfstream-V (G-V) aircraft will feature the GeoCAPE Airborne Simulator (GCAS) and combined High Spectral Resolution Lidar-2 (HSRL-2) and Ozone Differential Absorption Lidar (DIAL). This payload provides repeated high-resolution mapping of NO2, HCHO, ozone, and aerosols up to 3x per day over targeted cities. NASA Langley Research Center’s (LaRC’s) Gulfstream-III will measure city-scale emissions 2x per day over the targeted cities with the High-Altitude Lidar Observatory (HALO) and Airborne Visible InfraRed Imaging Spectrometer – Next Generation (AVIRS-NG). STAQS will also incorporate ground-based tropospheric ozone profiles from the NASA Tropospheric Ozone Lidar Network (TOLNet), NO2, HCHO, and ozone measurements from Pandora spectrometers, and will leverage existing networks operated by the EPA and state air quality agencies. The primary goal of STAQS is to improve our current understanding of air quality science under the TEMPO field of regard. Further goals include evaluating TEMPO level 2 data products, interpreting the temporal and spatial evolution of air quality events tracked by TEMPO, improving temporal estimates of anthropogenic, biogenic, and greenhouse gas emissions, and assessing the benefit of assimilating TEMPO data into chemical transport models. proprietary
@@ -14583,8 +14584,8 @@ Saskatchewan_Soils_125m_SSA_1346_2 BOREAS Agriculture Canada Central Saskatchewa
Sat_ActiveLayer_Thickness_Maps_1760_1 ABoVE: Active Layer Thickness from Remote Sensing Permafrost Model, Alaska, 2001-2015 ORNL_CLOUD STAC Catalog 2001-01-01 2015-12-31 -179.18, 55.57, -132.58, 70.21 https://cmr.earthdata.nasa.gov/search/concepts/C2143402571-ORNL_CLOUD.umm_json This dataset provides annual estimates of active layer thickness (ALT) at 1 km resolution across Alaska from 2001-2015. The ALT was estimated using a remote sensing-based soil process model incorporating global satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover extent (SCE), and Soil Moisture Active and Passive (SMAP) satellite soil moisture records. The study area covers the majority land area of Alaska except for areas of perennial ice/snow cover or open water. The ALT was defined as the maximum soil thawing depth throughout the year. The mean ALT and mean uncertainty from 2001 to 2015 are also provided. proprietary
Sat_ActiveLayer_Thickness_Maps_1760_1 ABoVE: Active Layer Thickness from Remote Sensing Permafrost Model, Alaska, 2001-2015 ALL STAC Catalog 2001-01-01 2015-12-31 -179.18, 55.57, -132.58, 70.21 https://cmr.earthdata.nasa.gov/search/concepts/C2143402571-ORNL_CLOUD.umm_json This dataset provides annual estimates of active layer thickness (ALT) at 1 km resolution across Alaska from 2001-2015. The ALT was estimated using a remote sensing-based soil process model incorporating global satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and snow cover extent (SCE), and Soil Moisture Active and Passive (SMAP) satellite soil moisture records. The study area covers the majority land area of Alaska except for areas of perennial ice/snow cover or open water. The ALT was defined as the maximum soil thawing depth throughout the year. The mean ALT and mean uncertainty from 2001 to 2015 are also provided. proprietary
SatelliteDerived_Forest_Mexico_2320_1 Satellite-Derived Forest Extent Likelihood Map for Mexico ORNL_CLOUD STAC Catalog 2010-01-01 2020-12-31 -120.31, 12.48, -84.29, 34.51 https://cmr.earthdata.nasa.gov/search/concepts/C2905454214-ORNL_CLOUD.umm_json This dataset provides a comparison of forest extent agreement from seven remote sensing-based products across Mexico. These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. The data are in cloud optimized GeoTIFF format and cover the period 2010-2020. A shapefile is included that outlines Mexico mainland areas. proprietary
-Scambos_PLR1441432 A Low-power, Quick-install Polar Observation System ('AMIGOS-II') for Monitoring Climate-ice-ocean Interactions SCIOPS STAC Catalog 2014-06-01 2015-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214604828-SCIOPS.umm_json The investigators propose to build and test a multi-sensor, automated measurement station for monitoring Arctic and Antarctic ice-ocean environments. The system, based on a previously successful design, will incorporate weather and climate sensors, camera, snow and firn sensors, instruments to measure ice motion, ice and ocean thermal profilers, hydrophone, and salinity sensors. This new system will have two-way communications for real-time data delivery and is designed for rapid deployment by a small field group. proprietary
Scambos_PLR1441432 A Low-power, Quick-install Polar Observation System ('AMIGOS-II') for Monitoring Climate-ice-ocean Interactions ALL STAC Catalog 2014-06-01 2015-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214604828-SCIOPS.umm_json The investigators propose to build and test a multi-sensor, automated measurement station for monitoring Arctic and Antarctic ice-ocean environments. The system, based on a previously successful design, will incorporate weather and climate sensors, camera, snow and firn sensors, instruments to measure ice motion, ice and ocean thermal profilers, hydrophone, and salinity sensors. This new system will have two-way communications for real-time data delivery and is designed for rapid deployment by a small field group. proprietary
+Scambos_PLR1441432 A Low-power, Quick-install Polar Observation System ('AMIGOS-II') for Monitoring Climate-ice-ocean Interactions SCIOPS STAC Catalog 2014-06-01 2015-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214604828-SCIOPS.umm_json The investigators propose to build and test a multi-sensor, automated measurement station for monitoring Arctic and Antarctic ice-ocean environments. The system, based on a previously successful design, will incorporate weather and climate sensors, camera, snow and firn sensors, instruments to measure ice motion, ice and ocean thermal profilers, hydrophone, and salinity sensors. This new system will have two-way communications for real-time data delivery and is designed for rapid deployment by a small field group. proprietary
SciSat-1.Ace.FTS.and.Maestro_4.0 SciSat-1: ACE-FTS and MAESTRO ESA STAC Catalog 2003-08-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336954-ESA.umm_json SCISAT-1 data aim at monitoring and analysing the chemical processes that control the distribution of ozone in the upper troposphere and stratosphere. It provides acquisitions from the 2 instruments MAESTRO and ACE-FTS. • MAESTRO: Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation. Dual-channel optical spectrometer in the spectral region of 285-1030 nm. The objective is to measure ozone, nitrogen dioxide and aerosol/cloud extinction (solar occultation measurements of atmospheric attenuation during satellite sunrise and sunset with the primary objective of assessing the stratospheric ozone budget). Solar occultation spectra are being used for retrieving vertical profiles of temperature and pressure, aerosols, and trace gases (O3, NO2, H2O, OClO, and BrO) involved in middle atmosphere ozone distribution. The use of two overlapping spectrometers (280 - 550 nm, 500 - 1030 nm) improves the stray-light performance. The spectral resolution is about 1-2 nm. • ACE-FTS: Fourier Transform Spectrometer The objective is to measure the vertical distribution of atmospheric trace gases, in particular of the regional polar O3 budget, as well as pressure and temperature (derived from CO2 lines). The instrument is an adapted version of the classical sweeping Michelson interferometer, using an optimized optical layout. The ACE-FTS measurements are recorded every 2 s. This corresponds to a measurement spacing of 2-6 km which decreases at lower altitudes due to refraction. The typical altitude spacing changes with the orbital beta angle. For historical reasons, the retrieved results are interpolated onto a 1 km "grid" using a piecewise quadratic method. For ACE-FTS version 1.0, the results were reported only on the interpolated grid (every 1 km from 0.5 to 149.5 km). For versions 2.2, both the "retrieval" grid and the "1 km" grid profiles are available. SCISAT-1 collection provides ACE-FTS and MAESTRO Level 2 Data. As of today, ACE-FTS products are available in version 4.1, while MAESTRO products are available in version 3.13. proprietary
Scotia_Prince_ferry_0 Scotia Prince ferry dataset OB_DAAC STAC Catalog 1998-06-06 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360640-OB_DAAC.umm_json Although the ferry that data were collected from no longer operates, longstanding data collection methods continue. The Scotia Prince ferry dataset has been reorganized and added to the GNATS experiment dataset (Gulf of Maine North Atlantic Time Series, 10.5067/SeaBASS/GNATS/DATA001). Please refer to that dataset to find data that were originally listed here. proprietary
Scotts_Fuel_1 Composition and origin of fuel from the hut of explorer Robert Falcon Scott, Cape Evans, Antarctica AU_AADC STAC Catalog 1910-08-15 1912-03-29 166.4, -77.633, 166.4, -77.633 https://cmr.earthdata.nasa.gov/search/concepts/C1214311239-AU_AADC.umm_json As a direct result of the 1989-90 trip as part of ASAC 245, a sample of petrol used by Scott on his ill-fated expedition to the South Pole was obtained. This petrol sample was supplied by the late Garth Varcoe of the New Zealand Antarctic Division following a discussion ensuing from a lecture given whilst on the Icebird when stuck in the ice off Davis. This sample is of intense historical interest and the results of the studies are in the download file. The material in the file reports the studies on the composition of the petrol which was left by the remaining members of Scott's group when they departed their base at Evans Head. The aim of this work was to identify the source of the fuel. A later study will attempt to comment on its suitability as a fuel for use under Antarctic conditions. There are five files on the CD. a)a poster presented at the Australian Organic Geochemistry Conference held in Leura, NSW in February of this year, b)a brief description highlighting some salient points of the poster; presented orally, c)an abstract of this work included in the conference proceedings, d)the conference proceedings and e)manuscript of a full paper submitted for publication in the Journal of Organic Geochemistry, including a table of data Geochemical analyses of the fuel used for the motor driven sledges used by the explorer Robert Falcon Scott for his 1911/1912 quest to the South Pole indicates that it is a straight run gasoline. The presence of bicadinanes, oleanane and other oleanoid angiosperm markers indicate that the feedstock oil was likely to be sourced from terrestrial source rocks of Tertiary age in the South East Asian region. The overall chemical composition of the fuel in its present state indicates that it may have been too heavy for usage in polar regions. proprietary
@@ -14645,8 +14646,8 @@ Seabirds_AAT_1 Distribution and abundance of breeding seabirds in the AAT AU_AAD
Seabirds_HIMI_1 Distribution and abundance of breeding seabirds at Heard Island and the McDonald Islands AU_AADC STAC Catalog 1901-01-01 70, -55, 75, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214313740-AU_AADC.umm_json Distribution and abundance of breeding seabirds at Heard I and the McDonald Is. This dataset comprises a broad range of component datasets derived from ground surveys aerial photography and oblique photography. Since the data have also been derived from old station logs for the 1947-54 period, and from published and unpublished records for the 1947-present day period. Aerial and oblique photography has been used to obtain supplementary information on distribution and abundance of seabirds in the region. Recent surveys, 2000/01 onwards, have made use of GPS for more precise geographic information on seabird nests and colonies. At present there are a number of child metadata records attached to this record. See the link above for details. proprietary
Seagrass_Mapping_Florida_0 Water quality measurements near the Big Bend Seagrasses Aquatic Preserve, Florida OB_DAAC STAC Catalog 2010-05-17 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360643-OB_DAAC.umm_json Water quality measurements taken near the Big Bend Seagrasses Aquatic Preserve in Florida. proprietary
Searcher_0 Measurements from the Baltic Sea in 1999 OB_DAAC STAC Catalog 1999-07-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360656-OB_DAAC.umm_json Measurements from the Baltic Sea in 1999. proprietary
-Seasonality_Tundra_Vegetation_1606_1 ABoVE: Climate Drivers of Pan-Arctic Tundra Vegetation Productivity, 1982-2015 ORNL_CLOUD STAC Catalog 1982-01-01 2015-12-31 -180, 70, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2162145436-ORNL_CLOUD.umm_json This dataset provides a summary of potential climate drivers of Arctic tundra vegetation productivity that have been compiled for growing seasons from 1982 to 2015. The scale of interest is the entire pan-arctic non-alpine tundra and the continental subdivisions of the North American and the Eurasian Arctic North of 70 degrees. These climate drivers include (1) maximum normalized difference vegetation index (MaxNDVI) and time-integrated NDVI (TI-NDVI), (2) summer sea ice concentrations, (3) oceanic heat content, (4) land surface temperature, and (5) summer warmth index (SWI). Data are provided variously as timeseries and weekly and bi-weekly averages over selected time ranges and study regions with calculated trends and trend significance. Data collected over 33 years were compiled to observe seasonal trends of vegetation productivity and to detect dynamics between arctic vegetation and climate drivers. proprietary
Seasonality_Tundra_Vegetation_1606_1 ABoVE: Climate Drivers of Pan-Arctic Tundra Vegetation Productivity, 1982-2015 ALL STAC Catalog 1982-01-01 2015-12-31 -180, 70, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2162145436-ORNL_CLOUD.umm_json This dataset provides a summary of potential climate drivers of Arctic tundra vegetation productivity that have been compiled for growing seasons from 1982 to 2015. The scale of interest is the entire pan-arctic non-alpine tundra and the continental subdivisions of the North American and the Eurasian Arctic North of 70 degrees. These climate drivers include (1) maximum normalized difference vegetation index (MaxNDVI) and time-integrated NDVI (TI-NDVI), (2) summer sea ice concentrations, (3) oceanic heat content, (4) land surface temperature, and (5) summer warmth index (SWI). Data are provided variously as timeseries and weekly and bi-weekly averages over selected time ranges and study regions with calculated trends and trend significance. Data collected over 33 years were compiled to observe seasonal trends of vegetation productivity and to detect dynamics between arctic vegetation and climate drivers. proprietary
+Seasonality_Tundra_Vegetation_1606_1 ABoVE: Climate Drivers of Pan-Arctic Tundra Vegetation Productivity, 1982-2015 ORNL_CLOUD STAC Catalog 1982-01-01 2015-12-31 -180, 70, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2162145436-ORNL_CLOUD.umm_json This dataset provides a summary of potential climate drivers of Arctic tundra vegetation productivity that have been compiled for growing seasons from 1982 to 2015. The scale of interest is the entire pan-arctic non-alpine tundra and the continental subdivisions of the North American and the Eurasian Arctic North of 70 degrees. These climate drivers include (1) maximum normalized difference vegetation index (MaxNDVI) and time-integrated NDVI (TI-NDVI), (2) summer sea ice concentrations, (3) oceanic heat content, (4) land surface temperature, and (5) summer warmth index (SWI). Data are provided variously as timeseries and weekly and bi-weekly averages over selected time ranges and study regions with calculated trends and trend significance. Data collected over 33 years were compiled to observe seasonal trends of vegetation productivity and to detect dynamics between arctic vegetation and climate drivers. proprietary
Secret_0 Studies of Ecological and Chemical Responses to Environmental Trends (SECRET) OB_DAAC STAC Catalog 1998-08-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360657-OB_DAAC.umm_json Measurements spanning from the California coast to Hawaii in the mid-Pacific Ocean from 1998 to 2006. proprietary
Semantic Segmentation of Crop Type in Ghana_1 Semantic Segmentation of Crop Type in Ghana MLHUB STAC Catalog 2020-01-01 2023-01-01 -2, 8, 1, 11 https://cmr.earthdata.nasa.gov/search/concepts/C2781412078-MLHUB.umm_json Automatic, accurate crop type maps can provide unprecedented information for understanding food systems, especially in developing countries where ground surveys are infrequent. However, little work has applied existing methods to these data scarce environments, which also have unique challenges of irregularly shaped fields, frequent cloud coverage, small plots, and a severe lack of training data. To address this gap in the literature, we provide the first crop type semantic segmentation dataset of small holder farms, specifically in Ghana and South Sudan. We are also the first to utilize high resolution, high frequency satellite data in segmenting small holder farms. The dataset includes time series of satellite imagery from Sentinel-1, Sentinel-2, and PlanetScope satellites throughout 2016 and 2017. For each tile/chip in the dataset, there are time series of imagery from each of the satellites, as well as a corresponding label that defines the crop type at each pixel. The label has only one value at each pixel location, and assumes that the crop type remains the same across the full time span of the satellite image time series. In many cases where ground truth was not available, pixels have no label and are set to a value of 0. proprietary
Semantic Segmentation of Crop Type in South Sudan_1 Semantic Segmentation of Crop Type in South Sudan MLHUB STAC Catalog 2020-01-01 2023-01-01 24, 1, 36, 13 https://cmr.earthdata.nasa.gov/search/concepts/C2781412590-MLHUB.umm_json Automatic, accurate crop type maps can provide unprecedented information for understanding food systems, especially in developing countries where ground surveys are infrequent. However, little work has applied existing methods to these data scarce environments, which also have unique challenges of irregularly shaped fields, frequent cloud coverage, small plots, and a severe lack of training data. To address this gap in the literature, we provide the first crop type semantic segmentation dataset of small holder farms, specifically in Ghana and South Sudan. We are also the first to utilize high resolution, high frequency satellite data in segmenting small holder farms. The dataset includes time series of satellite imagery from Sentinel-1, Sentinel-2, and PlanetScope satellites throughout 2016 and 2017. For each tile/chip in the dataset, there are time series of imagery from each of the satellites, as well as a corresponding label that defines the crop type at each pixel. The label has only one value at each pixel location, and assumes that the crop type remains the same across the full time span of the satellite image time series. In many cases where ground truth was not available, pixels have no label and are set to a value of 0. proprietary
@@ -14666,27 +14667,27 @@ Skelton_Aeromag_Data Aeromagnetic data centered over Skelton Neve, Antarctica: A
SkySat.Full.Archive.and.New.Tasking_9.0 SkySat Full Archive and New Tasking ESA STAC Catalog 2013-11-13 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C1965336955-ESA.umm_json "The SkySat Level 1 Basic Scene, Level 3B Ortho Scene and Level 3B Consolidated full archive and new tasking products are available as part of the Planet imagery offer. The SkySat Basic Scene product is uncalibrated and in a raw digital number format, not corrected for any geometric distortions inherent to the imaging process. Rational Polynomial Coefficients (RPCs) are provided to enable orthorectification by the user. • Basic Panchromatic Scene product – unorthorectified, radiometrically corrected, panchromatic (PAN) imagery. • Basic Panchromatic DN Scene product – unorthorectified, panchromatic (PAN) imagery. • Basic L1A Panchromatic DN Scene product – unorthorectified, pre-super resolution, panchromatic (PAN) imagery. • Basic Analytic Scene product – unorthorectified, radiometrically corrected, 4-band multispectral (BGR-NIR) imagery. • Basic Analytic DN Scene product – unorthorectified, 4-band multispectral (BGR-NIR) imagery. Basic Scene Product Components and Format Product Components and Format • Image File (GeoTIFF format) • Metadata File (JSON format) • Rational Polynomial Coefficients (Text File) • UDM File (GeoTIFF format) Image Configurations • 1-band Panchromatic/Panchromatic DN Image (PAN) • 4-band Analytic/Analytic DN Image (Blue, Green, Red, NIR) Ground Sampling Distance (nadir) • SkySat-1 & -2: 0.86 m (PAN), 1.0 m (MS) • SkySat-3 to -15: 0.65 m (PAN), 0.8 m (MS). 0.72 m (PAN) and 1.0 m (MS) for data acquired prior to 30/06/2020 • SkySat-16 to -21: 0.57 m (PAN), 0.75 m (MS) Geolocation Accuracy <50 m RMSE The SkySat Ortho Scene product is sensor- and geometrically-corrected (using DEMs with a post spacing of 30 – 90 m) and is projected to a cartographic map projection; the accuracy of the product varies from region-to-region based on available GCPs. • Ortho Panchromatic Scene product – orthorectified, radiometrically corrected, panchromatic (PAN) imagery. • Ortho Panchromatic DN Scene product – orthorectified, panchromatic (PAN), uncalibrated digital number imagery. • Ortho Analytic Scene product – orthorectified, 4-band multispectral (BGR-NIR) imagery. Radiometric corrections are applied to correct for any sensor artifacts and transformation to top-of-atmosphere radiance. • Ortho Analytic DN Scene product – orthorectified, 4-band multispectral (BGR-NIR), uncalibrated digital number imagery. Radiometric corrections are applied to correct for any sensor artifacts. • Ortho Pansharpened Multispectral Scene product – orthorectified, pansharpened, 4-band (BGR-NIR) imagery. • Ortho Visual Scene product – orthorectified, pansharpened, colour-corrected (using a colour curve) 3-band (RGB) imagery. Ortho Scene Product Components and Format Product Components and Format • Image File (GeoTIFF format) • Metadata File (JSON format) • Rational Polynomial Coefficients (Text File) • UDM File (GeoTIFF format) Image Configurations • 1-band Panchromatic/Panchromatic DN Image (PAN) • 4-band Analytic/Analytic DN Image (Blue, Green, Red, NIR) • 4-band Pansharpened Multispectral Image (Blue, Green, Red, NIR) • 3-band Pansharpened (Visual) Image (Red, Green, Blue) Orthorectified Pixel Size 50 cm Projection UTM WGS84 Geolocation Accuracy <10 m RMSE The SkySat Ortho Collect product is created by composing SkySat Ortho Scene products along an imaging strip into segments typically unifying ~60 individual SkySat Ortho Scenes, resulting in an image with a footprint of approximately 20 km x 5.9 km. The products may contain artifacts resulting from the composing process, particular offsets in areas of stitched source scenes. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
SkySatESAarchive_8.0 Skysat ESA archive ESA STAC Catalog 2016-02-29 -180, -84, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C2547572338-ESA.umm_json "The SkySat ESA archive collection consists of SkySat products requested by ESA supported projects over their areas of interest around the world and that ESA collected over the years. The dataset regularly grows as ESA collects new products. Two different product types are offered, Ground Sampling Distance at nadir up to 65 cm for panchromatic and up to 0.8m for multi-spectral. EO-SIP Product Type Product Description Content SSC_DEF_SC Basic and Ortho scene Level 1B 4-bands Analytic /DN Basic scene Level 1B 4-bands Panchromatic /DN Basic scene Level 1A 1-band Panchromatic DN Pre Sup resolution Basic scene Level 3B 3-bands Visual Ortho Scene Level 3B 4-bands Pansharpened Multispectral Ortho Scene Level 3B 4-bands Analytic/DN/SR Ortho Scene Level 3B 1-band Panchromatic /DN Ortho Scene SSC_DEF_CO Ortho Collect Visual 3-band Pansharpened Image Multispectral 4-band Pansharpened Image Multispectral 4-band Analytic/DN/SR Image (B, G, R, N) 1-band Panchromatic Image The Basic Scene product is uncalibrated, not radiometrically corrected for atmosphere or for any geometric distortions inherent in the imaging process: Analytic - unorthorectified, radiometrically corrected, multispectral BGRN Analytic DN - unorthorectified, multispectral BGRN Panchromatic - unorthorectified, radiometrically corrected, panchromatic (PAN) Panchromatic DN - unorthorectified, panchromatic (PAN) L1A Panchromatic DN - unorthorectified, pre-super resolution, panchromatic (PAN) The Ortho Scene product is sensor and geometrically corrected, and is projected to a cartographic map projection: Visual - orthorectified, pansharpened, and colour-corrected (using a colour curve) 3-band RGB Imagery Pansharpened Multispectral - orthorectified, pansharpened 4-band BGRN Imagery Analytic SR - orthorectified, multispectral BGRN. Atmospherically corrected Surface Reflectance product. Analytic - orthorectified, multispectral BGRN. Radiometric corrections applied to correct for any sensor artifacts and transformation to top-of-atmosphere radiance. Analytic DN - orthorectified, multispectral BGRN, uncalibrated digital number imagery product Radiometric corrections applied to correct for any sensor artifacts Panchromatic - orthorectified, radiometrically correct, panchromatic (PAN) Panchromatic DN - orthorectified, panchromatic (PAN), uncalibrated digital number imagery product The Ortho Collect product is created by composing SkySat Ortho Scenes along an imaging strip. The product may contain artifacts resulting from the composing process, particular offsets in areas of stitched source scenes. Spatial coverage: Check the spatial coverage of the collection on a _$$map$$ https://tpm-ds.eo.esa.int/smcat/SkySat/ available on the Third Party Missions Dissemination Service. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
Smallholder Cashew Plantations in Benin_1 Smallholder Cashew Plantations in Benin MLHUB STAC Catalog 2020-01-01 2023-01-01 2.4636579, 9.0570625, 2.5618896, 9.1603783 https://cmr.earthdata.nasa.gov/search/concepts/C2781412245-MLHUB.umm_json This dataset contains labels for cashew plantations in a 120 km^2 area in the center of Benin. Each pixel is classified for Well-managed plantation, Poorly-managed plantation, No plantation and other classes. The labels are generated using a combination of ground data collection with a handheld GPS device, and final corrections based on Airbus Pléiades imagery. proprietary
-SnowMeltDuration_PMicrowave_1843_1.1 ABoVE: Passive Microwave-derived Annual Snow Melt Duration Date Maps, 1988-2018 ALL STAC Catalog 1988-02-09 2018-07-20 -180, 51.6, -107.83, 72.41 https://cmr.earthdata.nasa.gov/search/concepts/C2223093928-ORNL_CLOUD.umm_json This dataset provides the annual period of snowpack melting (i.e., snow melt duration, SMD) across northwest Canada; Alaska, U.S.; and parts of far eastern Russia at 6.25 km resolution for the period 1988-2018. SMD is the number of days between the main melt onset date (MMOD) and the last day of seasonal snow cover when the melting of snow is complete. These dates were derived from the Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR). This dataset documents variability in SMD across space and the 31-year temporal period. The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies. proprietary
SnowMeltDuration_PMicrowave_1843_1.1 ABoVE: Passive Microwave-derived Annual Snow Melt Duration Date Maps, 1988-2018 ORNL_CLOUD STAC Catalog 1988-02-09 2018-07-20 -180, 51.6, -107.83, 72.41 https://cmr.earthdata.nasa.gov/search/concepts/C2223093928-ORNL_CLOUD.umm_json This dataset provides the annual period of snowpack melting (i.e., snow melt duration, SMD) across northwest Canada; Alaska, U.S.; and parts of far eastern Russia at 6.25 km resolution for the period 1988-2018. SMD is the number of days between the main melt onset date (MMOD) and the last day of seasonal snow cover when the melting of snow is complete. These dates were derived from the Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR). This dataset documents variability in SMD across space and the 31-year temporal period. The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies. proprietary
+SnowMeltDuration_PMicrowave_1843_1.1 ABoVE: Passive Microwave-derived Annual Snow Melt Duration Date Maps, 1988-2018 ALL STAC Catalog 1988-02-09 2018-07-20 -180, 51.6, -107.83, 72.41 https://cmr.earthdata.nasa.gov/search/concepts/C2223093928-ORNL_CLOUD.umm_json This dataset provides the annual period of snowpack melting (i.e., snow melt duration, SMD) across northwest Canada; Alaska, U.S.; and parts of far eastern Russia at 6.25 km resolution for the period 1988-2018. SMD is the number of days between the main melt onset date (MMOD) and the last day of seasonal snow cover when the melting of snow is complete. These dates were derived from the Making Earth Science Data Records for Use in Research Environments (MEaSUREs) Calibrated Enhanced-Resolution Passive Microwave (PMW) EASE-Grid Brightness Temperature (Tb) Earth System Data Record (ESDR). This dataset documents variability in SMD across space and the 31-year temporal period. The data from 1988-2016 included a coastal mask removing coastal pixels due to potential water contamination from coarse brightness temperature observations (Dersken et al., 2012). There is not a coastal mask for the 2017-2018 data. The full data are included, and data users should be aware that coastal values can be adversely affected by adjacent water bodies. proprietary
Snow_Cover_Extent_and_Depth_1757_1 ABoVE: High Resolution Cloud-Free Snow Cover Extent and Snow Depth, Alaska, 2001-2017 ORNL_CLOUD STAC Catalog 2001-01-01 2017-12-30 -179.18, 55.57, -132.58, 71.42 https://cmr.earthdata.nasa.gov/search/concepts/C2143402490-ORNL_CLOUD.umm_json This dataset provides estimates of maximum snow cover extent (SCE) and snow depth for each 8-day composite period from 2001 to 2017 at 1 km resolution across Alaska. The study area covers the majority land area of Alaska except for areas covered by perennial ice/snow or open water. A downscaling scheme was used in which Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis 0.5 degree snow depth data were interpolated to a finer 1 km spatial grid. In the methods used, the downscaling scheme incorporated MODIS SCE (MOD10A2) to better account for the influence of local topography on the 1km snow distribution patterns. For MODIS cloud-contaminated pixels, persistent and patchy cloud cover conditions were improved by applying an elevation-based spatial filtering algorithm to predict snow occurrence. Cloud-free MODIS SCE data were then used to downscale MERRA-2 snow depth data. For each snow-covered 1 km pixel indicated by the MODIS data, the snow depth was estimated based on the snow depth of the neighboring MERRA-2 0.5 grid cell, with weights predicted using a spatial filter. proprietary
Snow_Cover_Extent_and_Depth_1757_1 ABoVE: High Resolution Cloud-Free Snow Cover Extent and Snow Depth, Alaska, 2001-2017 ALL STAC Catalog 2001-01-01 2017-12-30 -179.18, 55.57, -132.58, 71.42 https://cmr.earthdata.nasa.gov/search/concepts/C2143402490-ORNL_CLOUD.umm_json This dataset provides estimates of maximum snow cover extent (SCE) and snow depth for each 8-day composite period from 2001 to 2017 at 1 km resolution across Alaska. The study area covers the majority land area of Alaska except for areas covered by perennial ice/snow or open water. A downscaling scheme was used in which Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis 0.5 degree snow depth data were interpolated to a finer 1 km spatial grid. In the methods used, the downscaling scheme incorporated MODIS SCE (MOD10A2) to better account for the influence of local topography on the 1km snow distribution patterns. For MODIS cloud-contaminated pixels, persistent and patchy cloud cover conditions were improved by applying an elevation-based spatial filtering algorithm to predict snow occurrence. Cloud-free MODIS SCE data were then used to downscale MERRA-2 snow depth data. For each snow-covered 1 km pixel indicated by the MODIS data, the snow depth was estimated based on the snow depth of the neighboring MERRA-2 0.5 grid cell, with weights predicted using a spatial filter. proprietary
Snow_Depth_Data_Images_1656_1 Snow Depth, Stratigraphy, and Temperature in Wrangell St Elias NP, Alaska, 2016-2018 ORNL_CLOUD STAC Catalog 2016-09-01 2018-03-20 -143.32, 62.26, -143, 62.39 https://cmr.earthdata.nasa.gov/search/concepts/C2170971586-ORNL_CLOUD.umm_json This dataset includes data from late-March snow surveys and hourly digital camera images from two study areas within the Wrangell St Elias National Park, Alaska. These data comprise snow density, stratigraphy, and temperature profiles obtained by snow pits; and snow depth data obtained from transects between snow pits. Daily snow depths, adjacent to each pit, were derived from hourly camera images of snow stakes placed adjacent to each pit. These data were collected to constrain and validate a physically-based, spatially-distributed snow evolution model used to simulate snow conditions in Dall sheep habitat. The two study areas are both located within the Jacksina Park Unit (JPU). The first study area, surveyed in 2017, included the northern end of Jaeger Mesa and an area near Rambler mine in the North East of the JPU. The second study area, surveyed in 2018, was within the upper watershed of Pass Creek in the North of the JPU. The remote cameras operated from September 2016 to August 2017 on Jaeger Mesa/Rambler Mine and from September 2017 to July 2018 at Pass Creek. proprietary
Snow_Wildlife_Tracks_AK_WA_2188_1 Snow Properties and Wildlife Tracks in Washington and Alaska ORNL_CLOUD STAC Catalog 2021-01-09 2023-03-13 -150.01, 48.05, -117.17, 63.97 https://cmr.earthdata.nasa.gov/search/concepts/C2772851281-ORNL_CLOUD.umm_json This dataset contains three field seasons of snow-wildlife observations conducted at 707 sites from January 2021 to March 2023 in Washington and Alaska, spanning a broad range of snow conditions. Relatively fresh tracks (usually <24 h) of common large mammal predators (bobcats, coyotes, cougars, and wolves) and their ungulate prey (caribou, Dall sheep, moose, mule deer, and white-tailed deer) were investigated to determine how snow affects predator-prey interactions. The track sink depth and dimensions (width and length) of three consecutive footprints were measured from one individual. Age class was recorded for moose based either on visual confirmation of an individual creating snow tracks or based on track dimensions. The ability to differentiate age classes for smaller ungulates was more uncertain, so age classes for deer, caribou, or sheep were not specified. Animal gait was identified using a simple classification scheme. Data also include animal species, snow density, hardness, total ice, surface temperature, and vegetation type. To best capture snow hardness, surface penetrability and hand-hardness were measured throughout the snowpack. The data are provided in comma-separated values (CSV) format. proprietary
Snowmelt_timing_maps_V2_1712_2 Snowmelt Timing Maps Derived from MODIS for North America, Version 2, 2001-2018 ORNL_CLOUD STAC Catalog 2001-01-01 2018-12-31 -180, 10, 0, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2764725108-ORNL_CLOUD.umm_json This data set provides snowmelt timing maps (STMs), cloud interference maps, and a map with the count of calculated snowmelt timing values for North America. The STMs are based on the Moderate Resolution Imaging Spectroradiometer (MODIS) standard 8-day composite snow-cover product MOD10A2 collection 6 for the period 2001-01-01 to 2018-12-31. The STMs were created by conducting a time-series analysis of the MOD10A2 snow maps to identify the DOY of snowmelt on a per-pixel basis. Snowmelt timing (no-snow) was defined as a snow-free reading following two consecutive snow-present readings for a given 500-m pixel. The count of STM values is also reported, which represents the number of years on record in the STMs from 2001-2018. proprietary
-Snowpack_Dall_Sheep_Track_1583_1 ABoVE: Dall Sheep Track Sinking Depths, Snow Depth, Hardness, and Density, 2017 ALL STAC Catalog 2017-03-19 2017-03-22 -143.06, 62.26, -143.01, 62.28 https://cmr.earthdata.nasa.gov/search/concepts/C2162140002-ORNL_CLOUD.umm_json This dataset contains Dall sheep (Ovis dalli dalli) hoof sinking depths in snow tracks, and snow depth, hardness, and density measurements in snow pits adjacent to the tracks. Snow measurements were collected between March 19-22, 2017 at sites on Jaeger Mesa in the Wrangell Mountains (WRST), Alaska. Estimated sheep age classes and track site coordinates are also provided. proprietary
Snowpack_Dall_Sheep_Track_1583_1 ABoVE: Dall Sheep Track Sinking Depths, Snow Depth, Hardness, and Density, 2017 ORNL_CLOUD STAC Catalog 2017-03-19 2017-03-22 -143.06, 62.26, -143.01, 62.28 https://cmr.earthdata.nasa.gov/search/concepts/C2162140002-ORNL_CLOUD.umm_json This dataset contains Dall sheep (Ovis dalli dalli) hoof sinking depths in snow tracks, and snow depth, hardness, and density measurements in snow pits adjacent to the tracks. Snow measurements were collected between March 19-22, 2017 at sites on Jaeger Mesa in the Wrangell Mountains (WRST), Alaska. Estimated sheep age classes and track site coordinates are also provided. proprietary
+Snowpack_Dall_Sheep_Track_1583_1 ABoVE: Dall Sheep Track Sinking Depths, Snow Depth, Hardness, and Density, 2017 ALL STAC Catalog 2017-03-19 2017-03-22 -143.06, 62.26, -143.01, 62.28 https://cmr.earthdata.nasa.gov/search/concepts/C2162140002-ORNL_CLOUD.umm_json This dataset contains Dall sheep (Ovis dalli dalli) hoof sinking depths in snow tracks, and snow depth, hardness, and density measurements in snow pits adjacent to the tracks. Snow measurements were collected between March 19-22, 2017 at sites on Jaeger Mesa in the Wrangell Mountains (WRST), Alaska. Estimated sheep age classes and track site coordinates are also provided. proprietary
SoilResp_HeterotrophicResp_1928_1 Global Gridded 1-km Soil and Soil Heterotrophic Respiration Derived from SRDB v5 ORNL_CLOUD STAC Catalog 1961-01-01 2016-06-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2345796019-ORNL_CLOUD.umm_json This dataset provides global gridded estimates of annual soil respiration (Rs) and soil heterotrophic respiration (Rh) and associated uncertainties at 1 km resolution. Mean soil respiration was estimated using a quantile regression forest model utilizing data from the global Soil Respiration Database Version 5 (SRDB-V5) and covariates of mean annual temperature, seasonal precipitation, and vegetative cover. The SRDB holds results of field studies of soil respiration from around the globe. A total of 4,115 records from 1,036 studies were selected from SRDB-V5. SRDB-V5 features more soil respiration data published in Russian and Chinese scientific literature for better global spatio-temporal coverage and improved global climate-space representation. These soil respiration records were combined with global meteorological, land cover, and topographic data and then evaluated with variable selection using random forests. The standard deviation and coefficient of variation of Rs are included and were also derived from the same model. Global heterotrophic respiration was calculated from Rs estimates. The data are produced in part from SRDB-V5 inputs that cover the period 1961-2016. proprietary
SoilSCAPE_1339_1 Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA ORNL_CLOUD STAC Catalog 2011-08-03 2019-12-14 -120.99, 31.74, -83.66, 42.3 https://cmr.earthdata.nasa.gov/search/concepts/C2736724942-ORNL_CLOUD.umm_json This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites in four states (California, Arizona, Oklahoma, and Michigan) in the United States. SoilSCAPE used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data at up to 12 sites over varying durations since August 2011. At its maximum, the network consisted of over 200 wireless sensor installations (nodes), with a range of 6 to 27 nodes per site. The soil moisture sensors (EC-5 and 5-TM from Decagon Devices) were installed at three to four depths, nominally at 5, 20, and 50 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. Temperature sensors were installed at 5 cm depth at six of the sites. Data collection started in August 2011 and continues at eight sites through the present. The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional (airborne, e.g. NASA's Airborne Microwave Observation of Subcanopy and Subsurface Mission - AirMOSS) and national (spaceborne, e.g. NASA's Soil Moisture Active Passive - SMAP) scales. proprietary
SoilSCAPE_V2_2049_2 Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, Version 2 ORNL_CLOUD STAC Catalog 2021-12-03 2023-02-03 -110.05, -36.72, 174.62, 37.2 https://cmr.earthdata.nasa.gov/search/concepts/C2736725173-ORNL_CLOUD.umm_json This dataset contains in-situ soil moisture profile and soil temperature data collected at 30-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites since 2021 in the United States and New Zealand. The SoilSCAPE network has used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data over varying durations since 2011. Since 2021, the SoilSCAPE has upgraded the two previously active sites in Arizona and added several new sites in the United States and New Zealand. These new sites typically use the METER Teros-12 soil moisture sensor. At its maximum, the new network consisted of 57 wireless sensor installations (nodes), with a range of 6 to 8 nodes per site. Each SoilSCAPE site contains multiple wireless end-devices (EDs). Each ED supports up to five soil moisture probes typically installed at 5, 10, 20, and 30 cm below the surface. Sites in Arizona have soil moisture probes installed at up to 75 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional and national (e.g. NASA's Cyclone Global Navigation Satellite System - CYGNSS and Soil Moisture Active Passive - SMAP) scales. The data are provided in NetCDF format. proprietary
-Soil_ActiveLayer_Properties_AK_2315_1 ABoVE: Active Layer Soil Characteristics at Selected Sites Across Alaska ALL STAC Catalog 2016-08-09 2018-07-07 -149.53, 63.88, -146.56, 68.56 https://cmr.earthdata.nasa.gov/search/concepts/C2849255421-ORNL_CLOUD.umm_json This dataset provides soil active layer characteristics from nine locations across Alaska. Soil samples were collected in 2016 except for one site which was sampled in 2018. Soil cores were collected from each site using a steel barrel and plastic sample tube attached to a hand drill. At the majority of sites, samples were taken from each end of three 30-m transects (i.e. samples collected at the 0 m and 30 m location of each transect). The entire thawed horizon (active layer) was sampled where possible, and the length of cores varies among sites. Cores were kept frozen until analysis in the lab. Samples were sectioned by horizon (organic and mineral), and the organic horizon was split into subsections so that no section was longer than approximately 10 cm. Coarse roots were removed, dried and weighed. Soils were measured for gravimetric water content, percent soil organic matter (SOM), pH, and bulk density. Locations were selected to investigate fire disturbance, to span the range of permafrost regions from continuous to sporadic, and to cover vegetation types from boreal forests, tussock tundra, upland willow/herbaceous scrub, and lowland fen and wet tundra sites across Alaska. The data are provided in comma-separated values (CSV) format. proprietary
Soil_ActiveLayer_Properties_AK_2315_1 ABoVE: Active Layer Soil Characteristics at Selected Sites Across Alaska ORNL_CLOUD STAC Catalog 2016-08-09 2018-07-07 -149.53, 63.88, -146.56, 68.56 https://cmr.earthdata.nasa.gov/search/concepts/C2849255421-ORNL_CLOUD.umm_json This dataset provides soil active layer characteristics from nine locations across Alaska. Soil samples were collected in 2016 except for one site which was sampled in 2018. Soil cores were collected from each site using a steel barrel and plastic sample tube attached to a hand drill. At the majority of sites, samples were taken from each end of three 30-m transects (i.e. samples collected at the 0 m and 30 m location of each transect). The entire thawed horizon (active layer) was sampled where possible, and the length of cores varies among sites. Cores were kept frozen until analysis in the lab. Samples were sectioned by horizon (organic and mineral), and the organic horizon was split into subsections so that no section was longer than approximately 10 cm. Coarse roots were removed, dried and weighed. Soils were measured for gravimetric water content, percent soil organic matter (SOM), pH, and bulk density. Locations were selected to investigate fire disturbance, to span the range of permafrost regions from continuous to sporadic, and to cover vegetation types from boreal forests, tussock tundra, upland willow/herbaceous scrub, and lowland fen and wet tundra sites across Alaska. The data are provided in comma-separated values (CSV) format. proprietary
+Soil_ActiveLayer_Properties_AK_2315_1 ABoVE: Active Layer Soil Characteristics at Selected Sites Across Alaska ALL STAC Catalog 2016-08-09 2018-07-07 -149.53, 63.88, -146.56, 68.56 https://cmr.earthdata.nasa.gov/search/concepts/C2849255421-ORNL_CLOUD.umm_json This dataset provides soil active layer characteristics from nine locations across Alaska. Soil samples were collected in 2016 except for one site which was sampled in 2018. Soil cores were collected from each site using a steel barrel and plastic sample tube attached to a hand drill. At the majority of sites, samples were taken from each end of three 30-m transects (i.e. samples collected at the 0 m and 30 m location of each transect). The entire thawed horizon (active layer) was sampled where possible, and the length of cores varies among sites. Cores were kept frozen until analysis in the lab. Samples were sectioned by horizon (organic and mineral), and the organic horizon was split into subsections so that no section was longer than approximately 10 cm. Coarse roots were removed, dried and weighed. Soils were measured for gravimetric water content, percent soil organic matter (SOM), pH, and bulk density. Locations were selected to investigate fire disturbance, to span the range of permafrost regions from continuous to sporadic, and to cover vegetation types from boreal forests, tussock tundra, upland willow/herbaceous scrub, and lowland fen and wet tundra sites across Alaska. The data are provided in comma-separated values (CSV) format. proprietary
Soil_Carbon_Flux_Maps_1683_1 Gridded Winter Soil CO2 Flux Estimates for pan-Arctic and Boreal Regions, 2003-2100 ORNL_CLOUD STAC Catalog 1993-01-01 2100-11-30 -180, -84.69, 179.9, 89.98 https://cmr.earthdata.nasa.gov/search/concepts/C2143812328-ORNL_CLOUD.umm_json This dataset provides gridded estimates of soil CO2 flux (g C m-2 d-1) for the winter non-growing season (NGS) across pan-Arctic and Boreal permafrost regions (>49 Deg N), at 25 km spatial resolution. The data are the daily average flux over a monthly period for two climate periods: the baseline climate period represents 2003-2018 and the future climate scenarios period represents 2018-2100 under Representative Concentration Pathways (RCP) 4.5 and 8.5. The data were produced by applying a Boosted Regression Tree machine learning approach to create gridded estimates of emissions based on in situ observations of NGS fluxes provided in a related dataset. The resulting monthly average flux data records can be used to calculate annual NGS soil CO2 flux budgets from 2003-2100. proprietary
Soil_Moisture_Alaska_Alberta_2123_1 Hourly Soil Moisture Logger Data, Alberta and Alaska, 2017-2021 ORNL_CLOUD STAC Catalog 2017-07-24 2021-07-29 -148.81, 56.66, -115.11, 69.63 https://cmr.earthdata.nasa.gov/search/concepts/C2633820284-ORNL_CLOUD.umm_json This dataset includes hourly in-situ soil moisture measurements from data loggers in predominantly organic soils (very low bulk density) at two locations: 1) along the Sag River in Alaska, U.S., and 2) near Red Earth Creek in Alberta, Canada. The dataset also provides soil moisture probe periods, temperature probe readings, as well as calibration coefficients and soil profile measurements used to create per probe calibrations for derived volumetric moisture content. The Campbell Scientific CR200 data loggers used CS625 water content reflectometers and temperature probe 109. Further details to the derivation of the calibrations are provided in a supplementary document. The purpose of the dataset is to provide field measurements that can be used for calibration/validation for satellite-based soil moisture retrieval algorithms. With some interruptions, the dataset exists from July 2017 to July 2021. The data are provided in comma-separated values (CSV) format. proprietary
Soil_Sensors_1 Data collected from in-situ soil sensors placed at Macquarie Island and Casey Station AU_AADC STAC Catalog 2005-01-01 110.52394, -66.28192, 158.9392, -54.498737 https://cmr.earthdata.nasa.gov/search/concepts/C1214313810-AU_AADC.umm_json "Data are collected for the purposes of monitoring on-ground works at Australian Antarctic stations associated with the remediation of petroleum hydrocarbon contaminated soil. Output datasets consist of soil oxygen (%), soil temperature (C), soil moisture content (VWC - Volumetric Water Content %), and aeration manifold pressure as measured by buried sensors (O2, T C, VWC) or manifold instruments (pressure). Sensor types are either: AD590 (temperature C) AD592 (temperature C) Figaro KE25 (% oxygen) Vegetronix VH400 (Volumetric Water Content %) 26PCD (Pressure, kPa) Sensors are attached via instrument cables to Datataker dt80 series loggers, which are housed in waterproof containers mounted on buildings, or inside buildings at Australian Antarctic stations. At the Macquarie Island isthmus, oxygen sensors are attached to buried groundwater monitoring wells (screened PVC tubes, known as mini-piezometers). Pressure sensors are attached to air distribution manifolds (part of an in-situ aeration distribution network), and temperature sensors are buried in the soil profile. Sensor nomenclature is as follows: FF0807/1/O2 (Fuel Farm, 2008 installation, mini-piezometer number 07, Sensor 1, Oxygen sensor) MPH_PS_3 (Main Power House, pressure sensor number 03) Biopiles consist of excavated soil placed in temporary, geo-engineered liner cells. Soil oxygen, soil temperature, and soil moisture content are typically measured at 50 cm height intervals from within the soil piles. Temperature and moisture are also typically measured from within the subgrade and liner materials - common nomenclature for sensor names are as follows: BP1/0.5SS_G11/O2 (Biopile 1, buried 0.5 m in soil profile, location G11, Oxygen sensor) BP1/AGM_G1/T(Biopile 1, Above GeoMembrane, Location G1, Temperature sensor) BP6/AGCL_N1/M (Biopile 6, Above Geosynthetic Clay Liner, Location N1, Moisture sensor) BP6/IGCL_N9/M (Biopile 6, Inside Geosynthetic Clay Liner, Location N9, Moisture sensor) EXT/-30SS_E1/M (External soil location, 30 cm below sediment surface, Sensor 1, Moisture sensor) Permeable Reactive Barrier (PRB's) are permeable gates emplaced within the regolith to treat hydrocarbon contaminated groundwater/meltwater and prevent offsite migration of contaminants (primarily hydrocarbons). The barriers have undergone several design iterations, but have consisted of staged (3 sections) permeable reactive or non-reactive filter media (Granular Activated Carbon, Silica sand, Zeolite, MaxBac (TM), Zeopro (TM), Zero Valent Iron), which are placed in buried galvanised shipping cages. The original PRB (installed 2005/06) is named ""PRB"", the second smaller PRB (named the Upper PRB or ""UPRB"" due to its higher elevation in the ) was installed in 2010/11 to treat contaminated groundwater around the MPH settling tank bund and protected the area cleaned as part of the MPH excavation. From this date, the original PRB has also been referred to as the ""lower PRB"". Sensor nomenclature is as follows: C_MP9/700/T (MiniPiezometer 9, 700 mm below ground surface, Temperature sensor) C_CG3_3/600/02 (Cage 3,Section 3, 600 mm below ground surface, Oxygen sensor) These data are downloaded from the sensors to the Australian Antarctic Division on a daily basis. Data are collected by the sensors every 5-20 minutes. As of 2013-03-04, the following personnel have been involved in the project: Greg Hince (AAD) - Project Manager, Field Remediation (11/12-ongoing). Principle Contact Ian Snape (AAD) - Project Principal (Macquarie Island and Casey Station), Macquarie Island 2008 field team. Geoff Stevens (University of Melbourne) - Project Principal - Casey Lower PRB installation Ben Raymond (AAD) - Calibration and Installation of sensors for Macquarie Island 08/09 field season, maintenance of database and remote troubleshooting of dataloggers. Tim Spedding (ex AAD) - Field Project Manager (08/09-10/11), Macquarie Island 2008 field team Dan Wilkins (AAD) - Datalogger management and system design (2009 onwards), Casey station sensor installation 10/11 and 11/12. John Rayner (ex AAD) - System design - Oxygen sensors. Macquarie Island 2008 field team. Installation of lower PRB (Casey) in 05/06. Lauren Wise (AAD) - Field maintenance and system operation (Macquarie Island, 10/11 and 12/13) Rebecca McWatters (AAD)- Casey Station sensors installation 10/11, 11/12, 12/13 Susan Ferguson (ex AAD) - Macquarie Island 2008 field team, Macquarie Island system maintenance 2009. Brett Quinton (ex AAD) - Macquarie Island system maintenance 2009 Charles Sutherland (AAD contractor/expeditioner) - Macquarie Island system maintenance 12/13 field season Robby Kilpatrick (AAD contractor/expeditioner) - Calibration and Installation of sensors for Macquarie Island 11/12 field season Kathryn Mumford (AAS Project Co-investigator, University of Melbourne) - Installation of lower PRB (Casey) in 05/06. Tom Statham (University of Melbourne, PhD student) - System installation, Casey 10/11 Warren Nichols - Oxygen sensor modifications (resin encasement) Rebecca Miller (AAD contractor/expeditioner) - Calibration and Installation of sensors for Casey EPH biopile - 12/13 Field Season Dan Jones (Queens University, Canada) - Calibration and Installation of sensors for Casey EPH biopile - 12/13 Field Season Various members of AAD Telecommunications Team (on ground troubleshooting and maintenance)" proprietary
Soil_Temp_Moisture_Alaska_1869_1 ABoVE: Soil Temperature and VWC at Unburned and Burned Sites Across Alaska, 2016-2023 ORNL_CLOUD STAC Catalog 2016-08-11 2023-09-02 -163.24, 61.27, -146.56, 68.99 https://cmr.earthdata.nasa.gov/search/concepts/C2143401688-ORNL_CLOUD.umm_json This dataset provides soil temperature and volumetric water content (VWC) measurements at 15 cm depth collected at 12 selected boreal and tundra sites located across Alaska. Each site is equipped with a HOBO MicroStation Data Logger that hosts two soil temperature sensors (HOBO S-TMB-M006 Temperature Smart Sensor), and two soil moisture sensors (HOBO S-SMD-M005 10HS Soil Moisture Smart Sensor). Each sensor was installed horizontally at a depth of 15 cm within the soil profile. Samples of soil from seven sites were taken to a laboratory for determination of site-specific soil moisture sensor calibration curves to correct raw measurements. Data were nominally recorded at an hourly frequency and downloaded from the sites at least annually for the period 2016-08-11 to 2023-09-02, but data coverage varies by site. These measurements were collected at the same sites as previously archived CO2 efflux and thaw depth data. The data are provided in comma-separated values (CSV) format. proprietary
Soil_Temp_Moisture_Alaska_1869_1 ABoVE: Soil Temperature and VWC at Unburned and Burned Sites Across Alaska, 2016-2023 ALL STAC Catalog 2016-08-11 2023-09-02 -163.24, 61.27, -146.56, 68.99 https://cmr.earthdata.nasa.gov/search/concepts/C2143401688-ORNL_CLOUD.umm_json This dataset provides soil temperature and volumetric water content (VWC) measurements at 15 cm depth collected at 12 selected boreal and tundra sites located across Alaska. Each site is equipped with a HOBO MicroStation Data Logger that hosts two soil temperature sensors (HOBO S-TMB-M006 Temperature Smart Sensor), and two soil moisture sensors (HOBO S-SMD-M005 10HS Soil Moisture Smart Sensor). Each sensor was installed horizontally at a depth of 15 cm within the soil profile. Samples of soil from seven sites were taken to a laboratory for determination of site-specific soil moisture sensor calibration curves to correct raw measurements. Data were nominally recorded at an hourly frequency and downloaded from the sites at least annually for the period 2016-08-11 to 2023-09-02, but data coverage varies by site. These measurements were collected at the same sites as previously archived CO2 efflux and thaw depth data. The data are provided in comma-separated values (CSV) format. proprietary
-Soil_Temperature_Profiles_AK_1767_1 ABoVE: Soil Temperature Profiles, USArray Seismic Stations, AK and Canada, 2016-2019 ORNL_CLOUD STAC Catalog 2016-06-25 2019-08-22 -163.18, 63.89, -134.34, 69.92 https://cmr.earthdata.nasa.gov/search/concepts/C2143402511-ORNL_CLOUD.umm_json This dataset includes soil temperature profile measurements taken at 16 monitoring sites in Alaska, USA, and at one site in Yukon, Canada. The six sites are collocated with seismic stations of the USArray program. The measurement dates and depths vary per site as does measurement frequency (hourly or every 6 hours). Measurements were made from the soil surface to a maximum depth of 1.5 m. Measurements were made from 2016-2018 at two sites, 2017-2019 at four sites, and 2018-2019 at 11 sites using temperature sensors attached to HOBO data loggers. These measurement stations complement existing temperature monitoring networks allowing for better characterization of ground temperatures and permafrost conditions across Alaska. proprietary
Soil_Temperature_Profiles_AK_1767_1 ABoVE: Soil Temperature Profiles, USArray Seismic Stations, AK and Canada, 2016-2019 ALL STAC Catalog 2016-06-25 2019-08-22 -163.18, 63.89, -134.34, 69.92 https://cmr.earthdata.nasa.gov/search/concepts/C2143402511-ORNL_CLOUD.umm_json This dataset includes soil temperature profile measurements taken at 16 monitoring sites in Alaska, USA, and at one site in Yukon, Canada. The six sites are collocated with seismic stations of the USArray program. The measurement dates and depths vary per site as does measurement frequency (hourly or every 6 hours). Measurements were made from the soil surface to a maximum depth of 1.5 m. Measurements were made from 2016-2018 at two sites, 2017-2019 at four sites, and 2018-2019 at 11 sites using temperature sensors attached to HOBO data loggers. These measurement stations complement existing temperature monitoring networks allowing for better characterization of ground temperatures and permafrost conditions across Alaska. proprietary
+Soil_Temperature_Profiles_AK_1767_1 ABoVE: Soil Temperature Profiles, USArray Seismic Stations, AK and Canada, 2016-2019 ORNL_CLOUD STAC Catalog 2016-06-25 2019-08-22 -163.18, 63.89, -134.34, 69.92 https://cmr.earthdata.nasa.gov/search/concepts/C2143402511-ORNL_CLOUD.umm_json This dataset includes soil temperature profile measurements taken at 16 monitoring sites in Alaska, USA, and at one site in Yukon, Canada. The six sites are collocated with seismic stations of the USArray program. The measurement dates and depths vary per site as does measurement frequency (hourly or every 6 hours). Measurements were made from the soil surface to a maximum depth of 1.5 m. Measurements were made from 2016-2018 at two sites, 2017-2019 at four sites, and 2018-2019 at 11 sites using temperature sensors attached to HOBO data loggers. These measurement stations complement existing temperature monitoring networks allowing for better characterization of ground temperatures and permafrost conditions across Alaska. proprietary
Sonoma_County_Forest_AGB_1764_1 CMS: LiDAR Biomass Improved for High Biomass Forests, Sonoma County, CA, USA, 2013 ORNL_CLOUD STAC Catalog 2013-09-01 2013-09-01 -123.54, 38.11, -122.34, 38.85 https://cmr.earthdata.nasa.gov/search/concepts/C2389021440-ORNL_CLOUD.umm_json This data set provides estimates of above-ground woody biomass and uncertainty at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha), were generated using a combination of airborne LiDAR data and field plot measurements with a parametric modeling approach. The relationship between field estimated and airborne LiDAR estimated aboveground biomass density is represented as a parametric model that predicts biomass as a function of canopy cover and 50th percentile and 90th percentile LiDAR heights at a 30-m resolution. To estimate uncertainty, the biomass model was re-fit 1,000 times through a sampling of the variance-covariance matrix of the fitted parametric model. This produced 1,000 estimates of biomass per pixel. The 5th and 95th percentiles, and the standard deviation of these pixel biomass estimates, were calculated. proprietary
South Africa Crop Type Competition_1 South Africa Crop Type Competition MLHUB STAC Catalog 2020-01-01 2023-01-01 17.818514, -34.1538276, 19.7650866, -30.7480751 https://cmr.earthdata.nasa.gov/search/concepts/C2781412651-MLHUB.umm_json This dataset was produced as part of the [Radiant Earth Spot the Crop Challenge](https://zindi.africa/hackathons/radiant-earth-spot-the-crop-hackathon). The objective of the competition was to create a machine learning model to classify fields by crop type from images collected during the growing season by the Sentinel-2 and Sentinel-1 satellites. proprietary
Southern_Boreal_Plot_Attribute_1740_1 ABoVE: Characterization of Burned and Unburned Boreal Forest Stands, SK, Canada, 2016 ALL STAC Catalog 2016-05-30 2016-06-16 -109.17, 54.09, -104.69, 57.36 https://cmr.earthdata.nasa.gov/search/concepts/C2143402623-ORNL_CLOUD.umm_json This dataset provides the results of field measurements and estimates of carbon stocks and combustion rates that characterize burned and unburned southern boreal forest stands near the La Ronge and Weyakwin communities in central Saskatchewan (SK), Canada. Measurements were completed in 2016 at 47 stands that burned in the 2015 Saskatchewan wildfires (Egg, Philion, and Brady) and at 32 unburned stands in comparable adjacent areas. Stands were characterized through field observations and sampling of the vegetative community (i.e., tree species, abundance, and biophysical measurements, stand age, coarse woody debris, history of fires or logging), soils (i.e., soil moisture class, unburned and burned soil organic layer depth, samples for bulk density and carbon analyses), and basic landscape geophysical traits. From these results, the pre-fire carbon stocks and carbon combustion values from both the above- and below-ground pools were estimated using a combination of linear and mixed-effects modeling and were calibrated against carbons stocks from the unburned stands. Estimates of uncertainty were generated for above- and below-ground carbon stocks and combustion values using a Monte Carlo framework paired with classic uncertainty propagation techniques. proprietary
@@ -14768,8 +14769,8 @@ TEMPO_O3TOT_L3_V03 TEMPO gridded ozone total column V03 (PROVISIONAL) LARC_CLOUD
TEMPO_RADT_L1_V03 TEMPO geolocated Earth radiances twilight V03 (PROVISIONAL) LARC_CLOUD STAC Catalog 2023-08-01 -170, 10, -10, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2930766795-LARC_CLOUD.umm_json Level 1 twilight radiance files provide radiance measured during twilight hours to capture city lights at TEMPO’s native spatial resolution, ~10 km^2 at the center of the Field of Regard (FOR), for individual granules. Each granule covers the entire North-South TEMPO FOR but only a portion of the East-West FOR. The files are provided in netCDF4 format, and contain information on radiometrically calibrated and geolocated radiances for the UV and visible bands, corresponding noise, geolocation, viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes image processing steps to produce radiometrically calibrated radiances with nominal navigation. These data reached provisional validation on December 9, 2024. proprietary
TEMPO_RAD_L1_V02 TEMPO geolocated Earth radiances V02 (BETA) LARC_CLOUD STAC Catalog 2023-08-01 -170, 10, -10, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2842845562-LARC_CLOUD.umm_json Level 1 radiance files provide radiance information at TEMPO’s native spatial resolution, ~10 km^2 at the center of the Field of Regard (FOR), for individual granules. Each granule covers the entire North-South TEMPO FOR but only a portion of the East-West FOR. The files are provided in netCDF4 format, and contain information on radiometrically and wavelength calibrated and geolocated radiances for the UV and visible bands, corresponding noise, parameterized wavelength grid, geolocation, viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes multiple steps: (1) Image processing to produce radiometrically calibrated radiance, (2) Additional wavelength calibration to improve wavelength registration, (3) Image Navigation and Registration (INR) using GOES-R data, and (4) post INR processing geolocation tagging and polarization correction. Please refer to the ATBD for details. These data are beta. Beta maturity is defined as: the product is minimally validated but may still contain significant errors; it is based on product quick looks using the initial calibration parameters. Because the products at this stage have minimal validation, users should refrain from making conclusive public statements regarding science and applications of the data products until a product is designated at the provisional validation status. The TEMPO Level 1 ATBD is still being finalized. For access to Version 1.0 ATBD, please contact the ASDC at larc-dl-asdc-tempo@mail.nasa.gov. proprietary
TEMPO_RAD_L1_V03 TEMPO geolocated Earth radiances V03 (PROVISIONAL) LARC_CLOUD STAC Catalog 2023-08-01 -170, 10, -10, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2930759336-LARC_CLOUD.umm_json Level 1 radiance files provide radiance information at TEMPO’s native spatial resolution, ~10 km^2 at the center of the Field of Regard (FOR), for individual granules. Each granule covers the entire North-South TEMPO FOR but only a portion of the East-West FOR. The files are provided in netCDF4 format, and contain information on radiometrically and wavelength calibrated and geolocated radiances for the UV and visible bands, corresponding noise, parameterized wavelength grid, geolocation, viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes multiple steps: (1) Image processing to produce radiometrically calibrated radiance, (2) Additional wavelength calibration to improve wavelength registration, (3) Image Navigation and Registration (INR) using GOES-R data, and (4) post INR processing geolocation tagging. These data reached provisional validation on December 9, 2024. proprietary
-TEMR_RSFCE Air Temperature Time Series SCIOPS STAC Catalog 1883-01-01 1987-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608675-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by Computer Centre North Administration for hydrometeorology in 1990 and containes air temperature from 68 stations in Arhangelsk, Vologda regions and Komi ASSR in Russia. Data is currently stored on magnetic tape (800 bit/inch). proprietary
TEMR_RSFCE Air Temperature Time Series ALL STAC Catalog 1883-01-01 1987-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608675-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by Computer Centre North Administration for hydrometeorology in 1990 and containes air temperature from 68 stations in Arhangelsk, Vologda regions and Komi ASSR in Russia. Data is currently stored on magnetic tape (800 bit/inch). proprietary
+TEMR_RSFCE Air Temperature Time Series SCIOPS STAC Catalog 1883-01-01 1987-12-31 25, 23.21, -175, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214608675-SCIOPS.umm_json Hydrometeorological data on the conditions of the environment are held by the Russian State Fund of data. This dataset was created by Computer Centre North Administration for hydrometeorology in 1990 and containes air temperature from 68 stations in Arhangelsk, Vologda regions and Komi ASSR in Russia. Data is currently stored on magnetic tape (800 bit/inch). proprietary
TG02_Balloon_VOC_1110_1 LBA-ECO TG-02 Biogenic VOC Emissions from Brazilian Amazon Forest and Pasture Sites ORNL_CLOUD STAC Catalog 1998-03-22 2000-02-16 -62.2, -10.08, -54.97, -0.86 https://cmr.earthdata.nasa.gov/search/concepts/C2768941787-ORNL_CLOUD.umm_json This data set reports concentrations of biogenic volatile organic compounds (BVOCs) collected from tethered balloon-sampling platforms above selected forest and pasture sites in the Brazilian Amazon in March 1998, February 1999, and February 2000. The air samples were collected from forested sites in Brazil: the Tapajos forest (Para) in the Tapajos/Xingu moist forest; Balbina (Amazonas) in the Uatuma moist forest; and Jaru (Rondonia) in the Purus/Madeira moist forest. Two other sites were also located in Rondonia: at a forest reserve (Rebio Jaru) and a pasture (Fazenda Nossa Senhora Aparecida). The BVOCs measured included isoprene, alpha and beta pinene, camphene, sabinene, myrcene, limonene, and other monoterpenes. Approximately 24 to 40 soundings, including as many as four VOC samples collected simultaneously at various altitudes, were made at each site. There is one comma-delimited data file with this data set. proprietary
TG03_AERONET_AOT_1128_1 LBA-ECO TG-03 Aeronet Aerosol Optical Thickness Measurements, Brazil: 1993-2005 ORNL_CLOUD STAC Catalog 1993-01-01 2005-01-01 -70.31, -20.45, -48.28, -1.2 https://cmr.earthdata.nasa.gov/search/concepts/C2768942874-ORNL_CLOUD.umm_json This data set includes aerosol optical thickness measurements from the CIMEL sunphotometer for 22 sites in Brazil during the period from 1993-2005. The AERONET (AErosol RObotic NETwork) program is an inclusive federation of ground-based remote sensing aerosol networks established by AERONET and the PHOtometrie pour le Traitement Operationnel de Normalisation Satellitaire (PHOTONS) and greatly expanded by AEROCAN (the Canadian sunphotometer network) and other agency, institute and university partners. The goal is to assess aerosol optical properties and validate satellite retrievals of aerosol optical properties. The network imposes standardization of instruments, calibration, and processing. Data from this collaboration provides globally distributed observations of spectral aerosol optical depths, inversion products, and precipitable water in geographically diverse aerosol regimes. Three levels of data are available from the AERONET website: Level 1.0 (unscreened), Level 1.5 (cloud-screened), and Level 2.0 (cloud-screened and quality-assured). Data provided here are Level 2.0. There are 22 comma-delimited data files with this data set and one companion text file which contains the latitude, longitude, and elevation of the 22 sites. proprietary
TG03_Aeronet_Solar_Flux_1137_1 LBA-ECO TG-03 Solar Surface Irradiance and PAR, Brazilian Amazon: 1999-2004 ORNL_CLOUD STAC Catalog 1999-01-01 2004-12-31 -67.87, -15.73, -54.95, -1.92 https://cmr.earthdata.nasa.gov/search/concepts/C2781384398-ORNL_CLOUD.umm_json This data set includes solar surface irradiance from Kipp and Zonen CM-21 pyranometers, both total unfiltered and filtered (RG695), and photosynthetically active radiation (PAR) from Skye-Probetech SKE-510 PAR sensors. Measurements were made at six sites acrosss the Brazilian Amazon during the period from 1999 to 2004. These sites were co-located with AERONET (AErosol RObotic NETwork) program sites. There are 17 comma-delimited data files (.csv) with this data set. The AERONET program is an inclusive federation of ground-based remote sensing aerosol networks established by AERONET and the PHOtometrie pour le Traitement Operationnel de Normalisation Satellitaire (PHOTONS) and greatly expanded by AEROCAN (the Canadian sunphotometer network) and other agency, institute and university partners. The goal is to assess aerosol optical properties and validate satellite retrievals of those properties. The network imposes standardization of instruments, calibration, and processing. proprietary
@@ -15372,11 +15373,11 @@ Tropical Cyclone Wind Estimation Competition_1 Tropical Cyclone Wind Estimation
TundraTransect_VegRefl_Soil_2232_1 Spectral Reflectance and Ancillary Data, Tundra Transect, North Slope, AK, 2000-2022 ORNL_CLOUD STAC Catalog 2000-06-30 2022-08-08 -156.6, 71.32, -156.6, 71.32 https://cmr.earthdata.nasa.gov/search/concepts/C2840820936-ORNL_CLOUD.umm_json This dataset provides visible-near infrared spectral reflectance, descriptions of vegetation cover, surface temperature, the total fraction of absorbed photosynthetically active radiation (fAPAR, 2001 only), permafrost active layer depth, elevation, and soil temperature at 5 cm depth. Measurements were made at every meter along a 100-m transect aligned mainly in an east-west direction, located approximately 300 m southeast of the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML) baseline observatory near Utqiagvik, Alaska. Reflectance measurements were collected at nearly weekly intervals through the growing seasons of 2000 to 2002 to describe characteristics of green-up, peak growth, and senescence. Reflectance measurements were also collected once near peak growth in 2022. Ancillary measurements were collected at intervals through the 2001 and 2002 growing seasons. proprietary
TundraVeg_Reflectance_Soil_CO2_1960_1 Tundra Plant Reflectance, CO2 Exchange, PAM Fluorometry, and Pigments, AK, 2001-2002 ORNL_CLOUD STAC Catalog 2001-06-08 2002-08-16 -157.41, 70.45, -156.6, 71.32 https://cmr.earthdata.nasa.gov/search/concepts/C2262495116-ORNL_CLOUD.umm_json This dataset provides measurements at tundra plots collected near Utqiagvik and Atqasuk, AK, including visible-near infrared spectral reflectance, chamber gas exchange measurements of CO2, pulse amplitude modulated (PAM) fluorometry, chlorophyll pigment contents, along with surface temperature, permafrost active layer depth, and soil temperature at 5 cm, through the growing seasons of 2001 and 2002. At all plots, spectral reflectance was measured using a portable spectrometer configured with a straight fiber optic foreoptic, surface temperatures were measured using a handheld Everest Infrared Thermometer, and thaw depth (or active layer depth) was measured using a metal rod graduated in centimeter intervals. At small plots (~15 cm) at Utqiagvik (referred to as Patch plots) chambers were constructed that enclosed an individual patch to determine photosynthetic rate and estimate respiration rate (made by covering the chamber in a dark cloth). Efficiency using PAM fluorometer, ambient yield estimations, and rapid light curve measurements were taken. Chlorophyll concentration was measured with a portable spectrometer configured as a spectrophotometer. At larger plots (approximately 1 m2) which were part of the International Tundra EXperiment (ITEX plots) at Utqiagvik (referred to as Barrow) and Atqasuk, a sub-sample of five control and five warmed plots at each site were fitted with 0.45 m diameter polyvinyl chloride collars for chamber flux measurements. To determine the total fraction of absorbed photosynthetically active radiation (fAPAR), a series of photosynthetically active radiation (PAR) measurements were made using a custom-made light bar consisting of a linear array of GaAsP sensors mounted within an aluminum U-bar under a white plastic diffuser. In addition, a visual estimate was made of the fraction of standing dead vegetation based on percent cover. The data are provided in comma-separated values (*.csv) format. In addition, photographs of plots and instruments are provided. proprietary
Tundra_Fire_Veg_Plots_1547_1 Arctic Vegetation Plots in Burned and Unburned Tundra, Alaska, 2011-2012 ORNL_CLOUD STAC Catalog 2011-07-14 2012-07-30 -164.69, 65.36, -146.65, 70.09 https://cmr.earthdata.nasa.gov/search/concepts/C2162122251-ORNL_CLOUD.umm_json This dataset provides environmental and vegetation data collected in late June and July of 2011 and of 2012 from study plots located in tundra fire scars and adjacent unburned tundra areas on the Seward Peninsula and the northern foothills of the Brooks Range in Arctic Alaska. The surveys focused on upland tundra settings and provide information on vegetative differences between the burned and unburned sites. The sampling design established a chronosequence of sites that varied in time since last fire to better understand post-fire vegetation successional trajectories. Complete species lists and their cover abundance data are provided for both study areas. Environmental data include the baseline plot descriptive information for vegetation, soils, and site factors. No soil samples were collected. proprietary
-Tundra_Greeness_Temp_Trends_1893_1 ABoVE: Landsat Tundra Greenness and Summer Air Temperatures, Arctic Tundra, 1985-2016 ALL STAC Catalog 1985-07-01 2016-08-31 -180, 31.49, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2143401680-ORNL_CLOUD.umm_json This dataset provides annual tundra greenness and summer air temperatures at a resolution of 50 km over the pan-Arctic tundra biome above 31.5 degrees over the time period 1985 to 2016. Annual tundra greenness was assessed using the maximum Normalized Difference Vegetation Index (NDVImax) derived from surface reflectance measured by sensors on the Landsat satellites. Summer air temperatures were quantified using the Summer Warmth Index (SWI) derived from an ensemble of five global temperature datasets. Tabular data include NDVImax, SWI, and estimates of uncertainty using Monte Carlo simulations at 45,334 vegetated sampling sites. Raster data provide (1) annual SWI from 1985 to 2016; (2) temporal trends in annual NDVImax and SWI from 1985 to 2016 and from 2000 to 2016; and (3) temporal correlations between annual NDVImax - SWI during these two periods. Each raster also includes estimates of uncertainty that were generated using Monte Carlo simulations. This dataset provides a new pan-Arctic product for assessing inter-annual variability in tundra using moderate resolution observations from the Landsat satellites. proprietary
Tundra_Greeness_Temp_Trends_1893_1 ABoVE: Landsat Tundra Greenness and Summer Air Temperatures, Arctic Tundra, 1985-2016 ORNL_CLOUD STAC Catalog 1985-07-01 2016-08-31 -180, 31.49, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2143401680-ORNL_CLOUD.umm_json This dataset provides annual tundra greenness and summer air temperatures at a resolution of 50 km over the pan-Arctic tundra biome above 31.5 degrees over the time period 1985 to 2016. Annual tundra greenness was assessed using the maximum Normalized Difference Vegetation Index (NDVImax) derived from surface reflectance measured by sensors on the Landsat satellites. Summer air temperatures were quantified using the Summer Warmth Index (SWI) derived from an ensemble of five global temperature datasets. Tabular data include NDVImax, SWI, and estimates of uncertainty using Monte Carlo simulations at 45,334 vegetated sampling sites. Raster data provide (1) annual SWI from 1985 to 2016; (2) temporal trends in annual NDVImax and SWI from 1985 to 2016 and from 2000 to 2016; and (3) temporal correlations between annual NDVImax - SWI during these two periods. Each raster also includes estimates of uncertainty that were generated using Monte Carlo simulations. This dataset provides a new pan-Arctic product for assessing inter-annual variability in tundra using moderate resolution observations from the Landsat satellites. proprietary
+Tundra_Greeness_Temp_Trends_1893_1 ABoVE: Landsat Tundra Greenness and Summer Air Temperatures, Arctic Tundra, 1985-2016 ALL STAC Catalog 1985-07-01 2016-08-31 -180, 31.49, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2143401680-ORNL_CLOUD.umm_json This dataset provides annual tundra greenness and summer air temperatures at a resolution of 50 km over the pan-Arctic tundra biome above 31.5 degrees over the time period 1985 to 2016. Annual tundra greenness was assessed using the maximum Normalized Difference Vegetation Index (NDVImax) derived from surface reflectance measured by sensors on the Landsat satellites. Summer air temperatures were quantified using the Summer Warmth Index (SWI) derived from an ensemble of five global temperature datasets. Tabular data include NDVImax, SWI, and estimates of uncertainty using Monte Carlo simulations at 45,334 vegetated sampling sites. Raster data provide (1) annual SWI from 1985 to 2016; (2) temporal trends in annual NDVImax and SWI from 1985 to 2016 and from 2000 to 2016; and (3) temporal correlations between annual NDVImax - SWI during these two periods. Each raster also includes estimates of uncertainty that were generated using Monte Carlo simulations. This dataset provides a new pan-Arctic product for assessing inter-annual variability in tundra using moderate resolution observations from the Landsat satellites. proprietary
Tundra_Leaf_Spectra_2005_1 Tundra Plant Leaf-level Spectral Reflectance and Chlorophyll Fluorescence, 2019-2021 ORNL_CLOUD STAC Catalog 2019-07-19 2021-09-30 -156.6, 64.83, -147.81, 71.31 https://cmr.earthdata.nasa.gov/search/concepts/C2262495547-ORNL_CLOUD.umm_json This dataset provides leaf-level visible-near infrared spectral reflectance, chlorophyll fluorescence spectra, species, plant functional type (PFT), and chlorophyll content of common high latitude plant samples collected near Fairbanks, Utqiagvik, and Toolik, Alaska, U.S., during the summers of 2019, 2020, and 2021. A FluoWat leaf clip was used to measure leaf-level visible-near infrared spectral reflectance and chlorophyll fluorescence spectra. Fluorescence yield (Fyield) was calculated as the ratio of the emitted fluorescence divided by the absorbed radiation for the wavelengths from 400 nm up to the wavelength of the cut off for the FluoWat low pass filter (either 650 or 700 nm). Chlorophyll content of samples was measured using a CCM-300 Chlorophyll Content. The data are provided in comma-separated values (.csv) format. proprietary
-Turbid9_0 2004 Measurements made in the Chesapeake Bay OB_DAAC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.umm_json Measurements made in the Chesapeake Bay in 2004. proprietary
Turbid9_0 2004 Measurements made in the Chesapeake Bay ALL STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.umm_json Measurements made in the Chesapeake Bay in 2004. proprietary
+Turbid9_0 2004 Measurements made in the Chesapeake Bay OB_DAAC STAC Catalog 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.umm_json Measurements made in the Chesapeake Bay in 2004. proprietary
Turkish_Seas_0 Turkish Seas pigment measurements OB_DAAC STAC Catalog 1997-09-17 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360690-OB_DAAC.umm_json Chlorophyll-a and pigment measurements made in the seas surrounding Turkey between 1997 and 1999. proprietary
UAEM1LME_002 MISR Level 1B2 Local Mode Ellipsoid Radiance Data subset for the UAE region V002 LARC STAC Catalog 2004-08-02 2004-08-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1627523796-LARC.umm_json Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Level 1B2 Local Mode Ellipsoid Radiance Data subset for the UAE region V002 contains the ellipsoid projected TOA parameters for the single local mode scene, resampled to WGS84 ellipsoid. proprietary
UAEM1LMT_002 MISR Level 1B2 Local Mode Terrain Radiance Data subset for the UAE region V002 LARC STAC Catalog 2004-08-02 2004-08-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1627523809-LARC.umm_json Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Level 1B2 Local Mode Terrain Radiance Data subset for the UAE region V002 contains the terrain-projected TOA radiance for the single local mode scene, resampled at the surface and topographically corrected. proprietary
@@ -15440,16 +15441,16 @@ UAVSAR_POL_SLOPE_1 UAVSAR_POLSAR_SLOPE ASF STAC Catalog 2008-07-24 165.585938,
UAVSAR_POL_STOKES_1 UAVSAR_POLSAR_STOKES ASF STAC Catalog 2008-07-24 165.585938, -47.989922, 137.636719, 83.84881 https://cmr.earthdata.nasa.gov/search/concepts/C1214419355-ASF.umm_json UAVSAR PolSAR Scene Stokes proprietary
UAV_Imagery_BigLakeTrail_1834_1 Multispectral Imagery, NDVI, and Terrain Models, Big Trail Lake, Fairbanks, AK, 2019 ORNL_CLOUD STAC Catalog 2019-08-04 2019-08-04 -147.83, 64.92, -147.81, 64.92 https://cmr.earthdata.nasa.gov/search/concepts/C2761782139-ORNL_CLOUD.umm_json This dataset provides multispectral reflectance imagery (green at 550 nm, red at 660 nm, red edge at 735 nm, and near-infrared at 790 nm), normalized difference vegetation index (NDVI), and digital surface and terrain models for a 0.5 km2 area surrounding Big Trail Lake (BTL) in the Goldstream Creek Valley north of Fairbanks, Alaska. These high spatial resolution maps (13 cm x 13 cm) were generated by unmanned aerial vehicle (UAV) imagery collected on 2019-08-04. Raw images (n=908) were combined into mosaic layers that incorporated ground control points with centimeter accuracy. These layers were then used to generate vegetation, water body, and elevation maps and then combined with in situ measurements of methane flux to improve upscaling models of greenhouse gas emissions. proprietary
UCLA_DEALIASED_SASS_L3_1 SEASAT SCATTEROMETER DEALIASED OCEAN WIND VECTORS (JPL-UCLA-AES) POCLOUD STAC Catalog 1978-07-07 1978-10-11 -180, -70, 180, 70 https://cmr.earthdata.nasa.gov/search/concepts/C2617197672-POCLOUD.umm_json Contains dealiased ocean wind vector components (zonal and meridional) derived from the Seasat-A Scatterometer (SASS) provided on a global 1x1 degree grid. Dealiasing of the SASS data was achieved manually using ship observations in a joint effort between JPL, UCLA and AES. This data set underwent restoration in 1997. Data are provided in ASCII text files at six hour intervals. proprietary
-UKASSEL_GLOBAL_IRRIGATED_AREA A Digital Global Map of Irrigated Areas SCIOPS STAC Catalog 1995-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214608839-SCIOPS.umm_json "For the purpose of global modeling of water use and crop production, a digital global map of irrigated areas was developed. The map depicts the areal percentage of each 0.5 deg. by 0.5 deg grid cell that was equipped for irrigation in 1995. It was derived by combininginformation from large-scale maps with outlines of irrigated areas (one or more countries per map), FAO data on total irrigated area per country in 1995 and national data on total irrigated area per county, drainage basin or federal state. In the documentation of the map, the data and map sources as well as the map generation process is described, and the data uncertainty is discussed. ""http://www.usf.uni-kassel.de/usf/archiv/dokumente/kwws/kwws.4.pdf"" We plan to improve this map in the future. Therefore, comments, information and data that might contribute to this effort are highly welcome." proprietary
UKASSEL_GLOBAL_IRRIGATED_AREA A Digital Global Map of Irrigated Areas ALL STAC Catalog 1995-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214608839-SCIOPS.umm_json "For the purpose of global modeling of water use and crop production, a digital global map of irrigated areas was developed. The map depicts the areal percentage of each 0.5 deg. by 0.5 deg grid cell that was equipped for irrigation in 1995. It was derived by combininginformation from large-scale maps with outlines of irrigated areas (one or more countries per map), FAO data on total irrigated area per country in 1995 and national data on total irrigated area per county, drainage basin or federal state. In the documentation of the map, the data and map sources as well as the map generation process is described, and the data uncertainty is discussed. ""http://www.usf.uni-kassel.de/usf/archiv/dokumente/kwws/kwws.4.pdf"" We plan to improve this map in the future. Therefore, comments, information and data that might contribute to this effort are highly welcome." proprietary
-UM0405_26_aerosol_optical Aerosol optical thickness - UM0405_26_aerosol_optical SCIOPS STAC Catalog 2004-12-31 2005-01-25 18, -68, 115, -32 https://cmr.earthdata.nasa.gov/search/concepts/C1221420727-SCIOPS.umm_json The aerosol optical thickness was measured with a sunphotometer. The measurement was conducted only clear sky condition. proprietary
+UKASSEL_GLOBAL_IRRIGATED_AREA A Digital Global Map of Irrigated Areas SCIOPS STAC Catalog 1995-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214608839-SCIOPS.umm_json "For the purpose of global modeling of water use and crop production, a digital global map of irrigated areas was developed. The map depicts the areal percentage of each 0.5 deg. by 0.5 deg grid cell that was equipped for irrigation in 1995. It was derived by combininginformation from large-scale maps with outlines of irrigated areas (one or more countries per map), FAO data on total irrigated area per country in 1995 and national data on total irrigated area per county, drainage basin or federal state. In the documentation of the map, the data and map sources as well as the map generation process is described, and the data uncertainty is discussed. ""http://www.usf.uni-kassel.de/usf/archiv/dokumente/kwws/kwws.4.pdf"" We plan to improve this map in the future. Therefore, comments, information and data that might contribute to this effort are highly welcome." proprietary
UM0405_26_aerosol_optical Aerosol optical thickness - UM0405_26_aerosol_optical ALL STAC Catalog 2004-12-31 2005-01-25 18, -68, 115, -32 https://cmr.earthdata.nasa.gov/search/concepts/C1221420727-SCIOPS.umm_json The aerosol optical thickness was measured with a sunphotometer. The measurement was conducted only clear sky condition. proprietary
-UM0506_26_aerosol_optical Aerosol optical thickness ALL STAC Catalog 2006-01-03 2006-01-30 18, -68, 115, -32 https://cmr.earthdata.nasa.gov/search/concepts/C1214595208-SCIOPS.umm_json The aerosol optical thickness was measured with a sunphotometer. The measurement was conducted only clear sky condition. proprietary
+UM0405_26_aerosol_optical Aerosol optical thickness - UM0405_26_aerosol_optical SCIOPS STAC Catalog 2004-12-31 2005-01-25 18, -68, 115, -32 https://cmr.earthdata.nasa.gov/search/concepts/C1221420727-SCIOPS.umm_json The aerosol optical thickness was measured with a sunphotometer. The measurement was conducted only clear sky condition. proprietary
UM0506_26_aerosol_optical Aerosol optical thickness SCIOPS STAC Catalog 2006-01-03 2006-01-30 18, -68, 115, -32 https://cmr.earthdata.nasa.gov/search/concepts/C1214595208-SCIOPS.umm_json The aerosol optical thickness was measured with a sunphotometer. The measurement was conducted only clear sky condition. proprietary
+UM0506_26_aerosol_optical Aerosol optical thickness ALL STAC Catalog 2006-01-03 2006-01-30 18, -68, 115, -32 https://cmr.earthdata.nasa.gov/search/concepts/C1214595208-SCIOPS.umm_json The aerosol optical thickness was measured with a sunphotometer. The measurement was conducted only clear sky condition. proprietary
UM0708_25_multi-frequency_acoustic Acoustic data of multi-frequency acoustic system ALL STAC Catalog 2007-12-24 2008-02-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214595173-SCIOPS.umm_json Vertical profiles of volume backscattering strength recorded by multi-frequency acoustic system for estimate size-abundance spectra of small zooplankton. The system was horizontally mounted on CTD frame and the observation was vertically performed from surface to 200 m at 23 stations. proprietary
UM0708_25_multi-frequency_acoustic Acoustic data of multi-frequency acoustic system SCIOPS STAC Catalog 2007-12-24 2008-02-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214595173-SCIOPS.umm_json Vertical profiles of volume backscattering strength recorded by multi-frequency acoustic system for estimate size-abundance spectra of small zooplankton. The system was horizontally mounted on CTD frame and the observation was vertically performed from surface to 200 m at 23 stations. proprietary
-UM0809_33_nano Abundance and composition of nano, picoplankton, microzooplankton ALL STAC Catalog 2009-01-12 2009-01-25 38, -70, 75, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214595104-SCIOPS.umm_json Water samples from 5 depths (0-100 m) were collected by Niskin bottles at 9 stations (L1, L3, L5, L9, L12, L37, L33, Ⅰ-10, Ⅱ-7) off Lützow-Holm Bay during Umitaka-maru cruise (Jan-Feb. 2008). The waters were fixed by 0.2% of lugol's acid solution (500 ml), 0.3% of bouin solution (500 ml) and 20 % of glutaraldehyde (100ml). http://biows.ac.jp/~plankton/um0809-1a.png proprietary
UM0809_33_nano Abundance and composition of nano, picoplankton, microzooplankton SCIOPS STAC Catalog 2009-01-12 2009-01-25 38, -70, 75, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214595104-SCIOPS.umm_json Water samples from 5 depths (0-100 m) were collected by Niskin bottles at 9 stations (L1, L3, L5, L9, L12, L37, L33, Ⅰ-10, Ⅱ-7) off Lützow-Holm Bay during Umitaka-maru cruise (Jan-Feb. 2008). The waters were fixed by 0.2% of lugol's acid solution (500 ml), 0.3% of bouin solution (500 ml) and 20 % of glutaraldehyde (100ml). http://biows.ac.jp/~plankton/um0809-1a.png proprietary
+UM0809_33_nano Abundance and composition of nano, picoplankton, microzooplankton ALL STAC Catalog 2009-01-12 2009-01-25 38, -70, 75, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214595104-SCIOPS.umm_json Water samples from 5 depths (0-100 m) were collected by Niskin bottles at 9 stations (L1, L3, L5, L9, L12, L37, L33, Ⅰ-10, Ⅱ-7) off Lützow-Holm Bay during Umitaka-maru cruise (Jan-Feb. 2008). The waters were fixed by 0.2% of lugol's acid solution (500 ml), 0.3% of bouin solution (500 ml) and 20 % of glutaraldehyde (100ml). http://biows.ac.jp/~plankton/um0809-1a.png proprietary
UMD_GEOL388_0 Measurements from the Atlantic Ocean made by the University of Maryland (UMD) OB_DAAC STAC Catalog 2003-01-05 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360691-OB_DAAC.umm_json Measurements from the Atlantic Ocean made by the University of Maryland between New England, Bermuda, and Brazil in 2003. proprietary
UNEP_GRID_SF_AFRICA_third version Africa Population Distribution Database and Administrative Units from UNEP/GRID-Sioux Falls ALL STAC Catalog 1960-01-01 1990-12-31 -18, -35, 52, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2232848311-CEOS_EXTRA.umm_json The African administrative boundaries and population database is part of an ongoing effort to improve global, spatially referenced demographic data holdings. Such databases are useful for a variety of applications including strategic-level agricultural research and applications in the analysis of the human dimensions of global change This documentation describes the third version of a database of administrative units with associated population figures for Africa. The first version was compiled for UNEP's Global Desertification Atlas (UNEP 1992, Deichmann and Eklundh 1991), while the second version represented an update and expansion of this first product (Deichmann 1994, WRI 1995). The work discussed in the following paragraphs is also related to NCGIA activities to produce a global database of subnational population estimates (Tobler et al. 1995), and an improved database for the Asian continent (Deichmann 1996a). The new version for Africa provides considerably more detail: more than 4700 administrative units, compared to about 800 in the first and 2200 in the second version. In addition, for each of these units a population estimate was compiled for 1960, 70, 80 and 90 which provides an indication of past population dynamics in Africa. proprietary
UNEP_GRID_SF_AFRICA_third version Africa Population Distribution Database and Administrative Units from UNEP/GRID-Sioux Falls CEOS_EXTRA STAC Catalog 1960-01-01 1990-12-31 -18, -35, 52, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2232848311-CEOS_EXTRA.umm_json The African administrative boundaries and population database is part of an ongoing effort to improve global, spatially referenced demographic data holdings. Such databases are useful for a variety of applications including strategic-level agricultural research and applications in the analysis of the human dimensions of global change This documentation describes the third version of a database of administrative units with associated population figures for Africa. The first version was compiled for UNEP's Global Desertification Atlas (UNEP 1992, Deichmann and Eklundh 1991), while the second version represented an update and expansion of this first product (Deichmann 1994, WRI 1995). The work discussed in the following paragraphs is also related to NCGIA activities to produce a global database of subnational population estimates (Tobler et al. 1995), and an improved database for the Asian continent (Deichmann 1996a). The new version for Africa provides considerably more detail: more than 4700 administrative units, compared to about 800 in the first and 2200 in the second version. In addition, for each of these units a population estimate was compiled for 1960, 70, 80 and 90 which provides an indication of past population dynamics in Africa. proprietary
@@ -15463,8 +15464,8 @@ USAP-0732711 Collaborative Research in IPY: Abrupt Environmental Change in the L
USAP-0732917_1 Collaborative Research in IPY: Abrupt Environmental Change in the Larsen Ice Shelf System, a Multidisciplinary Approach - Marine Ecosystems AMD_USAPDC STAC Catalog 2007-09-15 2015-08-31 -60.5, -65, -55.4, -63.1 https://cmr.earthdata.nasa.gov/search/concepts/C2534800063-AMD_USAPDC.umm_json A profound transformation in ecosystem structure and function is occurring in coastal waters of the western Weddell Sea, with the collapse of the Larsen B ice shelf. This transformation appears to be yielding a redistribution of energy flow between chemoautotrophic and photosynthetic production, and to be causing the rapid demise of the extraordinary seep ecosystem discovered beneath the ice shelf. This event provides an ideal opportunity to examine fundamental aspects of ecosystem transition associated with climate change. We propose to test the following hypotheses to elucidate the transformations occurring in marine ecosystems as a consequence of the Larsen B collapse: (1) The biogeographic isolation and sub-ice shelf setting of the Larsen B seep has led to novel habitat characteristics, chemoautotrophically dependent taxa and functional adaptations. (2) Benthic communities beneath the former Larsen B ice shelf are fundamentally different from assemblages at similar depths in the Weddell sea-ice zone, and resemble oligotrophic deep-sea communities. Larsen B assemblages are undergoing rapid change. (3) The previously dark, oligotrophic waters of the Larsen B embayment now support a thriving phototrophic community, with production rates and phytoplankton composition similar to other productive areas of the Weddell Sea. To document rapid changes occurring in the Larsen B ecosystem, we will use a remotely operated vehicle, shipboard samplers, and moored sediment traps. We will characterize microbial, macrofaunal and megafaunal components of the seep community; evaluate patterns of surface productivity, export flux, and benthic faunal composition in areas previously covered by the ice shelf, and compare these areas to the open sea-ice zone. These changes will be placed within the geological, glaciological and climatological context that led to ice-shelf retreat, through companion research projects funded in concert with this effort. Together these projects will help predict the likely consequences of ice-shelf collapse to marine ecosystems in other regions of Antarctica vulnerable to climate change. The research features international collaborators from Argentina, Belgium, Canada, Germany, Spain and the United Kingdom. The broader impacts include participation of a science writer; broadcast of science segments by members of the Jim Lehrer News Hour (Public Broadcasting System); material for summer courses in environmental change; mentoring of graduate students and postdoctoral fellows; and showcasing scientific activities and findings to students and public through podcasts. proprietary
USAP-0944266 Climate, Ice Dynamics and Biology using a Deep Ice Core from the West Antarctic Ice Sheet Ice Divide (0944266) AMD_USAPDC STAC Catalog 2010-08-01 2015-07-31 -112.1115, -79.481, -112.1115, -79.481 https://cmr.earthdata.nasa.gov/search/concepts/C2532070632-AMD_USAPDC.umm_json This award supports renewal of funding of the WAIS Divide Science Coordination Office (SCO). The Science Coordination Office (SCO) was established to represent the research community and facilitates the project by working with support organizations responsible for logistics, drilling, and core curation. During the last five years, 26 projects have been individually funded to work on this effort and 1,511 m of the total 3,470 m of ice at the site has been collected. This proposal seeks funding to continue the SCO and related field operations needed to complete the WAIS Divide ice core project. Tasks for the SCO during the second five years include planning and oversight of logistics, drilling, and core curation; coordinating research activities in the field; assisting in curation of the core in the field; allocating samples to individual projects; coordinating the sampling effort; collecting, archiving, and distributing data and other information about the project; hosting an annual science meeting; and facilitating collaborative efforts among the research groups. The intellectual merit of the WAIS Divide project is to better predict how human-caused increases in greenhouse gases will alter climate requires an improved understanding of how previous natural changes in greenhouse gases influenced climate in the past. Information on previous climate changes is used to validate the physics and results of climate models that are used to predict future climate. Antarctic ice cores are the only source of samples of the paleo-atmosphere that can be used to determine previous concentrations of carbon dioxide. Ice cores also contain records of other components of the climate system such as the paleo air and ocean temperature, atmospheric loading of aerosols, and indicators of atmospheric transport. The WAIS Divide ice core project has been designed to obtain the best possible record of greenhouse gases during the last glacial cycle (last ~100,000 years). The site was selected because it has the best balance of high annual snowfall (23 cm of ice equivalent/year), low dust Antarctic ice that does not compromise the carbon dioxide record, and favorable glaciology. The main science objectives of the project are to investigate climate forcing by greenhouse gases, initiation of climate changes, stability of the West Antarctic Ice Sheet, and cryobiology in the ice core. The project has numerous broader impacts. An established provider of educational material (Teachers' Domain) will develop and distribute web-based resources related to the project and climate change for use in K-12 classrooms. These resources will consist of video and interactive graphics that explain how and why ice cores are collected, and what they tell us about future climate change. Members of the national media will be included in the field team and the SCO will assist in presenting information to the general public. Video of the project will be collected and made available for general use. Finally, an opportunity will be created for cryosphere students and early career scientists to participate in field activities and core analysis. An ice core archive will be available for future projects and scientific discoveries from the project can be used by policy makers to make informed decisions. proprietary
USAP-0944348 Climate, Ice Dynamics and Biology using a Deep Ice Core from the West Antarctic Ice Sheet Ice Divide AMD_USAPDC STAC Catalog 2010-08-01 2015-07-31 -112.1115, -79.481, -112.1115, -79.481 https://cmr.earthdata.nasa.gov/search/concepts/C2532070599-AMD_USAPDC.umm_json This award supports renewal of funding of the WAIS Divide Science Coordination Office (SCO). The Science Coordination Office (SCO) was established to represent the research community and facilitates the project by working with support organizations responsible for logistics, drilling, and core curation. During the last five years, 26 projects have been individually funded to work on this effort and 1,511 m of the total 3,470 m of ice at the site has been collected. This proposal seeks funding to continue the SCO and related field operations needed to complete the WAIS Divide ice core project. Tasks for the SCO during the second five years include planning and oversight of logistics, drilling, and core curation; coordinating research activities in the field; assisting in curation of the core in the field; allocating samples to individual projects; coordinating the sampling effort; collecting, archiving, and distributing data and other information about the project; hosting an annual science meeting; and facilitating collaborative efforts among the research groups. The intellectual merit of the WAIS Divide project is to better predict how human-caused increases in greenhouse gases will alter climate requires an improved understanding of how previous natural changes in greenhouse gases influenced climate in the past. Information on previous climate changes is used to validate the physics and results of climate models that are used to predict future climate. Antarctic ice cores are the only source of samples of the paleo-atmosphere that can be used to determine previous concentrations of carbon dioxide. Ice cores also contain records of other components of the climate system such as the paleo air and ocean temperature, atmospheric loading of aerosols, and indicators of atmospheric transport. The WAIS Divide ice core project has been designed to obtain the best possible record of greenhouse gases during the last glacial cycle (last ~100,000 years). The site was selected because it has the best balance of high annual snowfall (23 cm of ice equivalent/year), low dust Antarctic ice that does not compromise the carbon dioxide record, and favorable glaciology. The main science objectives of the project are to investigate climate forcing by greenhouse gases, initiation of climate changes, stability of the West Antarctic Ice Sheet, and cryobiology in the ice core. The project has numerous broader impacts. An established provider of educational material (Teachers' Domain) will develop and distribute web-based resources related to the project and climate change for use in K-12 classrooms. These resources will consist of video and interactive graphics that explain how and why ice cores are collected, and what they tell us about future climate change. Members of the national media will be included in the field team and the SCO will assist in presenting information to the general public. Video of the project will be collected and made available for general use. Finally, an opportunity will be created for cryosphere students and early career scientists to participate in field activities and core analysis. An ice core archive will be available for future projects and scientific discoveries from the project can be used by policy makers to make informed decisions. proprietary
-USAP-1043471 A Study of Atmospheric Dust in the WAIS Divide Ice Core Based on Sr-Nd-Pb-He Isotopes ALL STAC Catalog 2011-08-01 2015-07-31 -112.5, -79.5, -112.086, -79.468 https://cmr.earthdata.nasa.gov/search/concepts/C2532071870-AMD_USAPDC.umm_json This award supports a project to obtain the first set of isotopic-based provenance data from the WAIS divide ice core. A lack of data from the WAIS prevents even a basic knowledge of whether different sources of dust blew around the Pacific and Atlantic sectors of the southern latitudes. Precise isotopic measurements on dust in the new WAIS ice divide core are specifically warranted because the data will be synergistically integrated with other high frequency proxies, such as dust concentration and flux, and carbon dioxide, for example. Higher resolution proxies will bridge gaps between our observations on the same well-dated, well-preserved core. The intellectual merit of the project is that the proposed analyses will contribute to the WAIS Divide Project science themes. Whether an active driver or passive recorder, dust is one of the most important but least understood components of regional and global climate. Collaborative and expert discussion with dust-climate modelers will lead to an important progression in understanding of dust and past atmospheric circulation patterns and climate around the southern latitudes, and help to exclude unlikely air trajectories to the ice sheets. The project will provide data to help evaluate models that simulate the dust patterns and cycle and the relative importance of changes in the sources, air trajectories and transport processes, and deposition to the ice sheet under different climate states. The results will be of broad interest to a range of disciplines beyond those directly associated with the WAIS ice core project, including the paleoceanography and dust- paleoclimatology communities. The broader impacts of the project include infrastructure and professional development, as the proposed research will initiate collaborations between LDEO and other WAIS scientists and modelers with expertise in climate and dust. Most of the researchers are still in the early phase of their careers and hence the project will facilitate long-term relationships. This includes a graduate student from UMaine, an undergraduate student from Columbia University who will be involved in lab work, in addition to a LDEO Postdoctoral scientist, and possibly an additional student involved in the international project PIRE-ICETRICS. The proposed research will broaden the scientific outlooks of three PIs, who come to Antarctic ice core science from a variety of other terrestrial and marine geology perspectives. Outreach activities include interaction with the science writers of the Columbia's Earth Institute for news releases and associated blog websites, public speaking, and involvement in an arts/science initiative between New York City's arts and science communities to bridge the gap between scientific knowledge and public perception. proprietary
USAP-1043471 A Study of Atmospheric Dust in the WAIS Divide Ice Core Based on Sr-Nd-Pb-He Isotopes AMD_USAPDC STAC Catalog 2011-08-01 2015-07-31 -112.5, -79.5, -112.086, -79.468 https://cmr.earthdata.nasa.gov/search/concepts/C2532071870-AMD_USAPDC.umm_json This award supports a project to obtain the first set of isotopic-based provenance data from the WAIS divide ice core. A lack of data from the WAIS prevents even a basic knowledge of whether different sources of dust blew around the Pacific and Atlantic sectors of the southern latitudes. Precise isotopic measurements on dust in the new WAIS ice divide core are specifically warranted because the data will be synergistically integrated with other high frequency proxies, such as dust concentration and flux, and carbon dioxide, for example. Higher resolution proxies will bridge gaps between our observations on the same well-dated, well-preserved core. The intellectual merit of the project is that the proposed analyses will contribute to the WAIS Divide Project science themes. Whether an active driver or passive recorder, dust is one of the most important but least understood components of regional and global climate. Collaborative and expert discussion with dust-climate modelers will lead to an important progression in understanding of dust and past atmospheric circulation patterns and climate around the southern latitudes, and help to exclude unlikely air trajectories to the ice sheets. The project will provide data to help evaluate models that simulate the dust patterns and cycle and the relative importance of changes in the sources, air trajectories and transport processes, and deposition to the ice sheet under different climate states. The results will be of broad interest to a range of disciplines beyond those directly associated with the WAIS ice core project, including the paleoceanography and dust- paleoclimatology communities. The broader impacts of the project include infrastructure and professional development, as the proposed research will initiate collaborations between LDEO and other WAIS scientists and modelers with expertise in climate and dust. Most of the researchers are still in the early phase of their careers and hence the project will facilitate long-term relationships. This includes a graduate student from UMaine, an undergraduate student from Columbia University who will be involved in lab work, in addition to a LDEO Postdoctoral scientist, and possibly an additional student involved in the international project PIRE-ICETRICS. The proposed research will broaden the scientific outlooks of three PIs, who come to Antarctic ice core science from a variety of other terrestrial and marine geology perspectives. Outreach activities include interaction with the science writers of the Columbia's Earth Institute for news releases and associated blog websites, public speaking, and involvement in an arts/science initiative between New York City's arts and science communities to bridge the gap between scientific knowledge and public perception. proprietary
+USAP-1043471 A Study of Atmospheric Dust in the WAIS Divide Ice Core Based on Sr-Nd-Pb-He Isotopes ALL STAC Catalog 2011-08-01 2015-07-31 -112.5, -79.5, -112.086, -79.468 https://cmr.earthdata.nasa.gov/search/concepts/C2532071870-AMD_USAPDC.umm_json This award supports a project to obtain the first set of isotopic-based provenance data from the WAIS divide ice core. A lack of data from the WAIS prevents even a basic knowledge of whether different sources of dust blew around the Pacific and Atlantic sectors of the southern latitudes. Precise isotopic measurements on dust in the new WAIS ice divide core are specifically warranted because the data will be synergistically integrated with other high frequency proxies, such as dust concentration and flux, and carbon dioxide, for example. Higher resolution proxies will bridge gaps between our observations on the same well-dated, well-preserved core. The intellectual merit of the project is that the proposed analyses will contribute to the WAIS Divide Project science themes. Whether an active driver or passive recorder, dust is one of the most important but least understood components of regional and global climate. Collaborative and expert discussion with dust-climate modelers will lead to an important progression in understanding of dust and past atmospheric circulation patterns and climate around the southern latitudes, and help to exclude unlikely air trajectories to the ice sheets. The project will provide data to help evaluate models that simulate the dust patterns and cycle and the relative importance of changes in the sources, air trajectories and transport processes, and deposition to the ice sheet under different climate states. The results will be of broad interest to a range of disciplines beyond those directly associated with the WAIS ice core project, including the paleoceanography and dust- paleoclimatology communities. The broader impacts of the project include infrastructure and professional development, as the proposed research will initiate collaborations between LDEO and other WAIS scientists and modelers with expertise in climate and dust. Most of the researchers are still in the early phase of their careers and hence the project will facilitate long-term relationships. This includes a graduate student from UMaine, an undergraduate student from Columbia University who will be involved in lab work, in addition to a LDEO Postdoctoral scientist, and possibly an additional student involved in the international project PIRE-ICETRICS. The proposed research will broaden the scientific outlooks of three PIs, who come to Antarctic ice core science from a variety of other terrestrial and marine geology perspectives. Outreach activities include interaction with the science writers of the Columbia's Earth Institute for news releases and associated blog websites, public speaking, and involvement in an arts/science initiative between New York City's arts and science communities to bridge the gap between scientific knowledge and public perception. proprietary
USAP-1043623_1 Air-Sea Fluxes of Momentum, Heat, and Carbon Dioxide at High Wind Speeds in the Southern Ocean AMD_USAPDC STAC Catalog 2011-06-15 2015-05-31 117.5, -67.4, 146, -47 https://cmr.earthdata.nasa.gov/search/concepts/C2532072248-AMD_USAPDC.umm_json Accurate parameterizations of the air-sea fluxes of CO2 into the Southern Ocean, in particular at high wind velocity, are needed to better assess how projections of global climate warming in a windier world could affect the ocean carbon uptake, and alter the ocean heat budget at high latitudes. Air-sea fluxes of momentum, sensible and latent heat (water vapor) and carbon dioxide (CO2) are to be measured continuously underway on cruises using micrometeorological eddy covariance techniques adapted to ship-board use. The measured gas transfer velocity (K) is then to be related to other parameters known to affect air-sea-fluxes. A stated goal of this work is the collection of a set of direct air-sea flux measurements at high wind speeds, conditions where parameterization of the relationship of gas exchange to wind-speed remains contentious. The studies will be carried out at sites in the Southern Ocean using the USAP RV Nathaniel B Palmer as measurment platform. Co-located pCO2 data, to be used in the overall analysis and enabling internal consistency checks, are being collected from existing underway systems aboard the USAP research vessel under other NSF awards. proprietary
USAP-1043623_1 Air-Sea Fluxes of Momentum, Heat, and Carbon Dioxide at High Wind Speeds in the Southern Ocean ALL STAC Catalog 2011-06-15 2015-05-31 117.5, -67.4, 146, -47 https://cmr.earthdata.nasa.gov/search/concepts/C2532072248-AMD_USAPDC.umm_json Accurate parameterizations of the air-sea fluxes of CO2 into the Southern Ocean, in particular at high wind velocity, are needed to better assess how projections of global climate warming in a windier world could affect the ocean carbon uptake, and alter the ocean heat budget at high latitudes. Air-sea fluxes of momentum, sensible and latent heat (water vapor) and carbon dioxide (CO2) are to be measured continuously underway on cruises using micrometeorological eddy covariance techniques adapted to ship-board use. The measured gas transfer velocity (K) is then to be related to other parameters known to affect air-sea-fluxes. A stated goal of this work is the collection of a set of direct air-sea flux measurements at high wind speeds, conditions where parameterization of the relationship of gas exchange to wind-speed remains contentious. The studies will be carried out at sites in the Southern Ocean using the USAP RV Nathaniel B Palmer as measurment platform. Co-located pCO2 data, to be used in the overall analysis and enabling internal consistency checks, are being collected from existing underway systems aboard the USAP research vessel under other NSF awards. proprietary
USAP-1056396_1 CAREER: Protist Nutritional Strategies in Permanently Stratified Antarctic Lakes AMD_USAPDC STAC Catalog 2011-05-01 2016-04-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532071892-AMD_USAPDC.umm_json This project supported an integrated research and education program in the fields of polar biology and environmental microbiology, focusing on single-celled eukaryotes (protists) in high latitude ice-covered Antarctic lakes systems. Protists play important roles in energy flow and material cycling, and act as both primary producers (fixing inorganic carbon by photosynthesis) and consumers (preying on bacteria by phagotrophic digestion). The McMurdo Dry Valleys (MDV) located in Victoria Land, Antarctica, harbor microbial communities which are isolated in the unique aquatic ecosystem of perennially ice-capped lakes. The project studied: (1) the impact of permanent biogeochemical gradients on protist trophic strategy, (2) the effect of major abiotic drivers (light and nutrients) on the distribution of two key mixotrophic and photoautotrophic protist species, and (3) the effect of episodic nutrient pulses on mixotroph communities in high latitude (ultraoligotrophic) MDV lakes versus low latitude (eutrophic) watersheds. Sampling dates: February 4 – April 10, 2008; November 11- 28, 2012; December 12, 2012 Sampling locations/depths: East Lobe Lake Bonney/5m, 10m, 13m, 15m, 20m, 25m, 30m West Lobe Lake Bonney/5m, 10m, 13m, 15m, 20m, 25m, 30m Lake Fryxell/5m, 7m, 9m, 11m, 12m, 15m Lake Vanda/10m, 20m, 30m, 40m, 50m, 60m, 70m, 75m, 80m Two kinds of metadata from this project are available: 1) DNA sequence data – DNA was extracted from filtered lake water (1-2L) collected from sampling locations and dates reported above. Environmental DNA was PCR-amplified using primers specific for the following genes: 16S rRNA, 18S rRNA, rbcL, cbbM, nifJ, psbA. Genes were sequenced on an Applied Biosystems DNA analyzer or an Illumina MiSeq or HiSeq instruments. All DNA sequences from this project are available via GenBank. 2) Limnological metadata - Limnological data was collected from sampling locations and dates reported above. Data includes PAR, conductivity, temperature, Chlorophyll a, and macronutrients and is available via the McMurdo Dry Valleys LTER Data Center. proprietary
@@ -15485,23 +15486,23 @@ USAP-1443637_1 Analysis of Voltage-gated Ion Channels in Antarctic Fish AMD_USAP
USAP-1444167_1 Antarctic Notothenioid Fishes: Sentinel Taxa for Southern Ocean Warming AMD_USAPDC STAC Catalog 2015-07-01 2020-06-30 -70, -76, -55, -58 https://cmr.earthdata.nasa.gov/search/concepts/C2532072217-AMD_USAPDC.umm_json "Antarctic fish and their early developmental stages are an important component of the food web that sustains life in the cold Southern Ocean (SO) that surrounds Antarctica. They feed on smaller organisms and in turn are eaten by larger animals, including seals and killer whales. Little is known about how rising ocean temperatures will impact the development of Antarctic fish embryos and their growth after hatching. This project will address this gap by assessing the effects of elevated temperatures on embryo viability, on the rate of embryo development, and on the gene ""toolkits"" that respond to temperature stress. One of the two species to be studied does not produce red blood cells, a defect that may make its embryos particularly vulnerable to heat. The outcomes of this research will provide the public and policymakers with ""real world"" data that are necessary to inform decisions and design strategies to cope with changes in the Earth's climate, particularly with respect to protecting life in the SO. The project will also further the NSF goals of training new generations of scientists, including providing scientific training for undergraduate and graduate students, and of making scientific discoveries available to the general public. This includes the unique educational opportunity for undergraduates to participate in research in Antarctica and engaging the public in several ways, including the development of professionally-produced educational videos with bi-lingual closed captioning. Since the onset of cooling of the SO about 40 million years ago, evolution of Antarctic marine organisms has been driven by the development of cold temperatures. Because body temperatures of Antarctic fishes fall in a narrow range determined by their habitat (-1.9 to +2.0 C), they are particularly attractive models for understanding how organismal physiology and biochemistry have been shaped to maintain life in a cooling environment. Yet these fishes are now threatened by rapid warming of the SO. The long-term objective of this project is to understand the capacities of Antarctic fishes to acclimatize and/or adapt to oceanic warming through analysis of their underlying genetic ""toolkits."" This objective will be accomplished through three Specific Aims: 1) assessing the effects of elevated temperatures on gene expression during development of embryos; 2) examining the effects of elevated temperatures on embryonic morphology and on the temporal and spatial patterns of gene expression; and 3) evaluating the evolutionary mechanisms that have led to the loss of the red blood cell genetic program by the white-blooded fishes. Aims 1 and 2 will be investigated by acclimating experimental embryos of both red-blooded and white-blooded fish to elevated temperatures. Differential gene expression will be examined through the use of high throughput RNA sequencing. The temporal and spatial patterns of gene expression in the context of embryonic morphology (Aim 2) will be determined by microscopic analysis of embryos ""stained"" with (hybridized to) differentially expressed gene probes revealed by Aim 1; other key developmental marker genes will also be used. The genetic lesions resulting from loss of red blood cells by the white-blooded fishes (Aim 3) will be examined by comparing genes and genomes in the two fish groups." proprietary
USAP-1542778 Climate History and Flow Processes from Physical Analyses of the SPICECORE South Pole Ice Core AMD_USAPDC STAC Catalog 2016-06-01 2019-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2532071857-AMD_USAPDC.umm_json This award supports a three-year effort to study physical properties of the South Pole ice core to help provide a high-time-resolution history of trace gases and other paleoclimatic indicators from an especially cold site with high preservation potential for important signals. The physical-properties studies include visual inspection to identify any flow disturbances and for identifying annual layers and other features, and combined bubble, grain and ice crystal orientation studies to better understand the processes occurring in the ice that affect the climate record and the ice-sheet behavior. Success of these efforts will provide necessary support for dating and quality control to others studying the ice core, as well as determining the climate history of the site, flow state, and key physical processes in ice. The intellectual merits of the project include better understanding of physical processes, paleoclimatic reconstruction, dating of the ice, and quality assurance. Visual inspection of the core will help identify evidence of flow disturbances that would disrupt the integrity of the climate record and will reveal volcanic horizons and other features of interest. Annual layer counting will be conducted to help estimate accumulation rate over time as recorded in the ice core. Measurements of C-axis fabric, grain size and shapes, and bubble characteristics will provide information about processes occurring in the ice sheet as well as the history of ice flow, current flow state and how the ice is flowing and how easily it will flow in the future. Analysis of this data in conjunction with microCT data will help to reveal grain-scale processes. The broader impacts of the project include support for an early-career, post-doctoral researcher, and improved paleoclimatic data of societal relevance. The results will be incorporated into the active program of education and outreach which have educated many students, members of the public and policy makers through the sharing of information and educational materials about all aspects of ice core science and paleoclimate. proprietary
USAP-1543383_1 Antarctic Fish and MicroRNA Control of Development and Physiology AMD_USAPDC STAC Catalog 2016-09-01 2019-08-31 -66, -66, -58, -62 https://cmr.earthdata.nasa.gov/search/concepts/C2532072220-AMD_USAPDC.umm_json microRNAs (miRNAs) are key post-transcriptional regulators of gene expression that modulate development and physiology in temperate animals. Although miRNAs act by binding to messenger RNAs (mRNAs), a process that is strongly sensitive to temperature, miRNAs have yet not been studied in Antarctic animals, including Notothenioid fish, which dominate the Southern Ocean. This project will compare miRNA regulation in 1) Antarctic vs. temperate fish to learn the roles of miRNA regulation in adaptation to constant cold; and in 2) bottom-dwelling, dense-boned, red-blooded Nototheniods vs. high buoyancy, osteopenic, white-blooded icefish to understand miRNA regulation in specialized organs after the evolution of the loss of hemoglobin genes and red blood cells, the origin of enlarged heart and vasculature, and the evolution of increased buoyancy, which arose by decreased bone mineralization and increased lipid deposition. Aim 1 is to test the hypothesis that Antarctic fish evolved miRNA-related genome specializations in response to constant cold. The project will compare four Antarctic Notothenioid species to two temperate Notothenioids and two temperate laboratory species to test the hypotheses that (a) Antarctic fish evolved miRNA genome repertoires by loss of ancestral genes and/or gain of new genes, (b) express miRNAs that are involved in cold tolerance, and (c) respond to temperature change by changing miRNA gene expression. Aim 2 is to test the hypothesis that the evolution of icefish from red-blooded bottom-dwelling ancestors was accompanied by an altered miRNA genomic repertoire, sequence, and/or expression. The project will test the hypotheses that (a) miRNAs in icefish evolved in sequence and/or in expression in icefish specializations, including head kidney (origin of red blood cells); heart (changes in vascular system), cranium and pectoral girdle (reduced bone mineral density); and skeletal muscle (lipid deposition), and (b) miRNAs that evolved in icefish specializations had ancestral functions related to their derived roles in icefish, as determined by functional tests of zebrafish orthologs of icefish miRNAs in developing zebrafish. The program will isolate, sequence, and determine the expression of miRNAs and mRNAs using high-throughput transcriptomics and novel software. Results will show how the microRNA system evolves in vertebrate animals pushed to physiological extremes and provide insights into the prospects of key species in the most rapidly warming part of the globe. proprietary
-USAP-1543498_1 A Full Lifecycle Approach to Understanding Adélie Penguin Response to Changing Pack Ice Conditions in the Ross Sea AMD_USAPDC STAC Catalog 2016-06-01 165, -78, -150, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532074621-AMD_USAPDC.umm_json "The Ross Sea region of the Southern Ocean is experiencing growing sea ice cover in both extent and duration. These trends contrast those of the well-studied, western Antarctic Peninsula area, where sea ice has been disappearing. Unlike the latter, little is known about how expanding sea ice coverage might affect the regional Antarctic marine ecosystem. This project aims to better understand some of the potential effects of the changing ice conditions on the marine ecosystem using the widely-recognized indicator species - the Adélie Penguin. A four-year effort will build on previous results spanning 19 seasons at Ross Island to explore how successes or failures in each part of the penguin's annual cycle are effected by ice conditions and how these carry over to the next annual recruitment cycle, especially with respect to the penguin's condition upon arrival in the spring. Education and public outreach activities will continually be promoted through the PenguinCam and PenguinScience websites (sites with greater than 1 million hits a month) and ""NestCheck"" (a site that is logged-on by >300 classrooms annually that allows students to follow penguin families in their breeding efforts). To encourage students in pursuing educational and career pathways in the Science Technology Engineering and Math fields, the project will also provide stories from the field in a Penguin Journal, develop classroom-ready activities aligned with New Generation Science Standards, increase the availability of instructional presentations as powerpoint files and short webisodes. The project will provide additional outreach activities through local, state and national speaking engagements about penguins, Antarctic science and climate change. The annual outreach efforts are aimed at reaching over 15,000 students through the website, 300 teachers through presentations and workshops, and 500 persons in the general public. The project also will train four interns (undergraduate and graduate level), two post-doctoral researchers, and a science writer/photographer.
The project will accomplish three major goals, all of which relate to how Adélie Penguins adapt to, or cope with environmental change. Specifically the project seeks to determine 1) how changing winter sea ice conditions in the Ross Sea region affect penguin migration, behavior and survival and alter the carry-over effects (COEs) to subsequent reproduction; 2) the interplay between extrinsic and intrinsic factors influencing COEs over multiple years of an individual's lifetime; and 3) how local environmental change may affect population change via impacts to nesting habitat, interacting with individual quality and COEs. Retrospective analyses will be conducted using 19 years of colony based data and collect additional information on individually marked, known-age and known-history penguins, from new recruits to possibly senescent individuals. Four years of new information will be gained from efforts based at two colonies (Cape Royds and Crozier), using radio frequency identification tags to automatically collect data on breeding and foraging effort of marked, known-history birds to explore penguin response to resource availability within the colony as well as between colonies (mates, nesting material, habitat availability). Additional geolocation/time-depth recorders will be used to investigate travels and foraging during winter of these birds. The combined efforts will allow an assessment of the effects of penguin behavior/success in one season on its behavior in the next (e.g. how does winter behavior affect arrival time and body condition on subsequent breeding). It is at the individual level that penguins are responding successfully, or not, to ongoing marine habitat change in the Ross Sea region." proprietary
USAP-1543498_1 A Full Lifecycle Approach to Understanding Adélie Penguin Response to Changing Pack Ice Conditions in the Ross Sea ALL STAC Catalog 2016-06-01 165, -78, -150, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532074621-AMD_USAPDC.umm_json "The Ross Sea region of the Southern Ocean is experiencing growing sea ice cover in both extent and duration. These trends contrast those of the well-studied, western Antarctic Peninsula area, where sea ice has been disappearing. Unlike the latter, little is known about how expanding sea ice coverage might affect the regional Antarctic marine ecosystem. This project aims to better understand some of the potential effects of the changing ice conditions on the marine ecosystem using the widely-recognized indicator species - the Adélie Penguin. A four-year effort will build on previous results spanning 19 seasons at Ross Island to explore how successes or failures in each part of the penguin's annual cycle are effected by ice conditions and how these carry over to the next annual recruitment cycle, especially with respect to the penguin's condition upon arrival in the spring. Education and public outreach activities will continually be promoted through the PenguinCam and PenguinScience websites (sites with greater than 1 million hits a month) and ""NestCheck"" (a site that is logged-on by >300 classrooms annually that allows students to follow penguin families in their breeding efforts). To encourage students in pursuing educational and career pathways in the Science Technology Engineering and Math fields, the project will also provide stories from the field in a Penguin Journal, develop classroom-ready activities aligned with New Generation Science Standards, increase the availability of instructional presentations as powerpoint files and short webisodes. The project will provide additional outreach activities through local, state and national speaking engagements about penguins, Antarctic science and climate change. The annual outreach efforts are aimed at reaching over 15,000 students through the website, 300 teachers through presentations and workshops, and 500 persons in the general public. The project also will train four interns (undergraduate and graduate level), two post-doctoral researchers, and a science writer/photographer.
The project will accomplish three major goals, all of which relate to how Adélie Penguins adapt to, or cope with environmental change. Specifically the project seeks to determine 1) how changing winter sea ice conditions in the Ross Sea region affect penguin migration, behavior and survival and alter the carry-over effects (COEs) to subsequent reproduction; 2) the interplay between extrinsic and intrinsic factors influencing COEs over multiple years of an individual's lifetime; and 3) how local environmental change may affect population change via impacts to nesting habitat, interacting with individual quality and COEs. Retrospective analyses will be conducted using 19 years of colony based data and collect additional information on individually marked, known-age and known-history penguins, from new recruits to possibly senescent individuals. Four years of new information will be gained from efforts based at two colonies (Cape Royds and Crozier), using radio frequency identification tags to automatically collect data on breeding and foraging effort of marked, known-history birds to explore penguin response to resource availability within the colony as well as between colonies (mates, nesting material, habitat availability). Additional geolocation/time-depth recorders will be used to investigate travels and foraging during winter of these birds. The combined efforts will allow an assessment of the effects of penguin behavior/success in one season on its behavior in the next (e.g. how does winter behavior affect arrival time and body condition on subsequent breeding). It is at the individual level that penguins are responding successfully, or not, to ongoing marine habitat change in the Ross Sea region." proprietary
-USAP-1544526_1 Activity, Preservation and Fossilization of Cryptoendolithic Microorganisms in Antarctica AMD_USAPDC STAC Catalog 2016-09-01 2017-08-31 160, -77.8, 163.7, -76.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532069950-AMD_USAPDC.umm_json Cryptoendoliths are organisms that colonize microscopic cavities of rocks, which give them protection and allow them to inhabit extreme environments, such as the cold, arid desert of the Dry Valleys of Antarctica. Fossilized cryptoendoliths preserve the forms and features of organisms from the past and thus provide a unique opportunity to study the organisms' life histories and environments. To study this fossil record, there needs to be a better understanding of what environmental conditions allow these fossils to form. A climate gradient currently exists in the Dry Valleys that allows us to study living, dead, and fossilized cryptoendoliths from mild to increasingly harsh environments; providing insight to the limits of life and how these fossils are formed. This project will develop instruments to detect the biological activity of the live microorganisms and conduct laboratory experiments to determine the environmental limits of their survival. The project also will characterize the chemical and structural features of the living, dead, and fossilized cryptoendoliths to understand how they become fossilized. Knowing how microorganisms are preserved as fossils in cold and dry environments like Antarctica can help to refine methods that can be used to search for and identify evidence for extraterrestrial life in similar habitats on planets such as Mars. This project includes training of graduate and undergraduate students. Little is known about cryptoendolithic microfossils and their formation processes in cold, arid terrestrial habitats of the Dry Valleys of Antarctica, where a legacy of activity is discernible in the form of biosignatures including inorganic materials and microbial fossils that preserve and indicate traces of past biological activity. The overarching goals of the proposed work are: (1) to determine how rates of microbial respiration and biodegradation of organic matter control microbial fossilization; and (2) to characterize microbial fossils and their living counterparts to elucidate mechanisms for fossilization. Using samples collected across an increasingly harsher (more cold and dry) climatic gradient that encompasses living, dead, and fossilized cryptoendolithic microorganisms, the proposed work will: (1) develop an instrument to be used in the field that can measure small concentrations of CO2 in cryptoendolithic habitats in situ; (2) use microscopy techniques to characterize endolithic microorganisms as well as the chemical and morphological characteristics of biosignatures and microbial fossils. A metagenomic survey of microbial communities in these samples will be used to characterize differences in diversity, identify if specific microorganisms (e.g. prokaryotes, eukaryotes) are more capable of surviving under these harsh climatic conditions, and to corroborate microscopic observations of the viability states of these microorganisms. proprietary
+USAP-1543498_1 A Full Lifecycle Approach to Understanding Adélie Penguin Response to Changing Pack Ice Conditions in the Ross Sea AMD_USAPDC STAC Catalog 2016-06-01 165, -78, -150, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532074621-AMD_USAPDC.umm_json "The Ross Sea region of the Southern Ocean is experiencing growing sea ice cover in both extent and duration. These trends contrast those of the well-studied, western Antarctic Peninsula area, where sea ice has been disappearing. Unlike the latter, little is known about how expanding sea ice coverage might affect the regional Antarctic marine ecosystem. This project aims to better understand some of the potential effects of the changing ice conditions on the marine ecosystem using the widely-recognized indicator species - the Adélie Penguin. A four-year effort will build on previous results spanning 19 seasons at Ross Island to explore how successes or failures in each part of the penguin's annual cycle are effected by ice conditions and how these carry over to the next annual recruitment cycle, especially with respect to the penguin's condition upon arrival in the spring. Education and public outreach activities will continually be promoted through the PenguinCam and PenguinScience websites (sites with greater than 1 million hits a month) and ""NestCheck"" (a site that is logged-on by >300 classrooms annually that allows students to follow penguin families in their breeding efforts). To encourage students in pursuing educational and career pathways in the Science Technology Engineering and Math fields, the project will also provide stories from the field in a Penguin Journal, develop classroom-ready activities aligned with New Generation Science Standards, increase the availability of instructional presentations as powerpoint files and short webisodes. The project will provide additional outreach activities through local, state and national speaking engagements about penguins, Antarctic science and climate change. The annual outreach efforts are aimed at reaching over 15,000 students through the website, 300 teachers through presentations and workshops, and 500 persons in the general public. The project also will train four interns (undergraduate and graduate level), two post-doctoral researchers, and a science writer/photographer.
The project will accomplish three major goals, all of which relate to how Adélie Penguins adapt to, or cope with environmental change. Specifically the project seeks to determine 1) how changing winter sea ice conditions in the Ross Sea region affect penguin migration, behavior and survival and alter the carry-over effects (COEs) to subsequent reproduction; 2) the interplay between extrinsic and intrinsic factors influencing COEs over multiple years of an individual's lifetime; and 3) how local environmental change may affect population change via impacts to nesting habitat, interacting with individual quality and COEs. Retrospective analyses will be conducted using 19 years of colony based data and collect additional information on individually marked, known-age and known-history penguins, from new recruits to possibly senescent individuals. Four years of new information will be gained from efforts based at two colonies (Cape Royds and Crozier), using radio frequency identification tags to automatically collect data on breeding and foraging effort of marked, known-history birds to explore penguin response to resource availability within the colony as well as between colonies (mates, nesting material, habitat availability). Additional geolocation/time-depth recorders will be used to investigate travels and foraging during winter of these birds. The combined efforts will allow an assessment of the effects of penguin behavior/success in one season on its behavior in the next (e.g. how does winter behavior affect arrival time and body condition on subsequent breeding). It is at the individual level that penguins are responding successfully, or not, to ongoing marine habitat change in the Ross Sea region." proprietary
USAP-1544526_1 Activity, Preservation and Fossilization of Cryptoendolithic Microorganisms in Antarctica ALL STAC Catalog 2016-09-01 2017-08-31 160, -77.8, 163.7, -76.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532069950-AMD_USAPDC.umm_json Cryptoendoliths are organisms that colonize microscopic cavities of rocks, which give them protection and allow them to inhabit extreme environments, such as the cold, arid desert of the Dry Valleys of Antarctica. Fossilized cryptoendoliths preserve the forms and features of organisms from the past and thus provide a unique opportunity to study the organisms' life histories and environments. To study this fossil record, there needs to be a better understanding of what environmental conditions allow these fossils to form. A climate gradient currently exists in the Dry Valleys that allows us to study living, dead, and fossilized cryptoendoliths from mild to increasingly harsh environments; providing insight to the limits of life and how these fossils are formed. This project will develop instruments to detect the biological activity of the live microorganisms and conduct laboratory experiments to determine the environmental limits of their survival. The project also will characterize the chemical and structural features of the living, dead, and fossilized cryptoendoliths to understand how they become fossilized. Knowing how microorganisms are preserved as fossils in cold and dry environments like Antarctica can help to refine methods that can be used to search for and identify evidence for extraterrestrial life in similar habitats on planets such as Mars. This project includes training of graduate and undergraduate students. Little is known about cryptoendolithic microfossils and their formation processes in cold, arid terrestrial habitats of the Dry Valleys of Antarctica, where a legacy of activity is discernible in the form of biosignatures including inorganic materials and microbial fossils that preserve and indicate traces of past biological activity. The overarching goals of the proposed work are: (1) to determine how rates of microbial respiration and biodegradation of organic matter control microbial fossilization; and (2) to characterize microbial fossils and their living counterparts to elucidate mechanisms for fossilization. Using samples collected across an increasingly harsher (more cold and dry) climatic gradient that encompasses living, dead, and fossilized cryptoendolithic microorganisms, the proposed work will: (1) develop an instrument to be used in the field that can measure small concentrations of CO2 in cryptoendolithic habitats in situ; (2) use microscopy techniques to characterize endolithic microorganisms as well as the chemical and morphological characteristics of biosignatures and microbial fossils. A metagenomic survey of microbial communities in these samples will be used to characterize differences in diversity, identify if specific microorganisms (e.g. prokaryotes, eukaryotes) are more capable of surviving under these harsh climatic conditions, and to corroborate microscopic observations of the viability states of these microorganisms. proprietary
+USAP-1544526_1 Activity, Preservation and Fossilization of Cryptoendolithic Microorganisms in Antarctica AMD_USAPDC STAC Catalog 2016-09-01 2017-08-31 160, -77.8, 163.7, -76.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532069950-AMD_USAPDC.umm_json Cryptoendoliths are organisms that colonize microscopic cavities of rocks, which give them protection and allow them to inhabit extreme environments, such as the cold, arid desert of the Dry Valleys of Antarctica. Fossilized cryptoendoliths preserve the forms and features of organisms from the past and thus provide a unique opportunity to study the organisms' life histories and environments. To study this fossil record, there needs to be a better understanding of what environmental conditions allow these fossils to form. A climate gradient currently exists in the Dry Valleys that allows us to study living, dead, and fossilized cryptoendoliths from mild to increasingly harsh environments; providing insight to the limits of life and how these fossils are formed. This project will develop instruments to detect the biological activity of the live microorganisms and conduct laboratory experiments to determine the environmental limits of their survival. The project also will characterize the chemical and structural features of the living, dead, and fossilized cryptoendoliths to understand how they become fossilized. Knowing how microorganisms are preserved as fossils in cold and dry environments like Antarctica can help to refine methods that can be used to search for and identify evidence for extraterrestrial life in similar habitats on planets such as Mars. This project includes training of graduate and undergraduate students. Little is known about cryptoendolithic microfossils and their formation processes in cold, arid terrestrial habitats of the Dry Valleys of Antarctica, where a legacy of activity is discernible in the form of biosignatures including inorganic materials and microbial fossils that preserve and indicate traces of past biological activity. The overarching goals of the proposed work are: (1) to determine how rates of microbial respiration and biodegradation of organic matter control microbial fossilization; and (2) to characterize microbial fossils and their living counterparts to elucidate mechanisms for fossilization. Using samples collected across an increasingly harsher (more cold and dry) climatic gradient that encompasses living, dead, and fossilized cryptoendolithic microorganisms, the proposed work will: (1) develop an instrument to be used in the field that can measure small concentrations of CO2 in cryptoendolithic habitats in situ; (2) use microscopy techniques to characterize endolithic microorganisms as well as the chemical and morphological characteristics of biosignatures and microbial fossils. A metagenomic survey of microbial communities in these samples will be used to characterize differences in diversity, identify if specific microorganisms (e.g. prokaryotes, eukaryotes) are more capable of surviving under these harsh climatic conditions, and to corroborate microscopic observations of the viability states of these microorganisms. proprietary
USAP-1643534_1 Biological and Physical Drivers of Oxygen Saturation and Net Community Production Variability along the Western Antarctic Peninsula AMD_USAPDC STAC Catalog 2016-06-15 2023-07-15 -83, -73, -56, -62 https://cmr.earthdata.nasa.gov/search/concepts/C2532075509-AMD_USAPDC.umm_json "This project seeks to make detailed measurements of the oxygen content of the surface ocean along the Western Antarctic Peninsula. Detailed maps of changes in net oxygen content will be combined with measurements of the surface water chemistry and phytoplankton distributions. The project will determine the extent to which on-shore or offshore phytoplankton blooms along the peninsula are likely to lead to different amounts of carbon being exported to the deeper ocean. The project will analyze oxygen in relation to argon that will allow determination of the physical and biological contributions to surface ocean oxygen dynamics. These assessments will be combined with spatial and temporal distributions of nutrients (iron and macronutrients) and irradiances. This will allow the investigators to unravel the complex interplay between ice dynamics, iron and physical mixing dynamics as they relate to Net Community Production (NCP) in the region. NCP measurements will be normalized to Particulate Organic Carbon (POC) and be used to help identify area of ""High Biomass and Low NCP"" and those with ""Low Biomass and High NCP"" as a function of microbial plankton community composition. The team will use machine learning methods- including decision tree assemblages and genetic programming- to identify plankton groups key to facilitating biological carbon fluxes. Decomposing the oxygen signal along the West Antarctic Peninsula will also help elucidate biotic and abiotic drivers of the O2 saturation to further contextualize the growing inventory of oxygen measurements (e.g. by Argo floats) throughout the global oceans." proprietary
-USAP-1643722_1 A High Resolution Atmospheric Methane Record from the South Pole Ice Core ALL STAC Catalog 2017-02-01 2019-01-31 180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2534799946-AMD_USAPDC.umm_json This award supports a project to measure the concentration of the gas methane in air trapped in an ice core collected from the South Pole. The data will provide an age scale (age as a function of depth) by matching the South Pole methane changes with similar data from other ice cores for which the age vs. depth relationship is well known. The ages provided will allow all other gas measurements made on the South Pole core (by the PI and other NSF supported investigators) to be interpreted accurately as a function of time. This is critical because a major goal of the South Pole coring project is to understand the history of rare gases in the atmosphere like carbon monoxide, carbon dioxide, ethane, propane, methyl chloride, and methyl bromide. Relatively little is known about what controls these gases in the atmosphere despite their importance to atmospheric chemistry and climate. Undergraduate assistants will work on the project and be introduced to independent research through their work. The PI will continue visits to local middle schools to introduce students to polar science, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) as part of the project. Methane concentrations from a major portion (2 depth intervals, excluding the brittle ice-zone which is being measured at Penn State University) of the new South Pole ice core will be used to create a gas chronology by matching the new South Pole ice core record with that from the well-dated WAIS Divide ice core record. In combination with measurements made at Penn State, this will provide gas dating for the entire 50,000-year record. Correlation will be made using a simple but powerful mid-point method that has been previously demonstrated, and other methods of matching records will be explored. The intellectual merit of this work is that the gas chronology will be a fundamental component of this ice core project, and will be used by the PI and other investigators for dating records of atmospheric composition, and determining the gas age-ice age difference independently of glaciological models, which will constrain processes that affected firn densification in the past. The methane data will also provide direct stratigraphic markers of important perturbations to global biogeochemical cycles (e.g., rapid methane variations synchronous with abrupt warming and cooling in the Northern Hemisphere) that will tie other ice core gas records directly to those perturbations. A record of the total air content will also be produced as a by-product of the methane measurements and will contribute to understanding of this parameter. The broader impacts include that the work will provide a fundamental data set for the South Pole ice core project and the age scale (or variants of it) will be used by all other investigators working on gas records from the core. The project will employ an undergraduate assistant(s) in both years who will conduct an undergraduate research project which will be part of the student's senior thesis or other research paper. The project will also offer at least one research position for the Oregon State University Summer REU site program. Visits to local middle schools, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) will also be part of the project. proprietary
USAP-1643722_1 A High Resolution Atmospheric Methane Record from the South Pole Ice Core AMD_USAPDC STAC Catalog 2017-02-01 2019-01-31 180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2534799946-AMD_USAPDC.umm_json This award supports a project to measure the concentration of the gas methane in air trapped in an ice core collected from the South Pole. The data will provide an age scale (age as a function of depth) by matching the South Pole methane changes with similar data from other ice cores for which the age vs. depth relationship is well known. The ages provided will allow all other gas measurements made on the South Pole core (by the PI and other NSF supported investigators) to be interpreted accurately as a function of time. This is critical because a major goal of the South Pole coring project is to understand the history of rare gases in the atmosphere like carbon monoxide, carbon dioxide, ethane, propane, methyl chloride, and methyl bromide. Relatively little is known about what controls these gases in the atmosphere despite their importance to atmospheric chemistry and climate. Undergraduate assistants will work on the project and be introduced to independent research through their work. The PI will continue visits to local middle schools to introduce students to polar science, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) as part of the project. Methane concentrations from a major portion (2 depth intervals, excluding the brittle ice-zone which is being measured at Penn State University) of the new South Pole ice core will be used to create a gas chronology by matching the new South Pole ice core record with that from the well-dated WAIS Divide ice core record. In combination with measurements made at Penn State, this will provide gas dating for the entire 50,000-year record. Correlation will be made using a simple but powerful mid-point method that has been previously demonstrated, and other methods of matching records will be explored. The intellectual merit of this work is that the gas chronology will be a fundamental component of this ice core project, and will be used by the PI and other investigators for dating records of atmospheric composition, and determining the gas age-ice age difference independently of glaciological models, which will constrain processes that affected firn densification in the past. The methane data will also provide direct stratigraphic markers of important perturbations to global biogeochemical cycles (e.g., rapid methane variations synchronous with abrupt warming and cooling in the Northern Hemisphere) that will tie other ice core gas records directly to those perturbations. A record of the total air content will also be produced as a by-product of the methane measurements and will contribute to understanding of this parameter. The broader impacts include that the work will provide a fundamental data set for the South Pole ice core project and the age scale (or variants of it) will be used by all other investigators working on gas records from the core. The project will employ an undergraduate assistant(s) in both years who will conduct an undergraduate research project which will be part of the student's senior thesis or other research paper. The project will also offer at least one research position for the Oregon State University Summer REU site program. Visits to local middle schools, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) will also be part of the project. proprietary
+USAP-1643722_1 A High Resolution Atmospheric Methane Record from the South Pole Ice Core ALL STAC Catalog 2017-02-01 2019-01-31 180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2534799946-AMD_USAPDC.umm_json This award supports a project to measure the concentration of the gas methane in air trapped in an ice core collected from the South Pole. The data will provide an age scale (age as a function of depth) by matching the South Pole methane changes with similar data from other ice cores for which the age vs. depth relationship is well known. The ages provided will allow all other gas measurements made on the South Pole core (by the PI and other NSF supported investigators) to be interpreted accurately as a function of time. This is critical because a major goal of the South Pole coring project is to understand the history of rare gases in the atmosphere like carbon monoxide, carbon dioxide, ethane, propane, methyl chloride, and methyl bromide. Relatively little is known about what controls these gases in the atmosphere despite their importance to atmospheric chemistry and climate. Undergraduate assistants will work on the project and be introduced to independent research through their work. The PI will continue visits to local middle schools to introduce students to polar science, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) as part of the project. Methane concentrations from a major portion (2 depth intervals, excluding the brittle ice-zone which is being measured at Penn State University) of the new South Pole ice core will be used to create a gas chronology by matching the new South Pole ice core record with that from the well-dated WAIS Divide ice core record. In combination with measurements made at Penn State, this will provide gas dating for the entire 50,000-year record. Correlation will be made using a simple but powerful mid-point method that has been previously demonstrated, and other methods of matching records will be explored. The intellectual merit of this work is that the gas chronology will be a fundamental component of this ice core project, and will be used by the PI and other investigators for dating records of atmospheric composition, and determining the gas age-ice age difference independently of glaciological models, which will constrain processes that affected firn densification in the past. The methane data will also provide direct stratigraphic markers of important perturbations to global biogeochemical cycles (e.g., rapid methane variations synchronous with abrupt warming and cooling in the Northern Hemisphere) that will tie other ice core gas records directly to those perturbations. A record of the total air content will also be produced as a by-product of the methane measurements and will contribute to understanding of this parameter. The broader impacts include that the work will provide a fundamental data set for the South Pole ice core project and the age scale (or variants of it) will be used by all other investigators working on gas records from the core. The project will employ an undergraduate assistant(s) in both years who will conduct an undergraduate research project which will be part of the student's senior thesis or other research paper. The project will also offer at least one research position for the Oregon State University Summer REU site program. Visits to local middle schools, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) will also be part of the project. proprietary
USAP-1643864_1 Collaborative Research: Borehole Logging to Classify Volcanic Signatures in Antarctic Ice AMD_USAPDC STAC Catalog 2017-05-08 -112.085, -79.467, -112.085, -79.467 https://cmr.earthdata.nasa.gov/search/concepts/C2532074603-AMD_USAPDC.umm_json This dataset comprises new photographs and measurements of a WAIS Divide vertical thin section, WDC-06A 420 VTS, previously prepared and measured by J. Fitzpatrick, D. E. Voigt, and R. Alley (dataset DOI: 10.7265/N5W093VM; http://www.usap-dc.org/view/dataset/609605) as part of a larger study of the WAIS Divide ice core (Fitzpatrick, J. et al, 2014, Physical properties of the WAIS Divide ice core, Journal of Glaciology, 60, 224, 1181-1198. (doi:10.3189/2014JoG14J100). These images were taken as a design test of our new automated lightweight c-axis analyzer, dubbed ALPACA, which implements the ice fabric analysis functionality of the Wilen system used by Fitzpatrick et al. in an easily-portable, field-deployable form factor. proprietary
USAP-1644004_1 Collaborative Research: Foraging Ecology and Physiology of the Leopard Seal AMD_USAPDC STAC Catalog 2017-10-01 2022-09-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2560369942-AMD_USAPDC.umm_json This research project is a multidisciplinary effort that brings together a diverse team of scientists from multiple institutions together to understand the foraging behavior and physiology of leopard seals and their role in the Southern Ocean food web. The project will examine the physiology and behavior of leopard seals to in an effort to determine their ability to respond to potential changes in their habitat and foraging areas. Using satellite tracking devices the team will examine the movement and diving behavior of leopard seals and couple this information with measurements of their physiological capacity. The project will determine whether leopard seals- who feed on diverse range of prey- are built differently than their deep diving relatives the Weddell and elephant seal who feed on fish and squid. The team will also determine whether leopard seals are operating at or near their physiological capability to determine how much, if any, ?reserve capacity? they might have to forage and live in changing environments. A better understanding of their home ranges, movement patterns, and general behavior will also be informative to help in managing human-leopard seal interactions. The highly visual nature of the data and analysis for this project lends itself to public and educational display and outreach, particularly as they relate to the changing Antarctic habitats. The project will use the research results to educate the public on the unique physiological and ecological adaptations to extreme environments seen in diving marine mammals, including adaptations to exercise under low oxygen conditions and energy utilization, which affect and dictate the lifestyle of these exceptional organisms. The results of the project will also contribute to the broader understanding that may enhance the aims of managing marine living resources. The leopard seal is an apex predator in the Antarctic ecosystem. This project seeks to better understand the ability of the leopard seal to cope with a changing environment. The project will first examine the foraging behavior and habitat utilization of leopard seals using satellite telemetry. Specifically, satellite telemetry tags will be used to obtain dive profiles and movement data for individuals across multiple years. Diet and trophic level positions across multiple temporal scales will then be determined from physiological samples (e.g., blood, vibrissae, blubber fatty acids, stable isotopes, fecal matter). Oceanographic data will be integrated with these measures to develop habitat models that will be used to assess habitat type, habitat utilization, habitat preference, and home range areas for individual animals. Diet composition for individual seals will be evaluated to determine whether specific animals are generalists or specialists. Second, the team will investigate the physiological adaptations that allow leopard seals to be apex predators and determine to what extent leopard seals are working at or near their physiological limit. Diving behavior and physiology of leopard seals will be evaluated (for instance the aerobic dive limit for individual animals and skeletal muscle adaptations will be determined for diving under hypoxic conditions). Data from time-depth recorders will be used to determine foraging strategies for individual seals, and these diving characteristics will be related to physiological variables (e.g., blood volume, muscle oxygen stores) to better understand the link between foraging behavior and physiology. The team will compare myoglobin storage in swimming muscles associated with both forelimb and hind limb propulsion and the use of anaerobic versus aerobic metabolic systems while foraging. proprietary
USAP-1644073_1 Collaborative Research: Cobalamin and Iron Co-Limitation Of Phytoplankton Species in Terra Nova Bay AMD_USAPDC STAC Catalog 2017-08-18 2020-08-31 -116, -79, 160, -72 https://cmr.earthdata.nasa.gov/search/concepts/C2532074465-AMD_USAPDC.umm_json Phytoplankton blooms in the coastal waters of the Ross Sea, Antarctica are typically dominated by either diatoms or Phaeocystis Antarctica (a flagellated algae that often can form large colonies in a gelatinous matrix). The project seeks to determine if an association of bacterial populations with Phaeocystis antarctica colonies can directly supply Phaeocystis with Vitamin B12, which can be an important co-limiting micronutrient in the Ross Sea. The supply of an essential vitamin coupled with the ability to grow at lower iron concentrations may put Phaeocystis at a competitive advantage over diatoms. Because Phaeocystis cells can fix more carbon than diatoms and Phaeocystis are not grazed as efficiently as diatoms, the project will help in refining understanding of carbon dynamics in the region as well as the basis of the food web webs. Such understanding also has the potential to help refine predictive ecological models for the region. The project will conduct public outreach activities and will contribute to undergraduate and graduate research. Engagement of underrepresented students will occur during summer student internships. A collaboration with Italian Antarctic researchers, who have been studying the Terra Nova Bay ecosystem since the 1980s, aims to enhance the project and promote international scientific collaborations. The study will test whether a mutualistic symbioses between attached bacteria and Phaeocystis provides colonial cells a mechanism for alleviating chronic Vitamin B12 co-limitation effects thereby conferring them with a competitive advantage over diatom communities. The use of drifters in a time series study will provide the opportunity to track in both space and time a developing algal bloom in Terra Nova Bay and to determine community structure and the physiological nutrient status of microbial populations. A combination of flow cytometry, proteomics, metatranscriptomics, radioisotopic and stable isotopic labeling experiments will determine carbon and nutrient uptake rates and the role of bacteria in mitigating potential vitamin B12 and iron limitation. Membrane inlet and proton transfer reaction mass spectrometry will also be used to estimate net community production and release of volatile organic carbon compounds that are climatically active. Understanding how environmental parameters can influence microbial community dynamics in Antarctic coastal waters will advance an understanding of how changes in ocean stratification and chemistry could impact the biogeochemistry and food web dynamics of Southern Ocean ecosystems. proprietary
USAP-1644197_1 Collaborative Research: New Constraints on Post-Glacial Rebound and Holocene Environmental History along the Northern Antarctic Peninsula from Raised Beaches AMD_USAPDC STAC Catalog 2017-08-08 2021-08-31 -65, -65, -55, -61 https://cmr.earthdata.nasa.gov/search/concepts/C2605088269-AMD_USAPDC.umm_json Glacier ice loss from Antarctica has the potential to lead to a significant rise in global sea level. One line of evidence for accelerated glacier ice loss has been an increase in the rate at which the land has been rising across the Antarctic Peninsula as measured by GPS receivers. However, GPS observations of uplift are limited to the last two decades. One goal of this study is to determine how these newly observed rates of uplift compare to average rates of uplift across the Antarctic Peninsula over a longer time interval. Researchers reconstructed past sea levels using the age and elevation of ancient beaches now stranded above sea level on the low-lying coastal hills of the Antarctica Peninsula and determined the rate of uplift over the last 5,000 years. The researchers analyzed the structure of the beaches using ground-penetrating radar and the characteristics of beach sediments to understand how sea-level rise and past climate changes are recorded in beach deposits. We found that unlike most views of how sea level changed across Antarctica over the last 5,000 years, its history is complex with periods of increasing rates of sea-level fall as well as short periods of potential sea-level rise. We attribute these oscillations in the nature of sea-level change across the Antarctic Peninsula to changes in the ice sheet over the last 5,000 years. These changes in sea level also suggest our understanding of the Earth structure beneath the Antarctic Peninsula need to be revised. The beach deposits themselves also record periods of climate change as reflected in the size and shape of their cobbles. This project has lead to the training of five graduate students, three undergraduate students, and outreach talks to k-12 schools in three communities. proprietary
-USAP-1644234_1 A Test of Global and Antarctic Models for Cosmogenic-nuclide Production Rates using High-precision Dating of 40Ar/39Ar Lava Flows from Mount Erebus AMD_USAPDC STAC Catalog 2017-07-15 2022-06-30 166.17, -77.7, 167.75, -77.3 https://cmr.earthdata.nasa.gov/search/concepts/C2586847142-AMD_USAPDC.umm_json Nontechnical Description: The age of rocks and soils at the surface of the Earth can help answer multiple questions that are important for human welfare, including: when did volcanoes erupt and are they likely to erupt again? when did glaciers advance and what do they tell us about climate? what is the frequency of hazards such as landslides, floods, and debris flows? how long does it take soils to form and is erosion of soils going to make farming unsustainable? One method that is used thousands of times every year to address these questions is called 'cosmogenic surface-exposure dating'. This method takes advantage of cosmic rays, which are powerful protons and neutrons produced by supernova that constantly bombard the Earth's atmosphere. Some cosmic rays reach Earth's surface and produce nuclear reactions that result in rare isotopes. Measuring the quantity of the rare isotopes enables the length of time that the rock or soil has been exposed to the atmosphere to be calculated. The distribution of cosmic rays around the globe depends on Earth's magnetic field, and this distribution must be accurately known if useful exposure ages are to be obtained. Currently there are two remaining theories, narrowed down from many, of how to calculate this distribution. Measurements from a site that is at both high altitude and high latitude (close to the poles) are needed to test the two theories. This study involves both field and lab research and includes a Ph.D. student and an undergraduate student. The research team will collect rocks from lava flows on an active volcano in Antarctica named Mount Erebus and measure the amounts of two rare isotopes: 36Cl and 3He. The age of eruption of the samples will be determined using a highly accurate method that does not depend on cosmic rays, called 40Ar/39Ar dating. The two cosmic-ray theories will be used to calculate the ages of the samples using the 36Cl and 3He concentrations and will then be compared to the ages calculated from the 40Ar/39Ar dating. The accurate cosmic-ray theory will be the one that gives the same ages as the 40Ar/39Ar dating. Identification of the accurate theory will enable use of the cosmogenic surface dating methods anywhere on earth. Technical Description: Nuclides produced by cosmic rays in rocks at the surface of the earth are widely used for Quaternary geochronology and geomorphic studies and their use is increasing every year. The recently completed CRONUS-Earth Project (Cosmic-Ray Produced Nuclides on Earth) has systematically evaluated the production rates and theoretical underpinnings of cosmogenic nuclides. However, the CRONUS-Earth Project was not able to discriminate between the two leading theoretical approaches: the original Lal model (St) and the new Lifton-Sato-Dunai model (LSD). Mathematical models used to scale the production of the nuclides as a function of location on the earth, elevation, and magnetic field configuration are an essential component of this dating method. The inability to distinguish between the two models was because the predicted production rates did not differ sufficiently at the location of the calibration sites. The cosmogenic-nuclide production rates that are predicted by the two models differ significantly from each other at Erebus volcano, Antarctica. Mount Erebus is therefore an excellent site for testing which production model best describes actual cosmogenic-nuclide production variations over the globe. The research team recently measured 3He and 36Cl in mineral separates extracted from Erebus lava flows. The exposure ages for each nuclide were reproducible within each flow (~2% standard deviation) and in very good agreement between the 3He and the 36Cl ages. However, the ages calculated by the St and LSD scaling methods differ by ~15-25% due to the sensitivity of the production rate to the scaling at this latitude and elevation. These results lend confidence that Erebus qualifies as a suitable high- latitude/high-elevation calibration site. The remaining component that is still lacking is accurate and reliable independent (i.e., non-cosmogenic) ages, however, published 40Ar/39Ar ages are too imprecise and typically biased to older ages due to excess argon contained in melt inclusions. The research team's new 40Ar/39Ar data show that previous problems with Erebus anorthoclase geochronology are now overcome with modern mass spectrometry and better sample preparation. This indicates a high likelihood of success for this proposal in defining an accurate global scaling model. Although encouraging, much remains to be accomplished. This project will sample lava flows over 3 km in elevation and determine their 40Ar/39Ar and exposure ages. These combined data will discriminate between the two scaling methods, resulting in a preferred scaling model for global cosmogenic geochronology. The LSD method contains two sub-methods, the 'plain' LSD scales all nuclides the same, whereas LSDn scales each nuclide individually. The project can discriminate between these models using 3He and 36Cl data from lava flows at different elevations, because the first model predicts that the production ratio for these two nuclides will be invariant with elevation and the second that there should be ~10% difference over the range of elevations to be sampled. Finally, the project will provide a local, finite-age calibration site for cosmogenic-nuclide investigations in Antarctica. proprietary
USAP-1644234_1 A Test of Global and Antarctic Models for Cosmogenic-nuclide Production Rates using High-precision Dating of 40Ar/39Ar Lava Flows from Mount Erebus ALL STAC Catalog 2017-07-15 2022-06-30 166.17, -77.7, 167.75, -77.3 https://cmr.earthdata.nasa.gov/search/concepts/C2586847142-AMD_USAPDC.umm_json Nontechnical Description: The age of rocks and soils at the surface of the Earth can help answer multiple questions that are important for human welfare, including: when did volcanoes erupt and are they likely to erupt again? when did glaciers advance and what do they tell us about climate? what is the frequency of hazards such as landslides, floods, and debris flows? how long does it take soils to form and is erosion of soils going to make farming unsustainable? One method that is used thousands of times every year to address these questions is called 'cosmogenic surface-exposure dating'. This method takes advantage of cosmic rays, which are powerful protons and neutrons produced by supernova that constantly bombard the Earth's atmosphere. Some cosmic rays reach Earth's surface and produce nuclear reactions that result in rare isotopes. Measuring the quantity of the rare isotopes enables the length of time that the rock or soil has been exposed to the atmosphere to be calculated. The distribution of cosmic rays around the globe depends on Earth's magnetic field, and this distribution must be accurately known if useful exposure ages are to be obtained. Currently there are two remaining theories, narrowed down from many, of how to calculate this distribution. Measurements from a site that is at both high altitude and high latitude (close to the poles) are needed to test the two theories. This study involves both field and lab research and includes a Ph.D. student and an undergraduate student. The research team will collect rocks from lava flows on an active volcano in Antarctica named Mount Erebus and measure the amounts of two rare isotopes: 36Cl and 3He. The age of eruption of the samples will be determined using a highly accurate method that does not depend on cosmic rays, called 40Ar/39Ar dating. The two cosmic-ray theories will be used to calculate the ages of the samples using the 36Cl and 3He concentrations and will then be compared to the ages calculated from the 40Ar/39Ar dating. The accurate cosmic-ray theory will be the one that gives the same ages as the 40Ar/39Ar dating. Identification of the accurate theory will enable use of the cosmogenic surface dating methods anywhere on earth. Technical Description: Nuclides produced by cosmic rays in rocks at the surface of the earth are widely used for Quaternary geochronology and geomorphic studies and their use is increasing every year. The recently completed CRONUS-Earth Project (Cosmic-Ray Produced Nuclides on Earth) has systematically evaluated the production rates and theoretical underpinnings of cosmogenic nuclides. However, the CRONUS-Earth Project was not able to discriminate between the two leading theoretical approaches: the original Lal model (St) and the new Lifton-Sato-Dunai model (LSD). Mathematical models used to scale the production of the nuclides as a function of location on the earth, elevation, and magnetic field configuration are an essential component of this dating method. The inability to distinguish between the two models was because the predicted production rates did not differ sufficiently at the location of the calibration sites. The cosmogenic-nuclide production rates that are predicted by the two models differ significantly from each other at Erebus volcano, Antarctica. Mount Erebus is therefore an excellent site for testing which production model best describes actual cosmogenic-nuclide production variations over the globe. The research team recently measured 3He and 36Cl in mineral separates extracted from Erebus lava flows. The exposure ages for each nuclide were reproducible within each flow (~2% standard deviation) and in very good agreement between the 3He and the 36Cl ages. However, the ages calculated by the St and LSD scaling methods differ by ~15-25% due to the sensitivity of the production rate to the scaling at this latitude and elevation. These results lend confidence that Erebus qualifies as a suitable high- latitude/high-elevation calibration site. The remaining component that is still lacking is accurate and reliable independent (i.e., non-cosmogenic) ages, however, published 40Ar/39Ar ages are too imprecise and typically biased to older ages due to excess argon contained in melt inclusions. The research team's new 40Ar/39Ar data show that previous problems with Erebus anorthoclase geochronology are now overcome with modern mass spectrometry and better sample preparation. This indicates a high likelihood of success for this proposal in defining an accurate global scaling model. Although encouraging, much remains to be accomplished. This project will sample lava flows over 3 km in elevation and determine their 40Ar/39Ar and exposure ages. These combined data will discriminate between the two scaling methods, resulting in a preferred scaling model for global cosmogenic geochronology. The LSD method contains two sub-methods, the 'plain' LSD scales all nuclides the same, whereas LSDn scales each nuclide individually. The project can discriminate between these models using 3He and 36Cl data from lava flows at different elevations, because the first model predicts that the production ratio for these two nuclides will be invariant with elevation and the second that there should be ~10% difference over the range of elevations to be sampled. Finally, the project will provide a local, finite-age calibration site for cosmogenic-nuclide investigations in Antarctica. proprietary
-USAP-1656344_1 A Preliminary Assessment of the Influence of Ice Cover on Microbial Carbon and Energy Acquisition during the Antarctic Winter-spring Seasonal Transition AMD_USAPDC STAC Catalog 2016-08-01 2018-07-31 -64.1, -65, -63.9, -64.75 https://cmr.earthdata.nasa.gov/search/concepts/C2532071951-AMD_USAPDC.umm_json "This EAGER project will compare gene expression patterns in the planktonic communities under ice covers that form in coastal embayment's in the Antarctic Peninsula. Previous efforts taking advantage of unique ice conditions in November and December of 2015 allowed researchers to conduct an experiment to examine the role of sea ice cover on microbial carbon and energy transfer during the winter-spring transition. The EAGER effort will enable the researchers to conduct the ""omics"" analyses of the phytoplankton to determine predominant means by which energy is acquired and used in these settings. This EAGER effort will apply new expertise to fill an existing gap in ecological observations along the West Antarctic Peninsula. The principle product of the proposed work will be a novel dataset to be analyzed and by an early career researcher from an underserved community (veteran). The critical baseline data contained in this dataset enable a comparison of eukaryotic and prokaryotic gene expression patterns to establish the relative importance of chemoautotrophy, heterotrophy, mixotrophy, and phototrophy during the experiments. this information and data will be made immediately available to the broader scientific community, and will enable the development of further hypotheses on ecosystem change as sea ice cover changes in the region. Very little gene expression data is currently available for the Antarctic marine environment, and no gene expression data is available during the ecologically critical winter to spring transition. Moreover, ice cover in bays is common along the West Antarctic Peninsula yet the opportunity to study cryptophyte phytoplankton physiology beneath such ice conditions in coastal embayments is rare." proprietary
+USAP-1644234_1 A Test of Global and Antarctic Models for Cosmogenic-nuclide Production Rates using High-precision Dating of 40Ar/39Ar Lava Flows from Mount Erebus AMD_USAPDC STAC Catalog 2017-07-15 2022-06-30 166.17, -77.7, 167.75, -77.3 https://cmr.earthdata.nasa.gov/search/concepts/C2586847142-AMD_USAPDC.umm_json Nontechnical Description: The age of rocks and soils at the surface of the Earth can help answer multiple questions that are important for human welfare, including: when did volcanoes erupt and are they likely to erupt again? when did glaciers advance and what do they tell us about climate? what is the frequency of hazards such as landslides, floods, and debris flows? how long does it take soils to form and is erosion of soils going to make farming unsustainable? One method that is used thousands of times every year to address these questions is called 'cosmogenic surface-exposure dating'. This method takes advantage of cosmic rays, which are powerful protons and neutrons produced by supernova that constantly bombard the Earth's atmosphere. Some cosmic rays reach Earth's surface and produce nuclear reactions that result in rare isotopes. Measuring the quantity of the rare isotopes enables the length of time that the rock or soil has been exposed to the atmosphere to be calculated. The distribution of cosmic rays around the globe depends on Earth's magnetic field, and this distribution must be accurately known if useful exposure ages are to be obtained. Currently there are two remaining theories, narrowed down from many, of how to calculate this distribution. Measurements from a site that is at both high altitude and high latitude (close to the poles) are needed to test the two theories. This study involves both field and lab research and includes a Ph.D. student and an undergraduate student. The research team will collect rocks from lava flows on an active volcano in Antarctica named Mount Erebus and measure the amounts of two rare isotopes: 36Cl and 3He. The age of eruption of the samples will be determined using a highly accurate method that does not depend on cosmic rays, called 40Ar/39Ar dating. The two cosmic-ray theories will be used to calculate the ages of the samples using the 36Cl and 3He concentrations and will then be compared to the ages calculated from the 40Ar/39Ar dating. The accurate cosmic-ray theory will be the one that gives the same ages as the 40Ar/39Ar dating. Identification of the accurate theory will enable use of the cosmogenic surface dating methods anywhere on earth. Technical Description: Nuclides produced by cosmic rays in rocks at the surface of the earth are widely used for Quaternary geochronology and geomorphic studies and their use is increasing every year. The recently completed CRONUS-Earth Project (Cosmic-Ray Produced Nuclides on Earth) has systematically evaluated the production rates and theoretical underpinnings of cosmogenic nuclides. However, the CRONUS-Earth Project was not able to discriminate between the two leading theoretical approaches: the original Lal model (St) and the new Lifton-Sato-Dunai model (LSD). Mathematical models used to scale the production of the nuclides as a function of location on the earth, elevation, and magnetic field configuration are an essential component of this dating method. The inability to distinguish between the two models was because the predicted production rates did not differ sufficiently at the location of the calibration sites. The cosmogenic-nuclide production rates that are predicted by the two models differ significantly from each other at Erebus volcano, Antarctica. Mount Erebus is therefore an excellent site for testing which production model best describes actual cosmogenic-nuclide production variations over the globe. The research team recently measured 3He and 36Cl in mineral separates extracted from Erebus lava flows. The exposure ages for each nuclide were reproducible within each flow (~2% standard deviation) and in very good agreement between the 3He and the 36Cl ages. However, the ages calculated by the St and LSD scaling methods differ by ~15-25% due to the sensitivity of the production rate to the scaling at this latitude and elevation. These results lend confidence that Erebus qualifies as a suitable high- latitude/high-elevation calibration site. The remaining component that is still lacking is accurate and reliable independent (i.e., non-cosmogenic) ages, however, published 40Ar/39Ar ages are too imprecise and typically biased to older ages due to excess argon contained in melt inclusions. The research team's new 40Ar/39Ar data show that previous problems with Erebus anorthoclase geochronology are now overcome with modern mass spectrometry and better sample preparation. This indicates a high likelihood of success for this proposal in defining an accurate global scaling model. Although encouraging, much remains to be accomplished. This project will sample lava flows over 3 km in elevation and determine their 40Ar/39Ar and exposure ages. These combined data will discriminate between the two scaling methods, resulting in a preferred scaling model for global cosmogenic geochronology. The LSD method contains two sub-methods, the 'plain' LSD scales all nuclides the same, whereas LSDn scales each nuclide individually. The project can discriminate between these models using 3He and 36Cl data from lava flows at different elevations, because the first model predicts that the production ratio for these two nuclides will be invariant with elevation and the second that there should be ~10% difference over the range of elevations to be sampled. Finally, the project will provide a local, finite-age calibration site for cosmogenic-nuclide investigations in Antarctica. proprietary
USAP-1656344_1 A Preliminary Assessment of the Influence of Ice Cover on Microbial Carbon and Energy Acquisition during the Antarctic Winter-spring Seasonal Transition ALL STAC Catalog 2016-08-01 2018-07-31 -64.1, -65, -63.9, -64.75 https://cmr.earthdata.nasa.gov/search/concepts/C2532071951-AMD_USAPDC.umm_json "This EAGER project will compare gene expression patterns in the planktonic communities under ice covers that form in coastal embayment's in the Antarctic Peninsula. Previous efforts taking advantage of unique ice conditions in November and December of 2015 allowed researchers to conduct an experiment to examine the role of sea ice cover on microbial carbon and energy transfer during the winter-spring transition. The EAGER effort will enable the researchers to conduct the ""omics"" analyses of the phytoplankton to determine predominant means by which energy is acquired and used in these settings. This EAGER effort will apply new expertise to fill an existing gap in ecological observations along the West Antarctic Peninsula. The principle product of the proposed work will be a novel dataset to be analyzed and by an early career researcher from an underserved community (veteran). The critical baseline data contained in this dataset enable a comparison of eukaryotic and prokaryotic gene expression patterns to establish the relative importance of chemoautotrophy, heterotrophy, mixotrophy, and phototrophy during the experiments. this information and data will be made immediately available to the broader scientific community, and will enable the development of further hypotheses on ecosystem change as sea ice cover changes in the region. Very little gene expression data is currently available for the Antarctic marine environment, and no gene expression data is available during the ecologically critical winter to spring transition. Moreover, ice cover in bays is common along the West Antarctic Peninsula yet the opportunity to study cryptophyte phytoplankton physiology beneath such ice conditions in coastal embayments is rare." proprietary
-USAP-1744755_1 A mechanistic study of bio-physical interaction and air-sea carbon transfer in the Southern Ocean AMD_USAPDC STAC Catalog 2018-05-01 2022-04-30 -80, -70, -30, -45 https://cmr.earthdata.nasa.gov/search/concepts/C2545372297-AMD_USAPDC.umm_json Current generation of coupled climate models, that are used to make climate projections, lack the resolution to adequately resolve ocean mesoscale (10 - 100km) processes, exhibiting significant biases in the ocean carbon uptake. Mesoscale processes include many features including jets, fronts and eddies that are crucial for bio-physical interactions, air-sea CO2 exchange and the supply of iron to the surface ocean. This modeling project will support the eddy resolving regional simulations to understand the mechanisms that drives bio-physical interaction and air-sea exchange of carbon dioxide. proprietary
+USAP-1656344_1 A Preliminary Assessment of the Influence of Ice Cover on Microbial Carbon and Energy Acquisition during the Antarctic Winter-spring Seasonal Transition AMD_USAPDC STAC Catalog 2016-08-01 2018-07-31 -64.1, -65, -63.9, -64.75 https://cmr.earthdata.nasa.gov/search/concepts/C2532071951-AMD_USAPDC.umm_json "This EAGER project will compare gene expression patterns in the planktonic communities under ice covers that form in coastal embayment's in the Antarctic Peninsula. Previous efforts taking advantage of unique ice conditions in November and December of 2015 allowed researchers to conduct an experiment to examine the role of sea ice cover on microbial carbon and energy transfer during the winter-spring transition. The EAGER effort will enable the researchers to conduct the ""omics"" analyses of the phytoplankton to determine predominant means by which energy is acquired and used in these settings. This EAGER effort will apply new expertise to fill an existing gap in ecological observations along the West Antarctic Peninsula. The principle product of the proposed work will be a novel dataset to be analyzed and by an early career researcher from an underserved community (veteran). The critical baseline data contained in this dataset enable a comparison of eukaryotic and prokaryotic gene expression patterns to establish the relative importance of chemoautotrophy, heterotrophy, mixotrophy, and phototrophy during the experiments. this information and data will be made immediately available to the broader scientific community, and will enable the development of further hypotheses on ecosystem change as sea ice cover changes in the region. Very little gene expression data is currently available for the Antarctic marine environment, and no gene expression data is available during the ecologically critical winter to spring transition. Moreover, ice cover in bays is common along the West Antarctic Peninsula yet the opportunity to study cryptophyte phytoplankton physiology beneath such ice conditions in coastal embayments is rare." proprietary
USAP-1744755_1 A mechanistic study of bio-physical interaction and air-sea carbon transfer in the Southern Ocean ALL STAC Catalog 2018-05-01 2022-04-30 -80, -70, -30, -45 https://cmr.earthdata.nasa.gov/search/concepts/C2545372297-AMD_USAPDC.umm_json Current generation of coupled climate models, that are used to make climate projections, lack the resolution to adequately resolve ocean mesoscale (10 - 100km) processes, exhibiting significant biases in the ocean carbon uptake. Mesoscale processes include many features including jets, fronts and eddies that are crucial for bio-physical interactions, air-sea CO2 exchange and the supply of iron to the surface ocean. This modeling project will support the eddy resolving regional simulations to understand the mechanisms that drives bio-physical interaction and air-sea exchange of carbon dioxide. proprietary
+USAP-1744755_1 A mechanistic study of bio-physical interaction and air-sea carbon transfer in the Southern Ocean AMD_USAPDC STAC Catalog 2018-05-01 2022-04-30 -80, -70, -30, -45 https://cmr.earthdata.nasa.gov/search/concepts/C2545372297-AMD_USAPDC.umm_json Current generation of coupled climate models, that are used to make climate projections, lack the resolution to adequately resolve ocean mesoscale (10 - 100km) processes, exhibiting significant biases in the ocean carbon uptake. Mesoscale processes include many features including jets, fronts and eddies that are crucial for bio-physical interactions, air-sea CO2 exchange and the supply of iron to the surface ocean. This modeling project will support the eddy resolving regional simulations to understand the mechanisms that drives bio-physical interaction and air-sea exchange of carbon dioxide. proprietary
USAP-1744828_1 Collaborative Proposal: A High-Latitude Conjugate Area Array Experiment to Investigate Solar Wind - Magnetosphere - Ionosphere Coupling AMD_USAPDC STAC Catalog 2018-08-15 2022-07-31 6, -85, 89, -69 https://cmr.earthdata.nasa.gov/search/concepts/C2532075157-AMD_USAPDC.umm_json This proposal is directed toward an investigation of the coupling phenomena between the solar wind and the Earth's magnetosphere and ionosphere, particularly on the day side of the Earth and observed simultaneously at high latitudes in both northern and southern hemispheres. Through past NSF support, several magnetometers have been deployed in Antarctica, Greenland, and Svalbard, while new collaborations have been developed with the Polar Research Institute of China (PRIC) to further increase coverage through data sharing. This project will expand the existing Virginia Tech-PRIC partnership to include New Jersey Institute of Technology, University of New Hampshire, and the Technical University of Denmark and (1) construct two new stations to be deployed by PRIC along a chain from Zhongshan station to Dome A to complete a conjugate area array, (2) integrate data from all stations into a common format, and (3) address two focused science questions. Both instrument deployment and data processing efforts are motivated by a large number of solar wind-magnetosphere-ionosphere (SWMI) coupling science questions; this project will address two questions pertaining to Ultra Low Frequency (ULF) waves: (1) What is the global ULF response to Hot Flow Anomalies (HFA) and how is it affected by asymmetries in the SWMI system? (2) How do dawn-dusk and north-south asymmetries in the coupled SWMI system affect global ULF wave properties during periods with large, steady east-west Interplanetary Magnetic field (IMF By)? This proposal requires fieldwork in the Antarctic, but all fieldwork will be conducted by PRIC. proprietary
USAP-1744989_1 A Multi-scale Approach to Understanding Spatial and Population Variability in Emperor Penguins ALL STAC Catalog 2018-07-15 2022-06-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2705787178-AMD_USAPDC.umm_json This project on emperor penguin populations will quantify penguin presence/absence, and colony size and trajectory, across the entire Antarctic continent using high-resolution satellite imagery. For a subset of the colonies, population estimates derived from high-resolution satellite images will be compared with those determined by aerial surveys - these results have been uploaded to MAPPPD (penguinmap.com) and are freely available for use. This validated information will be used to determine population estimates for all emperor penguin colonies through iterations of supervised classification and maximum likelihood calculations on the high-resolution imagery. The effect of spatial, geophysical, and environmental variables on population size and decadal-scale trends will be assessed using generalized linear models. This research will result in a first ever empirical result for emperor penguin population trends and habitat suitability, and will leverage currently-funded NSF infrastructure and hosting sites to publish results in near-real time to the public. proprietary
USAP-1744989_1 A Multi-scale Approach to Understanding Spatial and Population Variability in Emperor Penguins AMD_USAPDC STAC Catalog 2018-07-15 2022-06-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2705787178-AMD_USAPDC.umm_json This project on emperor penguin populations will quantify penguin presence/absence, and colony size and trajectory, across the entire Antarctic continent using high-resolution satellite imagery. For a subset of the colonies, population estimates derived from high-resolution satellite images will be compared with those determined by aerial surveys - these results have been uploaded to MAPPPD (penguinmap.com) and are freely available for use. This validated information will be used to determine population estimates for all emperor penguin colonies through iterations of supervised classification and maximum likelihood calculations on the high-resolution imagery. The effect of spatial, geophysical, and environmental variables on population size and decadal-scale trends will be assessed using generalized linear models. This research will result in a first ever empirical result for emperor penguin population trends and habitat suitability, and will leverage currently-funded NSF infrastructure and hosting sites to publish results in near-real time to the public. proprietary
@@ -15530,8 +15531,8 @@ USAP-2046240_1 CAREER: Coastal Antarctic Snow Algae and Light Absorbing Particle
USAP-2046437_1 CAREER: Development of Unmanned Ground Vehicles for Assessing the Health of Secluded Ecosystems (ECHO) AMD_USAPDC STAC Catalog 2021-09-01 2026-08-31 -60, -80, 10, -55 https://cmr.earthdata.nasa.gov/search/concepts/C2532075144-AMD_USAPDC.umm_json Polar ecosystems currently experience significant impacts due to global changes. Measurable negative effects on polar wildlife have already occurred, such as population decreases of numerous seabird species, including the complete loss of colonies of one of the most emblematic species of the Antarctic, the emperor penguin. These existing impacts on polar species are alarming, especially because many polar species still remain poorly studied due to technical and logistical challenges imposed by the harsh environment and extreme remoteness. Developing technologies and tools for monitoring such wildlife populations is, therefore, a matter of urgency. This project aims to help close major knowledge gaps about the emperor penguin, in particular about their adaptive capability to a changing environment, by the development of next-generation tools to remotely study entire colonies. Specifically, the main goal of this project is to implement and test an autonomous unmanned ground vehicle equipped with Radio-frequency identification (RFID) antennas and wireless mesh communication data-loggers to: 1) identify RFID-tagged emperor penguins during breeding to studying population dynamics without human presence; and 2) receive GPS-TDR datasets from VHF-GPS-TDR data-loggers without human presence to study animal behavior and distribution at sea. The autonomous vehicles navigation through the colony will be aided by an existing remote penguin observatory (SPOT). Properly implemented, this technology can be used to study of the life history of individual penguins, and therefore gather data for behavioral and population dynamic studies. The education objectives of this CAREER project are designed to increase the interest in a STEM education for the next generation of scientists by combining the charisma of the emperor penguin with robotics research. Within this project, a new class on ecosystem robotics will be developed and taught, Robotics boot-camps will allow undergraduate students to remotely participate in Antarctic field trips, and an annual curriculum will be developed that allows K-12 students to follow the life of the emperor penguin during the breeding cycle, powered by real-time data obtained using the unmanned ground vehicle as well as the existing emperor penguin observatory. proprietary
USAP-2046800_1 CAREER: Ecosystem Impacts of Microbial Succession and Production at Antarctic Methane Seeps AMD_USAPDC STAC Catalog 2022-01-01 2026-12-31 162, -78, 168, -77 https://cmr.earthdata.nasa.gov/search/concepts/C2532075149-AMD_USAPDC.umm_json Due to persistent cold temperatures, geographical isolation, and resulting evolutionary distinctness of Southern Ocean fauna, the study of Antarctic reducing habitats has the potential to fundamentally alter our understanding of the biologic processes that inhibit greenhouse gas emissions from our oceans. Marine methane, a greenhouse gas 25x as potent as carbon dioxide for warming our atmosphere, is currently a minor component of atmospheric forcing due to the microbial oxidation of methane within the oceans. Based on studies of persistent deep-sea seeps at mid- and northern latitudes we have learned that bacteria and archaea create a ‘sediment filter’ that oxidizes methane prior to its release. As increasing global temperatures have and will continue to alter the rate and variance of methane release, the ability of the microbial filter to respond to fluctuations in methane cycles is a critical yet unexplored avenue of research. Antarctica contains vast reservoirs of methane, equivalent to all of the permafrost in the Arctic, and yet we know almost nothing about the fauna that may mitigate its release, as until recently, we had not discovered an active methane seep. In 2012, a methane seep was discovered in the Ross Sea, Antarctica that formed in 2011 providing the first opportunity to study an active Antarctic methane-fueled habitat and simultaneously the impact of microbial succession on the oxidation of methane, a critical ecosystem service. Previous work has shown that after 5 years of seepage, the community was at an early stage of succession and unable to mitigate the release of methane from the seafloor. In addition, additional areas of seepage had begun nearby. This research aims to quantify the community trajectory of these seeps in relation to their role in the Antarctic Ecosystem, from greenhouse gas mitigation through supporting the food web. Through the application of genomic and transcriptomic approaches, taxa involved in methane cycling and genes activated by the addition of methane will be identified and contrasted with those from other geographical locations. These comparisons will elucidate how taxa have evolved and adapted to the polar environment. This research uses a ‘genome to ecosystem’ approach to advance our understanding of organismal and systems ecology in Antarctica. By quantifying the trajectory of community succession following the onset of methane emission, the research will decipher temporal shifts in biodiversity/ecosystem function relationships. Phylogenomic approaches focusing on taxa involved in methane cycling will advance the burgeoning field of microbial biogeography on a continent where earth’s history may have had a profound yet unquantified impact on microbial evolution. Further, the research will empirically quantify the role of chemosynthesis as a form of export production from seeps and in non-seep habitats in the nearshore Ross Sea benthos, informing our understanding of Antarctic carbon cycling. proprietary
USAP-2055455_1 ANT LIA - Viral Ecogenomics of the Southern Ocean: Unifying Omics and Ecological Networks to Advance our Understanding of Antarctic Microbial Ecosystem Function AMD_USAPDC STAC Catalog 2021-05-01 2024-04-30 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532075626-AMD_USAPDC.umm_json "Part 1: Non-technical description: It is well known that the Southern Ocean plays an important role in global carbon cycling and also receives a disproportionately large influence of climate change. The role of marine viruses on ocean productivity is largely understudied, especially in this global region. This team proposes to use combination of genomics, flow cytometry, and network modeling to test the hypothesis that viral biogeography, infection networks, and viral impacts on microbial metabolism can explain variations in net community production (NCP) and carbon cycling in the Southern Ocean. The project includes the training of a postdoctoral scholar, graduate students and undergraduate students. It also includes the development of a new Polar Sci ReachOut program in partnership with the University of Michigan Museum of Natural History especially targeted to middle-school students and teachers and the general public. The team will also produce a Science for Tomorrow (SFT) program for use in middle schools in metro-Detroit communities and lead a summer Research Experience for Teachers (RET) fellows. Part 2: Technical description: The study will leverage hundreds of existing samples collected for microbes and viruses from the Antarctic Circumpolar Expedition (ACE). These samples provide the first contiguous survey of viral diversity and microbial communities around Antarctica. Viral networks are being studied in the context of biogeochemical data to model community networks and predict net community production (NCP), which will provide a way to evaluate the role of viruses in Southern Ocean carbon cycling. Using cutting edge molecular and flow cytometry approaches, this project addresses the following questions: 1) How/why are Southern Ocean viral populations distributed across environmental gradients? 2a) Do viruses interfere with ""keystone"" metabolic pathways and biogeochemical processes of microbial communities in the Southern Ocean? 2b) Does nutrient availability or other environmental variables drive changes in virus-microbe infection networks in the Southern Ocean? Results will be used to develop and evaluate generative models of NCP predictions that incorporate the importance of viral traits and virus-host interactions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria." proprietary
-USAP-2130663_1 2021 Antarctic Subsea Cable Workshop: High-Speed Connectivity Needs to Advance US Antarctic Science AMD_USAPDC STAC Catalog 2021-06-01 2023-05-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2556670196-AMD_USAPDC.umm_json Current networking capacity at McMurdo Station is insufficient to even be considered broadband, with a summer population of up to 1000 people sharing what is equivalent to the connection enjoyed by a typical family of three in the United States. The changing Antarctic ice sheets and Southern Ocean are large, complex systems that require cutting edge technology to do cutting edge research, with remote technology becoming increasingly useful and even necessary to monitor changes at sufficient spatial and temporal scales. Antarctic science also often involves large data-transfer needs not currently met by existing satellite communication infrastructure. This workshop will gather representatives from across Antarctic science disciplinesfrom astronomy to zoologyas well as research and education networking experts to explore the scientific advances that would be enabled through dramatically increased real-time network connectivity, and also consider opportunities for subsea cable instrumentation. This workshop will assess the importance of a subsea fiber optic cable for high-capacity real-time connectivity in the US Antarctic Program, which is at the forefront of some of the greatest climate-related challenges facing our planet. The workshop will: (1) document unmet or poorly met current scientific and logistic needs for connectivity; (2) explore connectivity needs for planned future research and note the scientific advances that would be possible if the full value of modern cyberinfrastructure-empowered research could be brought to the Antarctic research community; and (3) identify scientific opportunities in planning a fully instrumented communication cable as a scientific observatory. Due to the ongoing COVID-19 pandemic, the workshop will be hosted and streamed online. While the workshop will be limited to invited personnel in order to facilitate a collaborative working environment, broad community input will be sought via survey and via comment on draft outputs. A workshop summary document and report will be delivered to NSF. Increasing US Antarctic connectivity by orders of magnitude will be transformative for science and logistics, and it may well usher in a new era of Antarctic science that is more accessible, efficient and sustainable. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. proprietary
USAP-2130663_1 2021 Antarctic Subsea Cable Workshop: High-Speed Connectivity Needs to Advance US Antarctic Science ALL STAC Catalog 2021-06-01 2023-05-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2556670196-AMD_USAPDC.umm_json Current networking capacity at McMurdo Station is insufficient to even be considered broadband, with a summer population of up to 1000 people sharing what is equivalent to the connection enjoyed by a typical family of three in the United States. The changing Antarctic ice sheets and Southern Ocean are large, complex systems that require cutting edge technology to do cutting edge research, with remote technology becoming increasingly useful and even necessary to monitor changes at sufficient spatial and temporal scales. Antarctic science also often involves large data-transfer needs not currently met by existing satellite communication infrastructure. This workshop will gather representatives from across Antarctic science disciplinesfrom astronomy to zoologyas well as research and education networking experts to explore the scientific advances that would be enabled through dramatically increased real-time network connectivity, and also consider opportunities for subsea cable instrumentation. This workshop will assess the importance of a subsea fiber optic cable for high-capacity real-time connectivity in the US Antarctic Program, which is at the forefront of some of the greatest climate-related challenges facing our planet. The workshop will: (1) document unmet or poorly met current scientific and logistic needs for connectivity; (2) explore connectivity needs for planned future research and note the scientific advances that would be possible if the full value of modern cyberinfrastructure-empowered research could be brought to the Antarctic research community; and (3) identify scientific opportunities in planning a fully instrumented communication cable as a scientific observatory. Due to the ongoing COVID-19 pandemic, the workshop will be hosted and streamed online. While the workshop will be limited to invited personnel in order to facilitate a collaborative working environment, broad community input will be sought via survey and via comment on draft outputs. A workshop summary document and report will be delivered to NSF. Increasing US Antarctic connectivity by orders of magnitude will be transformative for science and logistics, and it may well usher in a new era of Antarctic science that is more accessible, efficient and sustainable. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. proprietary
+USAP-2130663_1 2021 Antarctic Subsea Cable Workshop: High-Speed Connectivity Needs to Advance US Antarctic Science AMD_USAPDC STAC Catalog 2021-06-01 2023-05-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2556670196-AMD_USAPDC.umm_json Current networking capacity at McMurdo Station is insufficient to even be considered broadband, with a summer population of up to 1000 people sharing what is equivalent to the connection enjoyed by a typical family of three in the United States. The changing Antarctic ice sheets and Southern Ocean are large, complex systems that require cutting edge technology to do cutting edge research, with remote technology becoming increasingly useful and even necessary to monitor changes at sufficient spatial and temporal scales. Antarctic science also often involves large data-transfer needs not currently met by existing satellite communication infrastructure. This workshop will gather representatives from across Antarctic science disciplinesfrom astronomy to zoologyas well as research and education networking experts to explore the scientific advances that would be enabled through dramatically increased real-time network connectivity, and also consider opportunities for subsea cable instrumentation. This workshop will assess the importance of a subsea fiber optic cable for high-capacity real-time connectivity in the US Antarctic Program, which is at the forefront of some of the greatest climate-related challenges facing our planet. The workshop will: (1) document unmet or poorly met current scientific and logistic needs for connectivity; (2) explore connectivity needs for planned future research and note the scientific advances that would be possible if the full value of modern cyberinfrastructure-empowered research could be brought to the Antarctic research community; and (3) identify scientific opportunities in planning a fully instrumented communication cable as a scientific observatory. Due to the ongoing COVID-19 pandemic, the workshop will be hosted and streamed online. While the workshop will be limited to invited personnel in order to facilitate a collaborative working environment, broad community input will be sought via survey and via comment on draft outputs. A workshop summary document and report will be delivered to NSF. Increasing US Antarctic connectivity by orders of magnitude will be transformative for science and logistics, and it may well usher in a new era of Antarctic science that is more accessible, efficient and sustainable. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. proprietary
USAP-2132641_1 ANT LIA: Do Molecular Data Support High Endemism and Divergent Evolution of Antarctic Marine Nematodes and their Host-associated Microbiomes? AMD_USAPDC STAC Catalog 2022-07-15 2026-06-30 -180, -80, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2544555474-AMD_USAPDC.umm_json Nematode worms are abundant and ubiquitous in marine sediment habitats worldwide, performing key functions such as nutrient cycling and sediment stability. However, study of this phylum suffers from a perpetual and severe taxonomic deficit, with less than 5,000 formally described marine species. Fauna from the Southern Ocean are especially poorly studied due to limited sampling and the general inaccessibility of the Antarctic benthos. This study is providing the first large-scale molecular-based investigation from marine nematodes in the Eastern Antarctic continental shelf, providing an important comparative dataset for the existing body of historical (morphological) taxonomic studies. This project uses a combination of classical taxonomy (microscopy) and modern -omics tools to achieve three overarching aims: 1) determine if molecular data supports high biodiversity and endemism of benthic meiofauna in Antarctic benthic ecosystems; 2) determine the proportion of marine nematode species that have a deep-sea versus shallow-water evolutionary origin on the Antarctic shelf, and assess patterns of cryptic speciation in the Southern Ocean; and 3) determine the most important drivers of the host-associated microbiome in Antarctic marine nematodes. This project is designed to rapidly advance knowledge of the evolutionary origins of Antarctic meiofauna, provide insight on population-level patterns within key indicator genera, and elucidate the potential ecological and environmental factors which may influence microbiome patterns. Broader Impacts activities include an intensive cruise- and land-based outreach program focusing on social media engagement and digital outreach products, raising awareness of Antarctic marine ecosystems and understudied microbial-animal relationships. The diverse research team includes female scientists, first-generation college students, and Latinx trainees. proprietary
USAP-2133684_1 Collaborative Research: ANT LIA Integrating Genomic and Phenotypic Analyses to understand Microbial Life in Antarctic Soils AMD_USAPDC STAC Catalog 2022-04-01 2025-03-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2660035273-AMD_USAPDC.umm_json Not all of Antarctica is covered in ice. In fact, soils are common to many parts of Antarctica, and these soils are often unlike any others found on Earth. Antarctic soils harbor unique microorganisms able to cope with the extremely cold and dry conditions common to much of the continent. For decades, microbiologists have been drawn to the unique soils in Antarctica, yet critical knowledge gaps remain. Most notably, it is unclear what properties allow certain microbes to thrive in Antarctic soils. By using a range of methods, this project is developing comprehensive model that discovers the unique genomic features of soils diversity, distributions, and adaptations that allow Antarctic soil microbes to thrive in extreme environments. The proposed work will be relevant to researchers in many fields, including engineers seeking to develop new biotechnologies, ecologists studying the contributions of these microbial communities to the functioning of Antarctic ecosystems, microbiologists studying novel microbial adaptations to extreme environmental conditions, and even astrobiologists studying the potential for life on Mars. More generally, the proposed research presents an opportunity to advance our current understanding of the microbial life found in one of the more distinctive microbial habitats on Earth, a habitat that is inaccessible to many scientists and a habitat that is increasingly under threat from climate change. The research project explores the microbial diversity in Antarctic soils and links specific features to different soil types and environmental conditions. The overarching questions include: What microbial taxa are found in a variety of Antarctic environments? What are the environmental preferences of specific taxa or lineages? What are the genomic and phenotypic traits of microorganisms that allow them to persist in extreme environments and determine biogeographical differneces? This project will analyze archived soils collected from across Antarctica by a network of international collaborators, with samples selected to span broad gradients in soil and site conditions. The project uses cultivation-independent, high-throughput genomic analysis methods and cultivation-dependent approaches to analyze bacterial and fungal communities in soil samples. The results will be used to predict the distributions of specific taxa and lineages, obtain genomic information for the more ubiquitous and abundant taxa, and quantify growth responses in vitro across gradients in temperature, moisture, and salinity. This integration of ecological, environmental, genomic, and trait-based information will provide a comprehensive understanding of microbial life in Antarctic soils. This project will also help facilitate new collaborations between scientists across the globe while providing undergraduate students with ''hands-on'' research experiences that introduce the next generation of scientists to the field of Antarctic biology. This award reflects NSF''s statutory mission and has been deemed worthy of support through evaluation using the Foundation''s intellectual merit and broader impacts review criteria. proprietary
USAP-2141555_1 CAREER: Using Otolith Chemistry to Reveal the Life History of Antarctic Toothfish in the Ross Sea, Antarctica: Testing Fisheries and Climate Change Impacts on a Top Fish Predator AMD_USAPDC STAC Catalog 2022-05-01 2027-04-30 161, -79, -151, -71.5 https://cmr.earthdata.nasa.gov/search/concepts/C2532075614-AMD_USAPDC.umm_json The Ross Sea, Antarctica, is one of the last large intact marine ecosystems left in the world, yet is facing increasing pressure from commercial fisheries and environmental change. It is the most productive stretch of the Southern Ocean, supporting an array of marine life, including Antarctic toothfish the regions top fish predator. While a commercial fishery for toothfish continues to grow in the Ross Sea, fundamental knowledge gaps remain regarding toothfish ecology and the impacts of toothfish fishing on the broader Ross Sea ecosystem. Recognizing the global value of the Ross Sea, a large (>2 million km2) marine protected area was adopted by the multi-national Commission for the Conservation of Antarctic Marine Living Resources in 2016. This research will fill a critical gap in the knowledge of Antarctic toothfish and deepen understanding of biological-physical interactions for fish ecology, while contributing to knowledge of impacts of fishing and environmental change on the Ross Sea system. This work will further provide innovative tools for studying connectivity among geographically distinct fish populations and for synthesizing and assessing the efficacy of a large-scale marine protected area. In developing an integrated research and education program in engaged scholarship, this project seeks to train the next generation of scholars to engage across the science-policy-public interface, engage with Southern Ocean stakeholders throughout the research process, and to deepen the publics appreciation of the Antarctic. A major research priority among Ross Sea scientists is to better understand the life history of the Antarctic toothfish and test the efficacy of the Ross Sea Marine Protected Area (MPA) in protecting against the impacts of overfishing and climate change. Like growth rings of a tree, fish ear bones, called otoliths, develop annual layers of calcium carbonate that incorporates elements from their environment. Otoliths offer information on the fishs growth and the surrounding ocean conditions. Hypothesizing that much of the Antarctic toothfish life cycle is structured by ocean circulation, this research employs a multi-disciplinary approach combining age and growth work with otolith chemistry testing, while also utilizing GIS mapping. The project will measure life history parameters as well as trace elements and stable isotopes in otoliths in three distinct sets collected over the last four decades in the Ross Sea. The information will be used to quantify the transport pathways Antarctic toothfish use across their life history, and across time, in the Ross Sea. The project will assess if toothfish populations from the Ross Sea are connected more widely across the Antarctic. By comparing life history and otolith chemistry data across time, the researchers will assess change in life history parameters and spatial dynamics and seek to infer if these changes are driven by fishing or climate change. Spatially mapping of these data will allow an assessment of the efficacy of the Ross Sea MPA in protecting toothfish and where further protections might be needed. This award reflects NSF''s statutory mission and has been deemed worthy of support through evaluation using the Foundation''s intellectual merit and broader impacts review criteria. proprietary
@@ -15540,13 +15541,13 @@ USAP-2149070_1 ANT LIA: Collaborative Research: Adaptations of Southern Ocean Di
USAP-2232891_1 ANT LIA: The Role of Sex Determination in the Radiation of Antarctic Notothenioid Fish AMD_USAPDC STAC Catalog 2023-08-15 2027-07-31 -180, -90, 180, -37 https://cmr.earthdata.nasa.gov/search/concepts/C2759058324-AMD_USAPDC.umm_json Antarctic animals face tremendous threats as Antarctic ice sheets melt and temperatures rise. About 34 million years ago, when Antarctica began to cool, most species of fish became locally extinct. A group called the notothenioids, however, survived due to the evolution of antifreeze. The group eventually split into over 120 species. Why did this group of Antarctic fishes evolve into so many species? One possible reason why a single population splits into two species relates to sex genes and sex chromosomes. Diverging species often have either different sex determining genes (genes that specify whether an individual’s gonads become ovaries or testes) or have different sex chromosomes (chromosomes that differ between males and females within a species, like the human X and Y chromosomes). We know the sex chromosomes of only a few notothenioid species and know the genetic basis for sex determination in none of them. The aims of this research are to: 1) identify sex chromosomes in species representing every major group of Antarctic notothenioid fish; 2) discover possible sex determining genes in every major group of Antarctic notothenioid fish; and 3) find sex chromosomes and possible sex determining genes in two groups of temperate, warmer water, notothenioid fish. These warmer water fish include groups that never experienced the frigid Southern Ocean and groups that had ancestors inhabiting Antarctic oceans that later adjusted to warmer waters. This project will help explain the mechanisms that led to the division of a group of species threatened by climate change. This information is critical to conserve declining populations of Antarctic notothenioids, which are major food sources for other Antarctic species such as bird and seals. The project will offer a diverse group of undergraduates the opportunity to develop a permanent exhibit at the Eugene Science Center Museum. The exhibit will describe the Antarctic environment and explain its rapid climate change. It will also introduce the continent’s bizarre fishes that live below the freezing point of water. The project will collaborate with the university’s Science and Comics Initiative and students in the English Department’s Comics Studies Minor to prepare short graphic novels explaining Antarctic biogeography, icefish specialties, and the science of this project as it develops. proprietary
USAP-2240780_1 ANT LIA: Collaborative Research: Mixotrophic Grazing as a Strategy to meet Nutritional Requirements in the Iron and Manganese Deficient Southern Ocean AMD_USAPDC STAC Catalog 2023-02-15 2026-01-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2639396983-AMD_USAPDC.umm_json Mixotrophic microorganisms that are capable of both photosynthetic and heterotrophic forms of metabolism are key contributors to primary productivity and organic carbon remineralization in the Southern Ocean. However, uncertainties in their grazing behavior and physiology prevent an accurate understanding of microbial food web dynamics and biogeochemical cycling in the Antarctic ecosystem. Polar mixotrophs have evolved to withstand extreme seasonality, including variable light, sea ice, temperature, and micronutrient concentrations. In particular, the Southern Ocean appears to be the only region of the world’s ocean where the bioessential trace metals iron (Fe) and manganese (Mn) are low enough to inhibit photosynthetic growth. The molecular physiology of mixotrophs experiencing Fe and Mn growth limitation has not yet been examined, and we lack an understanding of how seasonal changes in the availability of these micronutrients influence mixotrophic growth dynamics. We aim to examine whether grazing affords mixotrophs an ecological advantage in the Fe and Mn-deficient Southern Ocean, and to characterize the shifts in metabolic processes that occur during transitions in micronutrient conditions. Culture studies will directly measure growth responses, grazing behavior, and changes in elemental stoichiometry in response to Fe and Mn limitation. Transcriptomic analyses will reveal the metabolic underpinnings of trophic behavior and micronutrient stress responses, with implications for key biogeochemical processes such as carbon fixation, remineralization, and nutrient cycling. proprietary
USAP-2324998_1 ANT LIA: Collaborative Research: Evolutionary Patterns and Mechanisms of Trait Diversification in the Antarctic Notothenioid Radiation AMD_USAPDC STAC Catalog 2022-10-01 2025-01-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C3333666817-AMD_USAPDC.umm_json Part I: Nontechnical description The ecologically important notothenioid fish of the Southern Ocean surrounding Antarctica will be studied to address questions central to polar, evolutionary, and adaptational biology. The rapid diversification of the notothenioids into >120 species following a period of Antarctic glaciation and cooling of the Southern Ocean is thought to have been facilitated by key evolutionary innovations, including antifreeze glycoproteins to prevent freezing and bone reduction to increase buoyancy. In this project, a large dataset of genomic sequences will be used to evaluate the genetic mechanisms that underlie the broad pattern of novel trait evolution in these fish, including traits relevant to human diseases (e.g., bone density, renal function, and anemia). The team will develop new STEM-based research and teaching modules for undergraduate education at Northeastern University. The work will provide specific research training to scholars at all levels, including a post-doctoral researcher, a graduate student, undergraduate students, and high school students. The team will also contribute to public outreach, including, in part, the develop of teaching videos in molecular evolutionary biology and accompanying educational supplements. Part II: Technical description The researchers will leverage their comprehensive notothenioid phylogenomic dataset comprising >250,000 protein-coding exons and conserved non-coding elements across 44 ingroup and 2 outgroup species to analyze the genetic origins of three iconic notothenioid traits: (1) loss of erythrocytes by the icefish clade in a cold, stable and highly-oxygenated marine environment. (2) reduction in bone mass and retention of juvenile skeletal characteristics as buoyancy mechanisms to facilitate foraging. And (3) loss of kidney glomeruli to retain energetically expensive antifreeze glycoproteins. The team will first track patterns of change in erythroid-related genes throughout the notothenioid phylogeny. They will then examine whether repetitive evolution of a pedomorphic skeleton in notothenioids is based on parallel or divergent evolution of genetic regulators of heterochrony. Third, they will determine whether there is mutational bias in the mechanisms of loss and re-emergence of kidney glomeruli. Finally, identified genetic mechanisms of evolutionary change will be validated by experimental testing using functional genomic strategies in the zebrafish model system. proprietary
-USAP-9615281_1 Air-Ground Study of Tectonics at the Boundary Between the Eastern Ross Embayment and Western Marie Byrd Land, Antarctica: Basement Geology and Structure AMD_USAPDC STAC Catalog 1997-08-15 2002-07-31 -170, -84, -135, -76 https://cmr.earthdata.nasa.gov/search/concepts/C2532072225-AMD_USAPDC.umm_json This award supports a collaborative project that combines air and ground geological-geophysical investigations to understand the tectonic and geological development of the boundary between the Ross Sea Rift and the Marie Byrd Land (MBL) volcanic province. The project will determine the Cenozoic tectonic history of the region and whether Neogene structures that localized outlet glacier flow developed within the context of Cenozoic rifting on the eastern Ross Embayment margin, or within the volcanic province in MBL. The geological structure at the boundary between the Ross Embayment and western MBL may be a result of: 1) Cenozoic extension on the eastern shoulder of the Ross Sea rift; 2) uplift and crustal extension related to Neogene mantle plume activity in western MBL; or a combination of the two. Faulting and volcanism, mountain uplift, and glacier downcutting appear to now be active in western MBL, where generally East-to-West-flowing outlet glaciers incise Paleozoic and Mesozoic bedrock, and deglaciated summits indicate a previous North-South glacial flow direction. This study requires data collection using SOAR (Support Office for Aerogeophysical Research, a facility supported by Office of Polar Programs which utilizes high precision differential GPS to support a laser altimeter, ice-penetrating radar, a towed proton magnetometer, and a Bell BGM-3 gravimeter). This survey requires data for 37,000 square kilometers using 5.3 kilometer line spacing with 15.6 kilometer tie lines, and 86,000 square kilometers using a grid of 10.6 by 10.6 kilometer spacing. Data will be acquired over several key features in the region including, among other, the eastern edge of the Ross Sea rift, over ice stream OEO, the transition from the Edward VII Peninsula plateau to the Ford Ranges, the continuation to the east of a gravity high known from previous reconnaissance mapping over the Fosdick Metamorphic Complex, an d the extent of the high-amplitude magnetic anomalies (volcanic centers?) detected southeast of the northern Ford Ranges by other investigators. SOAR products will include glaciology data useful for studying driving stresses, glacial flow and mass balance in the West Antarctic Ice Sheet (WAIS). The ground program is centered on the southern Ford Ranges. Geologic field mapping will focus on small scale brittle structures for regional kinematic interpretation, on glaciated surfaces and deposits, and on datable volcanic rocks for geochronologic control. The relative significance of fault and joint sets, the timing relationships between them, and the probable context of their formation will also be determined. Exposure ages will be determined for erosion surfaces and moraines. Interpretation of potential field data will be aided by on ground sampling for magnetic properties and density as well as ground based gravity measurements. Oriented samples will be taken for paleomagnetic studies. Combined airborne and ground investigations will obtain basic data for describing the geology and structure at the eastern boundary of the Ross Embayment both in outcrop and ice covered areas, and may be used to distinguish between Ross Sea rift- related structural activity from uplift and faulting on the perimeter of the MBL dome and volcanic province. Outcrop geology and structure will be extrapolated with the aerogeophysical data to infer the geology that resides beneath the WAIS. The new knowledge of Neogene tectonics in western MBL will contribute to a comprehensive model for the Cenozoic Ross rift and to understanding of the extent of plume activity in MBL. Both are important for determining the influence of Neogene tectonics on the ice streams and WAIS. proprietary
USAP-9615281_1 Air-Ground Study of Tectonics at the Boundary Between the Eastern Ross Embayment and Western Marie Byrd Land, Antarctica: Basement Geology and Structure ALL STAC Catalog 1997-08-15 2002-07-31 -170, -84, -135, -76 https://cmr.earthdata.nasa.gov/search/concepts/C2532072225-AMD_USAPDC.umm_json This award supports a collaborative project that combines air and ground geological-geophysical investigations to understand the tectonic and geological development of the boundary between the Ross Sea Rift and the Marie Byrd Land (MBL) volcanic province. The project will determine the Cenozoic tectonic history of the region and whether Neogene structures that localized outlet glacier flow developed within the context of Cenozoic rifting on the eastern Ross Embayment margin, or within the volcanic province in MBL. The geological structure at the boundary between the Ross Embayment and western MBL may be a result of: 1) Cenozoic extension on the eastern shoulder of the Ross Sea rift; 2) uplift and crustal extension related to Neogene mantle plume activity in western MBL; or a combination of the two. Faulting and volcanism, mountain uplift, and glacier downcutting appear to now be active in western MBL, where generally East-to-West-flowing outlet glaciers incise Paleozoic and Mesozoic bedrock, and deglaciated summits indicate a previous North-South glacial flow direction. This study requires data collection using SOAR (Support Office for Aerogeophysical Research, a facility supported by Office of Polar Programs which utilizes high precision differential GPS to support a laser altimeter, ice-penetrating radar, a towed proton magnetometer, and a Bell BGM-3 gravimeter). This survey requires data for 37,000 square kilometers using 5.3 kilometer line spacing with 15.6 kilometer tie lines, and 86,000 square kilometers using a grid of 10.6 by 10.6 kilometer spacing. Data will be acquired over several key features in the region including, among other, the eastern edge of the Ross Sea rift, over ice stream OEO, the transition from the Edward VII Peninsula plateau to the Ford Ranges, the continuation to the east of a gravity high known from previous reconnaissance mapping over the Fosdick Metamorphic Complex, an d the extent of the high-amplitude magnetic anomalies (volcanic centers?) detected southeast of the northern Ford Ranges by other investigators. SOAR products will include glaciology data useful for studying driving stresses, glacial flow and mass balance in the West Antarctic Ice Sheet (WAIS). The ground program is centered on the southern Ford Ranges. Geologic field mapping will focus on small scale brittle structures for regional kinematic interpretation, on glaciated surfaces and deposits, and on datable volcanic rocks for geochronologic control. The relative significance of fault and joint sets, the timing relationships between them, and the probable context of their formation will also be determined. Exposure ages will be determined for erosion surfaces and moraines. Interpretation of potential field data will be aided by on ground sampling for magnetic properties and density as well as ground based gravity measurements. Oriented samples will be taken for paleomagnetic studies. Combined airborne and ground investigations will obtain basic data for describing the geology and structure at the eastern boundary of the Ross Embayment both in outcrop and ice covered areas, and may be used to distinguish between Ross Sea rift- related structural activity from uplift and faulting on the perimeter of the MBL dome and volcanic province. Outcrop geology and structure will be extrapolated with the aerogeophysical data to infer the geology that resides beneath the WAIS. The new knowledge of Neogene tectonics in western MBL will contribute to a comprehensive model for the Cenozoic Ross rift and to understanding of the extent of plume activity in MBL. Both are important for determining the influence of Neogene tectonics on the ice streams and WAIS. proprietary
+USAP-9615281_1 Air-Ground Study of Tectonics at the Boundary Between the Eastern Ross Embayment and Western Marie Byrd Land, Antarctica: Basement Geology and Structure AMD_USAPDC STAC Catalog 1997-08-15 2002-07-31 -170, -84, -135, -76 https://cmr.earthdata.nasa.gov/search/concepts/C2532072225-AMD_USAPDC.umm_json This award supports a collaborative project that combines air and ground geological-geophysical investigations to understand the tectonic and geological development of the boundary between the Ross Sea Rift and the Marie Byrd Land (MBL) volcanic province. The project will determine the Cenozoic tectonic history of the region and whether Neogene structures that localized outlet glacier flow developed within the context of Cenozoic rifting on the eastern Ross Embayment margin, or within the volcanic province in MBL. The geological structure at the boundary between the Ross Embayment and western MBL may be a result of: 1) Cenozoic extension on the eastern shoulder of the Ross Sea rift; 2) uplift and crustal extension related to Neogene mantle plume activity in western MBL; or a combination of the two. Faulting and volcanism, mountain uplift, and glacier downcutting appear to now be active in western MBL, where generally East-to-West-flowing outlet glaciers incise Paleozoic and Mesozoic bedrock, and deglaciated summits indicate a previous North-South glacial flow direction. This study requires data collection using SOAR (Support Office for Aerogeophysical Research, a facility supported by Office of Polar Programs which utilizes high precision differential GPS to support a laser altimeter, ice-penetrating radar, a towed proton magnetometer, and a Bell BGM-3 gravimeter). This survey requires data for 37,000 square kilometers using 5.3 kilometer line spacing with 15.6 kilometer tie lines, and 86,000 square kilometers using a grid of 10.6 by 10.6 kilometer spacing. Data will be acquired over several key features in the region including, among other, the eastern edge of the Ross Sea rift, over ice stream OEO, the transition from the Edward VII Peninsula plateau to the Ford Ranges, the continuation to the east of a gravity high known from previous reconnaissance mapping over the Fosdick Metamorphic Complex, an d the extent of the high-amplitude magnetic anomalies (volcanic centers?) detected southeast of the northern Ford Ranges by other investigators. SOAR products will include glaciology data useful for studying driving stresses, glacial flow and mass balance in the West Antarctic Ice Sheet (WAIS). The ground program is centered on the southern Ford Ranges. Geologic field mapping will focus on small scale brittle structures for regional kinematic interpretation, on glaciated surfaces and deposits, and on datable volcanic rocks for geochronologic control. The relative significance of fault and joint sets, the timing relationships between them, and the probable context of their formation will also be determined. Exposure ages will be determined for erosion surfaces and moraines. Interpretation of potential field data will be aided by on ground sampling for magnetic properties and density as well as ground based gravity measurements. Oriented samples will be taken for paleomagnetic studies. Combined airborne and ground investigations will obtain basic data for describing the geology and structure at the eastern boundary of the Ross Embayment both in outcrop and ice covered areas, and may be used to distinguish between Ross Sea rift- related structural activity from uplift and faulting on the perimeter of the MBL dome and volcanic province. Outcrop geology and structure will be extrapolated with the aerogeophysical data to infer the geology that resides beneath the WAIS. The new knowledge of Neogene tectonics in western MBL will contribute to a comprehensive model for the Cenozoic Ross rift and to understanding of the extent of plume activity in MBL. Both are important for determining the influence of Neogene tectonics on the ice streams and WAIS. proprietary
USAP-9725024_1 Circumpolar Deep Water and the West Antarctic Ice Sheet AMD_USAPDC STAC Catalog 1988-03-01 2002-02-28 140, -68, 150, -65 https://cmr.earthdata.nasa.gov/search/concepts/C2532072042-AMD_USAPDC.umm_json This project will study the dynamics of Circumpolar Deep Water intruding on the continental shelf of the West Antarctic coast, and the effect of this intrusion on the production of cold, dense bottom water, and melting at the base of floating glaciers and ice tongues. It will concentrate on the Amundsen Sea shelf, specifically in the region of the Pine Island Glacier, the Thwaites Glacier, and the Getz Ice Shelf. Circumpolar Deep Water (CDW) is a relatively warm water mass (warmer than +1.0 deg Celsius) which is normally confined to the outer edge of the continental shelf by an oceanic front separating this water mass from colder and saltier shelf waters. In the Amundsen Sea however, the deeper parts of the continental shelf are filled with nearly undiluted CDW, which is mixed upward, delivering significant amounts of heat to the base of the floating glacier tongues and the ice shelf. The melt rate beneath the Pine Island Glacier averages ten meters of ice per year with local annual rates reaching twenty meters. By comparison, melt rates beneath the Ross Ice Shelf are typically twenty to forty centimeters of ice per year. In addition, both the Pine Island and the Thwaites Glacier are extremely fast-moving, and have a significant effect on the regional ice mass balance of West Antarctica. This project therefore has an important connection to antarctic glaciology, particularly in assessing the combined effect of global change on the antarctic environment. The particular objectives of the project are (1) to delineate the frontal structure on the continental shelf sufficiently to define quantitatively the major routes of CDW inflow, meltwater outflow, and the westward evolution of CDW influence; (2) to use the obtained data set to validate a three-dimensional model of sub-ice ocean circulation that is currently under construction, and (3) to refine the estiamtes of in situ melting on the mass balance of the antarctic ice sheet. The observational program will be carried out from the research vessel Nathaniel B. Palmer in February and March, 1999. proprietary
-USARC_AERIAL_PHOTOS Aerial Photography of Antarctica CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, -62.83 https://cmr.earthdata.nasa.gov/search/concepts/C2231551700-CEOS_EXTRA.umm_json "The USARC maintains all US Aerial Antarctic Mapping photography and USGS flight indexes of the Antarctic. There are over 500,000 photographs in the collection. Most photographs are 9"" x 9"" black and white images taken with three Fairchild cameras each with a metrogon lense resulting in trimetrogon photography (left oblique, vertical and right oblique photographs). Special-purpose photographs showing sites of specific scientific interest ""vertical and handheld oblique as well as photographs taken from helicopters"" are also on file. Some color photographs are also available. Line indexes to identify coverage are available for most aerial photographic missions. Contact prints in either matte or glossy finish are available for inspection or stereoscopic viewing. Special feature options, such as ice and rock enhancements, may be special ordered." proprietary
USARC_AERIAL_PHOTOS Aerial Photography of Antarctica ALL STAC Catalog 1970-01-01 -180, -90, 180, -62.83 https://cmr.earthdata.nasa.gov/search/concepts/C2231551700-CEOS_EXTRA.umm_json "The USARC maintains all US Aerial Antarctic Mapping photography and USGS flight indexes of the Antarctic. There are over 500,000 photographs in the collection. Most photographs are 9"" x 9"" black and white images taken with three Fairchild cameras each with a metrogon lense resulting in trimetrogon photography (left oblique, vertical and right oblique photographs). Special-purpose photographs showing sites of specific scientific interest ""vertical and handheld oblique as well as photographs taken from helicopters"" are also on file. Some color photographs are also available. Line indexes to identify coverage are available for most aerial photographic missions. Contact prints in either matte or glossy finish are available for inspection or stereoscopic viewing. Special feature options, such as ice and rock enhancements, may be special ordered." proprietary
-USArray_Ground_Temperature_1680_1.1 ABoVE: Soil Temperature Profiles, USArray Seismic Stations, 2016-2021 ALL STAC Catalog 2016-05-13 2021-07-08 -165.35, 59.25, -141.59, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2143403529-ORNL_CLOUD.umm_json This dataset includes soil temperature profile measurements taken at 63 monitoring sites associated with the USArray program, located across the NASA ABoVE domain in interior Alaska. The measurement dates and depths vary per site as does measurement frequency (hourly or every 6 hours). Measurements were made from the soil surface to a maximum depth of 1.5 m from 2016-2021 using temperature sensors attached to HOBO data loggers. These measurement stations complement existing temperature monitoring networks allowing for better characterization of ground temperatures and permafrost conditions across Alaska. This station data complement an existing temperature monitoring network, allowing for better characterization of ground temperatures and permafrost conditions in northern and western Alaska. The temperature measurements are provided for each site in 64 data files in comma-separated values (.csv) format. Site descriptive data are also provided for soil, vegetation, and location. proprietary
+USARC_AERIAL_PHOTOS Aerial Photography of Antarctica CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, -62.83 https://cmr.earthdata.nasa.gov/search/concepts/C2231551700-CEOS_EXTRA.umm_json "The USARC maintains all US Aerial Antarctic Mapping photography and USGS flight indexes of the Antarctic. There are over 500,000 photographs in the collection. Most photographs are 9"" x 9"" black and white images taken with three Fairchild cameras each with a metrogon lense resulting in trimetrogon photography (left oblique, vertical and right oblique photographs). Special-purpose photographs showing sites of specific scientific interest ""vertical and handheld oblique as well as photographs taken from helicopters"" are also on file. Some color photographs are also available. Line indexes to identify coverage are available for most aerial photographic missions. Contact prints in either matte or glossy finish are available for inspection or stereoscopic viewing. Special feature options, such as ice and rock enhancements, may be special ordered." proprietary
USArray_Ground_Temperature_1680_1.1 ABoVE: Soil Temperature Profiles, USArray Seismic Stations, 2016-2021 ORNL_CLOUD STAC Catalog 2016-05-13 2021-07-08 -165.35, 59.25, -141.59, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2143403529-ORNL_CLOUD.umm_json This dataset includes soil temperature profile measurements taken at 63 monitoring sites associated with the USArray program, located across the NASA ABoVE domain in interior Alaska. The measurement dates and depths vary per site as does measurement frequency (hourly or every 6 hours). Measurements were made from the soil surface to a maximum depth of 1.5 m from 2016-2021 using temperature sensors attached to HOBO data loggers. These measurement stations complement existing temperature monitoring networks allowing for better characterization of ground temperatures and permafrost conditions across Alaska. This station data complement an existing temperature monitoring network, allowing for better characterization of ground temperatures and permafrost conditions in northern and western Alaska. The temperature measurements are provided for each site in 64 data files in comma-separated values (.csv) format. Site descriptive data are also provided for soil, vegetation, and location. proprietary
+USArray_Ground_Temperature_1680_1.1 ABoVE: Soil Temperature Profiles, USArray Seismic Stations, 2016-2021 ALL STAC Catalog 2016-05-13 2021-07-08 -165.35, 59.25, -141.59, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2143403529-ORNL_CLOUD.umm_json This dataset includes soil temperature profile measurements taken at 63 monitoring sites associated with the USArray program, located across the NASA ABoVE domain in interior Alaska. The measurement dates and depths vary per site as does measurement frequency (hourly or every 6 hours). Measurements were made from the soil surface to a maximum depth of 1.5 m from 2016-2021 using temperature sensors attached to HOBO data loggers. These measurement stations complement existing temperature monitoring networks allowing for better characterization of ground temperatures and permafrost conditions across Alaska. This station data complement an existing temperature monitoring network, allowing for better characterization of ground temperatures and permafrost conditions in northern and western Alaska. The temperature measurements are provided for each site in 64 data files in comma-separated values (.csv) format. Site descriptive data are also provided for soil, vegetation, and location. proprietary
USDA0113 Groundwater Quality in Beaver Creek Watershed, Tennessee CEOS_EXTRA STAC Catalog 1992-07-01 1992-08-31 -90.74, 34.56, -81.22, 37.12 https://cmr.earthdata.nasa.gov/search/concepts/C2232411621-CEOS_EXTRA.umm_json Analysis for 400 domestic wells for selected constituents. Reconnaissance of Ground Water Quality in Beaver Creek Watershed, Shelby, Tipton, Fayette, and Haywood counties, Tennessee. Collection Organization: USDA-CSREES/USGS - University of Tennessee; Institute of Agriculture Collection Methodology: Samples collected by UTAES staff, trained volunteers, and USGS Personnel - USGS conducted field and laboratory analysis. Collection Frequency: One-time. Update Characteristics: N/A STATISTICAL INFORMATION: 400 wells; 20 parameters per sample. LANGUAGE: English ACCESS/AVAILABILITY: Data Center: U.S. Geological Survey Dissemination Media: USGS Data Base Access Instructions: Contact the data center. proprietary
USDA0114 Groundwater Quality in Bedford and Coffee Counties, Tennessee CEOS_EXTRA STAC Catalog 1991-06-01 1991-07-31 -90.74, 34.56, -81.22, 37.12 https://cmr.earthdata.nasa.gov/search/concepts/C2232411616-CEOS_EXTRA.umm_json Analysis for 200 domestic wells and springs for selected constituents. Reconnaissance of Ground Water Quality in Bedford and Coffee Counties, TN. Collection Organization: USDA-CSREES/USGS - University of Tennessee; Institute of Agriculture Collection Methodology: Samples collected by UTAES staff, trained volunteers, and USGS Personnel - USGS conducted field and laboratory analysis. Collection Frequency: One-time. Update Characteristics: N/A STATISTICAL INFORMATION: 200 wells/springs; 7 parameters per sample. LANGUAGE: English ACCESS/AVAILABILITY: Data Center: U.S. Geological Survey Media: USGS Data Base Access Instructions: Contact the data center. proprietary
USDA0115 Groundwater Quality in Tennessee CEOS_EXTRA STAC Catalog 1984-01-01 1990-12-31 -90.74, 34.56, -81.22, 37.12 https://cmr.earthdata.nasa.gov/search/concepts/C2232411608-CEOS_EXTRA.umm_json Analysis of 150 wells for selected constituents, reconnaissance of Ground Water Quality in Tennessee. Collection Organization: USDA-CSREES - University of Tennessee; Institute of Agriculture Collection Methodology: Samples collected by USGS staff. USGS conducted field and laboratory analysis at their national lab. Collection Frequency: One-time. Update Characteristics: N/A STATISTICAL INFORMATION: 150 wells on farmsteads across Tennessee; 7 parameters per well. LANGUAGE: English ACCESS/AVAILABILITY: Data Center: U.S. Geological Survey Media: USGS Data Base. Access Instructions: Contact the data center. proprietary
@@ -15557,22 +15558,22 @@ USGS-DDS-11 Geology of the Conterminous United States at 1:2,500,000 Scale -- A
USGS-DDS-18-A_1.0 National Geochemical Database: National Uranium Resource Evaluation Data for the Conterminous United States CEOS_EXTRA STAC Catalog 1970-01-01 -162, 24, -66, 60 https://cmr.earthdata.nasa.gov/search/concepts/C2231552333-CEOS_EXTRA.umm_json This is an online version of a CD-ROM publication. It is intended for use only on DOS-based computer systems. The files must be downloaded onto your computer before they can be used. The files are presented here in two forms: as the original folders that were published on the CD-ROM and as a large zip file that you can use to download the entire product in one step. This publication contains National Uranium Resource Evaluation (NURE) data for the conterminous United States. The data has been compressed and requires GSSEARCH software for access. GSSEARCH, supplied below, runs only under DOS. [Summary provided by the USGS.] proprietary
USGS-DDS-19 Geology and Resource Assessment of Costa Rica at 1:500,000 Scale CEOS_EXTRA STAC Catalog 1970-01-01 -86, 8, -82, 11 https://cmr.earthdata.nasa.gov/search/concepts/C2231554233-CEOS_EXTRA.umm_json PROJECT OVERVIEW Conversion of the information from the original folio to a computerized digital format was undertaken to facilitate the presentation and analysis of earth-science data. Digital maps can be displayed at any scale or projection, whereas a paper map has a fixed scale and projection. However, most of the maps on this disc are not intended to be used at any scale more detailed than 1:500,000. A geographic information system (GIS) allows combining and overlaying of layers for analysis of spatial relations not readily apparent in the standard paper publication. Digital information on geology, geophysics, and geochemistry can be combined to create useful derivative products. HISTORY OF THE MAPS In 1986 and 1987, the U.S. Geological Survey (USGS), the Dirección General de Geología, Minas e Hidrocarburos, and the Universidad de Costa Rica conducted a mineral-resource assessment of the Republic of Costa Rica. The results were published as a large 80- by 50-cm color folio (U.S. Geological Survey and others, 1987). The 75-page document consists of maps as well as descriptive and interpretive text in English and Spanish covering physiographic, geologic, geochemical, geophysical, and mineral site themes as well as a mineral-resource assessment. The following maps are present in the original folio: 1) Physiographic base map at a scale of 1:500,000 with hypsography, place names, and drainage. 2) Geologic map at a scale of 1:500,000. 3) Regional geophysical maps, including gravity, aeromagnetic, and seismicity maps at various scales. 4) Mineral sites map at a scale of 1:500,000 showing mines, prospects, and occurrences. 5) Volcanological framework of the Tilarán region important for epithermal gold deposits at a scale of 1:100,000. 6) Rock sample locations, mining areas, and vein locations for several parts of the country. 7) Permissive areas delineated for selected mineral deposit types. 8) Digital elevation model. This CD-ROM contains most of the above maps; it lacks items 1 and 8 and the seismicity and aeromagnetic maps of item 3. The linework was digitized from preliminary and printed maps with GSMAP (Selner and Taylor, 1987), a USGS-authored program for map editing and publishing. Conversion from GSMAP to ARC/INFO was accomplished through the use of the GSMARC program (Green and Selner, 1988). The arcs and polygons were tagged using Alacarte (Wentworth and Fitzgibbon, 1991). [Summary provided by the USGS.] proprietary
USGS-DDS-27_1 Monthly average polar sea-ice concentration - USGS-DDS-27 CEOS_EXTRA STAC Catalog 1978-10-25 1991-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231553834-CEOS_EXTRA.umm_json The purpose of this data set is to provide paleoclimate researchers with a tool for estimating the average seasonal variation in sea-ice concentration in the modern polar oceans and for estimating the modern monthly sea-ice concentration at any given polar oceanic location. It is expected that these data will be compared with paleoclimate data derived from geological proxy measures such as faunal census analyses and stable-isotope analyses. The results can then be used to constrain general circulation models of climate change. This data set represents the results of calculations carried out on sea-ice-concentration data from the SMMR and SSM/I instruments. The original data were obtained from the National Snow and Ice Data Center (NSIDC). The data set also contains the source code of the programs that made the calculations. The objective was to derive monthly averages for the whole 13.25-year series (1978-1991) and to derive a composite series of monthly averages representing the variation of an average year. The resulting file set contains monthly images for each of the polar regions for each year, yielding 160 files for each pole, and composite monthly averages in which the years are combined, yielding 12 more files. Averaging the images in this way tends to reduce the number of grid cells that lack valid data; the composite averages are designed to suppress interannual variability. Also included in the data set are programs that can retrieve seasonal ice-concentration profiles at user-specified locations. These nongraphical data retrieval programs are provided in versions for UNIX, extended DOS, and Macintosh computers. Graphical browse utilities are included for the same computing platforms but require more sophisticated display systems. The data contained in this data set are derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/ Imager (SSM/I) data produced by the National Snow and Ice Data Center (NSIDC) at the University of Colorado in cooperation with the U.S. National Aeronautics and Space Administration (NASA) and the U.S. National Oceanic and Atmospheric Administration (NOAA). The basic data come from satellites of the U.S. Air Force Defense Meteorological Satellite Program. NSIDC distributes three collections of sea- ice-concentration grids on CD-ROM: data from the Nimbus-7 SMMR (October 25, 1978 through August 20, 1987) are provided on volume 7 of the SMMR Polar Data series (NASA, 1992); data from the SSM/I are provided on two separate volumes, covering the periods from July 9 of 1987 to December 31 of 1989, and from January 1 of 1990 through December 31 of 1991, respectively. The NASATEAM data from revision 2 of the SSM/I CD-ROM's were used to create the present data set. SMMR images were collected every 2 to 3 days, whereas SSM/I data are provided in daily ice-concentration grids. Apart from a number of small gaps (5 or fewer days) in the record, the only long period for which no data are available is December 3 of 1987 through January 12 of 1988, inclusive. As ancillary data, the ETOPO5 global gridded elevation and bathymetry data (Edwards, 1989) were interpolated to the resolution of the NSIDC data; the interpolated topographic data are included. The images are provided in three formats: Hierarchical Data Format (HDF), a flexible scientific data format developed at the National Center for Supercomputing Applications; Graphics Interchange Format (GIF); and Macintosh PICT format. The ice- concentration grids are distributed by NSIDC in HDF format. proprietary
-USGS-DDS-3 A Geologic Map of the Sea Floor in Western Massachusetts Bay, Constructed from Digital Sidescan-Sonar Images, Photography, and Sediment Samples ALL STAC Catalog 1970-01-01 -71.5, 42, -70, 43 https://cmr.earthdata.nasa.gov/search/concepts/C2231550375-CEOS_EXTRA.umm_json This data set describes sea floor characteristics for the Western Massachusetts Bay. This data set was created using sidescan-sonar imagery, photography, and sediment samples. proprietary
USGS-DDS-3 A Geologic Map of the Sea Floor in Western Massachusetts Bay, Constructed from Digital Sidescan-Sonar Images, Photography, and Sediment Samples CEOS_EXTRA STAC Catalog 1970-01-01 -71.5, 42, -70, 43 https://cmr.earthdata.nasa.gov/search/concepts/C2231550375-CEOS_EXTRA.umm_json This data set describes sea floor characteristics for the Western Massachusetts Bay. This data set was created using sidescan-sonar imagery, photography, and sediment samples. proprietary
+USGS-DDS-3 A Geologic Map of the Sea Floor in Western Massachusetts Bay, Constructed from Digital Sidescan-Sonar Images, Photography, and Sediment Samples ALL STAC Catalog 1970-01-01 -71.5, 42, -70, 43 https://cmr.earthdata.nasa.gov/search/concepts/C2231550375-CEOS_EXTRA.umm_json This data set describes sea floor characteristics for the Western Massachusetts Bay. This data set was created using sidescan-sonar imagery, photography, and sediment samples. proprietary
USGS-DDS-33_1.0 3-D Reservoir Characterization of the House Creek Oil Field, Powder River Basin, Wyoming, V1.00 CEOS_EXTRA STAC Catalog 1970-01-01 -111.4, 40.65, -103.7, 45.35 https://cmr.earthdata.nasa.gov/search/concepts/C2231553827-CEOS_EXTRA.umm_json "The Upper Cretaceous Sussex ""B"" sandstone was deposited as a probable transgressive-marine sand-ridge complex in a mid-shelf position. The ""B"" sandstone is bounded by upper and basal disconformities and encased in mudstones and low-porosity and low-permeability sandstones of the Cody Shale. Reservoir characteristics are controlled primarily by depositional and diagenetic heterogeneity at megascopic (field), macroscopic (well), and microscopic (rock sample) levels. To simplify, this means production of oil is controlled by stacking and interbedding of sandstone and mudstone beds and by geochemical changes through time that affect flow of fluids through the rock. More than 24.8 million barrels of oil (MMBO) have been produced from the Sussex ""B"" sandstone in the House Creek field, Powder River Basin, Wyoming. Greatest oil production, porosity, and permeability, the thickest reservoir sandstone intervals, and best lateral continuity of the primary reservoir facies are all located parallel and proximal to field axes. Decrease in reservoir quality west of the axes is due to greater heterogeneity from interbedding of low- and moderate-depositional-energy facies, with associated drop in porosity and permeability. Decrease in production east of the axes results primarily from a combination of seaward thinning of the primary reservoir facies and non-deposition of sand ridges. The House Creek field has two axis orientations; these are related to depositional patterns of the four sand ridges. Deposition of the ""B"" sandstone began in the southeastern corner of the field with sand ridge 1; axis orientation is about north 20 degrees west. Later-deposited sand ridges 2 through 4 are located west and north of sand ridge 1; their axis orientations are approximately north 32 degrees west. Progressive northward deposition of later sand ridges is probably concurrent with uplift of the northeast-trending Belle Fourche arch. Movement along the arch and of lineaments may have caused topographic highs that localized Sussex and Shannon deposition proximal to the arch. [Summary provided by the USGS.]" proprietary
USGS-DDS-33_1.0 3-D Reservoir Characterization of the House Creek Oil Field, Powder River Basin, Wyoming, V1.00 ALL STAC Catalog 1970-01-01 -111.4, 40.65, -103.7, 45.35 https://cmr.earthdata.nasa.gov/search/concepts/C2231553827-CEOS_EXTRA.umm_json "The Upper Cretaceous Sussex ""B"" sandstone was deposited as a probable transgressive-marine sand-ridge complex in a mid-shelf position. The ""B"" sandstone is bounded by upper and basal disconformities and encased in mudstones and low-porosity and low-permeability sandstones of the Cody Shale. Reservoir characteristics are controlled primarily by depositional and diagenetic heterogeneity at megascopic (field), macroscopic (well), and microscopic (rock sample) levels. To simplify, this means production of oil is controlled by stacking and interbedding of sandstone and mudstone beds and by geochemical changes through time that affect flow of fluids through the rock. More than 24.8 million barrels of oil (MMBO) have been produced from the Sussex ""B"" sandstone in the House Creek field, Powder River Basin, Wyoming. Greatest oil production, porosity, and permeability, the thickest reservoir sandstone intervals, and best lateral continuity of the primary reservoir facies are all located parallel and proximal to field axes. Decrease in reservoir quality west of the axes is due to greater heterogeneity from interbedding of low- and moderate-depositional-energy facies, with associated drop in porosity and permeability. Decrease in production east of the axes results primarily from a combination of seaward thinning of the primary reservoir facies and non-deposition of sand ridges. The House Creek field has two axis orientations; these are related to depositional patterns of the four sand ridges. Deposition of the ""B"" sandstone began in the southeastern corner of the field with sand ridge 1; axis orientation is about north 20 degrees west. Later-deposited sand ridges 2 through 4 are located west and north of sand ridge 1; their axis orientations are approximately north 32 degrees west. Progressive northward deposition of later sand ridges is probably concurrent with uplift of the northeast-trending Belle Fourche arch. Movement along the arch and of lineaments may have caused topographic highs that localized Sussex and Shannon deposition proximal to the arch. [Summary provided by the USGS.]" proprietary
USGS-DDS-74_2.0 Long-term Oceanographic Observations in Western Massachusetts Bay Offshore of Boston, Massachusetts: Data Report for 1989-2002 CEOS_EXTRA STAC Catalog 1989-12-01 2002-12-01 -71, 42, -70.5, 42.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231551840-CEOS_EXTRA.umm_json Long-term oceanographic observations have been made at two locations in western Massachusetts Bay: (1) Site A (42ý 22.6' N, 70ý 47.0' W, 33 m water depth) from from 1989 to 2002, and (2) Site B (42ý 9.8' N, 70ý 38.4' W, 21 m deter depth) from 1997 to 2002. Site A is approximately 1 km south of the new ocean outfall that began discharging treated sewage effluent from the Boston metropolitan area into Massachusetts Bay in September 2000. These long-term oceanographic observations have been collected by the U.S. Geological Survey (USGS) in partnership with the Massachusetts Water Resources Authority (MWRA) and with logistical support from the U. S. Coast Guard (USCG). This report presents time series data collected through December 2002, updating a similar report that presented data through December 2000 (Butman and others, 2002). The long-term observations at these two stations are part of a USGS study designed to understand the transport and long-term fate of sediments and associated contaminants in the Massachusetts Bays (see //woodshole.er.usgs.gov/project-pages/bostonharbor / and Butman and Bothner, 1997). The long-term observations document seasonal and inter-annual changes in currents, hydrography, and suspended-matter concentration in western Massachusetts Bay, and the importance of infrequent catastrophic events, such as major storms or hurricanes, in sediment resuspension and transport. They also provide observations for testing numerical models of circulation. This data report presents a description of the field program and instrumentation, an overview of the data through summary plots and statistics, and the data in NetCDF and ASCII format for the period December 1989 through December 2002. The objective of this report is to make the data available in digital form, and to provide summary plots and statistics to facilitate browsing of the long-term data set . [Summary provided by the USGS.] proprietary
USGS-DDS-79 Coastal Erosion and Wetland Change in Louisiana: Selected USGS Products CEOS_EXTRA STAC Catalog 1970-01-01 -94.3, 28.67, -88.54, 33.29 https://cmr.earthdata.nasa.gov/search/concepts/C2231552152-CEOS_EXTRA.umm_json Louisiana contains 25 percent of the vegetated wetlands and 40 percent of the tidal wetlands in the 48 conterminous States. These critical natural systems are being lost. Louisiana leads the Nation in coastal erosion and wetland loss as a result of a complex combination of natural processes (e.g. storms, sea-level rise, subsidence) and manmade alterations to the Mississippi River and the wetlands over the past 200 years. Erosion of several of the barrier islands, which lie offshore of the estuaries and wetlands and buffer and protect these important ecosystems from the open marine environment, exceeds 20 meters/year. The average rate of shoreline erosion is over 10 meters/year. Within the past 100 years, Louisiana's barrier islands have decreased in area by more than 40 percent, and some islands have lost more than 75 percent of their land area. If these loss rates continue, several of the barriers are expected to erode completely within the next three decades. Their disappearance will contribute to further loss and deterioration of wetlands and back-barrier estuaries and increase the risk to infrastructure. Coastal wetland environments, which include associated bays and estuaries, support a rich harvest of renewable natural resources with an estimated annual value of over $1 billion. More than 30 percent of the Nation's fisheries come from these wetlands, as well as 25 percent of oil and gas coming through the wetlands. Louisiana also has the highest rate of wetland loss: 80 percent of the Nation's total loss of wetlands has occurred in this State. The rate of wetland loss in the Mississippi River delta plain is estimated to be about 70 square kilometers/year -- the equivalent of a football field every 20 minutes. If these rates continue, an estimated 4,000 square kilometers of wetlands will be lost in the next 50 years. Losses of this magnitude have direct implications on the Nation's energy supplies, economic security, and environmental integrity. Over the past two decades, the USGS, working in partnership with other scientists in universities and State agencies, has led the research effort to document barrier erosion and wetland loss and understand the natural and manmade causes responsible. Some products resulting from this research, included in this DVD, are providing the baseline data and information being used for Federal-State wetlands restoration programs underway and being planned. [Summary provided by the USGS.] proprietary
-USGS-DDS_30_P-10_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Joaquin Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -121.388916, 34.890034, -118.58517, 37.83907 https://cmr.earthdata.nasa.gov/search/concepts/C2231552106-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 10 (San Joaquin Basin) are listed here by play number, type, and name: Number Type Name 1001 conventional Pliocene Non-associated Gas 1002 conventional Southeast Stable Shelf 1003 conventional Lower Bakersfield Arch 1004 conventional West Side Fold Belt Sourced by Post-Lower Miocene Rocks. 1005 conventional West Side Fold Belt Sourced by Pre-Middle Miocene Rocks 1006 conventional Northeast Shelf of Neogene Basin 1007 conventional Northern Area Non-associated Gas 1008 conventional Tejon Platform 1009 conventional South End Thrust Salient 1010 conventional East Central Basin and Slope North of Bakersfield Arch 1011 conventional Deep Overpressured Fractured Rocks of West Side Fold and Overthrust Belt proprietary
USGS-DDS_30_P-10_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Joaquin Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -121.388916, 34.890034, -118.58517, 37.83907 https://cmr.earthdata.nasa.gov/search/concepts/C2231552106-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 10 (San Joaquin Basin) are listed here by play number, type, and name: Number Type Name 1001 conventional Pliocene Non-associated Gas 1002 conventional Southeast Stable Shelf 1003 conventional Lower Bakersfield Arch 1004 conventional West Side Fold Belt Sourced by Post-Lower Miocene Rocks. 1005 conventional West Side Fold Belt Sourced by Pre-Middle Miocene Rocks 1006 conventional Northeast Shelf of Neogene Basin 1007 conventional Northern Area Non-associated Gas 1008 conventional Tejon Platform 1009 conventional South End Thrust Salient 1010 conventional East Central Basin and Slope North of Bakersfield Arch 1011 conventional Deep Overpressured Fractured Rocks of West Side Fold and Overthrust Belt proprietary
-USGS-DDS_30_P10_conventional 1995 National Oil and Gas Assessment Conventional Plays within the San Joaquin Basin Province CEOS_EXTRA STAC Catalog 1970-01-01 -121.388916, 34.890034, -118.58517, 37.83907 https://cmr.earthdata.nasa.gov/search/concepts/C2231550316-CEOS_EXTRA.umm_json The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. proprietary
+USGS-DDS_30_P-10_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Joaquin Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -121.388916, 34.890034, -118.58517, 37.83907 https://cmr.earthdata.nasa.gov/search/concepts/C2231552106-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 10 (San Joaquin Basin) are listed here by play number, type, and name: Number Type Name 1001 conventional Pliocene Non-associated Gas 1002 conventional Southeast Stable Shelf 1003 conventional Lower Bakersfield Arch 1004 conventional West Side Fold Belt Sourced by Post-Lower Miocene Rocks. 1005 conventional West Side Fold Belt Sourced by Pre-Middle Miocene Rocks 1006 conventional Northeast Shelf of Neogene Basin 1007 conventional Northern Area Non-associated Gas 1008 conventional Tejon Platform 1009 conventional South End Thrust Salient 1010 conventional East Central Basin and Slope North of Bakersfield Arch 1011 conventional Deep Overpressured Fractured Rocks of West Side Fold and Overthrust Belt proprietary
USGS-DDS_30_P10_conventional 1995 National Oil and Gas Assessment Conventional Plays within the San Joaquin Basin Province ALL STAC Catalog 1970-01-01 -121.388916, 34.890034, -118.58517, 37.83907 https://cmr.earthdata.nasa.gov/search/concepts/C2231550316-CEOS_EXTRA.umm_json The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. proprietary
+USGS-DDS_30_P10_conventional 1995 National Oil and Gas Assessment Conventional Plays within the San Joaquin Basin Province CEOS_EXTRA STAC Catalog 1970-01-01 -121.388916, 34.890034, -118.58517, 37.83907 https://cmr.earthdata.nasa.gov/search/concepts/C2231550316-CEOS_EXTRA.umm_json The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. proprietary
USGS-DS-91_1.1 Depth to the Juan De Fuca Slab Beneath the Cascadia Subduction Margin: A 3-D Model for Sorting Earthquakes CEOS_EXTRA STAC Catalog 1970-01-01 -130, 40, -120, 51 https://cmr.earthdata.nasa.gov/search/concepts/C2231552778-CEOS_EXTRA.umm_json The USGS presents an updated model of the Juan de Fuca slab beneath southern British Columbia, Washington, Oregon, and northern California, and use this model to separate earthquakes occurring above and below the slab surface. The model is based on depth contours previously published by Flück and others (1997). Our model attempts to rectify a number of shortcomings in the original model and to update it with new work. The most significant improvements include (1) a gridded slab surface in geo-referenced (ArcGIS) format, (2) continuation of the slab surface to its full northern and southern edges, (3) extension of the slab surface from 50-km depth down to 110-km beneath the Cascade arc volcanoes, and (4) revision of the slab shape based on new seismic-reflection and seismic-refraction studies. We have used this surface to sort earthquakes and present some general observations and interpretations of seismicity patterns revealed by our analysis. In addition, we provide files of earthquakes above and below the slab surface and a 3-D animation or fly-through showing a shaded-relief map with plate boundaries, the slab surface, and hypocenters for use as a visualization tool. [Summary provided by the USGS.] proprietary
USGS-OFR-92-299_1.0 Molecular and Isotopic Analyses of the Hydrocarbon Gases within Gas Hydrate-Bearing Rock Units of the Prudhoe Bay-Kuparuk River Area in Northern Alaska CEOS_EXTRA STAC Catalog 1979-05-01 1990-09-01 -150, 70, -148, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2231550014-CEOS_EXTRA.umm_json "Information about and data from the USGS Open-File Report 92-299 (Molecular and isotopic analyses of the hydrocarbon gases within gas hydrate-bearing rock units of the Prudhoe Bay-Kuparuk River area in northern Alaska) are available On-line via the World Wide Web: ""http://pubs.usgs.gov/of/of92-299//"" or ""http://pubs.usgs.gov/of/1992/of92-299/"" The following information about the data set was provided by the data center contact: The objective of this study was to document the molecular and isotopic composition of the gas trapped within the gas hydrate-bearing stratigraphic intervals overlying the Prudhoe Bay and Kuparuk River oil fields. To reach this objective, we have analyzed cuttings gas and free gas samples collected from 10 drilling-production wells in the Prudhoe Bay and Kuparuk River fields. The dataset includes a report documenting the materials, the procedures used to analyze them, and the results. Results are given in tabular form as spreadsheets showing headspace, headspace/free gas, and blended headspace analyses. Gas characteristics analyzed include nitrogen, carbon dioxide, methane, ethane, ethene, propane, propene, isobutane, n-butane, isopentane, n-pentane, stable carbon isotope composition of the methane, ethane, and carbon dioxide fractions, and deuterium isotope composition of the methane fraction. Methane is the most abundant hydrocarbon gas within the gas hydrate- bearing rock units of the Prudhoe Bay-Kuparuk River area in the North Slope of Alaska. Isotopic analysis indicates that both microbial and thermogenic processes have contributed to the formation of this methane. The thermogenic component probably migrated into the rock units from greater depths, since vitrinite reflectance measurements show that the units never endured temperatures within the thermogenic range. Approximately 50 to 70 percent of the methane within the gas hydrate units is thermogenic in origin. This is U.S. Geological Survey Open-File Report 92-299 This report is preliminary and has not been reviewed for conformity with U.S. Geological Survey editorial standards or with the North American Stratigraphic Code. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government." proprietary
USGS-PRISM-PACIFIC-OSTRACODES Modern and fossil ostracode census data from the Western Pacific Ocean and seas around Japan CEOS_EXTRA STAC Catalog 1990-01-01 1993-12-31 122, 25, 165, 63 https://cmr.earthdata.nasa.gov/search/concepts/C2231551101-CEOS_EXTRA.umm_json "This data set is part of the Pliocene Research, Interpretation, and Synoptic Mapping (PRISM) Project. This data set describes marine ostracode species and related sample and stratigraphic information produced as part of the USGS PRISM Project (Pliocene Research, Interpretation, and Synoptic Mapping). The general goals of PRISM are to reconstruct global climate during a period of extreme warmth about 3 million years ago and to determine the causes of the warmth and the subsequent climatic change towards colder climates about 2.5 million years ago. To do this, PRISM has been studying Pliocene deposits and their microfaunas and, by comparison with modern assemblages, estimating past boundary conditions such as ocean temperatures. To obtain more reliable estimates of past environments in paleoclimate studies, the use of ecologically sensitive species requires extensive modern datasets on living species with limited environmental tolerances. Thus, much of the data generated by PRISM consists of species counts from modern samples that form a ""coretop"" dataset applicable not only to PRISM Pliocene assemblages but also to Quaternary assemblages as well. This situation was especially true for ostracodes, a group of Crustacea that includes many species that have limited range of water temperatures required for survival, reproduction, or both. Fossil assemblages of ostracodes can therefore yield information on past bottom water conditions on continental shelves in the mixed ocean layer above the thermocline and they are especially useful where planktic foraminifers are rare or absent. However comprehensive datasets with quantitative ostracode data were not available for application to regional paleoceanographic studies. Further, because of the endemic nature of ostracodes living on continental shelves, separate modern datasets needed to be developed for regions of the Pacific, Atlantic and Arctic Oceans. The data contained in the files in this folder come from the western North Pacific Ocean, mainly the seas around Japan. These regions encompass subtropical to cold temperate and subfrigid marine climate zones and include faunas from the major Western North Pacific water masses such as the Oyashio and Kuroshio current systems. The ostracode data sets were developed in collaboration with Prof. Noriyuki Ikeya, Institute of Geosciences, Shizuoka University, Shizuoka, Japan, Prof. Ikeya's students, and other Japanese colleagues, with support from the USGS Global Change and Climate History Program and grants from the National Science Foundation (NSF grant INT: LTV-9013402) and the Japanese Society for the Promotion of Science (JSPS grant EPAR- 093). Most of the faunal slides are housed at Shizuoka University. Separate PRISM ostracode data sets contain modern and Pliocene species data from continental shelves of the Arctic and Atlantic Oceans and from deep sea environments. Among the various types of quantitative analyses used to evaluate the ostracode data, the Squared Chord Distance (SCD) coefficient of dissimilarity was found to be useful in identifying modern analog assemblages for fossil assemblages on the basis of the proportions of shared species between two samples. The ostracode data and analyses of them are discussed in detail in the following published scientific papers: Ikeya, Noriyuki and Cronin, Thomas. M., 1993, Quantitative analysis of Ostracoda and water masses around Japan: Application to Pliocene and Pleistocene paleoceanography: Micropaleontology, v. 39, p. 263-281. Cronin, T.M., Kitamura, A., Ikeya, N., Watanabe, M., and Kamiya, T., in press. Late Pliocene climate change 3.4-2.3 Ma: Paleoceanographic record from the Yabuta Formation, Sea of Japan: Palaeogeography, Palaeoclimatology, Palaeoecology." proprietary
USGSPHOTOS U.S. Geological Survey Aerial Photography USGS_LTA STAC Catalog 1937-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566204-USGS_LTA.umm_json The U.S. Geological Survey (USGS) Aerial Photography data set includes over 2.5 million film transparencies. Beginning in 1937, photographs were acquired for mapping purposes at different altitudes using various focal lengths and film types. The resultant black-and-white photographs contain less than 5 percent cloud cover and were acquired under rigid quality control and project specifications (e.g., stereo coverage, continuous area coverage of map or administrative units). Prior to the initiation of the National High Altitude Photography (NHAP) program in 1980, the USGS photography collection was one of the major sources of aerial photographs used for mapping the United States. Since 1980, the USGS has acquired photographs over project areas that require photographs at a larger scale than the photographs in the NHAP and National Aerial Photography Program collections. proprietary
-USGS_ALASKA_RADIOCARBON Alaska Radiocarbon Data Base; USGS, Menlo Park CEOS_EXTRA STAC Catalog 1951-01-01 -179, 50, -140, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2231549723-CEOS_EXTRA.umm_json This data base contains published radiocarbon dates with entries consisting of laboratory and reference numbers. The data set is subdivided into two segments including RCFILE which contains the radiocarbon dates and author citation; and RCBIB which is a complete bibliography of all published dates. The RCFILE can be sorted by date, author citation, latitude and longitude, geographic region, and quadrangle. The RCFILE is run using the software program 'Nutshell.' The combined size of the two files is 1,092,908 bytes. There are 3,609 radiocarbon age determinations (published ages with a reference). The following is a breakdown of the number of age determinations by geographic region: Northern 997, East-Central 417, West-Central 332, Southern 769, Southwestern 603, Southeastern 448, Offshore 35, and General 8. proprietary
USGS_ALASKA_RADIOCARBON Alaska Radiocarbon Data Base; USGS, Menlo Park ALL STAC Catalog 1951-01-01 -179, 50, -140, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2231549723-CEOS_EXTRA.umm_json This data base contains published radiocarbon dates with entries consisting of laboratory and reference numbers. The data set is subdivided into two segments including RCFILE which contains the radiocarbon dates and author citation; and RCBIB which is a complete bibliography of all published dates. The RCFILE can be sorted by date, author citation, latitude and longitude, geographic region, and quadrangle. The RCFILE is run using the software program 'Nutshell.' The combined size of the two files is 1,092,908 bytes. There are 3,609 radiocarbon age determinations (published ages with a reference). The following is a breakdown of the number of age determinations by geographic region: Northern 997, East-Central 417, West-Central 332, Southern 769, Southwestern 603, Southeastern 448, Offshore 35, and General 8. proprietary
+USGS_ALASKA_RADIOCARBON Alaska Radiocarbon Data Base; USGS, Menlo Park CEOS_EXTRA STAC Catalog 1951-01-01 -179, 50, -140, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2231549723-CEOS_EXTRA.umm_json This data base contains published radiocarbon dates with entries consisting of laboratory and reference numbers. The data set is subdivided into two segments including RCFILE which contains the radiocarbon dates and author citation; and RCBIB which is a complete bibliography of all published dates. The RCFILE can be sorted by date, author citation, latitude and longitude, geographic region, and quadrangle. The RCFILE is run using the software program 'Nutshell.' The combined size of the two files is 1,092,908 bytes. There are 3,609 radiocarbon age determinations (published ages with a reference). The following is a breakdown of the number of age determinations by geographic region: Northern 997, East-Central 417, West-Central 332, Southern 769, Southwestern 603, Southeastern 448, Offshore 35, and General 8. proprietary
USGS_ARSENIC_H2O Arsenic in ground water of the United States CEOS_EXTRA STAC Catalog 1973-01-01 1997-01-01 -125, 25, -67, 50 https://cmr.earthdata.nasa.gov/search/concepts/C2232411686-CEOS_EXTRA.umm_json "[From Arsenic in ground water of the United States, ""http://water.usgs.gov/nawqa/trace/arsenic/"" Arsenic is a naturally occurring element in the environment. Arsenic in ground water is largely the result of minerals dissolving naturally from weathered rocks and soils. Several types of cancer have been linked to arsenic in water. The US Environmental Protection Agency is currently reviewing the maximum contaminant level of arsenic permitted in drinking water, and will likely lower it, as recommended last year by the National Research Council. The USGS has developed a map that shows where and to what extent arsenic occurs in ground water across the country. Highest concentrations were found throughout the West and in parts of the Midwest and Northeast." proprietary
USGS_ASC_MarineEcoregionsLayer_1.0 Marine_Ecoregions_AK CEOS_EXTRA STAC Catalog 2007-01-01 -180, 42.42584, 180, 74.238594 https://cmr.earthdata.nasa.gov/search/concepts/C2231549548-CEOS_EXTRA.umm_json "ABSTRACT: To better understand of how and why marine ecosystems vary, we developed a map of ""Large Marine Ecosystems"" (LME) for the area surrounding Alaska. These LMEs were constructed using the best information available on bathymetry, currents, temperature, and primary productivity." proprietary
USGS_ASTER_HydrothermalAlterationMaps Hydrothermal Alteration Maps of the Central and Southern Basin and Range Province of the United States Compiled From Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Data CEOS_EXTRA STAC Catalog 2013-01-01 -120.40977, 30.652391, -107.4039, 42.39188 https://cmr.earthdata.nasa.gov/search/concepts/C2231554154-CEOS_EXTRA.umm_json ABSTRACT: Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and Interactive Data Language (IDL) logical operator algorithms were used to map hydrothermally altered rocks in the central and southern parts of the Basin and Range province of the United States. The hydrothermally altered rocks mapped in this study include (1) hydrothermal silica-rich rocks (hydrous quartz, chalcedony, opal, and amorphous silica), (2) propylitic rocks (calcite-dolomite and epidote-chlorite mapped as separate mineral groups), (3) argillic rocks (alunite-pyrophyllite-kaolinite), and (4) phyllic rocks (sericite-muscovite). A series of hydrothermal alteration maps, which identify the potential locations of hydrothermal silica-rich, propylitic, argillic, and phyllic rocks on Landsat Thematic Mapper (TM) band 7 orthorectified images, and shape files of hydrothermal alteration units are provided. proprietary
@@ -15594,47 +15595,47 @@ USGS_DDS-66_1.0 Assessment of the Alluvial Sediments in the Big Thompson River V
USGS_DDS-68 Coastal Vulnerability to Sea-Level Rise: A Preliminary Database for the U.S. Atlantic, Pacific, and Gulf of Mexico Coasts CEOS_EXTRA STAC Catalog 1970-01-01 -124.7608, 24.5485, -66.9578, 48.388 https://cmr.earthdata.nasa.gov/search/concepts/C2231553183-CEOS_EXTRA.umm_json "Coastal Changes Due to Sea-Level Rise: One of the most important applied problems in coastal geology today is determining the physical response of the coastline to sea-level rise. Predicting shoreline retreat, beach loss, cliff retreat, and land loss rates is critical to planning coastal zone management strategies and assessing biological impacts due to habitat change or destruction. Presently, long-term (>50 years) coastal planning and decision-making has been done piecemeal, if at all, for the nation's shoreline (National Research Council, 1990; 1995). Consequently, facilities are being located and entire communities are being developed without adequate consideration of the potential costs of protecting or relocating them from sea-level rise related erosion, flooding and storm damage. Recent estimates of future sea-level rise based on climate modeling (Wigley and Raper, 1992) suggest an increase in global eustatic sea-level of between 15 and 95 cm by 2100, with a ""best estimate"" of 50 cm (IPCC, 1995). This is more than double the rate of eustatic rise for the past century (Douglas, 1997; Peltier and Jiang, 1997). The prediction of coastal evolution is not straightforward. There is no standard methodology, and even the kinds of data required to make such predictions are the subject of much scientific debate. A number of predictive approaches have been used (National Research Council, 1990), including: 1. extrapolation of historical data (for example, coastal erosion rates); 2. static inundation modeling; 3. application of a simple geometric model (for example, the Bruun Rule); 4. application of a sediment dynamics/budget model; or 5. Monte Carlo (probabilistic) simulation based on parameterized physical forcing variables. Each of these approaches, however, has its shortcomings or can be shown to be invalid for certain applications (National Research Council, 1990). Similarly, the types of input data required vary widely, and for a given approach (for example, sediment budget), existing data may be indeterminate or may simply not exist (Klein and Nicholls, 1999). Furthermore, human manipulation of the coast in the form of beach nourishment, construction of seawalls, groins, and jetties, as well as coastal development itself, may dictate Federal, State and local priorities for coastal management without proper regard for geologic processes. Thus, the long-term decision to renourish or otherwise engineer a coastline may be the primary determining factor in how that coastal segment evolves. Variables Affecting Coastal Vulnerability: We use here a fairly simple classification of the relative vulnerability of different U.S. coastal environments to future rises in sea-level. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, and yields a relative measure of the system's natural vulnerability to the effects of sea-level rise (Klein and Nicholls, 1999). The vulnerability classification is based upon the relative contributions and interactions of six variables: 1. Tidal range, which contributes to inundation hazards. 2. Wave height, which is linked to inundation hazards. 3. Coastal slope (steepness or flatness of the coastal region), which is linked to the susceptibility of a coast to inundation by flooding and to the rapidity of shoreline retreat. 4. Shoreline erosion rates, which indicate how the given section of shoreline has been eroding. 5. Geomorphology, which indicates the relative erodibility of a given section of shoreline. 6. Historical rates of relative sea-level rise, which correspond to how the global (eustatic) sea-level rise and local tectonic processes (land motion such as uplift or subsidence) have affected a section of shoreline. The input data for this database of coastal vulnerability have been assembled using the original, and sometimes variable, horizontal resolution, which then was resampled to a 3-minute grid cell. A data set for each risk variable is then linked to each grid point. For mapping purposes, data stored in the 3-minute grid is transferred to a 1:2,000,000 vector shoreline with each segment of shoreline lying within a single grid cell. [Summary provided by the USGS.]" proprietary
USGS_DDS-72 Bathymetry and Acoustic Backscatter of Crater Lake, Oregon from Field Activity: S-1-00-OR CEOS_EXTRA STAC Catalog 2000-07-28 2000-08-03 -122.16555, 42.904907, -122.049835, 42.978516 https://cmr.earthdata.nasa.gov/search/concepts/C2231551066-CEOS_EXTRA.umm_json "These data are intended for science researchers, students, policy makers, and the general public. The data can be used with geographic information systems (GIS) or other software to display bathymetry and backscatter data of Crater Lake, Oregon. These data include high-resolution bathymetry and calibrated acoustic backscatter in XYZ ASCII and ArcInfo GRID format generated from the 2000 multibeam sonar survey of Crater Lake, Oregon. Information for USGS Coastal and Marine Geology related activities are online at ""http://walrus.wr.usgs.gov/infobank/s/s100or/html/s-1-00-or.meta.html"" These data not intended for navigational purposes. Please recognize the U.S. Geological Survey (USGS) as the source of this information. USGS-authored or produced data and information are in the public domain. Although these data have been used by the U.S. Geological Survey, U.S. Department of the Interior, these data and information are provided with the understanding that they are not guaranteed to be usable, timely, accurate, or complete. Users are cautioned to consider carefully the provisional nature of these data and information before using them for decisions that concern personal or public safety or the conduct of business that involves substantial monetary or operational consequences. Conclusions drawn from, or actions undertaken on the basis of, such data and information are the sole responsibility of the user. Neither the U.S. Government nor any agency thereof, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any data, software, information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. Trade, firm, or product names and other references to non-USGS products and services are provided for information only and do not constitute endorsement or warranty, express or implied, by the USGS, USDOI, or U.S. Government, as to their suitability, content, usefulness, functioning, completeness, or accuracy." proprietary
USGS_DDS_10_1 Modern Average Global Sea-Surface Temperature CEOS_EXTRA STAC Catalog 1981-10-01 1989-12-31 -180, -66, 180, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2231552931-CEOS_EXTRA.umm_json The purpose of this data set is to provide paleoclimate researchers with a tool for estimating the average seasonal variation in sea-surface temperature (SST) throughout the modern world ocean and for estimating the modern monthly and weekly sea-surface temperature at any given oceanic location. It is expected that these data will be compared with temperature estimates derived from geological proxy measures such as faunal census analyses and stable isotopic analyses. The results can then be used to constrain general circulation models of climate change. The data contained in this data set are derived from the NOAA Advanced Very High Resolution Radiometer Multichannel Sea Surface Temperature data (AVHRR MCSST), which are obtainable from the Distributed Active Archive Center at the Jet Propulsion Laboratory (JPL) in Pasadena, Calif. The JPL tapes contain weekly images of SST from October 1981 through December 1990 in nine regions of the world ocean: North Atlantic, Eastern North Atlantic, South Atlantic, Agulhas, Indian, Southeast Pacific, Southwest Pacific, Northeast Pacific, and Northwest Pacific. This data set represents the results of calculations carried out on the NOAA data and also contains the source code of the programs that made the calculations. The objective was to derive the average sea-surface temperature of each month and week throughout the whole 10-year series, meaning, for example, that data from January of each year would be averaged together. The result is 12 monthly and 52 weekly images for each of the oceanic regions. Averaging the images in this way tends to reduce the number of grid cells that lack valid data and to suppress interannual variability. As ancillary data, the ETOPO5 global gridded elevation and bathymetry data (Edwards, 1989) were interpolated to the resolution of the SST data; the interpolated topographic data are included. The images are provided in three formats: a modified form of run-length encoding (MRLE), Graphics Interchange Format (GIF), and Macintosh PICT format. Also included in the data set are programs that can retrieve seasonal temperature profiles at user-specified locations and that can decompress the data files. These nongraphical SST retrieval programs are provided in versions for UNIX, MS-DOS, and Macintosh computers. Graphical browse utilities are included for users of UNIX with the X Window System, 80386- based PC's, and Macintosh computers. proprietary
-USGS_DDS_P12_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Santa Maria Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -121.977486, 34.488464, -119.44189, 36.40565 https://cmr.earthdata.nasa.gov/search/concepts/C2231553039-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 12 (Santa Maria Basin) are listed here by play number, type, and name: Number Type Name 1201 conventional Anticlinal Trends - Onshore 1202 conventional Basin Margin 1204 conventional Diagenetic 1211 conventional Anticlinal Trends - Offshore State Waters proprietary
USGS_DDS_P12_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Santa Maria Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -121.977486, 34.488464, -119.44189, 36.40565 https://cmr.earthdata.nasa.gov/search/concepts/C2231553039-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 12 (Santa Maria Basin) are listed here by play number, type, and name: Number Type Name 1201 conventional Anticlinal Trends - Onshore 1202 conventional Basin Margin 1204 conventional Diagenetic 1211 conventional Anticlinal Trends - Offshore State Waters proprietary
-USGS_DDS_P12_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Santa Maria Basin Province - USGS_DDS_P12_conventional ALL STAC Catalog 1996-01-01 1996-12-31 -121.977486, 34.488464, -119.44189, 36.40565 https://cmr.earthdata.nasa.gov/search/concepts/C2231551861-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 12 (Santa Maria Basin) are listed here by play number and name: Number Name 1201 Anticlinal Trends - Onshore 1202 Basin Margin 1204 Diagenetic 1211 Anticlinal Trends - Offshore State Waters proprietary
+USGS_DDS_P12_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Santa Maria Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -121.977486, 34.488464, -119.44189, 36.40565 https://cmr.earthdata.nasa.gov/search/concepts/C2231553039-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 12 (Santa Maria Basin) are listed here by play number, type, and name: Number Type Name 1201 conventional Anticlinal Trends - Onshore 1202 conventional Basin Margin 1204 conventional Diagenetic 1211 conventional Anticlinal Trends - Offshore State Waters proprietary
USGS_DDS_P12_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Santa Maria Basin Province - USGS_DDS_P12_conventional CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -121.977486, 34.488464, -119.44189, 36.40565 https://cmr.earthdata.nasa.gov/search/concepts/C2231551861-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 12 (Santa Maria Basin) are listed here by play number and name: Number Name 1201 Anticlinal Trends - Onshore 1202 Basin Margin 1204 Diagenetic 1211 Anticlinal Trends - Offshore State Waters proprietary
-USGS_DDS_P13_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Ventura Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -120.58227, 33.84158, -117.37425, 34.824276 https://cmr.earthdata.nasa.gov/search/concepts/C2231554781-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 13 (Ventura Basin) are listed here by play number, type, and name: Number Type Name 1301 conventional Paleogene - Onshore 1302 conventional Neogene - Onshore 1304 conventional Cretaceous 1311 conventional Paleogene - Offshore State Waters 1312 conventional Neogene - Offshore State Waters proprietary
+USGS_DDS_P12_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Santa Maria Basin Province - USGS_DDS_P12_conventional ALL STAC Catalog 1996-01-01 1996-12-31 -121.977486, 34.488464, -119.44189, 36.40565 https://cmr.earthdata.nasa.gov/search/concepts/C2231551861-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 12 (Santa Maria Basin) are listed here by play number and name: Number Name 1201 Anticlinal Trends - Onshore 1202 Basin Margin 1204 Diagenetic 1211 Anticlinal Trends - Offshore State Waters proprietary
USGS_DDS_P13_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Ventura Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -120.58227, 33.84158, -117.37425, 34.824276 https://cmr.earthdata.nasa.gov/search/concepts/C2231554781-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 13 (Ventura Basin) are listed here by play number, type, and name: Number Type Name 1301 conventional Paleogene - Onshore 1302 conventional Neogene - Onshore 1304 conventional Cretaceous 1311 conventional Paleogene - Offshore State Waters 1312 conventional Neogene - Offshore State Waters proprietary
+USGS_DDS_P13_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Ventura Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -120.58227, 33.84158, -117.37425, 34.824276 https://cmr.earthdata.nasa.gov/search/concepts/C2231554781-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 13 (Ventura Basin) are listed here by play number, type, and name: Number Type Name 1301 conventional Paleogene - Onshore 1302 conventional Neogene - Onshore 1304 conventional Cretaceous 1311 conventional Paleogene - Offshore State Waters 1312 conventional Neogene - Offshore State Waters proprietary
USGS_DDS_P13_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Ventura Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -120.58227, 33.84158, -117.37425, 34.824276 https://cmr.earthdata.nasa.gov/search/concepts/C2231550109-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 13 (Ventura Basin) are listed here by play number and name: Number Name 1301 Paleogene - Onshore 1302 Neogene - Onshore 1304 Cretaceous 1311 Paleogene - Offshore State Waters 1312 Neogene - Offshore State Waters proprietary
USGS_DDS_P13_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Ventura Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -120.58227, 33.84158, -117.37425, 34.824276 https://cmr.earthdata.nasa.gov/search/concepts/C2231550109-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 13 (Ventura Basin) are listed here by play number and name: Number Name 1301 Paleogene - Onshore 1302 Neogene - Onshore 1304 Cretaceous 1311 Paleogene - Offshore State Waters 1312 Neogene - Offshore State Waters proprietary
USGS_DDS_P14_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Los Angeles Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -119.63631, 32.7535, -117.52315, 34.17464 https://cmr.earthdata.nasa.gov/search/concepts/C2231552049-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 14 (Los Angeles Basin) are listed here by play number, type, and name: Number Type Name 1401 conventional Santa Monica Fault System and Las Cienegas Fault and Block 1402 conventional Southwestern Shelf and Adjacent Offshore State Lands 1403 conventional Newport-Inglewood Deformation Zone and Southwestern Flank of Central Syncline 1404 conventional Whittier Fault Zone and Fullerton Embayment 1405 conventional Northern Shelf and Northern Flank of Central Syncline 1406 conventional Anaheim Nose 1407 conventional Chino Marginal Basin, Puente and San Jose Hills, and San Gabriel Valley Marginal Basin proprietary
USGS_DDS_P14_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Los Angeles Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -119.63631, 32.7535, -117.52315, 34.17464 https://cmr.earthdata.nasa.gov/search/concepts/C2231552049-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 14 (Los Angeles Basin) are listed here by play number, type, and name: Number Type Name 1401 conventional Santa Monica Fault System and Las Cienegas Fault and Block 1402 conventional Southwestern Shelf and Adjacent Offshore State Lands 1403 conventional Newport-Inglewood Deformation Zone and Southwestern Flank of Central Syncline 1404 conventional Whittier Fault Zone and Fullerton Embayment 1405 conventional Northern Shelf and Northern Flank of Central Syncline 1406 conventional Anaheim Nose 1407 conventional Chino Marginal Basin, Puente and San Jose Hills, and San Gabriel Valley Marginal Basin proprietary
-USGS_DDS_P14_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Los Angeles Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -119.63631, 32.7535, -117.52315, 34.17464 https://cmr.earthdata.nasa.gov/search/concepts/C2231554068-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 14 (Los Angeles Basin) are listed here by play number and name: Number Name 1401 Santa Monica Fault System and Las Cienegas Fault and Block 1402 Southwestern Shelf and Adjacent Offshore State Lands 1403 Newport-Inglewood Deformation Zone and Southwestern Flank of Central Syncline 1404 Whittier Fault Zone and Fullerton Embayment 1405 Northern Shelf and Northern Flank of Central Syncline 1406 Anaheim Nose 1407 Chino Marginal Basin, Puente and San Jose Hills, and San Gabriel Valley Marginal Basin proprietary
USGS_DDS_P14_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Los Angeles Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -119.63631, 32.7535, -117.52315, 34.17464 https://cmr.earthdata.nasa.gov/search/concepts/C2231554068-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 14 (Los Angeles Basin) are listed here by play number and name: Number Name 1401 Santa Monica Fault System and Las Cienegas Fault and Block 1402 Southwestern Shelf and Adjacent Offshore State Lands 1403 Newport-Inglewood Deformation Zone and Southwestern Flank of Central Syncline 1404 Whittier Fault Zone and Fullerton Embayment 1405 Northern Shelf and Northern Flank of Central Syncline 1406 Anaheim Nose 1407 Chino Marginal Basin, Puente and San Jose Hills, and San Gabriel Valley Marginal Basin proprietary
+USGS_DDS_P14_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Los Angeles Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -119.63631, 32.7535, -117.52315, 34.17464 https://cmr.earthdata.nasa.gov/search/concepts/C2231554068-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 14 (Los Angeles Basin) are listed here by play number and name: Number Name 1401 Santa Monica Fault System and Las Cienegas Fault and Block 1402 Southwestern Shelf and Adjacent Offshore State Lands 1403 Newport-Inglewood Deformation Zone and Southwestern Flank of Central Syncline 1404 Whittier Fault Zone and Fullerton Embayment 1405 Northern Shelf and Northern Flank of Central Syncline 1406 Anaheim Nose 1407 Chino Marginal Basin, Puente and San Jose Hills, and San Gabriel Valley Marginal Basin proprietary
USGS_DDS_P15_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Diego - Oceanside Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -117.75433, 32.527184, -115.904816, 34.236046 https://cmr.earthdata.nasa.gov/search/concepts/C2231553715-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 15 (San Diego - Oceanside) are listed here by play number, type, and name. proprietary
USGS_DDS_P15_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the San Diego - Oceanside Province ALL STAC Catalog 1990-12-01 1990-12-01 -117.75433, 32.527184, -115.904816, 34.236046 https://cmr.earthdata.nasa.gov/search/concepts/C2231553715-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 15 (San Diego - Oceanside) are listed here by play number, type, and name. proprietary
-USGS_DDS_P16_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Salton Trough Province ALL STAC Catalog 1990-12-01 1990-12-01 -116.66911, 32.634293, -114.74501, 34.02059 https://cmr.earthdata.nasa.gov/search/concepts/C2231548651-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 16 (Salton Trough) are listed here by play number, type, and name. proprietary
USGS_DDS_P16_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Salton Trough Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -116.66911, 32.634293, -114.74501, 34.02059 https://cmr.earthdata.nasa.gov/search/concepts/C2231548651-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 16 (Salton Trough) are listed here by play number, type, and name. proprietary
-USGS_DDS_P17_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Idaho - Snake River Downwarp Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -117.24303, 41.99332, -111.04548, 49.00115 https://cmr.earthdata.nasa.gov/search/concepts/C2231550494-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 17 (Idaho - Snake River Downwarp) are listed here by play number, type, and name: Number Type Name 1701 conventional Miocene Lacustrine (Lake Bruneau) 1702 conventional Pliocene Lacustrine (Lake Idaho) 1703 conventional Pre-Miocene 1704 conventional Older Tertiary proprietary
+USGS_DDS_P16_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Salton Trough Province ALL STAC Catalog 1990-12-01 1990-12-01 -116.66911, 32.634293, -114.74501, 34.02059 https://cmr.earthdata.nasa.gov/search/concepts/C2231548651-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 16 (Salton Trough) are listed here by play number, type, and name. proprietary
USGS_DDS_P17_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Idaho - Snake River Downwarp Province ALL STAC Catalog 1990-12-01 1990-12-01 -117.24303, 41.99332, -111.04548, 49.00115 https://cmr.earthdata.nasa.gov/search/concepts/C2231550494-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 17 (Idaho - Snake River Downwarp) are listed here by play number, type, and name: Number Type Name 1701 conventional Miocene Lacustrine (Lake Bruneau) 1702 conventional Pliocene Lacustrine (Lake Idaho) 1703 conventional Pre-Miocene 1704 conventional Older Tertiary proprietary
+USGS_DDS_P17_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Idaho - Snake River Downwarp Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -117.24303, 41.99332, -111.04548, 49.00115 https://cmr.earthdata.nasa.gov/search/concepts/C2231550494-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 17 (Idaho - Snake River Downwarp) are listed here by play number, type, and name: Number Type Name 1701 conventional Miocene Lacustrine (Lake Bruneau) 1702 conventional Pliocene Lacustrine (Lake Idaho) 1703 conventional Pre-Miocene 1704 conventional Older Tertiary proprietary
USGS_DDS_P17_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Idaho - Snake River Downwarp Province ALL STAC Catalog 1996-01-01 1996-12-31 -117.24303, 41.99332, -111.04548, 49.00115 https://cmr.earthdata.nasa.gov/search/concepts/C2231548537-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 17 (Idaho - Snake River Downwarp) are listed here by play number and name: Number Name 1701 Miocene Lacustrine (Lake Bruneau) 1702 Pliocene Lacustrine (Lake Idaho) 1703 Pre-Miocene 1704 Older Tertiary proprietary
USGS_DDS_P17_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Idaho - Snake River Downwarp Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -117.24303, 41.99332, -111.04548, 49.00115 https://cmr.earthdata.nasa.gov/search/concepts/C2231548537-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 17 (Idaho - Snake River Downwarp) are listed here by play number and name: Number Name 1701 Miocene Lacustrine (Lake Bruneau) 1702 Pliocene Lacustrine (Lake Idaho) 1703 Pre-Miocene 1704 Older Tertiary proprietary
-USGS_DDS_P18_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Western Great Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -122.29004, 32.717037, -114.13121, 44.563953 https://cmr.earthdata.nasa.gov/search/concepts/C2231554181-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 18 (Western Great Basin) are listed here by play number, type, and name: Number Type Name 1801 conventional Hornbrook Basin-Modoc Plateau 1802 conventional Eastern Oregon Neogene Basins 1803 conventional Permian-Triassic Source Rocks Northwestern Nevada and East Central and Eastern Oregon 1804 conventional Cretaceous Source Rocks, Northwestern Nevada 1805 conventional Neogene Source Rocks, Northwestern Nevada and Eastern California proprietary
USGS_DDS_P18_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Western Great Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -122.29004, 32.717037, -114.13121, 44.563953 https://cmr.earthdata.nasa.gov/search/concepts/C2231554181-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 18 (Western Great Basin) are listed here by play number, type, and name: Number Type Name 1801 conventional Hornbrook Basin-Modoc Plateau 1802 conventional Eastern Oregon Neogene Basins 1803 conventional Permian-Triassic Source Rocks Northwestern Nevada and East Central and Eastern Oregon 1804 conventional Cretaceous Source Rocks, Northwestern Nevada 1805 conventional Neogene Source Rocks, Northwestern Nevada and Eastern California proprietary
+USGS_DDS_P18_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Western Great Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -122.29004, 32.717037, -114.13121, 44.563953 https://cmr.earthdata.nasa.gov/search/concepts/C2231554181-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 18 (Western Great Basin) are listed here by play number, type, and name: Number Type Name 1801 conventional Hornbrook Basin-Modoc Plateau 1802 conventional Eastern Oregon Neogene Basins 1803 conventional Permian-Triassic Source Rocks Northwestern Nevada and East Central and Eastern Oregon 1804 conventional Cretaceous Source Rocks, Northwestern Nevada 1805 conventional Neogene Source Rocks, Northwestern Nevada and Eastern California proprietary
USGS_DDS_P18_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Western Great Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -122.29004, 32.717037, -114.13121, 44.563953 https://cmr.earthdata.nasa.gov/search/concepts/C2231549693-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 18 (Western Great Basin) are listed here by play number and name: Number Name 1801 Hornbrook Basin-Modoc Plateau 1802 Eastern Oregon Neogene Basins 1803 Permian-Triassic Source Rocks Northwestern Nevada and East Central and Eastern Oregon 1804 Cretaceous Source Rocks, Northwestern Nevada 1805 Neogene Source Rocks, Northwestern Nevada and Eastern California proprietary
USGS_DDS_P18_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Western Great Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -122.29004, 32.717037, -114.13121, 44.563953 https://cmr.earthdata.nasa.gov/search/concepts/C2231549693-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 18 (Western Great Basin) are listed here by play number and name: Number Name 1801 Hornbrook Basin-Modoc Plateau 1802 Eastern Oregon Neogene Basins 1803 Permian-Triassic Source Rocks Northwestern Nevada and East Central and Eastern Oregon 1804 Cretaceous Source Rocks, Northwestern Nevada 1805 Neogene Source Rocks, Northwestern Nevada and Eastern California proprietary
-USGS_DDS_P19_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Eastern Great Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -117.02622, 35.002083, -111.170425, 43.022377 https://cmr.earthdata.nasa.gov/search/concepts/C2231552402-CEOS_EXTRA.umm_json "The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 19 (Eastern Great Basin) are listed here by play number, type, and name: Number Type Name 1901 conventional Unconformity ""A"" 1902 conventional Late Paleozoic 1903 conventional Early Tertiary - Late Cretaceous Sheep Pass and Equivalents 1905 conventional Younger Tertiary Basins 1906 conventional Late Paleozoic - Mesozoic (Central Nevada) Thrust Belt 1907 conventional Sevier Frontal Zone" proprietary
USGS_DDS_P19_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Eastern Great Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -117.02622, 35.002083, -111.170425, 43.022377 https://cmr.earthdata.nasa.gov/search/concepts/C2231552402-CEOS_EXTRA.umm_json "The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 19 (Eastern Great Basin) are listed here by play number, type, and name: Number Type Name 1901 conventional Unconformity ""A"" 1902 conventional Late Paleozoic 1903 conventional Early Tertiary - Late Cretaceous Sheep Pass and Equivalents 1905 conventional Younger Tertiary Basins 1906 conventional Late Paleozoic - Mesozoic (Central Nevada) Thrust Belt 1907 conventional Sevier Frontal Zone" proprietary
-USGS_DDS_P19_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Eastern Great Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -117.02622, 35.002083, -111.170425, 43.022377 https://cmr.earthdata.nasa.gov/search/concepts/C2231551249-CEOS_EXTRA.umm_json "The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 19 (Eastern Great Basin) are listed here by play number and name: Number Name 1901 Unconformity ""A"" 1902 Late Paleozoic 1903 Early Tertiary - Late Cretaceous Sheep Pass and Equivalents 1905 Younger Tertiary Basins 1906 Late Paleozoic - Mesozoic (Central Nevada) Thrust Belt 1907 Sevier Frontal Zone" proprietary
+USGS_DDS_P19_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Eastern Great Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -117.02622, 35.002083, -111.170425, 43.022377 https://cmr.earthdata.nasa.gov/search/concepts/C2231552402-CEOS_EXTRA.umm_json "The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 19 (Eastern Great Basin) are listed here by play number, type, and name: Number Type Name 1901 conventional Unconformity ""A"" 1902 conventional Late Paleozoic 1903 conventional Early Tertiary - Late Cretaceous Sheep Pass and Equivalents 1905 conventional Younger Tertiary Basins 1906 conventional Late Paleozoic - Mesozoic (Central Nevada) Thrust Belt 1907 conventional Sevier Frontal Zone" proprietary
USGS_DDS_P19_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Eastern Great Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -117.02622, 35.002083, -111.170425, 43.022377 https://cmr.earthdata.nasa.gov/search/concepts/C2231551249-CEOS_EXTRA.umm_json "The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 19 (Eastern Great Basin) are listed here by play number and name: Number Name 1901 Unconformity ""A"" 1902 Late Paleozoic 1903 Early Tertiary - Late Cretaceous Sheep Pass and Equivalents 1905 Younger Tertiary Basins 1906 Late Paleozoic - Mesozoic (Central Nevada) Thrust Belt 1907 Sevier Frontal Zone" proprietary
+USGS_DDS_P19_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Eastern Great Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -117.02622, 35.002083, -111.170425, 43.022377 https://cmr.earthdata.nasa.gov/search/concepts/C2231551249-CEOS_EXTRA.umm_json "The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 19 (Eastern Great Basin) are listed here by play number and name: Number Name 1901 Unconformity ""A"" 1902 Late Paleozoic 1903 Early Tertiary - Late Cretaceous Sheep Pass and Equivalents 1905 Younger Tertiary Basins 1906 Late Paleozoic - Mesozoic (Central Nevada) Thrust Belt 1907 Sevier Frontal Zone" proprietary
USGS_DDS_P20_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Uinta - Piceance Basin Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231553991-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number, type, and name: Number Type Name 2001 conventional Piceance Tertiary Conventional 2002 conventional Uinta Tertiary Oil and Gas 2003 conventional Upper Cretaceous Conventional 2004 conventional Cretaceous Dakota to Jurassic 2005 conventional Permian-Pennsylvanian Sandstones and Carbonates 2007 continuous Tight Gas Piceance Mesaverde Williams Fork 2009 continuous Cretaceous Self-Sourced Fractured Shales Oil 2010 continuous Tight Gas Piceance Mesaverde Iles 2014 conventional Basin Margin Subthrusts 2015 continuous Tight Gas Uinta Tertiary East 2016 continuous Tight Gas Uinta Tertiary West 2018 continuous Basin Flank Uinta Mesaverde 2020 continuous Deep Synclinal Uinta Mesaverde 2050 coalbed gas Uinta Basin - Book Cliffs 2051 coalbed gas Uinta Basin - Sego 2052 coalbed gas Uinta Basin - Emery 2053 coalbed gas Piceance Basin - White River Dome 2054 coalbed gas Piceance Basin - Western Basin Margin 2055 coalbed gas Piceance Basin - Grand Hogback 2056 coalbed gas Piceance Basin - Divide Creek Anticline 2057 coalbed gas Piceance Basin - Igneous Intrusion proprietary
USGS_DDS_P20_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Uinta - Piceance Basin Province ALL STAC Catalog 1990-12-01 1990-12-01 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231553991-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number, type, and name: Number Type Name 2001 conventional Piceance Tertiary Conventional 2002 conventional Uinta Tertiary Oil and Gas 2003 conventional Upper Cretaceous Conventional 2004 conventional Cretaceous Dakota to Jurassic 2005 conventional Permian-Pennsylvanian Sandstones and Carbonates 2007 continuous Tight Gas Piceance Mesaverde Williams Fork 2009 continuous Cretaceous Self-Sourced Fractured Shales Oil 2010 continuous Tight Gas Piceance Mesaverde Iles 2014 conventional Basin Margin Subthrusts 2015 continuous Tight Gas Uinta Tertiary East 2016 continuous Tight Gas Uinta Tertiary West 2018 continuous Basin Flank Uinta Mesaverde 2020 continuous Deep Synclinal Uinta Mesaverde 2050 coalbed gas Uinta Basin - Book Cliffs 2051 coalbed gas Uinta Basin - Sego 2052 coalbed gas Uinta Basin - Emery 2053 coalbed gas Piceance Basin - White River Dome 2054 coalbed gas Piceance Basin - Western Basin Margin 2055 coalbed gas Piceance Basin - Grand Hogback 2056 coalbed gas Piceance Basin - Divide Creek Anticline 2057 coalbed gas Piceance Basin - Igneous Intrusion proprietary
-USGS_DDS_P20_continuous 1995 National Oil and Gas Assessment Continuous-Type Plays within the Uinta - Piceance Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231554716-CEOS_EXTRA.umm_json The purpose of the play map is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Continuous oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number and name: Number Name 2007 Tight Gas Piceance Mesaverde Williams Fork 2009 Cretaceous Self-Sourced Fractured Shales Oil 2010 Tight Gas Piceance Mesaverde Iles 2015 Tight Gas Uinta Tertiary East 2016 Tight Gas Uinta Tertiary West 2018 Basin Flank Uinta Mesaverde 2020 Deep Synclinal Uinta Mesaverde 2050 Uinta Basin - Book Cliffs 2051 Uinta Basin - Sego 2052 Uinta Basin - Emery 2053 Piceance Basin - White River Dome 2054 Piceance Basin - Western Basin Margin 2055 Piceance Basin - Grand Hogback 2056 Piceance Basin - Divide Creek Anticline 2057 Piceance Basin - Igneous Intrusion proprietary
USGS_DDS_P20_continuous 1995 National Oil and Gas Assessment Continuous-Type Plays within the Uinta - Piceance Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231554716-CEOS_EXTRA.umm_json The purpose of the play map is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Continuous oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number and name: Number Name 2007 Tight Gas Piceance Mesaverde Williams Fork 2009 Cretaceous Self-Sourced Fractured Shales Oil 2010 Tight Gas Piceance Mesaverde Iles 2015 Tight Gas Uinta Tertiary East 2016 Tight Gas Uinta Tertiary West 2018 Basin Flank Uinta Mesaverde 2020 Deep Synclinal Uinta Mesaverde 2050 Uinta Basin - Book Cliffs 2051 Uinta Basin - Sego 2052 Uinta Basin - Emery 2053 Piceance Basin - White River Dome 2054 Piceance Basin - Western Basin Margin 2055 Piceance Basin - Grand Hogback 2056 Piceance Basin - Divide Creek Anticline 2057 Piceance Basin - Igneous Intrusion proprietary
-USGS_DDS_P20_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Uinta - Piceance Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231552272-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number and name: Number Name 2001 Piceance Tertiary Conventional 2002 Uinta Tertiary Oil and Gas 2003 Upper Cretaceous Conventional 2004 Cretaceous Dakota to Jurassic 2005 Permian-Pennsylvanian Sandstones and Carbonates 2014 Basin Margin Subthrusts proprietary
+USGS_DDS_P20_continuous 1995 National Oil and Gas Assessment Continuous-Type Plays within the Uinta - Piceance Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231554716-CEOS_EXTRA.umm_json The purpose of the play map is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Continuous oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number and name: Number Name 2007 Tight Gas Piceance Mesaverde Williams Fork 2009 Cretaceous Self-Sourced Fractured Shales Oil 2010 Tight Gas Piceance Mesaverde Iles 2015 Tight Gas Uinta Tertiary East 2016 Tight Gas Uinta Tertiary West 2018 Basin Flank Uinta Mesaverde 2020 Deep Synclinal Uinta Mesaverde 2050 Uinta Basin - Book Cliffs 2051 Uinta Basin - Sego 2052 Uinta Basin - Emery 2053 Piceance Basin - White River Dome 2054 Piceance Basin - Western Basin Margin 2055 Piceance Basin - Grand Hogback 2056 Piceance Basin - Divide Creek Anticline 2057 Piceance Basin - Igneous Intrusion proprietary
USGS_DDS_P20_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Uinta - Piceance Basin Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231552272-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number and name: Number Name 2001 Piceance Tertiary Conventional 2002 Uinta Tertiary Oil and Gas 2003 Upper Cretaceous Conventional 2004 Cretaceous Dakota to Jurassic 2005 Permian-Pennsylvanian Sandstones and Carbonates 2014 Basin Margin Subthrusts proprietary
+USGS_DDS_P20_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Uinta - Piceance Basin Province ALL STAC Catalog 1996-01-01 1996-12-31 -111.486916, 38.14689, -105.87804, 40.85869 https://cmr.earthdata.nasa.gov/search/concepts/C2231552272-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 20 (Uinta - Piceance Basin) are listed here by play number and name: Number Name 2001 Piceance Tertiary Conventional 2002 Uinta Tertiary Oil and Gas 2003 Upper Cretaceous Conventional 2004 Cretaceous Dakota to Jurassic 2005 Permian-Pennsylvanian Sandstones and Carbonates 2014 Basin Margin Subthrusts proprietary
USGS_DDS_P2_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Central Alaska Province ALL STAC Catalog 1990-12-01 1990-12-01 -173.22636, 58.49761, -140.99017, 68.01999 https://cmr.earthdata.nasa.gov/search/concepts/C2231550471-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 2 (Central Alaska) are listed here by play number, type, and name: Number Type Name 201 conventional Central Alaska Cenozoic Gas 202 conventional Central Alaska Mesozoic Gas 203 conventional Central Alaska Paleozoic Oil 204 conventional Kandik Pre-Mid-Cretaceous Strata 205 conventional Kandik Upper Cretaceous and Tertiary Non-Marine Stata proprietary
USGS_DDS_P2_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Central Alaska Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -173.22636, 58.49761, -140.99017, 68.01999 https://cmr.earthdata.nasa.gov/search/concepts/C2231550471-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 2 (Central Alaska) are listed here by play number, type, and name: Number Type Name 201 conventional Central Alaska Cenozoic Gas 202 conventional Central Alaska Mesozoic Gas 203 conventional Central Alaska Paleozoic Oil 204 conventional Kandik Pre-Mid-Cretaceous Strata 205 conventional Kandik Upper Cretaceous and Tertiary Non-Marine Stata proprietary
USGS_DDS_P2_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Central Alaska Province ALL STAC Catalog 1996-01-01 1996-12-31 -173.22636, 58.49761, -140.99017, 68.01999 https://cmr.earthdata.nasa.gov/search/concepts/C2231551071-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 2 (Central Alaska) are listed here by play number and name: Number Name 201 Central Alaska Cenozoic Gas 202 Central Alaska Mesozoic Gas 203 Central Alaska Paleozoic Oil 204 Kandik Pre-Mid-Cretaceous Strata 205 Kandik Upper Cretaceous and Tertiary Non-Marine Stata proprietary
USGS_DDS_P2_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Central Alaska Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -173.22636, 58.49761, -140.99017, 68.01999 https://cmr.earthdata.nasa.gov/search/concepts/C2231551071-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 2 (Central Alaska) are listed here by play number and name: Number Name 201 Central Alaska Cenozoic Gas 202 Central Alaska Mesozoic Gas 203 Central Alaska Paleozoic Oil 204 Kandik Pre-Mid-Cretaceous Strata 205 Kandik Upper Cretaceous and Tertiary Non-Marine Stata proprietary
USGS_DOQ USGS Digital Orthophoto Quadrangles USGS_LTA STAC Catalog 1970-01-01 -126, 24, -66, 49 https://cmr.earthdata.nasa.gov/search/concepts/C1220566203-USGS_LTA.umm_json A Digital Orthophoto Quadrangle (DOQ) is a computer-generated image of an aerial photograph in which the image displacement caused by terrain relief and camera tilt has been removed. The DOQ combines the image characteristics of the original photograph with the georeferenced qualities of a map. DOQs are black and white (B/W), natural color, or color-infrared (CIR) images with 1-meter ground resolution. The USGS produces three types of DOQs: 1. 3.75-minute (quarter-quad) DOQs cover an area measuring 3.75-minutes longitude by 3.75-minutes latitude. Most of the U.S. is currently available, and the remaining locations should be complete by 2004. Quarter-quad DOQs are available in both Native and GeoTIFF formats. Native format consists of an ASCII keyword header followed by a series of 8-bit binary image lines for B/W and 24-bit band-interleaved-by-pixel (BIP) for color. DOQs in native format are cast to the Universal Transverse Mercator (UTM) projection and referenced to either the North American Datum (NAD) of 1927 (NAD27) or the NAD of 1983 (NAD83). GeoTIFF format consists of a georeferenced Tagged Image File Format (TIFF), with all geographic referencing information embedded within the .tif file. DOQs in GeoTIFF format are cast to the UTM projection and referenced to NAD83. The average file size of a B/W quarter quad is 40-45 megabytes, and a color file is generally 140-150 megabytes. Quarter-quad DOQs are distributed via File Transfer Protocol (FTP) as uncompressed files. 2. 7.5-minute (full-quad) DOQs cover an area measuring 7.5-minutes longitude by 7.5-minutes latitude. Full-quad DOQs are mostly available for Oregon, Washington, and Alaska. Limited coverage may also be available for other states. Full-quad DOQs are available in both Native and GeoTIFF formats. Native is formatted with an ASCII keyword header followed by a series of 8-bit binary image lines for B/W. DOQs in native format are cast to the UTM projection and referenced to either NAD27 or NAD83. GeoTIFF is a georeferenced Tagged Image File Format with referencing information embedded within the .tif file. DOQs in GeoTIFF format are cast to the UTM projection and referenced to NAD83. The average file size of a B/W full quad is 140-150 megabytes. Full-quad DOQs are distributed via FTP as uncompressed files. 3. Seamless DOQs are available for free download from the Seamless site. DOQs on this site are the most current version and are available for the conterminous U.S. [Summary provided by the USGS.] proprietary
-USGS_DS-845_PierScoutDatabase_1.0 A pier-scour database: 2,427 field and laboratory measurements of pier scour ALL STAC Catalog 1970-01-01 19.6, 16.916668, -52.62, 83.1 https://cmr.earthdata.nasa.gov/search/concepts/C2231553801-CEOS_EXTRA.umm_json The U.S. Geological Survey conducted a literature review to identify potential sources of published pier-scour data, and selected data were compiled into a digital spreadsheet called the 2014 USGS Pier-Scour Database (PSDb-2014) consisting of 569 laboratory and 1,858 field measurements. These data encompass a wide range of laboratory and field conditions and represent field data from 23 States within the United States and from 6 other countries. The digital spreadsheet is available on the Internet and offers a valuable resource to engineers and researchers seeking to understand pier-scour relations in the laboratory and field. proprietary
USGS_DS-845_PierScoutDatabase_1.0 A pier-scour database: 2,427 field and laboratory measurements of pier scour CEOS_EXTRA STAC Catalog 1970-01-01 19.6, 16.916668, -52.62, 83.1 https://cmr.earthdata.nasa.gov/search/concepts/C2231553801-CEOS_EXTRA.umm_json The U.S. Geological Survey conducted a literature review to identify potential sources of published pier-scour data, and selected data were compiled into a digital spreadsheet called the 2014 USGS Pier-Scour Database (PSDb-2014) consisting of 569 laboratory and 1,858 field measurements. These data encompass a wide range of laboratory and field conditions and represent field data from 23 States within the United States and from 6 other countries. The digital spreadsheet is available on the Internet and offers a valuable resource to engineers and researchers seeking to understand pier-scour relations in the laboratory and field. proprietary
+USGS_DS-845_PierScoutDatabase_1.0 A pier-scour database: 2,427 field and laboratory measurements of pier scour ALL STAC Catalog 1970-01-01 19.6, 16.916668, -52.62, 83.1 https://cmr.earthdata.nasa.gov/search/concepts/C2231553801-CEOS_EXTRA.umm_json The U.S. Geological Survey conducted a literature review to identify potential sources of published pier-scour data, and selected data were compiled into a digital spreadsheet called the 2014 USGS Pier-Scour Database (PSDb-2014) consisting of 569 laboratory and 1,858 field measurements. These data encompass a wide range of laboratory and field conditions and represent field data from 23 States within the United States and from 6 other countries. The digital spreadsheet is available on the Internet and offers a valuable resource to engineers and researchers seeking to understand pier-scour relations in the laboratory and field. proprietary
USGS_DS_2006_171 JAMSTEC multibeam surveys and submersible dives around the Hawaiian Islands: A collaborative Japan-USA exploration of Hawaii's deep seafloor CEOS_EXTRA STAC Catalog 1998-01-01 2002-12-31 -161, 16.75, -152.99988, 25.25005 https://cmr.earthdata.nasa.gov/search/concepts/C2231554487-CEOS_EXTRA.umm_json This database release, USGS Data Series 171, contains data collected during four Japan-USA collaborative cruises that characterize the seafloor around the Hawaiian Islands. The Japan Agency for Marine-Earth Science and Technology (JAMSTEC) sponsored cruises in 1998, 1999, 2001, and 2002, to build a greater understanding of the deep marine geology around the Hawaiian Islands. During these cruises, scientists surveyed over 600,000 square kilometers of the seafloor with a hull-mounted multibeam seafloor-mapping sonar system (SEA BEAM® 2112), observed the seafloor and collected samples using robotic and manned submersible dives, collected dredge and piston-core samples, and performed single-channel seismic surveys. To date, 32 research papers have been published describing results from these cruises. For a list of these articles see the bibliography. This digital database was compiled with ESRI ArcInfo version 7.2.2 and ArcGIS 9.0. The GIS files contain multibeam bathymetry, and acoustic backscatter data in ESRI grid format, and dive, seafloor sampling, and siesmic location data in ESRI shapefile format; ArcInfo-compatible GIS software is therefore required to use the files of this database. Metadata for the GIS files are available as text files. The GIS files were also symbolized and used to create Portable Document Format (PDF) files that are ready to be printed. Adobe Reader or other software that can translate PDFs is necessary to print these files. [Summary provided by the USGS.] proprietary
USGS_DS_2006_177 Digital database of recently active traces of the Hayward Fault, California CEOS_EXTRA STAC Catalog 1970-01-01 -128, 35, -120, 42 https://cmr.earthdata.nasa.gov/search/concepts/C2231553624-CEOS_EXTRA.umm_json The purpose of this map is to show the location of and evidence for recent movement on active fault traces within the Hayward Fault Zone, California. The mapped traces represent the integration of the following three different types of data: (1) geomorphic expression, (2) creep (aseismic fault slip),and (3) trench exposures. This publication is a major revision of an earlier map (Lienkaemper, 1992), which both brings up to date the evidence for faulting and makes it available formatted both as a digital database for use within a geographic information system (GIS) and for broader public access interactively using widely available viewing software. The pamphlet describes in detail the types of scientific observations used to make the map, gives references pertaining to the fault and the evidence of faulting, and provides guidance for use of and limitations of the map. [Summary provided by the USGS.] proprietary
USGS_DS_2006_180_1.0 Capitol Lake, Washington, 2004 Data Summary CEOS_EXTRA STAC Catalog 2004-09-21 2005-02-28 -122.9142, 47.0219, -122.9034, 47.0447 https://cmr.earthdata.nasa.gov/search/concepts/C2231548768-CEOS_EXTRA.umm_json At the request of the Washington Department of Ecology (WDOE), the US Geological Survey (USGS) collected bathymetry data in Capital Lake, Olympia, Wash., on September 21, 2004. The data are to be used to calculate sediment infilling rates within the lake as well as for developing the bottom boundary conditions for numerical models of water quality, sediment transport, and morphological change. In addition, the USGS collected sediment samples in Capitol Lake in February, 2005, to help characterize bottom sediment for numerical model calculations and substrate assessment. [Summary provided by the USGS.] proprietary
@@ -15645,8 +15646,8 @@ USGS_DS_2006_203 Archive of Digital Boomer Seismic Reflection Data Collected Dur
USGS_DS_2006_216 Base-Flow Yields of Watersheds in the Berkeley County Area, West Virginia CEOS_EXTRA STAC Catalog 2005-07-25 2006-05-04 -78.1, 39.15, -77.5, 39.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231554130-CEOS_EXTRA.umm_json Base-flow yields at approximately 50 percent of the annual mean ground-water recharge rate were estimated for watersheds in the Berkeley County area, W.Va. These base-flow yields were determined from two sets of discharge measurements made July 25-28, 2005, and May 4, 2006. Two sections of channel along Opequon Creek had net flow losses that are expressed as negative base-flow watershed yields; these and other base-flow watershed yields in the eastern half of the study area ranged from -940 to 2,280 gallons per day per acre ((gal/d)/acre) and averaged 395 (gal/d)/acre. The base-flow yields for watersheds in the western half of the study area ranged from 275 to 482 (gal/d)/acre and averaged 376 (gal/d)/acre. [Summary provided by the USGS.] proprietary
USGS_DS_2006_220 Hurricane Rita Surge Data, Southwestern Louisiana and Southeastern Texas, September to November 2005 CEOS_EXTRA STAC Catalog 1970-01-01 -98, 29, -90, 33 https://cmr.earthdata.nasa.gov/search/concepts/C2231548576-CEOS_EXTRA.umm_json Pressure transducers and high-water marks were used to document the inland water levels related to storm surge generated by Hurricane Rita in southwestern Louisiana and southeastern Texas. On September 22-23, 2005, an experimental monitoring network consisting of 47 pressure transducers (sensors) was deployed at 33 sites over an area of about 4,000 square miles to record the timing, extent, and magnitude of inland hurricane storm surge and coastal flooding. Sensors were programmed to record date and time, temperature, and barometric or water pressure. Water pressure was corrected for changes in barometric pressure and salinity. Elevation surveys using global-positioning systems and differential levels were used to relate all storm-surge water-level data, reference marks, benchmarks, sensor measuring points, and high-water marks to the North American Vertical Datum of 1988 (NAVD 88). The resulting data indicated that storm-surge water levels over 14 feet above NAVD 88 occurred at three locations and rates of water-level rise greater than 5 feet per hour occurred at three locations near the Louisiana coast. Quality-assurance measures were used to assess the variability and accuracy of the water-level data recorded by the sensors. Water-level data from sensors were similar to data from co-located sensors, permanent U.S. Geological Survey streamgages, and water-surface elevations performed by field staff. Water-level data from sensors at selected locations were compared to corresponding high-water mark elevations. In general, the water-level data from sensors were similar to elevations of high quality high-water marks, while reporting consistently higher than elevations of lesser quality high-water marks. [Summary provided by the USGS.] proprietary
USGS_DS_2006_221 Land-Cover and Imperviousness Data for Regional Areas near Denver, Colorado; Dallas-Fort Worth, Texas; and Milwaukee-Green Bay, Wisconsin - 2001 CEOS_EXTRA STAC Catalog 1999-01-01 2002-12-31 -106, 31, -86, 46 https://cmr.earthdata.nasa.gov/search/concepts/C2231548697-CEOS_EXTRA.umm_json This report describes the processing and results of land-cover and impervious surface derivation for parts of three metropolitan areas being studied as part of the U.S. Geological Survey's (USGS) National Water-Quality Assessment (NAWQA) Program Effects of Urbanization on Stream Ecosystems (EUSE). The data were derived primarily from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery from the period 1999-2002, and are provided as 30-meter resolution raster datasets. Data were produced to a standard consistent with data being produced as part of the USGS National Land Cover Database 2001 (NLCD01) Program, and were derived in cooperation with, and assistance from, NLCD01 personnel. The data were intended as surrogates for NLCD01 data because of the EUSE Program's time-critical need for updated land-cover for parts of the United States that would not be available in time from the NLCD01 Program. Six datasets are described in this report: separate land-cover (15-class categorical data) and imperviousness (0-100 percent continuous data) raster datasets for parts of the general Denver, Colorado area (South Platte River Basin), Dallas-Fort Worth, Texas area (Trinity River Basin), and Milwaukee-Green Bay, Wisconsin area (Western Lake Michigan Drainages). [Summary provided by the USGS.] proprietary
-USGS_DS_2006_224 Aeromagnetic Survey of Taylor Mountains Area in Southwest Alaska, A Website for the Distribution of Data ALL STAC Catalog 2004-04-17 2004-05-31 -160, 60, -156, 61 https://cmr.earthdata.nasa.gov/search/concepts/C2231550160-CEOS_EXTRA.umm_json An airborne high-resolution magnetic and coincidental horizontal magnetic graviometer survey was completed over the Taylor Mountains area in southwest Alaska. The flying was undertaken by McPhar Geosurveys Ltd. on behalf of the United States Geological Survey (USGS). First tests and calibration flights were completed by April 7, 2004, and data acquisition was initiated on April 17, 2004. The final data acquisition and final test/calibrations flight was completed on May 31, 2004. Data acquired during the survey totaled 8,971.15 line-miles. [Summary provided by the USGS.] proprietary
USGS_DS_2006_224 Aeromagnetic Survey of Taylor Mountains Area in Southwest Alaska, A Website for the Distribution of Data CEOS_EXTRA STAC Catalog 2004-04-17 2004-05-31 -160, 60, -156, 61 https://cmr.earthdata.nasa.gov/search/concepts/C2231550160-CEOS_EXTRA.umm_json An airborne high-resolution magnetic and coincidental horizontal magnetic graviometer survey was completed over the Taylor Mountains area in southwest Alaska. The flying was undertaken by McPhar Geosurveys Ltd. on behalf of the United States Geological Survey (USGS). First tests and calibration flights were completed by April 7, 2004, and data acquisition was initiated on April 17, 2004. The final data acquisition and final test/calibrations flight was completed on May 31, 2004. Data acquired during the survey totaled 8,971.15 line-miles. [Summary provided by the USGS.] proprietary
+USGS_DS_2006_224 Aeromagnetic Survey of Taylor Mountains Area in Southwest Alaska, A Website for the Distribution of Data ALL STAC Catalog 2004-04-17 2004-05-31 -160, 60, -156, 61 https://cmr.earthdata.nasa.gov/search/concepts/C2231550160-CEOS_EXTRA.umm_json An airborne high-resolution magnetic and coincidental horizontal magnetic graviometer survey was completed over the Taylor Mountains area in southwest Alaska. The flying was undertaken by McPhar Geosurveys Ltd. on behalf of the United States Geological Survey (USGS). First tests and calibration flights were completed by April 7, 2004, and data acquisition was initiated on April 17, 2004. The final data acquisition and final test/calibrations flight was completed on May 31, 2004. Data acquired during the survey totaled 8,971.15 line-miles. [Summary provided by the USGS.] proprietary
USGS_DS_2006_234_1.0 Nevada Magnetic and Gravity Maps and Data: A Website for the Distribution of Data CEOS_EXTRA STAC Catalog 1970-01-01 -120, 35, -114, 42 https://cmr.earthdata.nasa.gov/search/concepts/C2231548572-CEOS_EXTRA.umm_json Magnetic anomalies are due to variations in the Earth's magnetic field caused by the uneven distribution of magnetic minerals (primarily magnetite) in the rocks that make up the upper part of the Earth's crust. The features and patterns of the magnetic anomalies can be used to delineate details of subsurface geology, including the locations of buried faults and magnetite-bearing rocks and the depth to the base of sedimentary basins. This information is valuable for mineral exploration, geologic mapping, and environmental studies. The Nevada magnetic map is constructed from grids that combine information (see data processing details) collected in 82 separate magnetic surveys conducted between 1947 and 2004. The data from these surveys are of varying quality. The design and specifications (terrain clearance, sampling rates, line spacing, and reduction procedures) varied from survey to survey depending on the purpose of the project and the technology of that time. [Summary provided by the USGS.] proprietary
USGS_DS_2007_119 Archive of Digital Boomer Seismic Reflection Data Collected During USGS Field Activity 04SGI01 in the Withlacoochee River of West-Central Florida, March 2004 CEOS_EXTRA STAC Catalog 2004-03-01 2004-03-05 -82.4575, 28.519396, -82.168434, 29.043365 https://cmr.earthdata.nasa.gov/search/concepts/C2231550488-CEOS_EXTRA.umm_json In March of 2004, the U.S. Geological Survey conducted a geophysical survey in the Withlacoochee River of west-central Florida. This report serves as an archive of unprocessed digital boomer seismic reflection data, trackline maps, navigation files, GIS information, Field Activity Collection System (FACS) logs, observer's logbook, and FGDC metadata. Filtered and gained digital images of the seismic profiles are also provided. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Example SU processing scripts and USGS software for viewing the SEG-Y files (Zihlman, 1992) are also provided. [Summary provided by the USGS.] proprietary
USGS_DS_2007_242 Archive of Digital Chirp Seismic Reflection Data Collected During USGS Cruise 05SCC01 Offshore of Port Fourchon and Timbalier Bay, Louisiana, August 2005 CEOS_EXTRA STAC Catalog 2005-08-08 2005-08-11 -90.417816, 29.022211, -89.955574, 29.114426 https://cmr.earthdata.nasa.gov/search/concepts/C2231551890-CEOS_EXTRA.umm_json In August of 2005, the U.S. Geological Survey conducted geophysical surveys offshore of Port Fourchon and Timbalier Bay, Louisiana, and in nearby waterbodies. This report serves as an archive of unprocessed digital chirp seismic reflection data, trackline maps, navigation files, GIS information, Field Activity Collection System (FACS) logs, observer's logbook, and formal FGDC metadata. Filtered and gained digital images of the seismic profiles are also provided. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU). Example SU processing scripts and USGS software for viewing the SEG-Y files (Zihlman, 1992) are also provided. [Summary provided by the USGS.] proprietary
@@ -15753,10 +15754,10 @@ USGS_NPS_AcadiaAccuracy_Final Acadia National Park Vegetation Mapping Project -
USGS_NPS_AcadiaAccuracy_Final Acadia National Park Vegetation Mapping Project - Accuracy Assessment Points ALL STAC Catalog 2003-10-01 2003-10-01 -75.262726, 43.99941, -68.044304, 44.48051 https://cmr.earthdata.nasa.gov/search/concepts/C2231554200-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). Thematic accuracy requirements of the VMP specify 80% accuracy for each map class (theme) that represents National Vegetation Classification System (NVCS) associations (vegetation communities). The UMESC selected 728 field sites, all within Acadia National Park fee and easement lands, for a thematic accuracy assessment (AA) to the vegetation map. The sites were randomly generated, stratified to map class themes that represent NVCS natural/semi-natural vegetation communities using VMP standards. Certain modifications to the process were necessary to accommodate logistical challenges. Local botanists collected field data for 724 of the sites during the 1999 field season. Thematic AA used 688 sites. Sites not used for the analysis were due to the elimination of an entire map class because of irreconcilable classification concepts (19 sites), or to other reasons including unmanageable error with GPS coordinate, duplicate site location, and incomplete field data (17 sites). Regardless of their use in the analysis, all 724 AA sites collected are represented in the Accuracy Assessment Site Spatial Database. proprietary
USGS_NPS_AcadiaFieldPlots_Final Acadia National Park Vegetation Mapping Project - Field Plot Points ALL STAC Catalog 2003-10-01 2003-10-01 -68.65603, 44.017136, -68.045715, 44.404953 https://cmr.earthdata.nasa.gov/search/concepts/C2231549568-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). In support of mapping and classifying the vegetation, vegetation sample plots were collected and analyzed, identifying 53 National Vegetation Classification System natural/semi-natural associations (vegetation communities). Local botanists, via contract with The Nature Conservancy, collected 179 vegetation plot samples at Acadia National Park (NP) during the 1997-1999 field seasons. Maine Natural Areas Program performed ordination analysis using the field plot data and other existing vegetation data of the area. Vegetation communities of Acadia NP are defined and described at the local and global scale. All 179 vegetation plot samples are represented in the Vegetation Field Plot Spatial Database with selected data fields from the Project's PLOTS database. proprietary
USGS_NPS_AcadiaFieldPlots_Final Acadia National Park Vegetation Mapping Project - Field Plot Points CEOS_EXTRA STAC Catalog 2003-10-01 2003-10-01 -68.65603, 44.017136, -68.045715, 44.404953 https://cmr.earthdata.nasa.gov/search/concepts/C2231549568-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). In support of mapping and classifying the vegetation, vegetation sample plots were collected and analyzed, identifying 53 National Vegetation Classification System natural/semi-natural associations (vegetation communities). Local botanists, via contract with The Nature Conservancy, collected 179 vegetation plot samples at Acadia National Park (NP) during the 1997-1999 field seasons. Maine Natural Areas Program performed ordination analysis using the field plot data and other existing vegetation data of the area. Vegetation communities of Acadia NP are defined and described at the local and global scale. All 179 vegetation plot samples are represented in the Vegetation Field Plot Spatial Database with selected data fields from the Project's PLOTS database. proprietary
-USGS_NPS_AcadiaParkBoundary_Final Acadia National Park Vegetation Mapping Project - Park Boundary CEOS_EXTRA STAC Catalog 2003-10-01 2003-10-01 -68.944374, 43.99941, -68.02303, 44.48051 https://cmr.earthdata.nasa.gov/search/concepts/C2231550835-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). In support of the mapping project, various spatial database boundary coverages were either produced or modified from their original source. These boundary coverages are: 1) Project Boundary, 2) Map Data Boundary, 3) Park Boundary, and 4) Quad Boundary. The spatial coverages are projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. proprietary
USGS_NPS_AcadiaParkBoundary_Final Acadia National Park Vegetation Mapping Project - Park Boundary ALL STAC Catalog 2003-10-01 2003-10-01 -68.944374, 43.99941, -68.02303, 44.48051 https://cmr.earthdata.nasa.gov/search/concepts/C2231550835-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). In support of the mapping project, various spatial database boundary coverages were either produced or modified from their original source. These boundary coverages are: 1) Project Boundary, 2) Map Data Boundary, 3) Park Boundary, and 4) Quad Boundary. The spatial coverages are projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. proprietary
-USGS_NPS_AcadiaSpatialVeg_Final Acadia National Park Vegetation Mapping Project - Spatial Vegetation Data CEOS_EXTRA STAC Catalog 1997-05-27 1997-05-28 -69, 43.99574, -67.99682, 44.50385 https://cmr.earthdata.nasa.gov/search/concepts/C2231552959-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe's U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%. proprietary
+USGS_NPS_AcadiaParkBoundary_Final Acadia National Park Vegetation Mapping Project - Park Boundary CEOS_EXTRA STAC Catalog 2003-10-01 2003-10-01 -68.944374, 43.99941, -68.02303, 44.48051 https://cmr.earthdata.nasa.gov/search/concepts/C2231550835-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) has produced a vegetation spatial database coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). In support of the mapping project, various spatial database boundary coverages were either produced or modified from their original source. These boundary coverages are: 1) Project Boundary, 2) Map Data Boundary, 3) Park Boundary, and 4) Quad Boundary. The spatial coverages are projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. proprietary
USGS_NPS_AcadiaSpatialVeg_Final Acadia National Park Vegetation Mapping Project - Spatial Vegetation Data ALL STAC Catalog 1997-05-27 1997-05-28 -69, 43.99574, -67.99682, 44.50385 https://cmr.earthdata.nasa.gov/search/concepts/C2231552959-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe's U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%. proprietary
+USGS_NPS_AcadiaSpatialVeg_Final Acadia National Park Vegetation Mapping Project - Spatial Vegetation Data CEOS_EXTRA STAC Catalog 1997-05-27 1997-05-28 -69, 43.99574, -67.99682, 44.50385 https://cmr.earthdata.nasa.gov/search/concepts/C2231552959-CEOS_EXTRA.umm_json ABSTRACT: The U.S. Geological Survey (USGS) Upper Midwest Environmental Sciences Center (UMESC) has produced the Vegetation Spatial Database Coverage (vegetation map) for the Acadia National Park Vegetation Mapping Project, USGS-NPS Vegetation Mapping Program (VMP). The vegetation map is of Acadia National Park (NP) and extended environs, providing 99,693 hectares (246,347 acres) of map data. Of this coverage, 52,872 hectares (130,650 acres) is non-vegetated ocean, bay, and estuary (53% of coverage). Acadia NP comprises 19,276 hectares (47,633 acres) of the total data coverage area (19%, 40% not counting ocean and estuary data). Over 7,120 polygons make up the coverage, each with map class description and, for vegetation classes, physiognomic feature information. The spatial database provides crosswalk information to all National Vegetation Classification System (NVCS) floristic and physiognomic levels, and to other established classification systems (NatureServe's U.S. Terrestrial Ecological System Classification, Maine Natural Community Classification, and the USGS Land Use and Land Cover Classification). This mapping project has identified 53 NVCS associations (vegetation communities) at Acadia National Park through analyses of vegetation sample data. These associations are represented in the map coverage with 33 map classes. With all vegetation types, land use classes, and park specific categories combined, 57 map classes define the ground features within the project area (58 classes including the class for no map data). Each polygon within the spatial database map is identified with one of these map classes. In addition, physiognomic modifiers are added to map classes representing vegetation to describe the vegetation structure within a polygon (density, pattern, and height). The spatial database was produced from the interpretation of spring 1997 1:15,840-scale color infrared aerial photographs. The standard minimum mapping unit (MMU) applied is 0.5 hectares (1.25 acres). The interpreted data were transferred and automated using base maps produced from USGS digital orthophoto quadrangles. The finished spatial database is a single seamless coverage, projected in Universal Transverse Mercator, Zone 19, with datum in North American Datum of 1983. The estimated overall thematic accuracy for vegetation map classes is 80%. proprietary
USGS_NSHMP National Seismic Hazard Maps from the USGS National Seismic Hazard Mapping Project CEOS_EXTRA STAC Catalog 1970-01-01 170, 18, -65, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2231550531-CEOS_EXTRA.umm_json The National Seismic Hazard Mapping Project (NSHMP) provides online maps. The hazard maps depict probabilistic ground motions and spectral response with 10%, 5%, and 2% probabilities of exceedance (PE) in 50 years. These maps correspond to return times of approximately 500, 1000, and 2500 years, respectively. The maps are based on the assumption that earthquake occurrence is Poissonian, so that the probability of occurrence is time-independent. The maps cover all of the U.S. including Hawaii and Alaska along with other pertinent information related to earthquake hazards. proprietary
USGS_NWRC_LA_LandChange_1932-2010 Land Area Change in Coastal Louisiana from 1932 to 2010 CEOS_EXTRA STAC Catalog 1932-01-01 2010-12-31 -94, 29, -89, 31 https://cmr.earthdata.nasa.gov/search/concepts/C2231549617-CEOS_EXTRA.umm_json The analyses of landscape change presented in this dataset use historical surveys, aerial data, and satellite data to track landscape changes in coastal Louisiana. Persistent loss and gain data are presented for 1932-2010. The U.S. Geological Survey (USGS) analyzed landscape changes in coastal Louisiana by determining land and water classifications for 17 datasets. These datasets include survey data from 1932, aerial data from 1956, and Landsat Multispectral Scanner System (MSS) and Thematic Mapper (TM) data from the 1970s to 2010. proprietary
USGS_OF99-535_1.0 Middle Pliocene Paleoenvironmental Reconstruction: PRISM2 CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231553168-CEOS_EXTRA.umm_json As part of the USGS Global Change Research effort, the PRISM (Pliocene Research, Interpretation and Synoptic Mapping) Project has documented the characteristics of middle Pliocene climate on a global scale. The middle Pliocene was selected for detailed study because it spans the transition from relatively warm global climates when glaciers were absent or greatly reduced in the Northern Hemisphere to the generally cooler climates of the Pleistocene with expanded Northern Hemisphere ice sheets and prominent glacial-interglacial cycles. The purpose of this report is to document and explain the PRISM2 mid Pliocene reconstruction. The PRISM2 reconstruction consists of a series of 28 global scale data sets (Table 1) on a 2° latitude by 2° longitude grid. As such, it is the most complete and detailed global reconstruction of climate and environmental conditions older than the last glacial. PRISM2 evolved from a series of studies that summarized conditions at a large number of marine and terrestrial sites and areas (eg. Cronin and Dowsett, 1991; Poore and Sloan, 1996). The first global reconstruction of mid Pliocene climate (PRISM1) was based upon 64 marine sites and 74 terrestrial sites and included data sets representing annual vegetation and land ice, monthly sea surface temperature (SST) and sea-ice, sea level and topography on a 2°x2° grid (Dowsett et al. (1996) and Thompson and Fleming (1996)). The current reconstruction (PRISM2) is a revision of PRISM1 that incorporates several important differences: 1) Additional sites were added to the marine portion of the reconstruction to improve previous coverage. Sites from the Mediterranean Sea and Indian Ocean are incorporated for the first time in PRISM2. 2) All Pliocene sea surface temperature (SST) estimates were recalculated based upon a new core top calibration to the Reynolds and Smith (1995) adjusted optimum interpolation (AOI) SST data set. This reduced some of the problems previously encountered when different fossil groups were calibrated to different modern climatologies (Climate / Long Range Investigation Mapping and Predictions [CLIMAP], Goddard Institute for Space Sciences [GISS], Advanced Very High Resolution Radiometer [AVHRR], etc.). 3) PRISM2 uses a +25m rise in sea level for the Pliocene (PRISM1 used +35m), in keeping with much new data that has become available. 4) Although the change in global ice volume between PRISM1 and PRISM2 is minor, PRISM2 uses model results from Prentice (personal communication) to guide the areal and topographic distribution of Antarctic ice. This results in a more realistic Antarctic ice configuration in tune with the +25m sea level rise. proprietary
@@ -15871,8 +15872,8 @@ USGS_OFR_2003_230_1.1 Digital depth horizon compilations of the Alaskan North Sl
USGS_OFR_2003_235 High-resolution seismic-reflection surveys in the nearshore of outer Cape Cod, Massachusetts CEOS_EXTRA STAC Catalog 1970-01-01 -73.68, 41.06, -69.75, 43.07 https://cmr.earthdata.nasa.gov/search/concepts/C2231549794-CEOS_EXTRA.umm_json The U.S. Geological Survey (USGS) Woods Hole Field Center (WHFC), in cooperation with the USGS Water Resources Division conducted high-resolution seismic-reflection surveys along the nearshore areas of outer Cape Cod, Massachusetts from Chatham to Provincetown, Massachusetts. The objectives of this investigation were to determine the stratigraphy of the nearshore in relation to the Quaternary stratigraphy of outer Cape Cod by correlating units between the nearshore and onshore and to define the geologic framework of the region. [Summary provided by the USGS.] proprietary
USGS_OFR_2003_236_1.0 National Geochronological Database CEOS_EXTRA STAC Catalog 1970-01-01 -177.1, 13.71, -61.48, 76.63 https://cmr.earthdata.nasa.gov/search/concepts/C2231549399-CEOS_EXTRA.umm_json The National Geochronological Data Base (NGDB) was established by the United States Geological Survey (USGS) to collect and organize published isotopic (also known as radiometric) ages of rocks in the United States. The NGDB (originally known as the Radioactive Age Data Base, RADB) was started in 1974. A committee appointed by the Director of the USGS was given the mission to investigate the feasibility of compiling the published radiometric ages for the United States into a computerized data bank for ready access by the user community. A successful pilot program, which was conducted in 1975 and 1976 for the State of Wyoming, led to a decision to proceed with the compilation of the entire United States. For each dated rock sample reported in published literature, a record containing information on sample location, rock description, analytical data, age, interpretation, and literature citation was constructed and included in the NGDB. The NGDB was originally constructed and maintained on a mainframe computer, and later converted to a Helix Express relational database maintained on an Apple Macintosh desktop computer. The NGDB and a program to search the data files were published and distributed on Compact Disc-Read Only Memory (CD-ROM) in standard ISO 9660 format as USGS Digital Data Series DDS-14 (Zartman and others, 1995). As of May 1994, the NGDB consisted of more than 18,000 records containing over 30,000 individual ages, which is believed to represent approximately one-half the number of ages published for the United States through 1991. Because the organizational unit responsible for maintaining the database was abolished in 1996, and because we wanted to provide the data in more usable formats, we have reformatted the data, checked and edited the information in some records, and provided this online version of the NGDB. This report describes the changes made to the data and formats, and provides instructions for the use of the database in geographic information system (GIS) applications. The data are provided in *.mdb (Microsoft Access), *.xls (Microsoft Excel), and *.txt (tab-separated value) formats. We also provide a single non-relational file that contains a subset of the data for ease of use. [Summary provided by the USGS.] proprietary
USGS_OFR_2003_241_1.0 Contaminated Sediments Database for Long Island Sound and the New York Bight CEOS_EXTRA STAC Catalog 1956-01-01 1997-12-31 -74.99, 38.49333, -71, 41.44219 https://cmr.earthdata.nasa.gov/search/concepts/C2231551092-CEOS_EXTRA.umm_json The Contaminated Sediments Database for Long Island Sound and the New York Bight provides a compilation of published and unpublished sediment texture and contaminant data. This report provides maps of several of the contaminants in the database as well as references and a section on using the data to assess the environmental status of these coastal areas. The database contains information collected between 1956-1997; providing an historical foundation for future contaminant studies in the region. [Summary provided by the USGS.] proprietary
-USGS_OFR_2003_247_1.0 A Digital Geological Map Database For the State of Oklahoma CEOS_EXTRA STAC Catalog 1970-01-01 -103, 33, -94, 37 https://cmr.earthdata.nasa.gov/search/concepts/C2231550225-CEOS_EXTRA.umm_json This report consists of a compilation of twelve digital geologic maps provided in ARC/INFO interchange (e00) format for the state of Oklahoma. The source maps consisted of nine USGS 1:250,000-scale quadrangle maps and three 1:125,000 scale county maps. This publication presents a digital composite of these data intact and without modification across quadrangle boundaries to resolve geologic unit discontinuities. An ESRI ArcView shapefile formatted version and Adobe Acrobat (pdf) plot file of the compiled digital map are also provided. [Summary provided by the USGS.] proprietary
USGS_OFR_2003_247_1.0 A Digital Geological Map Database For the State of Oklahoma ALL STAC Catalog 1970-01-01 -103, 33, -94, 37 https://cmr.earthdata.nasa.gov/search/concepts/C2231550225-CEOS_EXTRA.umm_json This report consists of a compilation of twelve digital geologic maps provided in ARC/INFO interchange (e00) format for the state of Oklahoma. The source maps consisted of nine USGS 1:250,000-scale quadrangle maps and three 1:125,000 scale county maps. This publication presents a digital composite of these data intact and without modification across quadrangle boundaries to resolve geologic unit discontinuities. An ESRI ArcView shapefile formatted version and Adobe Acrobat (pdf) plot file of the compiled digital map are also provided. [Summary provided by the USGS.] proprietary
+USGS_OFR_2003_247_1.0 A Digital Geological Map Database For the State of Oklahoma CEOS_EXTRA STAC Catalog 1970-01-01 -103, 33, -94, 37 https://cmr.earthdata.nasa.gov/search/concepts/C2231550225-CEOS_EXTRA.umm_json This report consists of a compilation of twelve digital geologic maps provided in ARC/INFO interchange (e00) format for the state of Oklahoma. The source maps consisted of nine USGS 1:250,000-scale quadrangle maps and three 1:125,000 scale county maps. This publication presents a digital composite of these data intact and without modification across quadrangle boundaries to resolve geologic unit discontinuities. An ESRI ArcView shapefile formatted version and Adobe Acrobat (pdf) plot file of the compiled digital map are also provided. [Summary provided by the USGS.] proprietary
USGS_OFR_2003_265 Grand Canyon Riverbed Sediment Changes, Experimental Release of September 2000 - A Sample Data Set CEOS_EXTRA STAC Catalog 2000-08-28 2000-09-18 -112.09242, 36.08593, -111.47837, 36.93602 https://cmr.earthdata.nasa.gov/search/concepts/C2231552397-CEOS_EXTRA.umm_json An experimental water release from the Glen Canyon Dam into the Colorado River above Grand Canyon was conducted in September 2000 by the U.S. Bureau of Reclamation. The U.S. Geological Survey (USGS) conducted sidescan sonar surveys between Glen Canyon Dam (mile -15) and Diamond Creek (mile 220), Arizona (mile designations after Stevens, 1998) to determine the sediment characteristics of the Colorado River bed before and after the release. The first survey (R3-00-GC, 28 Aug to 5 Sep 2000) was conducted before the release when the river was at its Low Summer Steady Flow (LSSF) of 8,000 cfs. The second survey (R4-00-GC, 10 to 18 Sep 2000) was conducted immediately after the September 2000 experimental release when the average daily flow was as high as 30,800 cfs as measured below Glen Canyon Dam (Figure 2). Riverbed sediment properties interpreted from the sidescan sonar images include sediment type and sandwaves; overall changes in these properties between the two surveys were calculated. Sidescan sonar data from the USGS surveys were processed for segments of the Colorado River from Glen Canyon Dam (mile -15) to Phantom Ranch (mile 87.7, Figure 3). The surveys targeted pools between rapids that are part of the Grand Canyon Monitoring and Research Center (GCMRC http://www.gcmrc.gov/) physical sciences study. Maps interpreted from the sidescan sonar images show the distribution of sediment types (bedrock, boulders, pebbles or cobbles, and sand) and the extent of sandwaves for each of the pre- and post-flow surveys. The changes between the two surveys were calculated with spatial arithmetric and had properties of fining, coarsening, erosion, deposition, and the appearance or disappearance of sandwaves. This report describes GIS spatial data files for this project and provides examples of the data from the Colorado River near mile 2 below the confluence of the Paria and Colorado Rivers. The complete data set includes sidescan sonar images and interpreted map files for each of the pre- and post-flow surveys and the changes between the segments of rivers. [Summary provided by the USGS.] proprietary
USGS_OFR_2003_267 Catalog of Earthquake Hypocenters at Alaskan Volcanoes: January 1 through December 31, 2002 CEOS_EXTRA STAC Catalog 2002-01-01 2002-12-31 -170, 51, -130, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2231552354-CEOS_EXTRA.umm_json The Alaska Volcano Observatory (AVO), a cooperative program of the U.S. Geological Survey, the Geophysical Institute of the University of Alaska Fairbanks, and the Alaska Division of Geological and Geophysical Surveys, has maintained seismic monitoring networks at historically active volcanoes in Alaska since 1988 (Power and others, 1993; Jolly and others, 1996; Jolly and others, 2001; Dixon and others, 2002). The primary objectives of this program are the seismic monitoring of active, potentially hazardous, Alaskan volcanoes and the investigation of seismic processes associated with active volcanism. This catalog presents the basic seismic data and changes in the seismic monitoring program for the period January 1, 2002 through December 31, 2002. Appendix G contains a list of publications pertaining to seismicity of Alaskan volcanoes based on these and previously recorded data. The AVO seismic network was used to monitor twenty-four volcanoes in real time in 2002. These include Mount Wrangell, Mount Spurr, Redoubt Volcano, Iliamna Volcano, Augustine Volcano, Katmai Volcanic Group (Snowy Mountain, Mount Griggs, Mount Katmai, Novarupta, Trident Volcano, Mount Mageik, Mount Martin), Aniakchak Crater, Mount Veniaminof, Pavlof Volcano, Mount Dutton, Isanotski Peaks, Shishaldin Volcano, Fisher Caldera, Westdahl Peak, Akutan Peak, Makushin Volcano, Great Sitkin Volcano, and Kanaga Volcano (Figure 1). Monitoring highlights in 2002 include an earthquake swarm at Great Sitkin Volcano in May-June; an earthquake swarm near Snowy Mountain in July-September; low frequency (1-3 Hz) tremor and long-period events at Mount Veniaminof in September-October and in December; and continuing volcanogenic seismic swarms at Shishaldin Volcano throughout the year. Instrumentation and data acquisition highlights in 2002 were the installation of a subnetwork on Okmok Volcano, the establishment of telemetry for the Mount Veniaminof subnetwork, and the change in the data acquisition system to an EARTHWORM detection system. AVO located 7430 earthquakes during 2002 in the vicinity of the monitored volcanoes. This catalog includes: (1) a description of instruments deployed in the field and their locations; (2) a description of earthquake detection, recording, analysis, and data archival systems; (3) a description of velocity models used for earthquake locations; (4) a summary of earthquakes located in 2002; and (5) an accompanying UNIX tar-file with a summary of earthquake origin times, hypocenters, magnitudes, and location quality statistics; daily station usage statistics; and all HYPOELLIPSE files used to determine the earthquake locations in 2002. [Summary provided by the USGS.] proprietary
USGS_OFR_2003_85_1.0 Nearshore Benthic Habitat GIS for the Channel Islands National Marine Sanctuary and Southern California State Fisheries Reserves Volume 1 CEOS_EXTRA STAC Catalog 1970-01-01 -122, 33, -119, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2231551552-CEOS_EXTRA.umm_json The nearshore benthic habitat of the Santa Barbara coast and Channel Islands supports diverse marine life that is commercially, recreationally, and intrinsically valuable. Some of these resources are known to be endangered including a variety of rockfish and the white abalone. Agencies of the state of California and the United States have been mandated to preserve and enhance these resources. Data from sidescan sonar, bathymetry, video and dive observations, and physical samples are consolidated in a geographic information system (GIS). The GIS provides researchers and policymakers a view of the relationship among data sets to assist scienctific research and to help with economic and social policy-making decisions regarding this protected environment. [Summary provided by the USGS.] proprietary
@@ -15890,12 +15891,12 @@ USGS_OFR_2004_1038 Inventory of Significant Mineral Deposit Occurrences in the H
USGS_OFR_2004_1039 Location, Age, and Tectonic Significance of the Western Idaho Suture Zone CEOS_EXTRA STAC Catalog 1970-01-01 -118, 43, -112, 47 https://cmr.earthdata.nasa.gov/search/concepts/C2231552012-CEOS_EXTRA.umm_json The Western Idaho Suture Zone (WISZ) represents the boundary between crust overlying Proterozoic North American lithosphere and Late Paleozoic and Mesozoic intraoceanic crust accreted during Cretaceous time. Highly deformed plutons constituted of both arc and sialic components intrude the WISZ and in places are thrust over the accreted terranes. Pronounced variations in Sr, Nd, and O isotope ratios and in major and trace element composition occur across the suture zone in Mesozoic plutons. The WISZ is located by an abrupt west to east increase in initial 87Sr/86Sr ratios, traceable for over 300 km from eastern Washington near Clarkston, east along the Clearwater River thorough a bend to the south of about 110° from Orofino Creek to Harpster, and extending south-southwest to near Ola, Idaho, where Columbia River basalts conceal its extension to the south. K-Ar and 40Ar/39Ar apparent ages of hornblende and biotite from Jurassic and Early Cretaceous plutons in the accreted terranes are highly discordant within about 10 km of the WISZ, exhibiting patterns of thermal loss caused by deformation, subsequent batholith intrusion, and rapid rise of the continental margin. Major crustal movements within the WISZ commenced after about 135 Ma, but much of the displacement may have been largely vertical, during and following emplacement of batholith-scale silicic magmas. Deformation continued until at least 85 Ma and probably until 74 Ma, progressing from south to north. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1049_1.0 Geologic and Bathymetric Reconnaissance Overview of the San Pedro Shelf Region, Southern California CEOS_EXTRA STAC Catalog 2002-01-01 2002-12-31 -118.33333, 33.46667, -117.83333, 33.78333 https://cmr.earthdata.nasa.gov/search/concepts/C2231548808-CEOS_EXTRA.umm_json This report presents a series of maps that describe the bathymetry and late Quaternary geology of the San Pedro shelf area as interpreted from seismic-reflection profiles and 3.5-kHz and multibeam bathymetric data. Some of the seismic-reflection profiles were collected with Uniboom and 120-kJ sparker during surveys conducted by the U.S. Geological Survey (USGS) in 1973 (K-2-73-SC), 1978 (S-2-78-SC), and 1979 (S-2a-79-SC). The remaining seismic-reflection profiles were collected in 2000 using Geopulse boomer and minisparker during USGS cruise A-1-00-SC. The report consists of seven oversized sheets: 1. Map of 1978 and 1979 uniboom seismic-reflection and 3.5-kHz tracklines used to map faults and folds on San Pedro Shelf. 2. Maps of multibeam shaded bathymetric relief with faults and folds, and bathymetric contours. 3. Isopach map of unconsolidated sediment, seismic-reflection profile across the San Pedro shelf, seismic-reflection profile across San Gabriel paleo-valley. 4. Seismic-reflection profiles across the Palos Verdes Fault Zone. 5. Geologic map and samples of Uniboom and 120-kJ sparker seismic-reflection profiles used to make the map. 6. Map showing thickness of uppermost (Holocene?) sediment layer. 7. Map of San Gabriel Canyon paleo-valley and associated drainage basins. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1054 Assessment of Hazards Associated with the Bluegill Landslide, South-Central Idaho CEOS_EXTRA STAC Catalog 1970-01-01 -117.59, 41.64, -110.7, 49.35 https://cmr.earthdata.nasa.gov/search/concepts/C2231554051-CEOS_EXTRA.umm_json The Bluegill landslide, located in south-central Idaho, is part of a larger landslide complex that forms an area in the Salmon Falls Creek drainage named Sinking Canyon. The landslide is on public property administered by the U.S. Bureau of Land Management (BLM). As part of ongoing efforts to address possible public safety concerns, the BLM requested that the U.S. Geological Survey (USGS) conduct a preliminary hazard assessment of the landslide, examine possible mitigation options, and identify alternatives for further study and monitoring of the landslide. This report presents the findings of that assessment based on a field reconnaissance of the landslide on September 24, 2003, a review of data and information provided by BLM and researchers from Idaho State University, and information collected from other sources. [Summary provided by the USGS.] proprietary
-USGS_OFR_2004_1058 2002 Volcanic Activity in Alaska and Kamchatka: Summary of Events and Response of the Alaska Volcano Observatory ALL STAC Catalog 2002-01-01 -168, 46, -126, 76 https://cmr.earthdata.nasa.gov/search/concepts/C2231549438-CEOS_EXTRA.umm_json The Alaska Volcano Observatory (AVO) tracks activity at the more than 40 historically active volcanoes of the Aleutian Arc. As of December 31, 2002, 24 of these volcanoes are monitored with short-period seismometer networks. AVO's monitoring program also includes daily analysis of satellite imagery supported by occasional over flights and compilation of pilot reports, observations of local residents, and observations of mariners. In 2002, AVO responded to eruptive activity or suspect volcanic activity at 6 volcanic centers in Alaska - Wrangell, the Katmai Group, Veniaminof, Shishaldin, Emmons Lake (Hague), and Great Sitkin volcanoes. In addition to responding to eruptive activity at Alaskan volcanoes, AVO also disseminated information on behalf of the Kamchatkan Volcanic Eruption Response Team (KVERT) about activity at 5 Russian volcanoes - Sheveluch, Klyuchevskoy, Bezymianny, Karymsky, and Chikurachki. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1058 2002 Volcanic Activity in Alaska and Kamchatka: Summary of Events and Response of the Alaska Volcano Observatory CEOS_EXTRA STAC Catalog 2002-01-01 -168, 46, -126, 76 https://cmr.earthdata.nasa.gov/search/concepts/C2231549438-CEOS_EXTRA.umm_json The Alaska Volcano Observatory (AVO) tracks activity at the more than 40 historically active volcanoes of the Aleutian Arc. As of December 31, 2002, 24 of these volcanoes are monitored with short-period seismometer networks. AVO's monitoring program also includes daily analysis of satellite imagery supported by occasional over flights and compilation of pilot reports, observations of local residents, and observations of mariners. In 2002, AVO responded to eruptive activity or suspect volcanic activity at 6 volcanic centers in Alaska - Wrangell, the Katmai Group, Veniaminof, Shishaldin, Emmons Lake (Hague), and Great Sitkin volcanoes. In addition to responding to eruptive activity at Alaskan volcanoes, AVO also disseminated information on behalf of the Kamchatkan Volcanic Eruption Response Team (KVERT) about activity at 5 Russian volcanoes - Sheveluch, Klyuchevskoy, Bezymianny, Karymsky, and Chikurachki. [Summary provided by the USGS.] proprietary
+USGS_OFR_2004_1058 2002 Volcanic Activity in Alaska and Kamchatka: Summary of Events and Response of the Alaska Volcano Observatory ALL STAC Catalog 2002-01-01 -168, 46, -126, 76 https://cmr.earthdata.nasa.gov/search/concepts/C2231549438-CEOS_EXTRA.umm_json The Alaska Volcano Observatory (AVO) tracks activity at the more than 40 historically active volcanoes of the Aleutian Arc. As of December 31, 2002, 24 of these volcanoes are monitored with short-period seismometer networks. AVO's monitoring program also includes daily analysis of satellite imagery supported by occasional over flights and compilation of pilot reports, observations of local residents, and observations of mariners. In 2002, AVO responded to eruptive activity or suspect volcanic activity at 6 volcanic centers in Alaska - Wrangell, the Katmai Group, Veniaminof, Shishaldin, Emmons Lake (Hague), and Great Sitkin volcanoes. In addition to responding to eruptive activity at Alaskan volcanoes, AVO also disseminated information on behalf of the Kamchatkan Volcanic Eruption Response Team (KVERT) about activity at 5 Russian volcanoes - Sheveluch, Klyuchevskoy, Bezymianny, Karymsky, and Chikurachki. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1064 Coastal Vulnerability Assessment of Cape Hatteras National Seashore (CAHA) to Sea-Level Rise CEOS_EXTRA STAC Catalog 1970-01-01 -80, 33, -76, 38 https://cmr.earthdata.nasa.gov/search/concepts/C2231549408-CEOS_EXTRA.umm_json A coastal vulnerability index (CVI) was used to map the relative vulnerability of the coast to future sea-level rise within Cape Hatteras National Seashore (CAHA) in North Carolina. The CVI ranks the following in terms of their physical contribution to sea-level rise-related coastal change: geomorphology, regional coastal slope, rate of relative sea-level rise, historical shoreline change rates, mean tidal range, and mean significant wave height. The rankings for each variable were combined and an index value was calculated for 1-minute grid cells covering the park. The CVI highlights those regions where the physical effects of sea-level rise might be the greatest. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, yielding a quantitative, although relative, measure of the park's natural vulnerability to the effects of sea-level rise. The CVI provides an objective technique for evaluation and long-term planning by scientists and park managers. Cape Hatteras National Seashore consists of stable and washover dominated segments of barrier beach backed by wetland and marsh. The areas within Cape Hatteras that are likely to be most vulnerable to sea-level rise are those with the highest occurrence of overwash and the highest rates of shoreline change. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1067 Digital Database of Selected Aggregate and Related Resources in Ada, Boise, Canyon, Elmore, Gem, and Owyhee Counties, Southwestern Idaho CEOS_EXTRA STAC Catalog 1934-01-01 2003-12-31 -117.01154, 42.29952, -115.10053, 44.17547 https://cmr.earthdata.nasa.gov/search/concepts/C2231549777-CEOS_EXTRA.umm_json "The U.S. Geological Survey (USGS) compiled a database of aggregate sites and geotechnical sample data for six counties - Ada, Boise, Canyon, Elmore, Gem, and Owyhee - in southwest Idaho as part of a series of studies in support of the Bureau of Land Management (BLM) planning process. Emphasis is placed on sand and gravel sites in deposits of the Boise River, Snake River, and other fluvial systems and in Neogene lacustrine deposits. Data were collected primarily from unpublished Idaho Transportation Department (ITD) records and BLM site descriptions, published Army Corps of Engineers (ACE) records, and USGS sampling data. The results of this study provides important information needed by land-use planners and resource managers, particularly in the BLM, to anticipate and plan for demand and development of sand and gravel and other mineral material resources on public lands in response to the urban growth in southwestern Idaho. The aggregate database combines two data sets - site information and geotechnical sample data - into an integrated spatial database with 82 unique fields. The material source site data set includes information on 680 sites, and the geotechnical data set consists of selected information from 2,723 laboratory analyses of samples collected from many, but not all, of the sites. The 680 aggregate sites are divided into six classes: sand & gravel (614); rock quarry (43); cinder quarry (9); placer tailings (8); talus (4); and mine waste rock (2). Most importantly, the aggregate database includes detailed location information allowing individual sites to be located at least within a section and most often within a small parcel of a section. Additional information includes, but is not limited to: lithology-mineralogy or geologic formation (if known); surface ownership; size; production; permitting; agency; and number of samples. Geotechnical data include: lab number and test date; field parameters including sample location, type of material, and size; and the results of geotechnical analyses - gradation (grain size distribution), Los Angeles (LA) Degradation, sand equivalent, absorption, density, and several other tests. Ninety-five percent of the 2,723 geotechnical sample records include gradation data, and 72 percent of the samples have sand equivalent data. However, LA Degradation, absorption, and bulk density data are reported only in about 30 percent of the sample records. Large volumes of geotechnical data reside in a variety of accessible but little-used archives maintained by local and county highway districts, state transportation bureaus, and federal engineering, construction and transportation agencies. Integration of good quality geotechnical lithogeochemical information, particularly in digital form suitable for geospatial analysis, can produce profoundly superior databases that may allow more accurate and reliable ""expert"" decision making and improved land use planning. The database that accompanies this report, structured for direct import into geographic information system (GIS) software, is the first step toward producing such an integrated geologic-geotechnical spatial database. [Summary provided by the USGS.]" proprietary
-USGS_OFR_2004_1069 A 30-Year Record of Surface Mass Balance (1966-95) and Motion and Surface Altitude (1975-95) at Wolverine Glacier, Alaska CEOS_EXTRA STAC Catalog 1966-04-01 1995-12-31 -156, 57, -144, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2231554448-CEOS_EXTRA.umm_json Scientific measurements at Wolverine Glacier, on the Kenai Peninsula in south-central Alaska, began in April 1966. At three long-term sites in the research basin, the measurements included snow depth, snow density, heights of the glacier surface and stratigraphic summer surfaces on stakes, and identification of the surface materials. Calculations of the mass balance of the surface strata-snow, new firn, superimposed ice, and old firn and ice mass at each site were based on these measurements. Calculations of fixed-date annual mass balances for each hydrologic year (October 1 to September 30), as well as net balances and the dates of minimum net balance measured between time-transgressive summer surfaces on the glacier, were made on the basis of the strata balances augmented by air temperature and precipitation recorded in the basin. From 1966 through 1995, the average annual balance at site A (590 meters altitude) was -4.06 meters water equivalent; at site B (1,070 meters altitude), was -0.90 meters water equivalent; and at site C (1,290 meters altitude), was +1.45 meters water equivalent. Geodetic determination of displacements of the mass balance stake, and glacier surface altitudes was added to the data set in 1975 to detect the glacier motion responses to variable climate and mass balance conditions. The average surface speed from 1975 to 1996 was 50.0 meters per year at site A, 83.7 meters per year at site B, and 37.2 meters per year at site C. The average surface altitudes were 594 meters at site A, 1,069 meters at site B, and 1,293 meters at site C; the glacier surface altitudes rose and fell over a range of 19.4 meters at site A, 14.1 meters at site B, and 13.2 meters at site C. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1069 A 30-Year Record of Surface Mass Balance (1966-95) and Motion and Surface Altitude (1975-95) at Wolverine Glacier, Alaska ALL STAC Catalog 1966-04-01 1995-12-31 -156, 57, -144, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2231554448-CEOS_EXTRA.umm_json Scientific measurements at Wolverine Glacier, on the Kenai Peninsula in south-central Alaska, began in April 1966. At three long-term sites in the research basin, the measurements included snow depth, snow density, heights of the glacier surface and stratigraphic summer surfaces on stakes, and identification of the surface materials. Calculations of the mass balance of the surface strata-snow, new firn, superimposed ice, and old firn and ice mass at each site were based on these measurements. Calculations of fixed-date annual mass balances for each hydrologic year (October 1 to September 30), as well as net balances and the dates of minimum net balance measured between time-transgressive summer surfaces on the glacier, were made on the basis of the strata balances augmented by air temperature and precipitation recorded in the basin. From 1966 through 1995, the average annual balance at site A (590 meters altitude) was -4.06 meters water equivalent; at site B (1,070 meters altitude), was -0.90 meters water equivalent; and at site C (1,290 meters altitude), was +1.45 meters water equivalent. Geodetic determination of displacements of the mass balance stake, and glacier surface altitudes was added to the data set in 1975 to detect the glacier motion responses to variable climate and mass balance conditions. The average surface speed from 1975 to 1996 was 50.0 meters per year at site A, 83.7 meters per year at site B, and 37.2 meters per year at site C. The average surface altitudes were 594 meters at site A, 1,069 meters at site B, and 1,293 meters at site C; the glacier surface altitudes rose and fell over a range of 19.4 meters at site A, 14.1 meters at site B, and 13.2 meters at site C. [Summary provided by the USGS.] proprietary
+USGS_OFR_2004_1069 A 30-Year Record of Surface Mass Balance (1966-95) and Motion and Surface Altitude (1975-95) at Wolverine Glacier, Alaska CEOS_EXTRA STAC Catalog 1966-04-01 1995-12-31 -156, 57, -144, 66 https://cmr.earthdata.nasa.gov/search/concepts/C2231554448-CEOS_EXTRA.umm_json Scientific measurements at Wolverine Glacier, on the Kenai Peninsula in south-central Alaska, began in April 1966. At three long-term sites in the research basin, the measurements included snow depth, snow density, heights of the glacier surface and stratigraphic summer surfaces on stakes, and identification of the surface materials. Calculations of the mass balance of the surface strata-snow, new firn, superimposed ice, and old firn and ice mass at each site were based on these measurements. Calculations of fixed-date annual mass balances for each hydrologic year (October 1 to September 30), as well as net balances and the dates of minimum net balance measured between time-transgressive summer surfaces on the glacier, were made on the basis of the strata balances augmented by air temperature and precipitation recorded in the basin. From 1966 through 1995, the average annual balance at site A (590 meters altitude) was -4.06 meters water equivalent; at site B (1,070 meters altitude), was -0.90 meters water equivalent; and at site C (1,290 meters altitude), was +1.45 meters water equivalent. Geodetic determination of displacements of the mass balance stake, and glacier surface altitudes was added to the data set in 1975 to detect the glacier motion responses to variable climate and mass balance conditions. The average surface speed from 1975 to 1996 was 50.0 meters per year at site A, 83.7 meters per year at site B, and 37.2 meters per year at site C. The average surface altitudes were 594 meters at site A, 1,069 meters at site B, and 1,293 meters at site C; the glacier surface altitudes rose and fell over a range of 19.4 meters at site A, 14.1 meters at site B, and 13.2 meters at site C. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1074 Flood of June 4, 2002, in the Indian Creek Basin, Linn County, Iowa CEOS_EXTRA STAC Catalog 2002-06-04 2002-06-04 -96.97, 40.05, -89.82, 43.83 https://cmr.earthdata.nasa.gov/search/concepts/C2231549367-CEOS_EXTRA.umm_json Severe flooding occurred on June 4, 2002, in the Indian Creek Basin in Linn County, Iowa, following thunderstorm activity over east-central Iowa. The rain gage at Cedar Rapids, Iowa, recorded a 24-hour rainfall of 4.76 inches at 6:00 p.m. on June 4th. Radar indications estimated as much as 6 inches of rain fell in the headwaters of the Indian Creek Basin. Peak discharges on Indian Creek of 12,500 cubic feet per second at County Home Road north of Marion, Iowa, and 24,300 cubic feet per second at East Post Road in southeast Cedar Rapids, were determined for the flood. The recurrence interval for these peak discharges both exceed the theoretical 500-year flood as computed using flood-estimation equations developed by the U.S. Geological Survey. Information about the basin and flood history, the 2002 thunderstorms and associated flooding, and a profile of high-water marks are presented for selected reaches along Indian and Dry Creeks. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1075 Bedrock Geology and Mineral Resources of the Knoxville 1 degree x 2 degree Quadrangle, Tennessee, North Carolina, and South Carolina (Digital Version) CEOS_EXTRA STAC Catalog 1970-01-01 -90, 33, -78, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2231548820-CEOS_EXTRA.umm_json The following geographic information system (GIS) data layers provide a digital format for the map plate in Bulletin 1979 (Robinson et al., 1991), Bedrock Geology and Mineral Resources of the Knoxville 1 degree x 2 degree Quadrangle, Tennessee, North Carolina, and South Carolina. This open-file report is meant to supplement Bulletin 1979. The Knoxville 1 degree x 2 degree quadrangle spans the Southern Blue Ridge physiographic province at its widest point from eastern Tennessee across western North Carolina to the northwest corner of South Carolina. The quadrangle also contains small parts of the Valley and Ridge province in Tennessee and the Piedmont province in North and South Carolina. The bedrock geology for the coverage area is provided as a polygon coverage with bedrock unit information included. Mineral resources and geologic faults are provided as point and line files, respectively, to overlay the geology coverage. Detailed geologic information is provided in the attribute tables for these files, and .avl legend files are provided. [Summary provided by the USGS.] proprietary
USGS_OFR_2004_1083 Cross-Sections and Maps Showing Double-Difference Relocated Earthquakes from 1984-2000 along the Hayward and Calaveras Faults, California CEOS_EXTRA STAC Catalog 1984-01-01 2000-12-31 -124.9, 32.02, -113.61, 42.51 https://cmr.earthdata.nasa.gov/search/concepts/C2231554080-CEOS_EXTRA.umm_json This report present a cross-section and map views of earthquakes that occurred from 1984 to 2000 in the vicinity of the Hayward and Calaveras faults in the San Francisco Bay region, California. These earthquakes came from a catalog of events relocated using the double-difference technique, which provides superior relative locations of nearby events. As a result, structures such as fault surfaces and alignments of events along these surfaces are more sharply defined than in previous catalogs. [Summary provided by the USGS.] proprietary
@@ -16042,13 +16043,13 @@ USGS_OFR_99-78_1.0 Digital Data Sets Describing Water Use, Toxic Chemical Releas
USGS_OFR_99_414_1.0 Geologic Datasets for Weights-of-Evidence Analysis in Northeast Washington--3. Minerals-Related Permits on National Forests, 1967 to 1998 CEOS_EXTRA STAC Catalog 1998-01-01 1998-12-31 -121.25, 47.25, -117, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231554622-CEOS_EXTRA.umm_json This dataset was developed to provide mineral resource data for the region of northeast WA for use in future spatial analysis by a variety of users. This database is not meant to be used or displayed at any scale larger than 1:24,000. Permits to explore for and (or) develop mineral resources on Federal lands can be used to indicate locations and types of mineral-related activities on national forests. Permits for these activities require filing of a Notice of Intent to conduct mineral exploration activities and (or) a Plan of Operation, if significant land disturbance results. This compilation of notices and plans for the Colville, Kaniksu, Okanogan, and Wenatchee national forests between 1967 and 1998 is intended for use in combination with geologic and economic information to predict future mineral-related activities in the region. This dataset consists of one Excel 97 spreadsheet file (of99-414.xls) which contains information about permits on national forest lands in northeast Washington State. [Summary provided by the USGS.] proprietary
USGS_OFR_99_436 Archive of Sparker Subbottom Data Collected During USGS Cruise ALPH 98013, New York, 10-22 September, 1997 CEOS_EXTRA STAC Catalog 1998-09-10 1998-09-22 -74, 40.16, -73.25, 40.58 https://cmr.earthdata.nasa.gov/search/concepts/C2231550021-CEOS_EXTRA.umm_json This project will generate reconnaissance maps of the sea floor offshore of the New York - New Jersey metropolitan area -- the most heavily populated, and one of the most impacted coastal regions of the United States. The surveys will provide an overall synthesis of the sea floor environment, including seabed texture and bed forms, Quaternary strata geometry, and anthropogenic impact (e.g., ocean dumping, trawling, channel dredging). The goal of this project is to survey the offshore area, the harbor, and the southern shore of Long Island, providing a regional synthesis to support a wide range of management decisions and a basis for further process-oriented investigations. The project is conducted cooperatively with the U.S. Army Corps of Engineer (USACE). This CD-ROM contains digital high resolution seismic reflection data collected during the USGS ALPH 98013 cruise. The seismic-reflection data are stored as SEG-Y standard format that can be read and manipulated by most seismic-processing software. Much of the information specific to the data are contained in the headers of the SEG-Y format files. The file system format is ISO 9660 which can be read with DOS, Unix, and MAC operating systems with the appropriate CD-ROM driver software installed. [Summary provided by the USGS.] proprietary
USGS_OFR_99_438_1.0 Digital geologic map of part of the Thompson Falls 1:100,000 quadrangle, Idaho CEOS_EXTRA STAC Catalog 1999-01-01 1999-12-31 -116, 47.5, -115, 48 https://cmr.earthdata.nasa.gov/search/concepts/C2231554236-CEOS_EXTRA.umm_json This data set was developed to provide geologic map GIS of the Idaho portion of the Thompson Falls 1:100,000 quadrangle for use in future spatial analysis by a variety of users. This database is not meant to be used or displayed at any scale larger than 1:100,000 (e.g., 1:62,500 or 1:24,000). The geology of the Thompson Falls 1:100,000 quadrangle, Idaho was compiled by Reed S. Lewis in 1997 onto a 1:100,000-scale topographic base map for input into an Arc/Info geographic information system (GIS). The digital geologic map database can be queried in many ways to produce a variety of derivative geologic maps. This GIS consists of two major Arc/Info data sets: one line and polygon file (tf100k) containing geologic contacts and structures (lines) and geologic map rock units (polygons), and one point file (tfpnt) containing structural data. [Summary provided by the USGS.] proprietary
-USGS_OFR_Acid_Deposition Acid Deposition Sensitivity of the Southern Appalachian Assessment Area CEOS_EXTRA STAC Catalog 1970-01-01 -87, 31, -77, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2231550930-CEOS_EXTRA.umm_json The Acid Deposition Sensitivity of the Southern Appalachian Assessment Area is a project that studies areas having various susceptibilities to acid deposition from air pollution which are designated on a three tier ranking in the region of the Southern Appalachian Assessment (SAA). The assessment is being conducted by Federal agencies that are members of the Southern Appalachian Man and Biosphere (SAMAB) Cooperative. Sensitivities to acid deposition, ranked high, medium, and low are assigned on the basis of bedrock compositions and their associated soils, and their capacities to neutralize acid precipitation. The data is available in Arc/Info export format. [Summary provided by the USGS] proprietary
USGS_OFR_Acid_Deposition Acid Deposition Sensitivity of the Southern Appalachian Assessment Area ALL STAC Catalog 1970-01-01 -87, 31, -77, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2231550930-CEOS_EXTRA.umm_json The Acid Deposition Sensitivity of the Southern Appalachian Assessment Area is a project that studies areas having various susceptibilities to acid deposition from air pollution which are designated on a three tier ranking in the region of the Southern Appalachian Assessment (SAA). The assessment is being conducted by Federal agencies that are members of the Southern Appalachian Man and Biosphere (SAMAB) Cooperative. Sensitivities to acid deposition, ranked high, medium, and low are assigned on the basis of bedrock compositions and their associated soils, and their capacities to neutralize acid precipitation. The data is available in Arc/Info export format. [Summary provided by the USGS] proprietary
+USGS_OFR_Acid_Deposition Acid Deposition Sensitivity of the Southern Appalachian Assessment Area CEOS_EXTRA STAC Catalog 1970-01-01 -87, 31, -77, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2231550930-CEOS_EXTRA.umm_json The Acid Deposition Sensitivity of the Southern Appalachian Assessment Area is a project that studies areas having various susceptibilities to acid deposition from air pollution which are designated on a three tier ranking in the region of the Southern Appalachian Assessment (SAA). The assessment is being conducted by Federal agencies that are members of the Southern Appalachian Man and Biosphere (SAMAB) Cooperative. Sensitivities to acid deposition, ranked high, medium, and low are assigned on the basis of bedrock compositions and their associated soils, and their capacities to neutralize acid precipitation. The data is available in Arc/Info export format. [Summary provided by the USGS] proprietary
USGS_OFR_aqbound_1.0 Digital boundaries of the Antlers aquifer in southeastern Oklahoma CEOS_EXTRA STAC Catalog 1992-01-01 1992-12-31 -97.4976, 33.7288, -94.4684, 34.3644 https://cmr.earthdata.nasa.gov/search/concepts/C2231550862-CEOS_EXTRA.umm_json This data set was created for a project to develop data sets to support ground-water vulnerability analysis. The objective was to create and document a digital geospatial data set from a published report or map, or existing digital geospatial data sets that could be used in ground-water vulnerability analysis. This data set consists of digitized aquifer boundaries of the Antlers aquifer in southeastern Oklahoma. The Early Cretaceous-age Antlers Sandstone is an important source of water in an area that underlies about 4,400-square miles of all or part of Atoka, Bryan, Carter, Choctaw, Johnston, Love, Marshall, McCurtain, and Pushmataha Counties. The Antlers aquifer consists of sand, clay, conglomerate, and limestone in the outcrop area. The upper part of the Antlers aquifer consists of beds of sand, poorly cemented sandstone, sandy shale, silt, and clay. The Antlers aquifer is unconfined where it outcrops in about an 1,800-square-mile area. The data set includes the outcrop area of the Antlers Sandstone in Oklahoma and areas where the Antlers is overlain by alluvial and terrace deposits and a few small thin outcrops of the Goodland Limestone. Most of the aquifer boundary lines were extracted from published digital geology data sets. Some of the lines were interpolated in areas where the Antlers aquifer is overlain by alluvial and terrace deposits near streams and rivers. The interpolated lines are very similar to the aquifer boundaries published in a ground-water modeling report for the Antlers aquifer. The maps from which this data set was derived were scanned or digitized from maps published at a scale of 1:250,000. This data set is one of four digital map data sets being published together for this aquifer. The four data sets are: aqbound - aquifer boundaries cond - hydraulic conductivity recharg - aquifer recharge wlelev - water-level elevation contours proprietary
USGS_P-11_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Central Coastal Province ALL STAC Catalog 1990-12-01 1990-12-01 -123.80987, 34.66294, -118.997696, 39.082233 https://cmr.earthdata.nasa.gov/search/concepts/C2231552077-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 11 (Central Coastal) are listed here by play number, type, and name: Number Type Name 1101 conventional Point Arena Oil 1102 conventional Point Reyes Oil 1103 conventional Pescadero Oil 1104 conventional La Honda Oil 1105 conventional Bitterwater Oil 1106 conventional Salinas Oil 1107 conventional Western Cuyama Basin 1109 conventional Cox Graben proprietary
USGS_P-11_cells 1995 National Oil and Gas Assessment 1/4-Mile Cells within the Central Coastal Province CEOS_EXTRA STAC Catalog 1990-12-01 1990-12-01 -123.80987, 34.66294, -118.997696, 39.082233 https://cmr.earthdata.nasa.gov/search/concepts/C2231552077-CEOS_EXTRA.umm_json The purpose of the cell map is to display the exploration maturity, type of production, and distribution of production in quarter-mile cells in each of the oil and gas plays and each of the provinces defined for the 1995 U.S. National Oil and Gas Assessment. Cell maps for each oil and gas play were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in a play or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, or dry. The well information was initially retrieved from the Petroleum Information (PI) Well History Control System (WHCS), which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary WHCS data. No proprietary data are displayed or included in the cell maps. The data from WHCS were current as of December 1990 when the cell maps were created in 1994. Oil and gas plays within province 11 (Central Coastal) are listed here by play number, type, and name: Number Type Name 1101 conventional Point Arena Oil 1102 conventional Point Reyes Oil 1103 conventional Pescadero Oil 1104 conventional La Honda Oil 1105 conventional Bitterwater Oil 1106 conventional Salinas Oil 1107 conventional Western Cuyama Basin 1109 conventional Cox Graben proprietary
-USGS_P-11_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Central Coastal Province ALL STAC Catalog 1996-01-01 1996-12-31 -123.80987, 34.66294, -118.997696, 39.082233 https://cmr.earthdata.nasa.gov/search/concepts/C2231551956-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 11 (Central Coastal) are listed here by play number and name: Number Name 1101 Point Arena Oil 1102 Point Reyes Oil 1103 Pescadero Oil 1104 La Honda Oil 1105 Bitterwater Oil 1106 Salinas Oil 1107 Western Cuyama Basin 1109 Cox Graben proprietary
USGS_P-11_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Central Coastal Province CEOS_EXTRA STAC Catalog 1996-01-01 1996-12-31 -123.80987, 34.66294, -118.997696, 39.082233 https://cmr.earthdata.nasa.gov/search/concepts/C2231551956-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 11 (Central Coastal) are listed here by play number and name: Number Name 1101 Point Arena Oil 1102 Point Reyes Oil 1103 Pescadero Oil 1104 La Honda Oil 1105 Bitterwater Oil 1106 Salinas Oil 1107 Western Cuyama Basin 1109 Cox Graben proprietary
+USGS_P-11_conventional 1995 National Oil and Gas Assessment Conventional Plays within the Central Coastal Province ALL STAC Catalog 1996-01-01 1996-12-31 -123.80987, 34.66294, -118.997696, 39.082233 https://cmr.earthdata.nasa.gov/search/concepts/C2231551956-CEOS_EXTRA.umm_json The purpose of these files is to illustrate the geologic boundary of the play as defined for the 1995 U.S. National Assessment. The play was used as the fundamental assessment unit. The fundamental geologic unit used in the 1995 National Oil and Gas Assessment was the play, which is defined as a set of known or postulated oil and or gas accumulations sharing similar geologic, geographic, and temporal properties, such as source rock, migration pathways, timing, trapping mechanism, and hydrocarbon type. The geographic limit of each play was defined and mapped by the geologist responsible for each province. The play boundaries were defined geologically as the limits of the geologic elements that define the play, such as the limits of the reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are plays that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the play boundary. The play boundaries were defined in the period 1993-1994. Conventional oil and gas plays within province 11 (Central Coastal) are listed here by play number and name: Number Name 1101 Point Arena Oil 1102 Point Reyes Oil 1103 Pescadero Oil 1104 La Honda Oil 1105 Bitterwater Oil 1106 Salinas Oil 1107 Western Cuyama Basin 1109 Cox Graben proprietary
USGS_P1650-a_1.0 Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America CEOS_EXTRA STAC Catalog 1970-01-01 -170, 20, -80, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231552968-CEOS_EXTRA.umm_json This atlas explores the continental-scale relations between the geographic ranges of woody plant species and climate in North America. A 25-km equal-area grid of modern climatic and bioclimatic parameters was constructed from instrumental weather records. The geographic distributions of selected tree and shrub species were digitized, and the presence or absence of each species was determined for each cell on the 25-km grid, thus providing a basis for comparing climatic data and species' distributions. The relations between climate and plant distributions are explored in graphical and tabular form. The results of this effort are primarily intended for use in biogeographic, paleoclimatic, and global-change research. These web pages provide access to the text, digital representations of figures, and supplemental data files from USGS Professional Paper 1650, chapters A and B. A printed set of these volumes can be ordered from the USGS at a cost of US$63.00. To order, please call or write: USGS Information Services Box 25286 Denver Federal Center Denver, CO 80225 Tel: 303-202-4700; Fax: 303-202-4693 [Summary provided by the USGS.] proprietary
USGS_PA_DIGIT_1.0 Digital drainage basin boundaries of named streams in Pennsylvania CEOS_EXTRA STAC Catalog 1970-01-01 -76.4304, 39.7151, -74.6865, 42.0007 https://cmr.earthdata.nasa.gov/search/concepts/C2231548560-CEOS_EXTRA.umm_json "In 1989, the Pennsylvania Department of Environmental Resources (PaDER), in cooperation with the U.S. Geological Survey, Water Resources Division (USGS published the Pennsylvania (PA) Gazetteer of Streams. This publication contains information related to named streams in Pennsylvania. Drainage basin boundaries are delineated on the 7.5-minute series topographic paper quadrangle maps for PA and parts of the bordering states of New York, Maryland, Ohio, West Virginia, and Delaware. These boundaries enclose catchment areas for named streams officially recognized by the Board on Geographic Names and other unofficially named streams that flow through named hollows, using the hollow name, e.g. ""Smith Hollow"". This was done in an effort to name as many of the 64,000 streams as possible. In 1991, work began by USGS to put these drainage basin boundaries into digital form for use in a geographic information system (GIS). Digitizing started with USGS in Lemoyne, PA., but expanded with assistance by PaDER and the Natural Resource Conservation Service (NRCS), formerly the U.S Department of Agriculture, Soil Conservation Service (SCS). USGS performed all editing, attributing, and edgematching. There are 878, 7.5-minute quadrangle maps in PA. This documentation applies to only those maps in the Delaware River basin (164). Parts of the Delaware River drainage originate outside the PA border. At this time, no effort is being made by USGS to include those named stream basins. [Summary provided by the USGS.]" proprietary
USGS_PONTCHARTRAIN Geologic Framework and Processes of the Lake Pontchartrain Basin CEOS_EXTRA STAC Catalog 1970-01-01 -91, 29, -89, 31 https://cmr.earthdata.nasa.gov/search/concepts/C2231549642-CEOS_EXTRA.umm_json Lake Pontchartrain and adjacent lakes in Louisiana form one of the larger estuaries in the Gulf Coast region. The estuary drains the Pontchartrain Basin (at right), an area of over 12,000 km2 situated on the eastern side of the Mississippi River delta plain. In Louisiana, nearly one-third of the State population lives within the 14 parishes of the basin. Over the past 60 years, rapid growth and development within the basin, along with natural processes, have resulted in significant environmental degradation and loss of critical habitat in and around Lake Pontchartrain. Human activities associated with pollutant discharge and surface drainage have greatly affected the water quality in the lake. This change is evident in the bottom sediments, which record the historic health of the lake. Also, land-altering activities such as logging, dredging, and flood control in and around the lake, lead to shoreline erosion and loss of wetlands.The effects of pollution, shoreline erosion and wetland loss on the lake and surrounding areas have become a major public concern. To better understand the basin's origin and the processes driving its development and degradation requires a wide-ranging study involving many organizations and personnel. When the U.S. Geological Survey began the study of Lake Pontchartrain in 1994, information on four topics was needed: -Geologic Framework, or how the various sedimentary layers that make up the basin are put together -Sediment Characterization, that is, what are the sediments made of, where did they come from, and what kinds of pollutants do they contain -Shoreline and Wetland Change over time -what are the processes that control Water Circulation [Summary provided by the USGS.] proprietary
@@ -16061,14 +16062,14 @@ USGS_SESC_ExtinctFish Extinct North American Freshwater Fishes CEOS_EXTRA STAC C
USGS_SESC_ImperiledFish American Fisheries Society Imperiled Freshwater and Diadromous Fishes of North America CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231551557-CEOS_EXTRA.umm_json About: This website presents the 2008 American Fisheries Society Endangered Species Committee list of imperiled North American freshwater and diadromous fishes. The committee considered continental fishes native to Canada, Mexico, and the United States, evaluated their conservation status and determined the major threats impacting these taxa. We use the terms taxon (singular) or taxa (plural) to include named species, named subspecies, undescribed forms, and distinct populations as characterized by unique morphological, genetic, ecological, or other attributes warranting taxonomic recognition. Undescribed taxa are included, based on the above diagnostic criteria in combination with known geographic distributions and documentation deemed of scientific merit, as evidenced from publication in peer-reviewed literature, conference abstracts, unpublished theses or dissertations, or information provided by recognized taxonomic experts. Although we did not independently evaluate the taxonomic validity of undescribed taxa, the committee adopted a conservative approach to recognize them on the basis of prevailing evidence which suggests that these forms are sufficiently distinct to warrant conservation and management actions. Summary: This is the third compilation of imperiled (i.e., endangered, threatened, vulnerable) plus extinct freshwater and diadromous fishes of North America prepared by the American Fisheries Society's Endangered Species Committee. Since the last revision in 1989, imperilment of inland fishes has increased substantially. This list includes 700 extant taxa representing 133 genera and 36 families, a 92% increase over the 364 listed in 1989. The increase reflects the addition of distinct populations, previously non-imperiled fishes, and recently described or discovered taxa. Approximately 39% of described fish species of the continent are imperiled. There are 230 vulnerable, 190 threatened, and 280 endangered extant taxa; 61 taxa are presumed extinct or extirpated from nature. Of those that were imperiled in 1989, most (89%) are the same or worse in conservation status; only 6% have improved in status, and 5% were delisted for various reasons. Habitat degradation and nonindigenous species are the main threats to at-risk fishes, many of which are restricted to small ranges. Documenting the diversity and status of rare fishes is a critical step in identifying and implementing appropriate actions necessary for their protection and management. Maps: In collaboration with the World Wildlife Fund, the committee developed a map of freshwater ecoregions that combines spatial and faunistic information derived from Maxwell and others (1995), Abell and others (2000; 2008), U.S. Geological Survey Hydrologic Unit Code maps (Watermolen 2002), Atlas of Canada (2003), and Commission for Environmental Cooperation (2007). Eighty ecoregions were identified based on physiography and faunal assemblages of the Atlantic, Arctic, and Pacific basins. Each taxon on the list was assigned to one or more ecoregions that circumscribes its native distribution. A variety of sources were used to obtain distributional information, most notably Lee and others (1980), Hocutt and Wiley (1986), Page and Burr (1991), Behnke (2002), Miller and others (2005), numerous state and provincial fish books for the United States and Canada, and the primary literature, including original taxonomic descriptions. Taxa were also associated with the states or provinces where they naturally occur or occurred in the past. proprietary
USGS_SESC_ImperiledFreshwaterOrganisms Imperiled Freshwater Organisms of North America CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231549663-CEOS_EXTRA.umm_json This website provides access to maps and lists of imperiled freshwater organisms of North America as determined by the American Fisheries Society (AFS) Endangered Species Committee (ESC). At this website, one can view lists of animals by freshwater ecoregion, by state or province boundary, and plot distributions of these same creatures by ecoregions or political boundaries. Both the AFS and U.S. Geological Survey (USGS) have a long standing commitment to the advancement of aquatic sciences and sharing that information with the public. Since 1972, the ESC has been tracking the status of imperiled fishes and aquatic invertebrates in North America. Recently, the fish (2008) and crayfish (2007) subcommittees provided revised status lists of at-risk taxa, and the mussel and snail subcommittees are in the process of completing similar revisions. Historically, the revised AFS lists of imperiled fauna have been published in Fisheries. With rapid advances in technology and information transfer, there is a growing need to provide to stakeholders immediate and dynamic data on imperiled resources. The USGS is a leader in aquatic resource research that effectively disseminates results from those studies to the public through print and internet media. A Memorandum Of Understanding formally establishes an agreement between the AFS and USGS to create this website that will serve as a conduit for information exchange about imperiled aquatic organisms of North America. proprietary
USGS_SESC_SnailStatus American Fisheries Society List of Freshwater Snails from Canada and the United States CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231551686-CEOS_EXTRA.umm_json About: This website presents the 2013 American Fisheries Society Endangered Species Committee list of freshwater snails (Gastropods) of United States and Canada. The committee evaluated the conservation status and determined the major threats impacting these taxa. Summary: This is the first conservation status review for freshwater snails (gastropods) of Canada and the United States by the American Fisheries Society's Endangered Species Freshwater Gastropod Subcommittee. The goals of this contribution are to provide: 1) a current and comprehensive taxonomic authority list for all native freshwater gastropods of Canada and the United States, 2) provincial and state distributions as presently understood, 3) a conservation assessment, and, 4) references on their biology, distribution and conservation. Freshwater gastropods occupy every type of aquatic habitat ranging from subterranean aquifers to brawling montane headwater creeks. Gastropods are ubiquitous invertebrates and frequently dominate aquatic invertebrate biomass. Of the 703 gastropods documented by Johnson et al. (2013), 74% are imperiled or extinct (278 endangered, 102 threatened, 73 vulnerable, and 67 are considered extinct); only 157 species are considered stable. Map queries display species distributions in provinces and states in which they are believed to occur or occurred in the past, but considerable fieldwork is required to determine exact geographic limits of species. We hope this list stimulates a surge in the study of freshwater gastropods. Supporting Literature: Supporting literature for the North American freshwater gastropods assessment are organized alphabetically by state and province, followed by national, regional, and other general references. This literature compilation is not comprehensive, but offers considerable information for individuals interested in freshwater snails. Recovery Examples: Although the gastropod fauna of Canada and the United States is beleaguered by multiple forms of habitat loss, the fauna is resilient and capable of remarkable recovery when suitable habitat is available. Three examples of recovery demonstrate the inherent reviving potential of freshwater gastropods. Images of the incredible diversity of freshwater snails are presented in plates and photo gallery. Maps: Each species on the list was assigned to one or more states or provinces that circumscribe its native distribution. Mapped distributions indicate where taxa naturally occur or occurred in the past. Resources used to obtain distributional information include state and regional publications. proprietary
-USGS_SESC_SturgeonBiblio_3 A bibliography of all known publications & reports on the Gulf Sturgeon, Acipenser oxyrinchus desotoi. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231552134-CEOS_EXTRA.umm_json "This functional bibliography is meant to be a complete and comprehensive bibliography of all discoverable reports containing information on the Gulf Sturgeon (GS). This bibliography contains all known reports presenting, documenting, summarizing, listing, or interpreting information on the GS through 31 December 2013. Report citations are organized into four sections. Section I includes published scientific journal articles, books, dissertations and theses, published and unpublished technical reports, published harvest prohibitions, and online articles reporting substantive scientific information. Section II includes newspaper, newsletter, magazine, book, agency news releases, and online articles reporting on GS occurrences, mortalities, captures, jumping, boat collisions, aquaculture, historical photographs, and other largely non-scientific or anecdotal issues. Section III consists of books, theses, ecotour-guides, media articles, editorials, and blogs reporting a mix of anecdotal information, historical information, and opinion on GS conservation, habitat issues, exploitation, aquaculture, and human interaction - but presenting very limited or no substantive scientific information. Section IV includes videos, films and audio recordings documenting GS life history and behavior. Each reference includes a bibliographic citation, as well as a brief annotation of key topics in brackets, where possible. The names of journals, theses, dissertations, and books are given in bold within each citation, and relevant page numbers are noted in parentheses at the end of citations, where applicable. Newspaper and magazine article titles are placed within parentheses. Key topic annotations are inserted in bracketed italics on a separate line. If the reference reports GS information under a different common or scientific name (e.g., Atlantic Sturgeon, Common Sturgeon, Sturgeon, Sea Sturgeon, Acipenser oxyrinchus oxyrinchus, Acipenser oxyrhynchus or Acipenser sturio), a notation to that effect is given within the key words annotation line, e.g., [Reported as ""Atlantic sturgeon""]. A small number of reports could not be obtained. These include historical reports from newspapers and magazines long out of circulation. In these limited cases, titles are still provided to substantiate their existence. Other reports that are no longer readily available, but which have been obtained during preparation of this bibliography, have been archived in hardcopy and/or as scanned pdf files at USGS, SESC. Copies of such hard to obtain reports, if non-copyrighted, may be available upon request from USGS corresponding author, via email: mrandall@usgs.gov." proprietary
USGS_SESC_SturgeonBiblio_3 A bibliography of all known publications & reports on the Gulf Sturgeon, Acipenser oxyrinchus desotoi. CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231552134-CEOS_EXTRA.umm_json "This functional bibliography is meant to be a complete and comprehensive bibliography of all discoverable reports containing information on the Gulf Sturgeon (GS). This bibliography contains all known reports presenting, documenting, summarizing, listing, or interpreting information on the GS through 31 December 2013. Report citations are organized into four sections. Section I includes published scientific journal articles, books, dissertations and theses, published and unpublished technical reports, published harvest prohibitions, and online articles reporting substantive scientific information. Section II includes newspaper, newsletter, magazine, book, agency news releases, and online articles reporting on GS occurrences, mortalities, captures, jumping, boat collisions, aquaculture, historical photographs, and other largely non-scientific or anecdotal issues. Section III consists of books, theses, ecotour-guides, media articles, editorials, and blogs reporting a mix of anecdotal information, historical information, and opinion on GS conservation, habitat issues, exploitation, aquaculture, and human interaction - but presenting very limited or no substantive scientific information. Section IV includes videos, films and audio recordings documenting GS life history and behavior. Each reference includes a bibliographic citation, as well as a brief annotation of key topics in brackets, where possible. The names of journals, theses, dissertations, and books are given in bold within each citation, and relevant page numbers are noted in parentheses at the end of citations, where applicable. Newspaper and magazine article titles are placed within parentheses. Key topic annotations are inserted in bracketed italics on a separate line. If the reference reports GS information under a different common or scientific name (e.g., Atlantic Sturgeon, Common Sturgeon, Sturgeon, Sea Sturgeon, Acipenser oxyrinchus oxyrinchus, Acipenser oxyrhynchus or Acipenser sturio), a notation to that effect is given within the key words annotation line, e.g., [Reported as ""Atlantic sturgeon""]. A small number of reports could not be obtained. These include historical reports from newspapers and magazines long out of circulation. In these limited cases, titles are still provided to substantiate their existence. Other reports that are no longer readily available, but which have been obtained during preparation of this bibliography, have been archived in hardcopy and/or as scanned pdf files at USGS, SESC. Copies of such hard to obtain reports, if non-copyrighted, may be available upon request from USGS corresponding author, via email: mrandall@usgs.gov." proprietary
+USGS_SESC_SturgeonBiblio_3 A bibliography of all known publications & reports on the Gulf Sturgeon, Acipenser oxyrinchus desotoi. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2231552134-CEOS_EXTRA.umm_json "This functional bibliography is meant to be a complete and comprehensive bibliography of all discoverable reports containing information on the Gulf Sturgeon (GS). This bibliography contains all known reports presenting, documenting, summarizing, listing, or interpreting information on the GS through 31 December 2013. Report citations are organized into four sections. Section I includes published scientific journal articles, books, dissertations and theses, published and unpublished technical reports, published harvest prohibitions, and online articles reporting substantive scientific information. Section II includes newspaper, newsletter, magazine, book, agency news releases, and online articles reporting on GS occurrences, mortalities, captures, jumping, boat collisions, aquaculture, historical photographs, and other largely non-scientific or anecdotal issues. Section III consists of books, theses, ecotour-guides, media articles, editorials, and blogs reporting a mix of anecdotal information, historical information, and opinion on GS conservation, habitat issues, exploitation, aquaculture, and human interaction - but presenting very limited or no substantive scientific information. Section IV includes videos, films and audio recordings documenting GS life history and behavior. Each reference includes a bibliographic citation, as well as a brief annotation of key topics in brackets, where possible. The names of journals, theses, dissertations, and books are given in bold within each citation, and relevant page numbers are noted in parentheses at the end of citations, where applicable. Newspaper and magazine article titles are placed within parentheses. Key topic annotations are inserted in bracketed italics on a separate line. If the reference reports GS information under a different common or scientific name (e.g., Atlantic Sturgeon, Common Sturgeon, Sturgeon, Sea Sturgeon, Acipenser oxyrinchus oxyrinchus, Acipenser oxyrhynchus or Acipenser sturio), a notation to that effect is given within the key words annotation line, e.g., [Reported as ""Atlantic sturgeon""]. A small number of reports could not be obtained. These include historical reports from newspapers and magazines long out of circulation. In these limited cases, titles are still provided to substantiate their existence. Other reports that are no longer readily available, but which have been obtained during preparation of this bibliography, have been archived in hardcopy and/or as scanned pdf files at USGS, SESC. Copies of such hard to obtain reports, if non-copyrighted, may be available upon request from USGS corresponding author, via email: mrandall@usgs.gov." proprietary
USGS_SIR-5079_MSRiverFloodMaps Development of flood-inundation maps for the Mississippi River in Saint Paul, Minnesota CEOS_EXTRA STAC Catalog 1970-01-01 -93.15028, 44.90479, -92.999855, 44.97016 https://cmr.earthdata.nasa.gov/search/concepts/C2231549022-CEOS_EXTRA.umm_json Digital flood-inundation maps for a 6.3-mile reach of the Mississippi River in Saint Paul, Minnesota, were developed through a multi-agency effort by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers and in collaboration with the National Weather Service. The inundation maps, which can be accessed through the U.S. Geological Survey Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ and the National Weather Service Advanced Hydrologic Prediction Service site at http://water.weather.gov/ahps/inundation.php , depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage at the Mississippi River at Saint Paul (05331000). The National Weather Service forecasted peak-stage information at the streamgage may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the Mississippi River by means of a one-dimensional step-backwater model. The hydraulic model was calibrated using the most recent stage-discharge relation at the Robert Street location (rating curve number 38.0) of the Mississippi River at Saint Paul (streamgage 05331000), as well as an approximate water-surface elevation-discharge relation at the Mississippi River at South Saint Paul (U.S. Army Corps of Engineers streamgage SSPM5). The model also was verified against observed high-water marks from the recent 2011 flood event and the water-surface profile from existing flood insurance studies. The hydraulic model was then used to determine 25 water-surface profiles for flood stages at 1-foot intervals ranging from approximately bankfull stage to greater than the highest recorded stage at streamgage 05331000. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from high-resolution topography data, to delineate potential areas flooded and to determine the water depths within the inundated areas for each stage at streamgage 05331000. The availability of these maps along with information regarding current stage at the U.S. Geological Survey streamgage and forecasted stages from the National Weather Service provides enhanced flood warning and visualization of the potential effects of a forecasted flood for the city of Saint Paul and its residents. The maps also can aid in emergency management planning and response activities, such as evacuations and road closures, as well as for post-flood recovery efforts. proprietary
USGS_SOFIA_75_29_flows Baseline hydrologic data collection along the I-75 - State Road 29 corridor in the Big Cypress National Preserve CEOS_EXTRA STAC Catalog 2005-11-01 2009-09-30 -81.325, 25.75, -80.75, 26.25 https://cmr.earthdata.nasa.gov/search/concepts/C2231549536-CEOS_EXTRA.umm_json The objectives of this study are to develop and continue a program of surface water flow monitoring across I-75 and SR 29 in the I-75 corridor from Snake Road west to SR 29 and SR 29 from I-75 south to USGS site 02291000 Barron River near Everglades, Florida. Quarterly discharge measurements will be made along both reaches to assess hydrologic flow patterns and evaluate the feasibility of creating a stage-discharge/index-velocity relationship for this area. Data collected in this project will provide baseline information about a major current barrier to sheetflow, I-75. The data are expected to support the research on the existing linkages among geologic, hydrologic, chemical, climatological, and biological processes that currently shape the Everglades and will provide insight into the predrainage Everglades. The baseline flow will contribute to the Southwest Florida Feasibility Study addressing the health of upland and aquatic ecosystems in the 4,300 square mile area. proprietary
USGS_SOFIA_75_29_hydro_data Hydrologic Data Collected along I-75/SR29 corridor in Big Cypress National Preserve CEOS_EXTRA STAC Catalog 2005-11-01 2009-09-30 -81.325, 25.75, -80.75, 26.25 https://cmr.earthdata.nasa.gov/search/concepts/C2231549847-CEOS_EXTRA.umm_json The location of each site is shown on a Google Map. Data are available as a Google Map with links to Station Information and Data for each site. Data are available for 58 sites along I-75 and for 28 sites along State Road 29 in Big Cypress National Preserve. Data collected in this project will provide baseline information about a major current barrier to sheetflow, I-75. The data are expected to support the research on the existing linkages among geologic, hydrologic, chemical, climatological, and biological processes that currently shape the Everglades and will provide insight into the predrainage Everglades. The baseline flow will contribute to the Southwest Florida Feasibility Study addressing the health of upland and aquatic ecosystems in the 4,300 square mile area. proprietary
USGS_SOFIA_ACME_DB Aquatic Cycling of Mercury in the Everglades Project Database CEOS_EXTRA STAC Catalog 1995-01-01 2008-09-01 -80.1, 25, -81.6, 27.6 https://cmr.earthdata.nasa.gov/search/concepts/C2231554301-CEOS_EXTRA.umm_json Between 1995 and 2008, the Aquatic Mercury Cycling in the Everglades (ACME) project examined in detail the biogeochemical parameters that influence methylmercury (MeHg) production in the Florida Everglades. The interdisciplinary ACME team studied Hg cycling in the Everglades through a process-based, biogeochemical lens (Hurley et al. 1998). In the Everglades, as in most other ecosystems, inorganic mercury is transformed into methylmercury primarily by the action of anaerobic bacteria in surficial sediments and soils. The ACME project has been a collaborative research effort designed to understand the biogeochemical drivers of mercury cycling in the Greater Florida Everglades. The project is led be a team of scientists from the USGS and the Smithsonian Institution, with additional collaborators from the University of Wisconsin, Texas A&M, the SFWMD and FL DEP. ACME�s main objective has been to define the key processes that control the fate and transport of Hg in the Everglades. The study has used a process-oriented, multi-disciplinary approach, focusing on a suite of intensively-studied sites across the trophic gradient of the Water Conservation Areas and Everglades National Park. Since 1995, a core set of sites has been examined in detail through time, including changes in season and in hydrology. The biogeochemical parameters examined focus on those that impact net methylmercury (MeHg) production, and include sulfur, carbon and nutrient biogeochemistry. The study examined Hg and MeHg concentrations, and associated biogeochemical parameters in surface waters, soils, periphyton, emergent plants and biota. The core study sites have been supplemented with survey data across many additional sites in the Greater Everglades Ecosystem. The field study was also supplemented with experimental studies of Hg complexation, photochemistry, and bioavailability. The ACME project has been funded by a variety of agencies including the USGS, NSF, EPA, SFWMD and FL DEP. proprietary
-USGS_SOFIA_ASR_04 A retrospective and critical review of aquifer and storage (ASR) sites and conceptual framework of the Upper Floridian aquifer in south Florida ALL STAC Catalog 1999-10-01 2004-09-30 -82.55795, 24.441917, -79.84407, 27.586416 https://cmr.earthdata.nasa.gov/search/concepts/C2231549469-CEOS_EXTRA.umm_json The objectives of this study are to: (1) inventory and assess the strengths and weaknesses of available hydrogeologic, hydraulic, hydrochemical, well construction, and cycle test information at existing ASR sites, (2) conduct a critical review of the hydrogeology on a site-by-site basis and relate to existing regional hydrogeology frameworks, allowing for the delineation of hydrogeologic factors that may be important to recovery efficiency, (3) identify hydrogeologic, design, and management factors which locally or regionally constrain the efficient storage and recovery of fresh water within the Upper Floridan aquifer, and (4) conduct a comparative analysis of the performance of all ASR sites having adequate data. This five-year study is divided into two phases, the first of which was two years long. The first phase laid the groundwork for data inventory, review, and analysis, and the second phase will allow for collection of additional data as it becomes available, expand the hydrogeologic framework, and perform a more complete comparative analysis of ASR sites. The study is in the second phase. Aquifer storage and recovery (ASR) has been described as 'the storage of water in a suitable aquifer through a well during times when water is available, and recovery of the water from the same well during times when it is needed'. Water can be stored in aquifers with poor water quality. ASR in south Florida is proposed in the Comprehensive Everglades Restoration Plan (CERP) as a cost-effective water-supply alternative that can help meet needs of agricultural, municipal, and recreational users while providing the water critical for Everglades ecosystem restoration. In CERP, plans have been made to utilize ASR in the Floridan aquifer system on an unprecedented scale. Precedence for ASR in southern Florida has been set with wells having been constructed at over 30 sites, mostly by local municipalities or counties in coastal areas. The Upper Floridan aquifer, the aquifer used at most of these sites, is brackish to saline in south Florida, which can have a large impact on the recovery of the fresh or potable water recharged and stored. Few regional investigations of the Floridan aquifer system hydrogeology in south Florida have been conducted, and the focus of those studies was not on ASR. Lacking a regional ASR framework to aid the decision-making process, ASR well sites in south Florida have been primarily located based on factors such as land availability, source-water quality, and source-water proximity (preexisting surface-water bodies, surficial aquifer system well fields, or water treatment plants). Little effort has been made to link information collected from each site as part of a regional hydrogeologic analysis. Results of this study should help the managers of the CERP program in locating, designing, constructing, and cycle testing ASR wells. These results should help establish a standard cycle testing protocol that can be used to measure the performance of individual CERP wells or clusters of wells. proprietary
USGS_SOFIA_ASR_04 A retrospective and critical review of aquifer and storage (ASR) sites and conceptual framework of the Upper Floridian aquifer in south Florida CEOS_EXTRA STAC Catalog 1999-10-01 2004-09-30 -82.55795, 24.441917, -79.84407, 27.586416 https://cmr.earthdata.nasa.gov/search/concepts/C2231549469-CEOS_EXTRA.umm_json The objectives of this study are to: (1) inventory and assess the strengths and weaknesses of available hydrogeologic, hydraulic, hydrochemical, well construction, and cycle test information at existing ASR sites, (2) conduct a critical review of the hydrogeology on a site-by-site basis and relate to existing regional hydrogeology frameworks, allowing for the delineation of hydrogeologic factors that may be important to recovery efficiency, (3) identify hydrogeologic, design, and management factors which locally or regionally constrain the efficient storage and recovery of fresh water within the Upper Floridan aquifer, and (4) conduct a comparative analysis of the performance of all ASR sites having adequate data. This five-year study is divided into two phases, the first of which was two years long. The first phase laid the groundwork for data inventory, review, and analysis, and the second phase will allow for collection of additional data as it becomes available, expand the hydrogeologic framework, and perform a more complete comparative analysis of ASR sites. The study is in the second phase. Aquifer storage and recovery (ASR) has been described as 'the storage of water in a suitable aquifer through a well during times when water is available, and recovery of the water from the same well during times when it is needed'. Water can be stored in aquifers with poor water quality. ASR in south Florida is proposed in the Comprehensive Everglades Restoration Plan (CERP) as a cost-effective water-supply alternative that can help meet needs of agricultural, municipal, and recreational users while providing the water critical for Everglades ecosystem restoration. In CERP, plans have been made to utilize ASR in the Floridan aquifer system on an unprecedented scale. Precedence for ASR in southern Florida has been set with wells having been constructed at over 30 sites, mostly by local municipalities or counties in coastal areas. The Upper Floridan aquifer, the aquifer used at most of these sites, is brackish to saline in south Florida, which can have a large impact on the recovery of the fresh or potable water recharged and stored. Few regional investigations of the Floridan aquifer system hydrogeology in south Florida have been conducted, and the focus of those studies was not on ASR. Lacking a regional ASR framework to aid the decision-making process, ASR well sites in south Florida have been primarily located based on factors such as land availability, source-water quality, and source-water proximity (preexisting surface-water bodies, surficial aquifer system well fields, or water treatment plants). Little effort has been made to link information collected from each site as part of a regional hydrogeologic analysis. Results of this study should help the managers of the CERP program in locating, designing, constructing, and cycle testing ASR wells. These results should help establish a standard cycle testing protocol that can be used to measure the performance of individual CERP wells or clusters of wells. proprietary
+USGS_SOFIA_ASR_04 A retrospective and critical review of aquifer and storage (ASR) sites and conceptual framework of the Upper Floridian aquifer in south Florida ALL STAC Catalog 1999-10-01 2004-09-30 -82.55795, 24.441917, -79.84407, 27.586416 https://cmr.earthdata.nasa.gov/search/concepts/C2231549469-CEOS_EXTRA.umm_json The objectives of this study are to: (1) inventory and assess the strengths and weaknesses of available hydrogeologic, hydraulic, hydrochemical, well construction, and cycle test information at existing ASR sites, (2) conduct a critical review of the hydrogeology on a site-by-site basis and relate to existing regional hydrogeology frameworks, allowing for the delineation of hydrogeologic factors that may be important to recovery efficiency, (3) identify hydrogeologic, design, and management factors which locally or regionally constrain the efficient storage and recovery of fresh water within the Upper Floridan aquifer, and (4) conduct a comparative analysis of the performance of all ASR sites having adequate data. This five-year study is divided into two phases, the first of which was two years long. The first phase laid the groundwork for data inventory, review, and analysis, and the second phase will allow for collection of additional data as it becomes available, expand the hydrogeologic framework, and perform a more complete comparative analysis of ASR sites. The study is in the second phase. Aquifer storage and recovery (ASR) has been described as 'the storage of water in a suitable aquifer through a well during times when water is available, and recovery of the water from the same well during times when it is needed'. Water can be stored in aquifers with poor water quality. ASR in south Florida is proposed in the Comprehensive Everglades Restoration Plan (CERP) as a cost-effective water-supply alternative that can help meet needs of agricultural, municipal, and recreational users while providing the water critical for Everglades ecosystem restoration. In CERP, plans have been made to utilize ASR in the Floridan aquifer system on an unprecedented scale. Precedence for ASR in southern Florida has been set with wells having been constructed at over 30 sites, mostly by local municipalities or counties in coastal areas. The Upper Floridan aquifer, the aquifer used at most of these sites, is brackish to saline in south Florida, which can have a large impact on the recovery of the fresh or potable water recharged and stored. Few regional investigations of the Floridan aquifer system hydrogeology in south Florida have been conducted, and the focus of those studies was not on ASR. Lacking a regional ASR framework to aid the decision-making process, ASR well sites in south Florida have been primarily located based on factors such as land availability, source-water quality, and source-water proximity (preexisting surface-water bodies, surficial aquifer system well fields, or water treatment plants). Little effort has been made to link information collected from each site as part of a regional hydrogeologic analysis. Results of this study should help the managers of the CERP program in locating, designing, constructing, and cycle testing ASR wells. These results should help establish a standard cycle testing protocol that can be used to measure the performance of individual CERP wells or clusters of wells. proprietary
USGS_SOFIA_ASR_coordination Aquifer Storage and Recovery (ASR) Coordination CEOS_EXTRA STAC Catalog 2002-01-01 2004-12-31 -82.5, 25, -80, 27.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231553754-CEOS_EXTRA.umm_json ABSTRACT: The Comprehensive Everglades Restoration Plan (CERP) relies heavily on Aquifer Storage and Recovery (ASR) technology. The CERP includes approximately 333 ASR wells in South Florida with a total capacity of over 1.6 billion gallons per day. Much of the 'new water' in the CERP is derived from storing excess water that was previously discharged to the ocean. However, this new water would not be very useful unless there is a place to store it for use during dry periods. ASR is included in the CERP as one mechanism to provide this storage. Despite construction of some ASR facilities by local utilities, there remains a considerable number of significant technical and engineering-related uncertainties. Key Findings: 1) An analysis was conducted to describe and interpret the lithology of a part of the Upper Floridan aquifer penetrated by the Regional Observation Monitoring Program (ROMP) 29A test corehole in Highlands County, Florida. Information obtained was integrated into a conceptual model that delineates likely CERP ASR storage zones and confining units in the context of sequence stratigraphy. Carbonate sequence stratigraphy correlation strategies appear to reduce risk of miscorrelation of key ground-water flow units and confining units. 2) A hierarchical arrangement of rock unit cycles can be identified; High Frequency Cycle formed of peritidal, subtidal, and deeper subtidal) form High Frequency Sequence, and those can be grouped into Cycle Sequences. There appears to be a spatial relation among wells that penetrate water-bearing rocks having relatively high and low transmissivities. 3) Assuming hydrogeologic conditions observed in the ROMP 29A well are representative of in south-central Florida, the uppermost (Lower Hawthorn-Suwannee) of two likely CERP ASR storage zones does not appear to be viable with respect to the proposed 200 CERP ASR facility planned to be sited northwest of Lake Okeechobee. Insufficient data were available to adequately characterize the lower flow zone contained within the Avon Park Formation. proprietary
USGS_SOFIA_BigCypress_PineIsland_SatMap Big Cypress-Pine Island Satellite Image Map CEOS_EXTRA STAC Catalog 2000-01-27 -82.27, 25.78, -81.13, 26.7 https://cmr.earthdata.nasa.gov/search/concepts/C2231549800-CEOS_EXTRA.umm_json ABSTRACT: The map is a composite image of spectral bands 3 (630-690 nanometers, red), 4 (775-900 nanometers, near-infrared), and 5 (1,550-1750 nanometers, middle-infrared) and the new panchromatic band (520-900, green to near-infrared) acquired by the Landsat 7 enhanced thematic mapper (ETM) sensor on January 27, 2000. proprietary
USGS_SOFIA_Caloos_Franklin_Locks_flow Flow Monitoring Along the Tidal Caloosahatchee River and Tributaries West of Franklin Locks CEOS_EXTRA STAC Catalog 2007-01-01 2011-12-31 -82.04, 26.4, -81.6, 26.8 https://cmr.earthdata.nasa.gov/search/concepts/C2231552489-CEOS_EXTRA.umm_json Monitoring stations established thru this project are designed as part of a larger network needed for the Caloosahatchee River and tributaries that should remain in place long-term (~10 years). Data from monitoring stations included in this project will be evaluated during the third year of data collection in order to assess viability and need for changes . The objective of this study is to quantify freshwater flows into the tidal reach of the Caloosahatchee River, west of Franklin Locks. proprietary
@@ -16077,8 +16078,8 @@ USGS_SOFIA_CarbonFlux Carbon Flux and Greenhouse Gasses of Restored and Degraded
USGS_SOFIA_Ding_Darling_baseline Ding Darling National Wildlife Refuge - Greater Everglades Baseline Information and Response to CERP CEOS_EXTRA STAC Catalog 2009-10-01 2014-09-30 -82.5, 26.3, -81.6, 27 https://cmr.earthdata.nasa.gov/search/concepts/C2231549274-CEOS_EXTRA.umm_json The greater Everglades Restoration program includes a management plan for the C-43 Canal, or Caloosahatchee River. This plan affects the quantity, quality, and timing of freshwater releases at control structure S-79 at Franklin Locks. Freshwater contributions are from Lake Okeechobee, and farming runoff along the canal from Lake Okeechobee to the town of Alva. This study will provide basic information on the effects on the quality of water entering J. N. Ding Darling National Wildlife Refuge as the result of freshwater releases at control structure S-79 proprietary
USGS_SOFIA_EDEN_grid_shapefile_v02 EDEN Grid Shapefile CEOS_EXTRA STAC Catalog 1970-01-01 -81.51, 24.7, -79.9, 27.2 https://cmr.earthdata.nasa.gov/search/concepts/C2231549862-CEOS_EXTRA.umm_json This shapefile serves as a net (fishnet or grid) to be placed over the South Florida study area to allow for sampling within the 400 meter cells (grid cells or polygons). The origin and extent of the Everglades Depth Estimation Network (EDEN) grid were selected to cover not only existing Airborne Height Finder (AHF) data and current regions of interest for Everglades restoration, but to cover a rectangular area that includes all landscape units (USACE, 2004) and conservation areas in place at the time of its development. This will allow for future expansion of analyses throughout the Greater Everglades region should resources allow and scientific or management questions require it. Combined with the chosen extent, the 400m cell resolution produces a grid that is 675 rows and 375 columns.. The shapefile contains the 253125 grid cells described above. Some characteristics of this grid, such as the size of its cells, its origin, the area of Florida it is designed to represent, and individual grid cell identifiers, could not be changed once the grid database was developed. These characteristics were selected to design as robust a grid as possible and to ensure the grid’s long-term utility. proprietary
USGS_SOFIA_EDEN_proj Everglades Depth Estimation Network (EDEN) CEOS_EXTRA STAC Catalog 1999-01-01 2008-10-28 -81.3, 25, -80.16, 26.75 https://cmr.earthdata.nasa.gov/search/concepts/C2231550596-CEOS_EXTRA.umm_json The Everglades Depth Estimation Network (EDEN) is an integrated network of real-time water-level monitoring, ground elevation modeling, and water-surface modeling that provides scientists and managers with current (1999-present), on-line water-depth information for the entire freshwater portion of the Greater Everglades. Presented on a 400-square-meter grid spacing, EDEN offers a consistent and documented dataset that can be used by scientists and managers to:1) guide large-scale field operations, 2) integrate hydrologic and ecological responses, and 3) support biological and ecological assessments that measure ecosystem responses to the implementation of the comprehensive Everglades Restoration plan (CERP) from the U.S. Army Corps of Engineers in 1999. Research has shown that relatively high-resolution data are needed to explicitly represent variations in the Everglades topography and vegetation that are important for landscape analysis and modeling. The EDEN project will provide a better representation of water depths if elevation variation within each 400-meter grid cell can be taken into account. The EDEN network provides a framework to integrate data collected by other agencies in a common quality-assured database. In addition to real-time network, collaboration among agencies will provide the EDEN project with valuable historic vegetation and water-depth data. This is the first time these data have been compiled and analyzed as a collective set. proprietary
-USGS_SOFIA_Eco_hist_db_2008_present_2 2008 - Present Ecosystem History of South Florida's Estuaries Database version 2 CEOS_EXTRA STAC Catalog 2008-03-16 2012-09-30 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231549653-CEOS_EXTRA.umm_json The 2008 - Present Ecosystem History of South Florida's Estuaries Database contains listings of all sites (modern and core), and modern monitoring site survey information (water chemistry, floral and faunal data, etc.). Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - location information. Data are available for modern sites and cores in the general areas of Florida Bay, Biscayne Bay, and the southwest (Florida) coastal mangrove estuaries. Specific sites in the Florida Bay area include Taylor Creek, Bob Allen Key, Russell Bank, Pass Key, Whipray Basin, Rankin Bight, park Key, and Mud Creek core). Specific Biscayne Bay sites include Manatee Bay, Featherbed Bank, Card bank, No Name Bank, Middle Key, Black Point North, and Chicken Key. Sites on the southwest coast include Alligator Bay, Big Lostmans Bay, Broad River Bay, Roberts River mouth, Tarpon Bay, Lostmans River First and Second Bays, Harney River, Shark River near entrance to Ponce de Leon Bay, and Shark River channels. Modern field data contains (1) general information about the site, description, latitude and longitude, date of data collection, (2) water chemistry information, and (3) descriptive text of fauna and flora observed at the site. Core data contain basic location information. proprietary
USGS_SOFIA_Eco_hist_db_2008_present_2 2008 - Present Ecosystem History of South Florida's Estuaries Database version 2 ALL STAC Catalog 2008-03-16 2012-09-30 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231549653-CEOS_EXTRA.umm_json The 2008 - Present Ecosystem History of South Florida's Estuaries Database contains listings of all sites (modern and core), and modern monitoring site survey information (water chemistry, floral and faunal data, etc.). Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - location information. Data are available for modern sites and cores in the general areas of Florida Bay, Biscayne Bay, and the southwest (Florida) coastal mangrove estuaries. Specific sites in the Florida Bay area include Taylor Creek, Bob Allen Key, Russell Bank, Pass Key, Whipray Basin, Rankin Bight, park Key, and Mud Creek core). Specific Biscayne Bay sites include Manatee Bay, Featherbed Bank, Card bank, No Name Bank, Middle Key, Black Point North, and Chicken Key. Sites on the southwest coast include Alligator Bay, Big Lostmans Bay, Broad River Bay, Roberts River mouth, Tarpon Bay, Lostmans River First and Second Bays, Harney River, Shark River near entrance to Ponce de Leon Bay, and Shark River channels. Modern field data contains (1) general information about the site, description, latitude and longitude, date of data collection, (2) water chemistry information, and (3) descriptive text of fauna and flora observed at the site. Core data contain basic location information. proprietary
+USGS_SOFIA_Eco_hist_db_2008_present_2 2008 - Present Ecosystem History of South Florida's Estuaries Database version 2 CEOS_EXTRA STAC Catalog 2008-03-16 2012-09-30 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231549653-CEOS_EXTRA.umm_json The 2008 - Present Ecosystem History of South Florida's Estuaries Database contains listings of all sites (modern and core), and modern monitoring site survey information (water chemistry, floral and faunal data, etc.). Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - location information. Data are available for modern sites and cores in the general areas of Florida Bay, Biscayne Bay, and the southwest (Florida) coastal mangrove estuaries. Specific sites in the Florida Bay area include Taylor Creek, Bob Allen Key, Russell Bank, Pass Key, Whipray Basin, Rankin Bight, park Key, and Mud Creek core). Specific Biscayne Bay sites include Manatee Bay, Featherbed Bank, Card bank, No Name Bank, Middle Key, Black Point North, and Chicken Key. Sites on the southwest coast include Alligator Bay, Big Lostmans Bay, Broad River Bay, Roberts River mouth, Tarpon Bay, Lostmans River First and Second Bays, Harney River, Shark River near entrance to Ponce de Leon Bay, and Shark River channels. Modern field data contains (1) general information about the site, description, latitude and longitude, date of data collection, (2) water chemistry information, and (3) descriptive text of fauna and flora observed at the site. Core data contain basic location information. proprietary
USGS_SOFIA_Ever_hydr_FB_dynam Interrelationships of Everglades Hydrology and Florida Bay Dynamics CEOS_EXTRA STAC Catalog 1850-01-01 2004-12-31 -80.89015, 25.1004, -80.39827, 25.471722 https://cmr.earthdata.nasa.gov/search/concepts/C2231554284-CEOS_EXTRA.umm_json This interdisciplinary synthesis project is designed to identify and document the interrelation of Everglades’ hydrology and tidal dynamics of Florida Bay on ecosystem response to past environmental changes, both natural and human imposed. The project focuses on integrating historical, hydrological, and ecological findings of scientific investigations within the Southern Inland and Coastal System (SICS), which encompasses the transition zone between the wetlands of Taylor Slough and C-111 canal and nearshore embayments of Florida Bay. In the ecological component, hindcast simulations of historical flow events are being developed for ecological analyses. The Across Trophic Level System Simulation (ATLSS) ecological modeling team is collaborating with the SICS hydrologic modeling team to develop the necessary hydrologic inputs for refined indicator species models. The interconnected freshwater wetland and coastal marine ecosystems of south Florida have undergone numerous human disturbances, including the introduction of exotic species and the alteration of wetland hydroperiods, landscape characteristics, and drainage patterns through implementation of the extensive canal and road system and the expansion of agricultural activity. In this project, collaborative efforts are focused on documenting the impact of past hydrological and ecological changes along the southern Everglades interface with Florida Bay by reconstructing past hydroperiods and investigating the correlation of human-imposed and natural impacts on hydrological changes with shifts in biotic species. The primary objectives are to identify the historical effects of past management practices, to integrate refined hydrological and ecological modeling efforts at indicator species levels to identify cause-and-effect relationships, and to produce a report that documents findings that link hydrological and ecological changes to management practices, wherever evident. proprietary
USGS_SOFIA_Fbbslmap Florida Bay Bottom Salinity Maps CEOS_EXTRA STAC Catalog 1994-11-01 1996-12-31 -81.167, 24.83, -80.33, 25.33 https://cmr.earthdata.nasa.gov/search/concepts/C2231549334-CEOS_EXTRA.umm_json The maps show the bottom salinity for Florida Bay at 5ppt salinity intervals approximately every other month beginning in November 1994 through December 1996. Recent algal blooms and seagrass mortality have raised concerns about the water quality of Florida Bay, particularly its nutrient content (nitrogen and phosphorous), hypersalinity, and turbidity. Water quality is closely tied to sediment transport processes because resuspension of sediments increases turbidity, releases stored nutrients, and facilitates sediment export to the reef tract. The objective of this research is to provide a better understanding of how and when sediments within Florida Bay are resuspended and deposited, to define the spatial distribution of the potential for resuspension, to delineate patterns of potential bathymetric change, and to predict the impacts of storms or seagrass die-off on bathymetry and circulation within the bay. By combining these results with the findings of other research being conducted in Florida Bay, we hope to quantify sediment export from the bay, better define the nutrient input during resuspension events, and assist in modeling circulation and water quality. Results will enable long-term sediment deposition and erosion in various regions of the bay to be integrated with data on the anticipated sea-level rise to predict future water depths and volumes. Results from this project, together with established sediment production rates, will provide the basis for a sediment budget for Florida Bay. proprietary
USGS_SOFIA_Fbbtypes Florida Bay Bottom Types map - USGS_SOFIA_Fbbtypes CEOS_EXTRA STAC Catalog 1996-01-01 1997-01-31 -81.25, 24.75, -80.25, 25.25 https://cmr.earthdata.nasa.gov/search/concepts/C2231553376-CEOS_EXTRA.umm_json The map shows the bottom types for Florida Bay that resulted from site surveys and boat transects (summer 1996-January 1997) compared with aerial photographs (December 1994-January 1995) and SPOT satellite imagery (1987). The purpose of this map is to describe the bottom types found within Florida Bay for use in 1) assessing bottom friction associated with sediment and benthic communities and 2) providing a very general description for other research needs. For these purposes, two descriptors were considered particularly important: density of seagrass cover and sediment texture. Seagrass estimates are visual estimates of the amount of seagrass cover including both number of plants and leaf length. Therefore, seagrass cover may be greater in areas with long leaves than in areas with short blades, even though the number of shoots may be the same. Seagrass cover is a different measure than density (Zieman et al., 1989 or Durako et al., 1996). It is used here to more accurately reflect hydrodynamic influence than the standing crop of seagrass. The use and definitions of dense, intermediate and sparse seagrass cover are similar to those used by Scoffin (1970). This map and associated descriptions are not meant to assess ecologic communities or detail sedimentological facies. The resolution of the map has been selected in an effort to define broad regions for use in modeling efforts. For these purposes, small-scale changes in bottom type (e.g. small seagrass patches) are not delineated. proprietary
@@ -16102,12 +16103,12 @@ USGS_SOFIA_MeHg_degrad_rates Methylmercury Degradation Rates CEOS_EXTRA STAC Cat
USGS_SOFIA_SF_CIR_DOQs Color Infrared Digital Orthophoto Quadrangles for the South Florida Ecosystem Area CEOS_EXTRA STAC Catalog 1994-01-01 1999-12-31 -82.2, 24.6, -80.1, 27.8 https://cmr.earthdata.nasa.gov/search/concepts/C2231553946-CEOS_EXTRA.umm_json The digital orthophoto quadrangles (DOQ's) produced by the USGS for the South Florida Ecosystem Initiative iare color-infrared, 1-meter ground resolution quadrangle images covering 3.75 minutes of latitude by 3.75 minutes of longitude at a map scale of 12,000. Orthophotos combine the image characteristics of a photograph with the geometric qualities of a map. The primary digital orthophotoquadrangle (DOQ) is a 1-meter ground resolution, quarter-quadrangle (3.75 minutes of latitude by 3.75 minutes of longitude) image cast on the Universal Transverse Mercator projection (UTM) on the North American Datum of 1983 (NAD83). The geographic extent of the DOQ is equivalent to a quarter-quadrangle plus the overedge ranges from a minimum of 50 meters to a maximum of 300 meters beyond the extremes of the primary and secondary corner points. The overedge is included to facilitate tonal matching for mosaicking and for the placement of the NAD83 and secondary datum corner ticks. The normal orientation of data is by lines (rows) and samples (columns). Each line contains a series of pixels ordered from west to east with the order of the lines from north to south. The radiometric image brightness values are stored as 256 gray levels, ranging from 0 to 255. The standard, uncompressed gray scale DOQ format contains an ASCII header followed by a series of 8-bit image data lines. The keyword-based, ASCII header may vary in the number of data entries. The header is affixed to the beginning of the image and is composed of strings of 80 characters with an asterisk (*) as character 79 and an invisible newline character as character 80. Each keyword string contains information for either identification, display, or registration of the image. Additional strings of blanks are added to the header so that the length of a header line equals the number of bytes in a line of image data. The header line will be equal in length to the length of an image line. If the sum of the byte count of the header is less than the sample count of one DOQ image line, then the remainder of the header is padded with the requisite number of 80 character blank entries, each terminated with an asterisk and newline character. The objective of this project was to provide color infrared (CIR) digital orthophoto coverage for the entire south Florida ecosystem area. The main advantage of a digital orthophoto is that it gives a measurable image free of distortion. Therefore, the digital orthophotos for the ecosystem provide multi-use base images for identifying natural and manmade features and for determining their extent and boundaries; the images can also be used for the interpretation and classification of these areas. proprietary
USGS_SOFIA_SnailKites_AppleSnails Comprehensive Monitoring Plan for Snail Kites and Apple Snails in the Greater Everglades CEOS_EXTRA STAC Catalog 2010-01-01 2015-12-31 -81.6, 25, -80.6, 27.6 https://cmr.earthdata.nasa.gov/search/concepts/C2231554049-CEOS_EXTRA.umm_json The endangered snail kite (Rostrhamus sociabilis) is a wetland-dependent raptor feeding almost exclusively on a single species of aquatic snail, the Florida apple snail (Pomacea paludosa). The viability of the kite population is dependent on the hydrologic conditions (both short-term and long-term) that (1) maintain sufficient abundances and densities of apple snails, and (2) provide suitable conditions for snail kite foraging and nesting, which include specific vegetative community compositions. Many wetlands comprising its range are no longer sustained by the natural processes under which they evolved (USFWS 1999, RECOVER 2005), and not necessarily characteristic of the historical ecosystems that once supported the kite population (Bennetts and Kitchens 1999, Martin et al. 2008). Natural resource managers currently lack a fully integrative approach to managing hydrology and vegetative communities with respect to the apple snail and snail kite populations. At this point in time the kite population is approximately 1,218 birds (Cattau et al 2012), down from approximately 4000 birds in 1999. It is imperative to improve our understanding hydrological conditions effecting kite reproduction and recruitment. Water Conservation area 3-A, WCA3A, is one of the 'most critical' wetlands comprising the range of the kite in Florida (see Bennetts and Kitchens 1997, Mooij et al. 2002, Martin et al. 2006, 2008). Snail kite reproduction in WCA3A sharply decreased after 1998 (Martin et al. 2008), and alarmingly, no kites were fledged there in 2001, 2005, 2007, or 2008. Bowling (20098) found that juvenile movement probabilities away (emigrating) from WCA3A were significantly higher for the few kites that did fledge there in recent years (i.e. 2003, 2004, 2006) compared to those that fledged there in the 1990s. The paucity of reproduction in and the high probability of juveniles emigrating from WCA3A are likely indicative of habitat degradation (Bowling 20098, Martin et al. 2008), which may stem, at least in part, from a shift in water management regimes (Zweig and Kitchens 2008). Given the recent demographic trends in snail kite population, the need for a comprehensive conservation strategy is imperative; however, information gaps currently preclude our ability to simultaneously manage the hydrology in WCA3A with respect to vegetation, snails, and kites. While there have been significant efforts in filling critical information gaps regarding snail kite demography (e.g., Martin et al. 2008) and variation in apple snail density to water management issues (e.g., Darby et al. 2002, Karunaratne et al. 2006, Darby et al. 2008), there is surprisingly very little information relevant for management that directly links variation in apple snail density with the demography and behavior of snail kites (but see Bennetts et al. 2006). The U.S. Fish and Wildlife Service (USFWS), the U. S. Army Corps of Engineers, and the Florida Fish and Wildlife Conservation Commission (FWC) have increasingly sought information pertaining to the potential effects of specific hydrological management regimes with respect to the apple snail and snail kite populations, as well as the vegetative communities that support them. proprietary
USGS_SOFIA_YY_Males Development of YY male technology to control non-native fishes in the Greater Everglades CEOS_EXTRA STAC Catalog 2009-10-01 -81, 25, -80, 26 https://cmr.earthdata.nasa.gov/search/concepts/C2231552421-CEOS_EXTRA.umm_json Dozens of non-native fish species have established throughout south Florida (including Everglades National Park, Big Cypress National Preserve, Biscayne National Park and various state and private lands). Thus far, research on these species has focused on documenting their distributions, natural history, and physiological tolerances. Research is beginning to emerge on interactions of native species with non-natives, although it is only in the early stages. Research on control of non-native fishes in South Florida is also lacking, although it is potentially the most important and useful to natural resource managers. At present, the only management techniques available to control non-native fishes are physical removal, dewatering or ichthyocides. Unfortunately, all of these methods negatively impact native fauna as well as the targeted non-native fishes and require a great deal of effort (and therefore, funding). Herein, we propose a research program focused on applying a genetic technique common in aquaculture to control of non-native fishes. This proposal focuses on developing a technique (YY supermales) to control a non-native fish in South Florida (African jewelfish Hemichromis letourneuxi). However, the concept can be applied to a wide variety of species, including other fishes (e.g., brown hoplo Hoplosternum littorale), invasive applesnails (Pomacea spp.), the Australian red claw crayfish (Cherax spp.) and the green mussel (Perna veridis). proprietary
-USGS_SOFIA_aerial-photos Aerial Photos of the 1940s ALL STAC Catalog 1940-02-14 1940-08-21 -81.9, 24.41, -79.98, 26.22 https://cmr.earthdata.nasa.gov/search/concepts/C2231554384-CEOS_EXTRA.umm_json The images are available as .jpeg and as georeferenced .tiff files. With the exception of three images, all images are subset to 7500 pixels square. Individual photos can be selected from the 1940 flight lines image at http://sofia.usgs.gov/exchange/aerial-photos/40s_flight.html The numbering scheme for the aerial photos is an identification number consisting of the flight number followed by the photo or frame number. A foundation for Everglades research must include a clear understanding of the pre-drainage south Florida landscape. Knowledge of the spatial organization and structure of pre-drainage landscape communities such as mangrove forests, marshes, sloughs, wet prairies. And pinelands, is essential to provide potential endpoints, restoration goals and performance measures to gauge restoration success. Information contained in historical aerial photographs of the Everglades can aid in this endeavor. The earliest known aerial photographs are from the mid-to-late 1920s and resulted in the production of what are called T-sheets (Topographic sheets) for the coasts and shorelines of far south Florida. The position of the boundary between differing vegetation communities (the ecotone) can be accurately measured. If followed through time, changes in the position of these ecotones could potentially be used to judge effects of drainage on the Everglades ecosystem and to monitor restoration success. The Florida Integrated Science Center (FISC), a center of the U.S. Geological Survey's (USGS) Biological Resources Discipline (BRD), in collaboration with the Eastern Region Geography (ERG) of the Geography Discipline has created digital files of existing 1940 (1:40,000-scale) Black and White aerial photography for the South Florida region. These digital files are available through the SOFIA web site at http://sofia.usgs.gov/exchange/aerial-photos/index.html proprietary
USGS_SOFIA_aerial-photos Aerial Photos of the 1940s CEOS_EXTRA STAC Catalog 1940-02-14 1940-08-21 -81.9, 24.41, -79.98, 26.22 https://cmr.earthdata.nasa.gov/search/concepts/C2231554384-CEOS_EXTRA.umm_json The images are available as .jpeg and as georeferenced .tiff files. With the exception of three images, all images are subset to 7500 pixels square. Individual photos can be selected from the 1940 flight lines image at http://sofia.usgs.gov/exchange/aerial-photos/40s_flight.html The numbering scheme for the aerial photos is an identification number consisting of the flight number followed by the photo or frame number. A foundation for Everglades research must include a clear understanding of the pre-drainage south Florida landscape. Knowledge of the spatial organization and structure of pre-drainage landscape communities such as mangrove forests, marshes, sloughs, wet prairies. And pinelands, is essential to provide potential endpoints, restoration goals and performance measures to gauge restoration success. Information contained in historical aerial photographs of the Everglades can aid in this endeavor. The earliest known aerial photographs are from the mid-to-late 1920s and resulted in the production of what are called T-sheets (Topographic sheets) for the coasts and shorelines of far south Florida. The position of the boundary between differing vegetation communities (the ecotone) can be accurately measured. If followed through time, changes in the position of these ecotones could potentially be used to judge effects of drainage on the Everglades ecosystem and to monitor restoration success. The Florida Integrated Science Center (FISC), a center of the U.S. Geological Survey's (USGS) Biological Resources Discipline (BRD), in collaboration with the Eastern Region Geography (ERG) of the Geography Discipline has created digital files of existing 1940 (1:40,000-scale) Black and White aerial photography for the South Florida region. These digital files are available through the SOFIA web site at http://sofia.usgs.gov/exchange/aerial-photos/index.html proprietary
+USGS_SOFIA_aerial-photos Aerial Photos of the 1940s ALL STAC Catalog 1940-02-14 1940-08-21 -81.9, 24.41, -79.98, 26.22 https://cmr.earthdata.nasa.gov/search/concepts/C2231554384-CEOS_EXTRA.umm_json The images are available as .jpeg and as georeferenced .tiff files. With the exception of three images, all images are subset to 7500 pixels square. Individual photos can be selected from the 1940 flight lines image at http://sofia.usgs.gov/exchange/aerial-photos/40s_flight.html The numbering scheme for the aerial photos is an identification number consisting of the flight number followed by the photo or frame number. A foundation for Everglades research must include a clear understanding of the pre-drainage south Florida landscape. Knowledge of the spatial organization and structure of pre-drainage landscape communities such as mangrove forests, marshes, sloughs, wet prairies. And pinelands, is essential to provide potential endpoints, restoration goals and performance measures to gauge restoration success. Information contained in historical aerial photographs of the Everglades can aid in this endeavor. The earliest known aerial photographs are from the mid-to-late 1920s and resulted in the production of what are called T-sheets (Topographic sheets) for the coasts and shorelines of far south Florida. The position of the boundary between differing vegetation communities (the ecotone) can be accurately measured. If followed through time, changes in the position of these ecotones could potentially be used to judge effects of drainage on the Everglades ecosystem and to monitor restoration success. The Florida Integrated Science Center (FISC), a center of the U.S. Geological Survey's (USGS) Biological Resources Discipline (BRD), in collaboration with the Eastern Region Geography (ERG) of the Geography Discipline has created digital files of existing 1940 (1:40,000-scale) Black and White aerial photography for the South Florida region. These digital files are available through the SOFIA web site at http://sofia.usgs.gov/exchange/aerial-photos/index.html proprietary
USGS_SOFIA_analysis_hist_wq Analysis of Historic Water Quality Data CEOS_EXTRA STAC Catalog 1960-01-01 2005-09-30 -81.55, 25.11, -80.125, 26.75 https://cmr.earthdata.nasa.gov/search/concepts/C2231553759-CEOS_EXTRA.umm_json "The Big Cypress National Preserve (BICY), the Everglades National Park (EVER), and Loxahatchee National Wildlife Refuge (LOX) are water-dominated ecosystems that are susceptible to water-quality impacts. A comprehensive analysis of historical water-quality and ancillary data is needed to direct the restoration of the Everglades and the adoption of water-quality standards in BICY, EVER, and LOX because of their designations as Outstanding Florida Waters. Big Cypress National Preserve (BICY), Everglades National Park (EVER)), and Loxahatchee National Wildlife Refuge (LOX) maintain separate networks of hydrologic monitoring stations (hydrostations) for measuring the stage and quality of surface water throughout their units. The data collected at these sites provides a historical baseline for assessing hydrologic conditions and making a wide range of management decisions (both internally and externally). Surface-water stage data is relatively straight-forward to analyze, both in real time and relative to historic conditions, and has typically been conducted by in-house hydrology staff at both units. Analysis of surface water-quality data is generally regarded as being more complex because of the subtleness of trends, absence of continuous data (bi-monthly for BICY and monthly for EVER), and dependence on surface water depth and season. Collection and analysis of water-quality samples at BICY, EVER, and LOX are done under cooperative agreements with the South Florida Water Management District (SFWMD). Under these agreements, the Park Service collects the samples in the field and the SFWMD provides sampling equipment and laboratory analyses. EVER has been sampling water quality on a monthly basis at 9 ""internal marsh"" stations since 1984 as part of this program. BICY has been sampling water quality on a monthly basis at 10 ""internal"" stations since 1995 as part of this agreement, with water quality data at these sites extending as far back to 1988 (but not as part of the agreement). Water-quality data collected at the BICY and EVER stations has been archived and reported for short-time intervals (yearly and bi-yearly), but an analysis that covers all sampled parameters, extends over the full period of record, and provides comparisons between the two parks has yet to be performed. Water-quality data have been collected at 14 internal marsh sites in LOX by the U.S. Fish and Wildlife Service for over 10 years. These samples have been analyzed by SFWMD laboratory. In 2000, a study was begun by the U.S. Geological Survey to gather, edit, and interpret selected water-quality data from a variety of sources to improve the understanding of changes in water-quality in areas impacted by human activities or in more remote and relatively unimpacted areas of the Everglades and Big Cypress Swamp. One purpose is to look for long-term trends and possibly relate the trends to human or natural influences on water quality such as agriculture, drought, hurricanes, changes in water management, etc. Another purpose is to interpret data from the most remote and unimpacted areas to discern, if possible, what the natural background concentrations are for water-quality constituents that have sufficient data. An attempt will be made to find correlations between available water-quality, physical, and meteorological parameters. Such analyses of water-quality and ancillary data may assist in establishing water-quality standards appropriate for the designation as Outstanding Florida Waters in both the Everglades National Park and the Big Cypress National Preserve. Ancillary data such as precipitation, water-level, water flow, dates of major storms, and beginning and ending dates of water-control effects will be studied to relate their timing to any noticeable changes in water quality. The initial study area was in BICY and EVER; the study area was extended into LOX in 2003." proprietary
USGS_SOFIA_asr_data_lake_okee Aquifer Storage and Recovery Data (Lake Okeechobee) CEOS_EXTRA STAC Catalog 1999-08-01 2000-05-31 -81.08, 26.35, -80.28, 27.2 https://cmr.earthdata.nasa.gov/search/concepts/C2231554472-CEOS_EXTRA.umm_json The objective of this project was to determine geochemically significant water-quality characteristics of possible aquifer storage and recovery (ASR) source and receiving waters north of Lake Okeechobee and at a site along the Hillsboro Canal. The data from this study will be combined with similar information on the detailed composition of aquifer materials in ASR receiving zones to develop geochemical models. Such models are needed to evaluate the possible chemical reactions that may change the physical properties of the aquifer matrix and/or the quality of injected water prior to recovery. proprietary
-USGS_SOFIA_atlss_prog Across Trophic Level System Simulation (ATLSS) Program ALL STAC Catalog 1996-01-01 -81.30333, 24.696152, -80.26212, 25.847113 https://cmr.earthdata.nasa.gov/search/concepts/C2231554119-CEOS_EXTRA.umm_json The ATLSS (Across Trophic Level System Simulation) program addresses CERP’s (Comprehensive Everglades Restoration Plan) need for quantitative projections of effects of scenarios on biota of the Greater Everglades and can provide guidance to monitoring in an adaptive assessment framework. It does this through creating a suite of models for selected Everglades biota, which can translate the hydrologic scenarios into effects on habitat and demographic variables of populations. ATLSS is constructed as a multimodel, meaning that it includes a collection of linked models for various physical and biotic systems components of the Greater Everglades. The ATLSS models are all linked through a common framework of vegetative, topographic, and land use maps that allow for the necessary interaction between spatially explicit information on physical processes and the dynamics of organism response across the landscape. Currently, two important new developments are taking place. First the ATLSS models will soon migrate to a Web-based availability, so that they can be run remotely for various hydrologic scenarios and a set of different assumptions. Second, a vegetation succession model is being completed, which will allow projection of changes in vegetation types across the Everglades landscape as a function of changing hydrology, fire frequency, and nutrient loading. An essential component of restoration planning in South Florida has been the development and use of computer simulation models for the major physical processes driving the system, notably models of hydrology incorporating effects of alternative human control systems and non controlled inputs such as rainfall. The USGS’s ATLSS (Across Trophic Level System Simulation) Program utilizes the outputs of such physical system models as inputs to a variety of ecological models that compare the relative impacts of alternative hydrologic scenarios on the biotic components of South Florida. The immediate objective of ATLSS is to provide a rational, scientific basis for ranking the water management scenarios as part of to the planning process for Everglades restoration. The longer term goals of ATLSS are to help achieve a better understanding of components of the Everglades ecosystem, to provide an integrative tool for empirical studies, and to provide a framework monitoring and adaptive management schemes. The ATLSS Program coordinates and integrates the work of modelers and empirical ecologists at many universities and research centers. The ongoing goals in the ATLSS Program have been to produce models capable of projecting and comparing the effects of alternative hydrologic scenarios on various trophic components of the Everglades. The methodology involves: 1) a landscape structure; 2) a high resolution topography to estimate high resolution water depth across the landscape; 3) models to calculate spatially explicit species indices (SESI) for breeding and foraging success measures across the landscape; 4) spatially explicit individual-based (SEIB) computer simulation models of selected species populations; and 5) ability to plug into variety of visualization and evaluation tools to aid model development, validation, and comparison to field data. Included in this are numerous sub-projects for different species, vegetation succession, analysis of alternative approaches to developing high resolution, models which deal with estuarine systems, methods to allow users from a variety of agencies to access and run the models, and methods to enhance the computational efficiency of the simulations. The continuing general objective is to provide a flexible, efficient collection of methods, utilizing the best current science, to evaluate the relative impacts of alternative hydrologic plans on the biotic systems of South Florida. This is done in a spatially-explicit manner which allows different stakeholders to evaluate the impacts based upon their own criteria for the locations and biotic systems under consideration. There are four projects under the ATLSS program: 1. ATLSS Model Use in CERP Evaluations, Model Testing and Extension to Web-Based Interface 2. Development of an Internet Based GIS to Visualize ATLSS Datasets for Resource Managers 3. Spatial Decision Support for Biodiversity and Indicator Species Responses to CERP Project Activities 4. Integrating Wading Bird Empirical Data into a Model of Wading Bird Foraging Success as a Function of Hydrologic Conditions There are several submodels within the ATLSS Project, including: Alligators, Cape Sable Seaside Sparrows, Crayfish, Deer, Fish, Florida Panthers, Hydrology, Snail Kite, Landscape/Vegetation, and Wading Birds. Models currently available are: ATLSS SESI models: Cape sable seaside sparrow breeding potential index (Version 1.1) Snail kite breeding potential index (Version 1.1) Long-legged wading bird foraging condition index (Version 1.1) Short-legged wading bird foraging condition index (Version 1.1) Empirically-based fish biomass index (Version 1.1) White-tailed deer breeding potential index (Version 1.1) American alligator breeding potential index (Version 1.1) Everglades and slough crayfish (Version 1.1) Apple snail SESI model (Version 1.1) Spatially Explicit Demographic Models: Cape sable seaside sparrow demographic model (SIMSPAR - Version 1.3) Snail kite demographic model (EVERKITE - Version 3.1) Alligator demographic model (Version 1.1) Spatially Explicit Functional Group Models: Freshwater fish dynamics (ALFISH - Version 3.1.17) GIS Animal Tracking Tool: Florida panther tracking tool (PANTRACK - Version 1.1) Landscape Models: High Resolution Topography (HRT - Version 1.4.8) Vegetation productivity (HTDAM - Version 1.1) High Resolution Hydrology (HRH - Version 1.4.8) proprietary
USGS_SOFIA_atlss_prog Across Trophic Level System Simulation (ATLSS) Program CEOS_EXTRA STAC Catalog 1996-01-01 -81.30333, 24.696152, -80.26212, 25.847113 https://cmr.earthdata.nasa.gov/search/concepts/C2231554119-CEOS_EXTRA.umm_json The ATLSS (Across Trophic Level System Simulation) program addresses CERP’s (Comprehensive Everglades Restoration Plan) need for quantitative projections of effects of scenarios on biota of the Greater Everglades and can provide guidance to monitoring in an adaptive assessment framework. It does this through creating a suite of models for selected Everglades biota, which can translate the hydrologic scenarios into effects on habitat and demographic variables of populations. ATLSS is constructed as a multimodel, meaning that it includes a collection of linked models for various physical and biotic systems components of the Greater Everglades. The ATLSS models are all linked through a common framework of vegetative, topographic, and land use maps that allow for the necessary interaction between spatially explicit information on physical processes and the dynamics of organism response across the landscape. Currently, two important new developments are taking place. First the ATLSS models will soon migrate to a Web-based availability, so that they can be run remotely for various hydrologic scenarios and a set of different assumptions. Second, a vegetation succession model is being completed, which will allow projection of changes in vegetation types across the Everglades landscape as a function of changing hydrology, fire frequency, and nutrient loading. An essential component of restoration planning in South Florida has been the development and use of computer simulation models for the major physical processes driving the system, notably models of hydrology incorporating effects of alternative human control systems and non controlled inputs such as rainfall. The USGS’s ATLSS (Across Trophic Level System Simulation) Program utilizes the outputs of such physical system models as inputs to a variety of ecological models that compare the relative impacts of alternative hydrologic scenarios on the biotic components of South Florida. The immediate objective of ATLSS is to provide a rational, scientific basis for ranking the water management scenarios as part of to the planning process for Everglades restoration. The longer term goals of ATLSS are to help achieve a better understanding of components of the Everglades ecosystem, to provide an integrative tool for empirical studies, and to provide a framework monitoring and adaptive management schemes. The ATLSS Program coordinates and integrates the work of modelers and empirical ecologists at many universities and research centers. The ongoing goals in the ATLSS Program have been to produce models capable of projecting and comparing the effects of alternative hydrologic scenarios on various trophic components of the Everglades. The methodology involves: 1) a landscape structure; 2) a high resolution topography to estimate high resolution water depth across the landscape; 3) models to calculate spatially explicit species indices (SESI) for breeding and foraging success measures across the landscape; 4) spatially explicit individual-based (SEIB) computer simulation models of selected species populations; and 5) ability to plug into variety of visualization and evaluation tools to aid model development, validation, and comparison to field data. Included in this are numerous sub-projects for different species, vegetation succession, analysis of alternative approaches to developing high resolution, models which deal with estuarine systems, methods to allow users from a variety of agencies to access and run the models, and methods to enhance the computational efficiency of the simulations. The continuing general objective is to provide a flexible, efficient collection of methods, utilizing the best current science, to evaluate the relative impacts of alternative hydrologic plans on the biotic systems of South Florida. This is done in a spatially-explicit manner which allows different stakeholders to evaluate the impacts based upon their own criteria for the locations and biotic systems under consideration. There are four projects under the ATLSS program: 1. ATLSS Model Use in CERP Evaluations, Model Testing and Extension to Web-Based Interface 2. Development of an Internet Based GIS to Visualize ATLSS Datasets for Resource Managers 3. Spatial Decision Support for Biodiversity and Indicator Species Responses to CERP Project Activities 4. Integrating Wading Bird Empirical Data into a Model of Wading Bird Foraging Success as a Function of Hydrologic Conditions There are several submodels within the ATLSS Project, including: Alligators, Cape Sable Seaside Sparrows, Crayfish, Deer, Fish, Florida Panthers, Hydrology, Snail Kite, Landscape/Vegetation, and Wading Birds. Models currently available are: ATLSS SESI models: Cape sable seaside sparrow breeding potential index (Version 1.1) Snail kite breeding potential index (Version 1.1) Long-legged wading bird foraging condition index (Version 1.1) Short-legged wading bird foraging condition index (Version 1.1) Empirically-based fish biomass index (Version 1.1) White-tailed deer breeding potential index (Version 1.1) American alligator breeding potential index (Version 1.1) Everglades and slough crayfish (Version 1.1) Apple snail SESI model (Version 1.1) Spatially Explicit Demographic Models: Cape sable seaside sparrow demographic model (SIMSPAR - Version 1.3) Snail kite demographic model (EVERKITE - Version 3.1) Alligator demographic model (Version 1.1) Spatially Explicit Functional Group Models: Freshwater fish dynamics (ALFISH - Version 3.1.17) GIS Animal Tracking Tool: Florida panther tracking tool (PANTRACK - Version 1.1) Landscape Models: High Resolution Topography (HRT - Version 1.4.8) Vegetation productivity (HTDAM - Version 1.1) High Resolution Hydrology (HRH - Version 1.4.8) proprietary
+USGS_SOFIA_atlss_prog Across Trophic Level System Simulation (ATLSS) Program ALL STAC Catalog 1996-01-01 -81.30333, 24.696152, -80.26212, 25.847113 https://cmr.earthdata.nasa.gov/search/concepts/C2231554119-CEOS_EXTRA.umm_json The ATLSS (Across Trophic Level System Simulation) program addresses CERP’s (Comprehensive Everglades Restoration Plan) need for quantitative projections of effects of scenarios on biota of the Greater Everglades and can provide guidance to monitoring in an adaptive assessment framework. It does this through creating a suite of models for selected Everglades biota, which can translate the hydrologic scenarios into effects on habitat and demographic variables of populations. ATLSS is constructed as a multimodel, meaning that it includes a collection of linked models for various physical and biotic systems components of the Greater Everglades. The ATLSS models are all linked through a common framework of vegetative, topographic, and land use maps that allow for the necessary interaction between spatially explicit information on physical processes and the dynamics of organism response across the landscape. Currently, two important new developments are taking place. First the ATLSS models will soon migrate to a Web-based availability, so that they can be run remotely for various hydrologic scenarios and a set of different assumptions. Second, a vegetation succession model is being completed, which will allow projection of changes in vegetation types across the Everglades landscape as a function of changing hydrology, fire frequency, and nutrient loading. An essential component of restoration planning in South Florida has been the development and use of computer simulation models for the major physical processes driving the system, notably models of hydrology incorporating effects of alternative human control systems and non controlled inputs such as rainfall. The USGS’s ATLSS (Across Trophic Level System Simulation) Program utilizes the outputs of such physical system models as inputs to a variety of ecological models that compare the relative impacts of alternative hydrologic scenarios on the biotic components of South Florida. The immediate objective of ATLSS is to provide a rational, scientific basis for ranking the water management scenarios as part of to the planning process for Everglades restoration. The longer term goals of ATLSS are to help achieve a better understanding of components of the Everglades ecosystem, to provide an integrative tool for empirical studies, and to provide a framework monitoring and adaptive management schemes. The ATLSS Program coordinates and integrates the work of modelers and empirical ecologists at many universities and research centers. The ongoing goals in the ATLSS Program have been to produce models capable of projecting and comparing the effects of alternative hydrologic scenarios on various trophic components of the Everglades. The methodology involves: 1) a landscape structure; 2) a high resolution topography to estimate high resolution water depth across the landscape; 3) models to calculate spatially explicit species indices (SESI) for breeding and foraging success measures across the landscape; 4) spatially explicit individual-based (SEIB) computer simulation models of selected species populations; and 5) ability to plug into variety of visualization and evaluation tools to aid model development, validation, and comparison to field data. Included in this are numerous sub-projects for different species, vegetation succession, analysis of alternative approaches to developing high resolution, models which deal with estuarine systems, methods to allow users from a variety of agencies to access and run the models, and methods to enhance the computational efficiency of the simulations. The continuing general objective is to provide a flexible, efficient collection of methods, utilizing the best current science, to evaluate the relative impacts of alternative hydrologic plans on the biotic systems of South Florida. This is done in a spatially-explicit manner which allows different stakeholders to evaluate the impacts based upon their own criteria for the locations and biotic systems under consideration. There are four projects under the ATLSS program: 1. ATLSS Model Use in CERP Evaluations, Model Testing and Extension to Web-Based Interface 2. Development of an Internet Based GIS to Visualize ATLSS Datasets for Resource Managers 3. Spatial Decision Support for Biodiversity and Indicator Species Responses to CERP Project Activities 4. Integrating Wading Bird Empirical Data into a Model of Wading Bird Foraging Success as a Function of Hydrologic Conditions There are several submodels within the ATLSS Project, including: Alligators, Cape Sable Seaside Sparrows, Crayfish, Deer, Fish, Florida Panthers, Hydrology, Snail Kite, Landscape/Vegetation, and Wading Birds. Models currently available are: ATLSS SESI models: Cape sable seaside sparrow breeding potential index (Version 1.1) Snail kite breeding potential index (Version 1.1) Long-legged wading bird foraging condition index (Version 1.1) Short-legged wading bird foraging condition index (Version 1.1) Empirically-based fish biomass index (Version 1.1) White-tailed deer breeding potential index (Version 1.1) American alligator breeding potential index (Version 1.1) Everglades and slough crayfish (Version 1.1) Apple snail SESI model (Version 1.1) Spatially Explicit Demographic Models: Cape sable seaside sparrow demographic model (SIMSPAR - Version 1.3) Snail kite demographic model (EVERKITE - Version 3.1) Alligator demographic model (Version 1.1) Spatially Explicit Functional Group Models: Freshwater fish dynamics (ALFISH - Version 3.1.17) GIS Animal Tracking Tool: Florida panther tracking tool (PANTRACK - Version 1.1) Landscape Models: High Resolution Topography (HRT - Version 1.4.8) Vegetation productivity (HTDAM - Version 1.1) High Resolution Hydrology (HRH - Version 1.4.8) proprietary
USGS_SOFIA_avian_ecology_spoonbills Avian Ecology of the Greater Everglades (Roseate Spoonbill and Limpkins) CEOS_EXTRA STAC Catalog 2002-10-01 2005-09-30 -81.25, 24.875, -80.375, 25.375 https://cmr.earthdata.nasa.gov/search/concepts/C2231549705-CEOS_EXTRA.umm_json "The primary objectives of our research are to (1) quantify the changes in spatial distribution and success of nesting spoonbills relative to hydrologic patterns, (2) test hypotheses about the causal mechanisms for observed changes, (3) establish a science-based criteria for nesting distribution and success to be used as a performance measure for hydrologic restoration, and (4) estimate demographic parameters. To meet these objectives, we will use a combined field/modeling approach. Based on previous and concurrent research, hypothesized relationships between hydrology, fish populations, and spoonbill nesting distribution and success will be expressed in a simple, but spatially explicit, conceptual model. Field data will be collected and compared with predicted responses to monitor changes in spoonbill nesting as hydrologic restoration is implemented, and to test the hypothesized mechanisms for observed changes. Variation of hydrologic conditions among years and locations is a virtual certainty; thus we will treat this variation in a quasi-experimental framework where the variation in wet and dry season conditions constitutes a series of ""natural experiments"". Our project is designed to evaluate the effect of hydrologic restoration on the nesting distribution and success of Roseate Spoonbills (Ajaia ajaia) in Florida Bay and surrounding mangrove estuarine habitats. This project is further designed to test hypotheses about the causal mechanisms of observed changes. The Everglades ecosystem has suffered extensive degradation over the past century, including an 85-90% decrease in the numbers of wading birds. Previous monitoring of Roseate Spoonbills in Florida Bay over the past 50 years has shown that this species responds markedly to changes in hydrology and corresponding changes in prey abundance and availability. Shifts in nesting distribution and declines in nest success have been attributed to declines in prey populations as a direct result of water management. Consequently, the re-establishment of spoonbill colonies in northeast Florida Bay is one change predicted under a conceptual model of the mangrove estuarine transition zone of Florida Bay. Changes in nesting distribution and success will further be used as a performance measure for success of restoration efforts and will be incorporated in a model linking mangrove fish populations and spoonbills to alternative hydrologic scenarios." proprietary
USGS_SOFIA_ba_geologic_data Biscayne Aquifer geologic data CEOS_EXTRA STAC Catalog 1998-01-01 2005-12-31 -80.6, 25.5, -80.3, 26 https://cmr.earthdata.nasa.gov/search/concepts/C2231550961-CEOS_EXTRA.umm_json This report from which the data is taken identifies and characterizes candidate ground-water flow zones in the upper part of the shallow, eogenetic karst limestone of the Biscayne aquifer using GPR, cyclostratigraphy, borehole geophysical logs, continuously drilled cores, and paleontology. About 60 mi of GPR profiles were acquired and are used to calculate the depth to shallow geologic contacts and hydrogeologic units, image karst features, and produce a qualitative perspective of the porosity distribution within the upper part of the karstic Biscayne aquifer in the Lake Belt area of north-central Miami-Dade County. . Descriptions of lithology, rock fabric, cyclostratigraphy, and depositional environments of 50 test coreholes were linked to geophysical data to provide a more refined hydrogeologic framework for the upper part of the Biscayne aquifer. Interpretation of depositional environments was constrained by analysis of depositional textures and molluscan and benthic foraminiferal paleontology. Digital borehole images were used to help quantify large-scale vuggy porosity. Preliminary heat-pulse flowmeter data were coupled with the digital borehole image data to identify potential ground-water flow zones. The objectives of this cooperative project were to identify and characterize candidate ground-water flow zones in the upper part of the shallow, eogenetic karst limestone of the Biscayne aquifer using ground-penetrating radar, cyclostratigraphy, borehole geophysical logs, continuously drilled cores and paleontology. In 1998, the U.S. Geological Survey (USGS), in cooperation with the South Florida Water Management District (SFWMD), initiated a study to provide a regional-scale hydrogeologic framework of a shallow semiconfining unit within the Biscayne aquifer of southeastern Florida. Initially, the primary objective was to characterize and delineate a low-permeability zone in the upper part of the Biscayne aquifer that spans the base of the Miami Limestone and uppermost part of the Fort Thompson Formation. Delineation of this zone was to aid development of a conceptual hydrogeologic model to be used as input into the SFWMD Lake Belt ground-water model. The approximate area encompassed by the conceptual hydrogeologic model is shown as the study area at http://sofia.usgs.gov/exchange/cunningham/bbwelllocation.html. Subsequent analysis of the preliminary data suggested hydraulic compartmentalization occurred within the Biscayne aquifer, and that there was a need to characterize and delineate ground-water flow zones and relatively low-permeability zones within the upper part of the Biscayne aquifer. Consequently, preliminary results suggested that the historical understanding of the porosity and preferential pathways for Biscayne aquifer ground-water flow required considerable revision. This project was carried out in cooperation with the South Florida Water Management District (SFWMD). proprietary
USGS_SOFIA_bbcw_geophysical Biscayne Bay Coastal Wetlands Geophysical Data CEOS_EXTRA STAC Catalog 2004-01-01 -80.4, 25.4, -80.3, 25.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231549059-CEOS_EXTRA.umm_json The objectives of this data acquisition project were to complete the downhole geophysical logging including video and flowmeter logging of two core holes (9A and 11A), which are the deepest wells at monitor well sites 0009AB and 0011AB. The goal of the Comprehensive Everglades Restoration Plan Biscayne Bay Coastal Wetlands Project (BBCWP) is to rehydrate wetlands and reduce point-source discharge to Biscayne Bay. The BBCWP will replace lost overland flow and partially compensate for the reduction in ground-water seepage by redistributing, through a spreader system, available surface water entering the area from regional canals. The proposed redistribution of freshwater flow across a broad front is expected to restore or enhance freshwater wetlands, tidal wetlands, and near shore bay habitat. A critical component of the BBCWP is the development of a realistic representation of ground-water flow within the karst Biscayne aquifer. Mapping these ground-water flow units is key to the development of models that simulate ground-water flow from the Everglades and urban areas through the coastal wetlands to Biscayne Bay. Because there is little detailed hydrogeologic data of the Surficial aquifer (to depth) in this area, the Biscayne Bay Coastal Wetlands Project Delivery Team installed two monitor-well sites and collected the necessary detailed hydrogeologic data. The L-31 North Canal Seepage Management Pilot Project is intended to curtail easterly seepage emanating from within Everglades National Park (ENP). The pilot project is examining various seepage management technologies as well as operational changes that could be implemented to reduce the water losses from ENP. This project is in close proximity to Biscayne Bay so an effort has been made to combine ongoing work efforts at the two project areas. The distribution of seepage into the L-31 North Canal and beneath it is not known with any degree of certainty today. A canal draw down experiment was conducted to provide additional field data that will be utilized to refine seepage estimates in the study area as well as determine aquifer parameters in the study area. This project was funded by the USGS Florida Integrated Science Center and the South Florida Water Management District (SFWMD). proprietary
@@ -16124,8 +16125,8 @@ USGS_SOFIA_chron_isotope_geochem_FL_Keys Chronology and Isotope Geochemistry of
USGS_SOFIA_coastal_ever_tjslll_04 Coastal Everglades Wetlands: Hydrology, Vegetation and Sediment Dynamics CEOS_EXTRA STAC Catalog 2002-10-01 2009-12-31 -81.75, 25, -80.25, 26.25 https://cmr.earthdata.nasa.gov/search/concepts/C2231550711-CEOS_EXTRA.umm_json This project has three objectives (tasks): 1) operate and maintain the Mangrove Hydrology sampling network; 2) study the dynamics of coastal vegetation (mangroves, marshes) in relation to sea-level, fire, disturbance and restoration; and, 3) measure rates of sediment surface elevation change and soil accretion or loss in coastal mangrove forests and brackish marshes of the Everglades and determine how sediment elevation varies in relation to hydrology (i.e. the restoration). The objective of this project is to conduct integrated studies to develop an understanding of how hydrologic parameters, disturbance, sediment, and global change (e.g. sea level) influence ecological systems in coastal wetlands. Hydrological factors studied include surface and groundwater stage and conductivity, surface water flow, nutrient concentration and suspended sediment. Fire, freeze, hurricanes and lightning strikes are among the disturbances that are important in coastal wetlands. Sediment elevation changes in coastal wetlands as a function of plant growth and decomposition, accretion or erosion due to tides and surface water flows, fire (in freshwater peats) and hurricanes. Both positive and negative feedbacks on sediment elevation have been discovered. Sea level has increased almost 30cm in the past century. The influence of continued sea level rise on CERP for restoring coastal areas is unknown at present. These questions have been addressed by the development of an integrated network of sampling and measurement sites where instrumentation is collocated. Many sites have surface and ground water sampling wells, sediment elevations tables and permanent vegetation plots. Transects, with both permanent plots and hydrology sampling wells, have been established across the mangrove - marsh ecotone to examine the influence of hydrology and fires (both partly controllable), freezes and sea level (not manageable) on the position of the ecotone. proprietary
USGS_SOFIA_coastal_grads Coastal Gradients of Flow, Salinity, and Nutrients CEOS_EXTRA STAC Catalog 2003-01-01 2010-12-31 -81.125, 25.08, -80.08, 25.67 https://cmr.earthdata.nasa.gov/search/concepts/C2231552103-CEOS_EXTRA.umm_json Ten monitoring stations will be operated and maintained along the southwest coast of ENP, the Everglades wetlands, and along the coastlines of northeastern Florida Bay and northwest Barnes Sound. Data collected at these 10 stations will include water level, velocity, salinity, and temperature. Three stations (Upstream North River, North River, and West Highway Creek) will also include automatic samplers for the collection of water samples and determination of Total Nutrients (TN and TP). These 10 stations will complement information currently being generated through an existing network of 20 hydrologic monitoring stations of on-going USGS projects. By combining data collected from the ten monitoring stations and the existing monitoring network, information will be available across 9 generalized coastal gradients or transects. Data collected at all flow sites will be transmitted in near real time (every 1 or 4 hours) by way of satellite telemetry to the automated data processing system (ADAPS) database in the USGS Center for Water and Restoration Studies (CWRS) in Miami and available for CERP purposes. In addition to data from monitoring stations described above, salinity surveys will be performed along these 9 generalized transects, and these will include salinity, temperature, and GPS data from boat-mounted systems. Surveys will be performed regularly on a quarterly basis and twice following hydrologic events, totaling a maximum of 6 surveys per year. The Water Resources Development Act (WRDA) of 2000 authorized the Comprehensive Everglades Restoration Plan (CERP) as a framework for modifications and operational changes to the Central and Southern Florida Project needed to restore the south Florida ecosystem. Provisions within WRDA 2000 provide for specific authorization for an adaptive assessment and monitoring program. A Monitoring and Assessment Plan (MAP) has been developed as the primary tool to assess the system-wide performance of the CERP by the REstoration, COordination and VERification (RECOVER) program. The MAP presents the monitoring and supporting enhancement of scientific information and technology needed to measure the responses of the South Florida ecosystem. The MAP also presents the system-wide performance measures representative of the natural and human systems found in South Florida that will be evaluated to help determine the success of CERP. These system-wide performance measures address the responses of the South Florida ecosystem that the CERP is explicitly designed to improve, correct, or otherwise directly affect. A separate Performance Measure Documentation Report being prepared by RECOVER provides the scientific, technical, and legal basis for the performance measures. This project is intended to support the Greater Everglades (GE) Wetlands module of the MAP and is directly linked to the monitoring or supporting enhancement component In 2003, CERP MAP funding through the South Florida Water Management District established 10 monitoring stations as part of the Coastal Gradients Network. The purpose of this MAP project with the USACE is to continue operation of these 10 stations for the MAP activities. proprietary
USGS_SOFIA_coastal_grads_salsurveys Coastal Gradients Salinity Surveys CEOS_EXTRA STAC Catalog 2003-12-11 -81, 25.16, -80.38, 25.57 https://cmr.earthdata.nasa.gov/search/concepts/C2231553403-CEOS_EXTRA.umm_json Ten monitoring stations were operated and maintained along the southwest coast of ENP, the Everglades wetlands, and along the coastlines of northeastern Florida Bay and northwest Barnes Sound. Data collected at these 10 stations includes water level, velocity, salinity, and temperature. These 10 stations will complement information currently being generated through an existing network of 20 hydrologic monitoring stations of on-going USGS projects. The Water Resources Development Act (WRDA) of 2000 authorized the Comprehensive Everglades Restoration Plan (CERP) as a framework for modifications and operational changes to the Central and Southern Florida Project needed to restore the south Florida ecosystem. Provisions within WRDA 2000 provide for specific authorization for an adaptive assessment and monitoring program. A Monitoring and Assessment Plan (MAP) has been developed as the primary tool to assess the system-wide performance of the CERP by the REstoration, COordination and VERification (RECOVER) program. The MAP presents the monitoring and supporting enhancement of scientific information and technology needed to measure the responses of the South Florida ecosystem. The MAP also presents the system-wide performance measures representative of the natural and human systems found in South Florida that will be evaluated to help determine the success of CERP. These system-wide performance measures address the responses of the South Florida ecosystem that the CERP is explicitly designed to improve, correct, or otherwise directly affect. A separate Performance Measure Documentation Report being prepared by RECOVER provides the scientific, technical, and legal basis for the performance measures. This project is intended to support the Greater Everglades (GE) Wetlands module of the MAP and is directly linked to the monitoring or supporting enhancement component In 2003, CERP MAP funding through the South Florida Water Management District established 10 monitoring stations as part of the Coastal Gradients Network. The purpose of this MAP project with the USACE is to continue operation of these 10 stations for the MAP activities. proprietary
-USGS_SOFIA_coupled_sw-gw_model A Coupled Surface Water and Ground-Water Model to Simulate Past, Present, and Future Hydrologic Conditions in DOI Managed Lands CEOS_EXTRA STAC Catalog 1995-01-01 2009-09-30 -81.56, 25.02, -80, 25.75 https://cmr.earthdata.nasa.gov/search/concepts/C2231553820-CEOS_EXTRA.umm_json This project has two objectives: 1) update and reconfigure the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) modeling code to include all version modifications and enhancements in order to provide easier transition for coupling of models and 2) to develop a comprehensive model by using the established USGS Tides and Inflows to the Mangrove Ecotone (TIME) model application of the southern Everglades and linking it to a coupled surface and ground water model application of Biscayne Bay that is currently in development. The Comprehensive Everglades Restoration Plan (CERP) aims to reestablish predevelopment natural flows in the Everglades system and surrounding areas including Biscayne Bay. The changes proposed within this plan may cause significant alterations to the hydrologic conditions that exist in both Everglades National Park (ENP) and Biscayne National Park (BNP). System-wide, there are water management, water supply, and environmental concerns regarding the impact of wetland restoration on groundwater flow between the ENP and BNP and along the L-31 and C-111 canals. For example, restoration of wetlands may lead to increases in coastal ground-water levels and cause offshore springs in Biscayne Bay to become reestablished as a significant site of freshwater discharge in BNP. Accordingly, the CERP restoration activities may increase the rate of coastal groundwater discharge and aid transport of anthropogenic contaminants into the offshore marine ecosystem. Under this scenario, there is significant potential for habitat deterioration of many different threatened or endangered species of plants and animals that reside along the coastline of Biscayne Bay, in the Bay, or on the coral reef tract. In contrast to a surface water system which has been extensively compartmentalized and channelized, the Biscayne aquifer which flows under both ENP and BNP is continuous and not as amenable to partial domain simulation. A comprehensive model is needed to reliably and credibly assess the effects of groundwater flow and transport on both parks. Hydrologic conditions should be evaluated prior to substantial water delivery changes in order to protect these sensitive ecosystems. A numerical model that can simulate salinity and surface and ground-water flow patterns under different hydrologic conditions is an essential part of this effort. The USGS developed a coupled surface-water/ground-water numerical code known as the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) to represent the surface water and ground-water hydrologic conditions in south Florida, specifically in the Everglades. The FTLOADDS code combines the two-dimensional hydrodynamic surface-water model SWIFT2D to simulate variable density overland flow (Schaffranek, 2004; Swain, 2005), the three-dimensional ground-water model SEAWAT to simulate fully-saturated variable-density groundwater flow (Guo and Langevin, 2002), and accounts for leakage and salt flux between the surface water and ground water (Langevin and others, 2005). The code was then applied to two major testing regions: 1) the Southern Inland and Coastal Systems (SICS) model domain (Swain and others, 2004) and 2) the Tides and Inflows in the Mangroves of the Everglades (TIME) model domain. The first application used code versions 1.0 and 1.1 which only utilized the SWIFT2D surface-water code. Later applications in the SICS area used version 2.1 (Langevin and others, 2005) where SWIFT2D was coupled to the SEAWAT groundwater model code. The second domain, TIME (Wang and others, 2007), utilizes the enhanced version 2.2 code, which includes enhancements to the wetting and drying routines, changes to the frictional resistance terms applications, and calculations of evapotranspiration. In 2006, FTLOADDS was modified again to represent Biscayne Bay and surrounding areas. This will provide one large sub-regional model that will give an integrated comprehensive assessment of how different scenarios will affect water flows in both Everglades National Park and Biscayne National Park. Once calibrated, additional simulations will be performed to estimate predevelopment hydrologic conditions and to predict hydrologic conditions under one or more of the proposed restoration alternatives, using inputs from the Natural Systems Model (NSM) (SFWMD, 1997A) and the South Florida Water Management Model (SFWMM) (MacVicar and others, 1984, SFWMD, 1997B). proprietary
USGS_SOFIA_coupled_sw-gw_model A Coupled Surface Water and Ground-Water Model to Simulate Past, Present, and Future Hydrologic Conditions in DOI Managed Lands ALL STAC Catalog 1995-01-01 2009-09-30 -81.56, 25.02, -80, 25.75 https://cmr.earthdata.nasa.gov/search/concepts/C2231553820-CEOS_EXTRA.umm_json This project has two objectives: 1) update and reconfigure the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) modeling code to include all version modifications and enhancements in order to provide easier transition for coupling of models and 2) to develop a comprehensive model by using the established USGS Tides and Inflows to the Mangrove Ecotone (TIME) model application of the southern Everglades and linking it to a coupled surface and ground water model application of Biscayne Bay that is currently in development. The Comprehensive Everglades Restoration Plan (CERP) aims to reestablish predevelopment natural flows in the Everglades system and surrounding areas including Biscayne Bay. The changes proposed within this plan may cause significant alterations to the hydrologic conditions that exist in both Everglades National Park (ENP) and Biscayne National Park (BNP). System-wide, there are water management, water supply, and environmental concerns regarding the impact of wetland restoration on groundwater flow between the ENP and BNP and along the L-31 and C-111 canals. For example, restoration of wetlands may lead to increases in coastal ground-water levels and cause offshore springs in Biscayne Bay to become reestablished as a significant site of freshwater discharge in BNP. Accordingly, the CERP restoration activities may increase the rate of coastal groundwater discharge and aid transport of anthropogenic contaminants into the offshore marine ecosystem. Under this scenario, there is significant potential for habitat deterioration of many different threatened or endangered species of plants and animals that reside along the coastline of Biscayne Bay, in the Bay, or on the coral reef tract. In contrast to a surface water system which has been extensively compartmentalized and channelized, the Biscayne aquifer which flows under both ENP and BNP is continuous and not as amenable to partial domain simulation. A comprehensive model is needed to reliably and credibly assess the effects of groundwater flow and transport on both parks. Hydrologic conditions should be evaluated prior to substantial water delivery changes in order to protect these sensitive ecosystems. A numerical model that can simulate salinity and surface and ground-water flow patterns under different hydrologic conditions is an essential part of this effort. The USGS developed a coupled surface-water/ground-water numerical code known as the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) to represent the surface water and ground-water hydrologic conditions in south Florida, specifically in the Everglades. The FTLOADDS code combines the two-dimensional hydrodynamic surface-water model SWIFT2D to simulate variable density overland flow (Schaffranek, 2004; Swain, 2005), the three-dimensional ground-water model SEAWAT to simulate fully-saturated variable-density groundwater flow (Guo and Langevin, 2002), and accounts for leakage and salt flux between the surface water and ground water (Langevin and others, 2005). The code was then applied to two major testing regions: 1) the Southern Inland and Coastal Systems (SICS) model domain (Swain and others, 2004) and 2) the Tides and Inflows in the Mangroves of the Everglades (TIME) model domain. The first application used code versions 1.0 and 1.1 which only utilized the SWIFT2D surface-water code. Later applications in the SICS area used version 2.1 (Langevin and others, 2005) where SWIFT2D was coupled to the SEAWAT groundwater model code. The second domain, TIME (Wang and others, 2007), utilizes the enhanced version 2.2 code, which includes enhancements to the wetting and drying routines, changes to the frictional resistance terms applications, and calculations of evapotranspiration. In 2006, FTLOADDS was modified again to represent Biscayne Bay and surrounding areas. This will provide one large sub-regional model that will give an integrated comprehensive assessment of how different scenarios will affect water flows in both Everglades National Park and Biscayne National Park. Once calibrated, additional simulations will be performed to estimate predevelopment hydrologic conditions and to predict hydrologic conditions under one or more of the proposed restoration alternatives, using inputs from the Natural Systems Model (NSM) (SFWMD, 1997A) and the South Florida Water Management Model (SFWMM) (MacVicar and others, 1984, SFWMD, 1997B). proprietary
+USGS_SOFIA_coupled_sw-gw_model A Coupled Surface Water and Ground-Water Model to Simulate Past, Present, and Future Hydrologic Conditions in DOI Managed Lands CEOS_EXTRA STAC Catalog 1995-01-01 2009-09-30 -81.56, 25.02, -80, 25.75 https://cmr.earthdata.nasa.gov/search/concepts/C2231553820-CEOS_EXTRA.umm_json This project has two objectives: 1) update and reconfigure the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) modeling code to include all version modifications and enhancements in order to provide easier transition for coupling of models and 2) to develop a comprehensive model by using the established USGS Tides and Inflows to the Mangrove Ecotone (TIME) model application of the southern Everglades and linking it to a coupled surface and ground water model application of Biscayne Bay that is currently in development. The Comprehensive Everglades Restoration Plan (CERP) aims to reestablish predevelopment natural flows in the Everglades system and surrounding areas including Biscayne Bay. The changes proposed within this plan may cause significant alterations to the hydrologic conditions that exist in both Everglades National Park (ENP) and Biscayne National Park (BNP). System-wide, there are water management, water supply, and environmental concerns regarding the impact of wetland restoration on groundwater flow between the ENP and BNP and along the L-31 and C-111 canals. For example, restoration of wetlands may lead to increases in coastal ground-water levels and cause offshore springs in Biscayne Bay to become reestablished as a significant site of freshwater discharge in BNP. Accordingly, the CERP restoration activities may increase the rate of coastal groundwater discharge and aid transport of anthropogenic contaminants into the offshore marine ecosystem. Under this scenario, there is significant potential for habitat deterioration of many different threatened or endangered species of plants and animals that reside along the coastline of Biscayne Bay, in the Bay, or on the coral reef tract. In contrast to a surface water system which has been extensively compartmentalized and channelized, the Biscayne aquifer which flows under both ENP and BNP is continuous and not as amenable to partial domain simulation. A comprehensive model is needed to reliably and credibly assess the effects of groundwater flow and transport on both parks. Hydrologic conditions should be evaluated prior to substantial water delivery changes in order to protect these sensitive ecosystems. A numerical model that can simulate salinity and surface and ground-water flow patterns under different hydrologic conditions is an essential part of this effort. The USGS developed a coupled surface-water/ground-water numerical code known as the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) to represent the surface water and ground-water hydrologic conditions in south Florida, specifically in the Everglades. The FTLOADDS code combines the two-dimensional hydrodynamic surface-water model SWIFT2D to simulate variable density overland flow (Schaffranek, 2004; Swain, 2005), the three-dimensional ground-water model SEAWAT to simulate fully-saturated variable-density groundwater flow (Guo and Langevin, 2002), and accounts for leakage and salt flux between the surface water and ground water (Langevin and others, 2005). The code was then applied to two major testing regions: 1) the Southern Inland and Coastal Systems (SICS) model domain (Swain and others, 2004) and 2) the Tides and Inflows in the Mangroves of the Everglades (TIME) model domain. The first application used code versions 1.0 and 1.1 which only utilized the SWIFT2D surface-water code. Later applications in the SICS area used version 2.1 (Langevin and others, 2005) where SWIFT2D was coupled to the SEAWAT groundwater model code. The second domain, TIME (Wang and others, 2007), utilizes the enhanced version 2.2 code, which includes enhancements to the wetting and drying routines, changes to the frictional resistance terms applications, and calculations of evapotranspiration. In 2006, FTLOADDS was modified again to represent Biscayne Bay and surrounding areas. This will provide one large sub-regional model that will give an integrated comprehensive assessment of how different scenarios will affect water flows in both Everglades National Park and Biscayne National Park. Once calibrated, additional simulations will be performed to estimate predevelopment hydrologic conditions and to predict hydrologic conditions under one or more of the proposed restoration alternatives, using inputs from the Natural Systems Model (NSM) (SFWMD, 1997A) and the South Florida Water Management Model (SFWMM) (MacVicar and others, 1984, SFWMD, 1997B). proprietary
USGS_SOFIA_dade_biscayne_limit_west_arc Approximate Western Limit of the Biscayne Aquifer in Dade County, USGS WRIR 90-4108, figure 16 CEOS_EXTRA STAC Catalog 1939-01-01 1985-12-31 -80.874054, 25.422379, -80.652664, 25.98292 https://cmr.earthdata.nasa.gov/search/concepts/C2231550143-CEOS_EXTRA.umm_json The map shows the approxiamte western limit of the Biscayne aquifer in Miami-Dade County. Southeastern Florida is underlain by geologic units of varying permeability from land surface to depths between 150 and 400 ft. These units form an unconfined aquifer system that is the source of most of the potable water used in the area. This body of geologic units is called the surficial aquifer system. In parts of Dade, Broward, and Palm Beach Counties, a highly permeable part of that aquifer system has been named the Biscayne aquifer (Parker, 1951; Parker and others, 1955). Adjacent to or underlying the Biscayne aquifer are less-permeable but potentially important water-bearing units that also are part of the surficial aquifer system. Most previous hydrogeologic investigations in southeastern Florida concentrated on the populated coastal area. Drilling and monitoring activities were commonly restricted to zones used for water supply or to overlying zones. Hence, information on the characteristics of the western or deeper parts of the Biscayne aquifer and of sediments below the Biscayne aquifer in the surficial aquifer system was insufficient for present needs. Continuing increases in the demand for water from the surficial aquifer system in the highly populated coastal area of southeastern Florida and attendant concerns for the protection and management of the water supply have resulted in a study by the U.S. Geological Survey (USGS), in cooperation with the South Florida Water Management District, to define the extent of the surficial aquifer system and its regional hydrogeologic characteristics. The overall objectives of the regional study are to determine the geologic framework of the surficial aquifer system, the areal and vertical water-quality distribution, factors that affect water quality, the hydraulic characteristics of the components of the surficial aquifer system, and to describe ground-water flow in the aquifer system. proprietary
USGS_SOFIA_dade_config_base_biscayne_arc Configuration of the Base of the Biscayne Aquifer in Dade County, USGS WRIR 90-4108, figure 16 CEOS_EXTRA STAC Catalog 1939-01-01 1985-12-31 -80.858925, 25.187017, -80.11909, 25.986544 https://cmr.earthdata.nasa.gov/search/concepts/C2231549896-CEOS_EXTRA.umm_json The map shows the altitude below sea level of the base of the Biscayne aquifer in Miami-Dade County. The contour interval is 10 feet. Southeastern Florida is underlain by geologic units of varying permeability from land surface to depths between 150 and 400 ft. These units form an unconfined aquifer system that is the source of most of the potable water used in the area. This body of geologic units is called the surficial aquifer system. In parts of Dade, Broward, and Palm Beach Counties, a highly permeable part of that aquifer system has been named the Biscayne aquifer (Parker, 1951; Parker and others, 1955). Adjacent to or underlying the Biscayne aquifer are less-permeable but potentially important water-bearing units that also are part of the surficial aquifer system. Most previous hydrogeologic investigations in southeastern Florida concentrated on the populated coastal area. Drilling and monitoring activities were commonly restricted to zones used for water supply or to overlying zones. Hence, information on the characteristics of the western or deeper parts of the Biscayne aquifer and of sediments below the Biscayne aquifer in the surficial aquifer system was insufficient for present needs. Continuing increases in the demand for water from the surficial aquifer system in the highly populated coastal area of southeastern Florida and attendant concerns for the protection and management of the water supply have resulted in a study by the U.S. Geological Survey (USGS), in cooperation with the South Florida Water Management District, to define the extent of the surficial aquifer system and its regional hydrogeologic characteristics. The overall objectives of the regional study are to determine the geologic framework of the surficial aquifer system, the areal and vertical water-quality distribution, factors that affect water quality, the hydraulic characteristics of the components of the surficial aquifer system, and to describe ground-water flow in the aquifer system. proprietary
USGS_SOFIA_dade_config_base_glime_arc Configuration of the Base of the Gray Limestone Aquifer in Dade County, Fl, USGS WRIR 90-4108, figure 15 CEOS_EXTRA STAC Catalog 1939-01-01 1985-12-31 -80.85567, 25.2942, -80.331, 25.994343 https://cmr.earthdata.nasa.gov/search/concepts/C2231554187-CEOS_EXTRA.umm_json Contours of the altitude below sea level of the base of the highly permeable gray limestone aquifer in the Tamiami Formation are shown in this map. The aquifer, as mapped, includes all intervals of the gray limestone that are at least 10 ft. thick and have an estimated hydraulic conductivity of at least 100ft/d. The contour interval is 10 feet. Southeastern Florida is underlain by geologic units of varying permeability from land surface to depths between 150 and 400 ft. These units form an unconfined aquifer system that is the source of most of the potable water used in the area. This body of geologic units is called the surficial aquifer system. In parts of Dade, Broward, and Palm Beach Counties, a highly permeable part of that aquifer system has been named the Biscayne aquifer (Parker, 1951; Parker and others, 1955). Adjacent to or underlying the Biscayne aquifer are less-permeable but potentially important water-bearing units that also are part of the surficial aquifer system. Most previous hydrogeologic investigations in southeastern Florida concentrated on the populated coastal area. Drilling and monitoring activities were commonly restricted to zones used for water supply or to overlying zones. Hence, information on the characteristics of the western or deeper parts of the Biscayne aquifer and of sediments below the Biscayne aquifer in the surficial aquifer system was insufficient for present needs. Continuing increases in the demand for water from the surficial aquifer system in the highly populated coastal area of southeastern Florida and attendant concerns for the protection and management of the water supply have resulted in a study by the U.S. Geological Survey (USGS), in cooperation with the South Florida Water Management District, to define the extent of the surficial aquifer system and its regional hydrogeologic characteristics. The overall objectives of the regional study are to determine the geologic framework of the surficial aquifer system, the areal and vertical water-quality distribution, factors that affect water quality, the hydraulic characteristics of the components of the surficial aquifer system, and to describe ground-water flow in the aquifer system. proprietary
@@ -16135,8 +16136,8 @@ USGS_SOFIA_dawmet Ecosystem History: Terrestrial and Fresh-Water Ecosystems of s
USGS_SOFIA_discharge_tamiami_canal Discharge Data (Tamiami Canal) CEOS_EXTRA STAC Catalog 1986-01-01 2001-12-31 -81.5, 25.75, -80.5, 26 https://cmr.earthdata.nasa.gov/search/concepts/C2231553115-CEOS_EXTRA.umm_json The data are from the following four stations: Station 02288800 - Tamiami Canal Outlets, Monroe to Carnestown; Station 02288900 - Tamiami Canal Outlets, 40-Mile Bend to Monroe, near Miami, FL; Station 02289040 - Tamiami Canal Outlets, Levee 67A to 40-Mile Bend, near Miami, FL; Station 02289060 - Tamiami Canal Outlets, Levee 30 to Levee 67A, near Miami, FL. The data were compiled from records from 1986 to 1999 in the USGS Ft. Lauderdale, FL office of the Water Resources Discipline in 2000. Each station has numerous individual flow measurements at gages that were used in the calculation of the mean flow for each station. The data were collected by USGS personnel and the gages are maintained and operated by USGS Ft. Lauderdale office personnel. Canals are a major water-delivery component of the south Florida ecosystem. They interact with surrounding flow systems and waterbodies, either directly through structure discharges and levee overflows or indirectly through levee seepage and leakage, and thereby quantitatively affect wetland hydroperiods as well as estuarine salinities. Knowledge of this flow interaction, as well as timing, extent, and duration of inundation that it contributes to, is needed to identify and eliminate any potential adverse effects of altered flow conditions and transported constituents on vegetation and biota. Comprehensive analytical tools and methods are needed to assess the effects of nutrient and contaminant loads from agricultural and urban run-off entering canals and thereby conveyed into connected wetlands and other adjoining coastal ecosystems. These data from the individual gages were transferred to electronic form to provide a better understanding of the distribution of flow from north to south under the Tamiami Trail to aid in decisions about future changes to flow along the Trail. proprietary
USGS_SOFIA_dk_merc_cycl_bio Mercury Cycling and Bioaccumulation CEOS_EXTRA STAC Catalog 2000-10-01 2006-12-31 -81.33137, 24.67165, -80.22201, 25.890877 https://cmr.earthdata.nasa.gov/search/concepts/C2231550667-CEOS_EXTRA.umm_json This proposal identifies work elements that are logical extensions, and which build off, our previous work. Our overall scientific objective is to provide a complete understanding of the external factors (such as atmospheric mercury and sulfate runoff loads) and internal factors (such as hydroperiod maintenance and water chemistry) that result in the formation and bioaccumulation of MeHg in south Florida ecosystems, and to conduct this research is such a way that it will be directly useable by land and water resource managers. More specifically, we will seek to achieve the following subobjectives (1) Extend our mesocosms studies to provide a more omprehensive examination of the newly discovered 'new versus old' mercury effect by conducting studies under differing hydrologic conditions and sub-ecosystem settings so that our experimental results will be more generally applicable to the greater south Florida ecosystem including the STAs that have been recently constructed and are yielding very high levels of methylmercury but the cause is currently unknown; (2) Seek to further identify the mechanisms that result in extremely high levels of MeHg after natural drying and rewetting cycles in the Everglades and which have major implications for the Restoration Plan; (3) Further our studies on the production of methylmercury in south Florida estuaries and tidal marshes by conducting mass-balance studies of tidal marshes; (4) Begin to partner with wildlife toxicologists funded by the State of Florida to unravel the complexities surrounding methylmercury exposure and effects to higher order wildlife in south Florida; and , (5) Continue to participate with mercury ecosystem modelers who are funded by the State of Florida and the USEPA to evaluate the overall ecological effects of reducing mercury emissions and the risks associated with methylmercury exposure. Although ecological impacts from phosphorous contamination have become synonymous with water quality in south Florida, especially for Everglades restoration, there are several other contaminants presently entering the Everglades that may be of equal or greater impact, including: pesticides, herbicides, polycyclic aromatic hydrocarbons, and trace metals. This project focuses on mercury, a sparingly soluble trace metal that is principally derived from atmospheric sources and affects the entire south Florida ecosystem. Mercury interacts with another south Florida contaminant, sulfur, that is derived from agricultural runoff, and results in a problem with potentially serious toxicological impacts for all the aquatic food webs (marine and freshwater) in the south Florida ecosystem. The scientific focus of this project is to examine the complex interactions of these contaminants (synergistic and antagonistic), ecosystem responses to variations in contaminant loading (time and space dimensions), and how imminent ecosystem restoration steps may affect existing contaminant pools. The Everglades restoration program is prescribing ecosystem-wide changes to some of the physical, hydrological and chemical components of this ecosystem. However, it remains uncertain what overall effects will occur as these components react to the perturbations (especially the biological and chemical components) and toward what type of 'new ecosystem' the Everglades will evolve. The approaches used by this study have been purposefully chosen to yield results that should be directly useable by land management and restoration decision makers. Presently, we are addressing several major questions surrounding the mercury research field, and the Everglades Restoration program: (l) What, if any, ecological benefit to the Everglades would be realized if mercury emissions reductions would be enacted, and over what time scales (years or tens of years) would improvements be realized? (2) What is the role of old mercury (previously deposited and residing in soils and sediment) versus new mercury (recent deposition) in fueling the mercury problem? (3) In the present condition, is controlling sulfur or mercury inputs more important for reducing the mercury problem in the Everglades? (4) Does sulfur loading have any additional ecological impacts that have not been realized previously (e.g., toxicity to plant and animals) that may be contributing to an overall decreased ecological health? (5) Commercial fisheries in the Florida Bay are contaminated with mercury, is this mercury derived from Everglades runoff or atmospheric runoff? (6) What is the precise role of carbon (the third member of the 'methylmercury axis of evil', along with sulfur and mercury), and do we have to be concerned with high levels of natural carbon mobilization from agricultural runoff as well? (7) Hundreds of millions of dollars are being, or have been spent, on STA construction to reduce phosphorus loading to the Everglades, however, recently constructed STAs have yielded the highest known concentration of toxic methylmercury; can STA operations be altered to reduce methylmercury production and maintain a high level of phosphorus retention over extended periods of time? The centerpiece of our research continues to be the use of environmental chambers (enclosures or mesocosms), inside which we conduct dosing experiments using sulfate, dissolved organic carbon and mercury isotopic tracers. The goal of the mesocosm experiments is to quantify the in situ ecological response to our chemical dosing, and to also determine the ecosystem recovery time to the doses. proprietary
USGS_SOFIA_eco_assess_risk_toxics Ecological Risk Assessment of Toxic Substances in the Greater Everglades Ecosystem: Wildlife Effects and Exposure Assessment CEOS_EXTRA STAC Catalog 2000-10-01 2004-09-30 -81.125, 25.125, -80.125, 26.75 https://cmr.earthdata.nasa.gov/search/concepts/C2231551985-CEOS_EXTRA.umm_json This project will be carried out in several locations throughout those areas critical to the South Florida Restoration Initiative. These areas include: 1) Water Conservation Areas 1, 2, and 3 of the Central Everglades, 2) Everglades National Park, 3) Loxahatchee National Wildlife Refuge, 4) Big Cypress National Preserve, 5) multiple Miami Metropolitan area canals and drainages, and 6) restoration related STAs (STAs 1-6) adjacent to the Everglades. Specific site selections will be based upon consideration of USACE restoration plans and upon discussions with other place-based and CESI approved projects. The overall objectives are characterize the exposure of wildlife to contaminants within the aquatic ecosystems of South Florida, through a multi-stage process: a) screening of biota to identify hazards/contaminants posing risk, and b) evaluation of the potential effects of those contaminants on appropriate animal/wildlife receptors. This project will focus upon each of these stages/needs, with an emphasis on understanding the effects of contaminants on alligators, fishes, birds, amphibians and macroinvertebrates. Historically, little consideration has been given to environmental chemical stressors/contaminants within the ecosystem restoration efforts for the Greater Everglades Ecosystem. The restoration is primarily guided by determining and restoring the historical relationships between ecosystem function and hydrology. The restoration plan was formulated to restore the natural hydrology and therefore, the resultant landscape patterns, bio-diversity and wildlife abundance. However, additional efforts need to consider the role that chemical contaminants such as pesticides and other inorganic/organic contaminants play in the structure and function of the resultant South Florida ecosystems. Indeed, the current level of agriculture and expanding urbanization and development necessitate that more emphasis be placed on chemical contaminants within this sensitive ecosystem and the current restoration efforts. The primary goal of the proposed project, therefore, is to develop an improved understanding of the exposure/fate (i.e. degradation, metabolism, dissipation, accumulation and transport) and potential ecological effects produced as a result of chemical stressors and their interactions in South Florida freshwater and wetland ecosystems. The overall objectives are to evaluate the risk posed by contaminants to biota within the aquatic ecosystems of South Florida, through a multi-stage process: a) screening of biota to identify hazards/contaminants posing risk and b) evaluation of the potential effects of those contaminants on appropriate animal/wildlife receptors. This project will focus upon each of these stages/needs, with an emphasis on understanding the effects of contaminants on alligators, fishes, birds, amphibians and macroinvertebrates. The specific objectives of this project are to: 1. Assess current exposure and potential adverse effects for appropriate receptors/species within the South Florida ecosystems with some emphasis on DOI trust species. These efforts will determine whether natural populations are significantly exposed to a variety of chemical stressors/contaminants, such as mercury, chlorinated hydrocarbon pesticides, historic and/or current use agricultural chemicals, and/or mixtures, as well as document lethal and non-lethal adverse effects in multiple health, physiologic and/or endocrine endpoints. 2. Assess exposure and potential adverse effects for appropriate species within South Florida as a function of restoration implementation. proprietary
-USGS_SOFIA_eco_hist_db1995-2007_version 7 1995 - 2007 Ecosystem History of South Florida's Estuaries Database version 7 ALL STAC Catalog 1994-09-27 2007-04-03 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231554288-CEOS_EXTRA.umm_json The 1995 - 2007 Ecosystem History of South Florida's Estuaries Database contains listings of all sites (modern and core), modern monitoring site survey information (water chemistry, floral and faunal data, etc.), and published core data. Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - primarily faunal assemblages. Data are available for modern sites and cores in the general areas of Florida Bay, Biscayne Bay, and the southwest (Florida) coastal mangrove estuaries. Specific sites in the Florida Bay area include Taylor Creek, Bob Allen Key, Russell Bank, Pass Key, Whipray Basin, Rankin Bight, park Key, and Mud Creek core). Specific Biscayne Bay sites include Manatee Bay, Featherbed Bank, Card bank, No Name Bank, Middle Key, Black Point North, and Chicken Key. Sites on the southwest coast include Alligator Bay, Big Lostmans Bay, Broad River Bay, Roberts River mouth, Tarpon Bay, Lostmans River First and Second Bays, Harney River, Shark River near entrance to Ponce de Leon Bay, and Shark River channels. Modern field data contains (1) general information about the site, description, latitude and longitude, date of data collection, (2) water chemistry information, and (3) descriptive text of fauna and flora observed at the site. Core data contain either percent abundance data or actual counts of the distribution of mollusks, ostracodes, forams, and pollen within the cores collected in the estuaries. For some cores dinocyst or diatom data may be available. proprietary
USGS_SOFIA_eco_hist_db1995-2007_version 7 1995 - 2007 Ecosystem History of South Florida's Estuaries Database version 7 CEOS_EXTRA STAC Catalog 1994-09-27 2007-04-03 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231554288-CEOS_EXTRA.umm_json The 1995 - 2007 Ecosystem History of South Florida's Estuaries Database contains listings of all sites (modern and core), modern monitoring site survey information (water chemistry, floral and faunal data, etc.), and published core data. Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - primarily faunal assemblages. Data are available for modern sites and cores in the general areas of Florida Bay, Biscayne Bay, and the southwest (Florida) coastal mangrove estuaries. Specific sites in the Florida Bay area include Taylor Creek, Bob Allen Key, Russell Bank, Pass Key, Whipray Basin, Rankin Bight, park Key, and Mud Creek core). Specific Biscayne Bay sites include Manatee Bay, Featherbed Bank, Card bank, No Name Bank, Middle Key, Black Point North, and Chicken Key. Sites on the southwest coast include Alligator Bay, Big Lostmans Bay, Broad River Bay, Roberts River mouth, Tarpon Bay, Lostmans River First and Second Bays, Harney River, Shark River near entrance to Ponce de Leon Bay, and Shark River channels. Modern field data contains (1) general information about the site, description, latitude and longitude, date of data collection, (2) water chemistry information, and (3) descriptive text of fauna and flora observed at the site. Core data contain either percent abundance data or actual counts of the distribution of mollusks, ostracodes, forams, and pollen within the cores collected in the estuaries. For some cores dinocyst or diatom data may be available. proprietary
+USGS_SOFIA_eco_hist_db1995-2007_version 7 1995 - 2007 Ecosystem History of South Florida's Estuaries Database version 7 ALL STAC Catalog 1994-09-27 2007-04-03 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231554288-CEOS_EXTRA.umm_json The 1995 - 2007 Ecosystem History of South Florida's Estuaries Database contains listings of all sites (modern and core), modern monitoring site survey information (water chemistry, floral and faunal data, etc.), and published core data. Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - primarily faunal assemblages. Data are available for modern sites and cores in the general areas of Florida Bay, Biscayne Bay, and the southwest (Florida) coastal mangrove estuaries. Specific sites in the Florida Bay area include Taylor Creek, Bob Allen Key, Russell Bank, Pass Key, Whipray Basin, Rankin Bight, park Key, and Mud Creek core). Specific Biscayne Bay sites include Manatee Bay, Featherbed Bank, Card bank, No Name Bank, Middle Key, Black Point North, and Chicken Key. Sites on the southwest coast include Alligator Bay, Big Lostmans Bay, Broad River Bay, Roberts River mouth, Tarpon Bay, Lostmans River First and Second Bays, Harney River, Shark River near entrance to Ponce de Leon Bay, and Shark River channels. Modern field data contains (1) general information about the site, description, latitude and longitude, date of data collection, (2) water chemistry information, and (3) descriptive text of fauna and flora observed at the site. Core data contain either percent abundance data or actual counts of the distribution of mollusks, ostracodes, forams, and pollen within the cores collected in the estuaries. For some cores dinocyst or diatom data may be available. proprietary
USGS_SOFIA_eco_hist_db_version 3 Ecosystem History of South Florida Estuaries Data CEOS_EXTRA STAC Catalog 1994-02-24 2008-03-20 -81.83, 24.75, -80, 26.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231552167-CEOS_EXTRA.umm_json The Ecosystem History Access Database contains listings of all sites (modern and core), modern monitoring site survey information, and published core data. Two general types of data are contained within this database: 1) Modern Field Data and 2) Core data - primarily faunal assemblages. Scientists over the past few decades have noticed that the South Florida ecosystem has become increasingly stressed. The purposes of the ecosystem history projects (started in 1995) are to determine what south Florida's estuaries have looked like over time, how they have changed, and what is the rate and frequency of change. To accomplish this, shallow sediment cores are collected within the bays, and the faunal and floral remains, sediment geochemistry, and shell biochemistry are analyzed. Modern field data are collected from the same region as the cores and serve as proxies to allow accurate interpretation of past depositional environments. The USGS South Florida Ecosystem History Project is designed to integrate studies from a number of researchers compiling data from terrestrial, marine, and freshwater ecosystems within south Florida. The project is divided into 3 regions: Biscayne Bay and the Southeast coast, Florida Bay and the Southwest coast, and Terrestrial and Freshwater Ecosystems of Southern Florida. The purpose of the projects is to provide information about the ecosystem's recent history based on analyses of paleontology, geochemistry, hydrology, and sedimentology of cores taken from the south Florida region. Data generated from the South Florida Ecosystem History project will be integrated to provide biotic reconstructions for the area at selected time slices and will be useful in testing ecological models designed to predict floral and faunal response to changes in environmental parameters. Biscayne Bay is of interest to scientists because of the rapid urbanization that has occurred in the Miami area and includes Biscayne National Park. Dredging, propeller scars, and changes in freshwater input have altered parts of Biscayne Bay. Currently, the main freshwater input to Biscayne Bay is through the canal system, but many scientists believe subsurface springs used to introduce fresh groundwater into the Bay ecosystem. Study of the modern environment and core sediments from Biscayne Bay will provide important information on past salinity and seagrass coverage which will be useful for predicting future change within the Bay. Plant and animal communities in the South Florida ecosystem have undergone striking changes over the past few decades. In particular, Florida Bay has been plagued by seagrass die-offs, algal blooms, and declining sponge and shellfish populations. These alterations in the ecosystem have traditionally been attributed to human activities and development in the region. Scientists at the U.S. Geological Survey (USGS) are studying the paleoecological changes taking place in Florida Bay in hopes of understanding the physical environment to aid in the restoration process. As in Biscayne Bay, scientists must first determine which changes are part of the natural variation in Florida Bay and which resulted from human activities. To answer this question, scientists are studying both modern samples and piston cores that reveal changes over the past 150-600 years. These two types of data complement each other by providing information about the current state of the Bay, changes that occurred over time, and patterns of change. Terrestrial ecosystems of South Florida have undergone numerous human disturbances, ranging from alteration of the hydroperiod, fire history, and drainage patterns through implementation of the canal system to expansion of the agricultural activity to the introduction of exotic species such as Melalueca, Australian pine, and the Pepper Tree. Over historical time, dramatic changes in the ecosystem have been documented and these changes attributed to various human activities. However, cause-and-effect relationships between specific biotic and environmental changes have not been established scientifically. One part of the South Florida Ecosystem History group of project is designed to document changes in the terrestrial ecosystem quantitatively, to date any changes and determine whether they resulted from documented human activities, and to establish the baseline level of variability in the South Florida ecosystem to estimate whether the observed changes are greater than what would occur naturally. Specific goals of this part of the project are to 1) document the patterns of floral and faunal changes at sites throughout southern Florida over the last 150 years, 2) determine whether the changes occurred throughout the region or whether they were localized, 3) examine the floral and faunal history of the region over the last few millennia, 4) determine the baseline level of variability in the communities prior to significant human activity in the region, and 5) determine whether the fire frequency, extent, and influence can be quantified, and if so, document the fire history for sites in the region. proprietary
USGS_SOFIA_eco_hist_swcoast_srs_04 Ecosystem History of the Southwest Coast-Shark River Slough Outflow Area CEOS_EXTRA STAC Catalog 2003-10-01 2008-09-30 -81.75, 25, -80.83, 26 https://cmr.earthdata.nasa.gov/search/concepts/C2231554376-CEOS_EXTRA.umm_json The objectives of this project are to document impacts of changes in salinity, water quality, coastal plant and animal communities and other critical ecosystem parameters on a subdecadal-centennial scale in the southwest coastal region (from Whitewater Bay, north to the 10,000 Islands), and to correlate these changes with natural events and resource management practices. Emphasis will be placed on 1) determining the amount, timing and sources of freshwater influx (groundwater vs. runoff) into the coastal ecosystem prior to and since significant anthropogenic alteration of flow; and 2) determining whether the rate of mangrove and brackish marsh migration inland has increased since 20th century water diversion and what role sealevel rise might play in the migration. First, the environmental preferences and distributions of modern fauna and flora are established through analyses of modern samples in south Florida estuaries and coastal systems. Much of these data have already been obtained through project work conducted in Florida Bay and the terrestrial Everglades starting in 1995. These modern data are used as proxies for interpreting the historical data from Pb-210 and C-14 dated sediment cores based on assemblage analysis. On the basis of USGS data obtained from cores in Florida Bay and Biscayne Bay, the temporal span of the cores should be at a minimum the last 150 years; this is in agreement with University of Miami data showing sedimentation rates in Whitewater Bay to be approximately 1cm/year. For the estuarine/coastal ecosystems, a multidisciplinary, multiproxy approach will be utilized on cores from a transect from Whitewater Bay north to 10,000 Islands. Biochemical analyses of shells and chemical analyses of sediments will be used to refine data on salinity and nutrient supply, and isotopic analyses of shells will determine sources of water influx into the system. Nutrient analyses will be conducted to determine historical patterns of nutrient influx. To examine the inland migration of the mangrove/coastal marsh ecotone, transects from the mouth of the Shark and Harney Rivers inland into Shark River slough will be taken. These cores will be evaluated for floral remains, nutrients, charcoal, and if present, faunal remains. This project will provide 1) baseline data for restoration managers and hydrologic modelers on the amount and sources of freshwater influx into the southwest coastal zone and the quality of the water, 2) the relative position of the coastal marsh-mangrove ecotone at different periods in the past, and 3) data to test probabilities of system response to restoration changes. One of the primary goals of the Central Everglades Restoration Plan (CERP) is to restore the natural flow of water through the terrestrial Everglades and into the coastal zones. Historically, Shark River Slough, which flows through the central portion of the Everglades southwestward, was the primary flow path through the Everglades Ecosystem. However, this flow has been dramatically reduced over the last century as construction of canals, water conservation areas and the Tamiami Trail either retained or diverted flow from Shark River Slough. The reduction in flow and changes in water quality through Shark River have had a profound effect on the freshwater marshes and the associated coastal ecosystems. Additionally, the flow reduction may have shifted the balance of fresh to salt-water inflow along coastal zones, resulting in an acceleration of the rate of inland migration of mangroves into the freshwater marshes. For successful restoration to occur, it is critical to understand how CERP and the natural patterns of freshwater flow, precipitation, and sea level rise will affect the future maintenance of the mangrove-freshwater marsh ecotone and the coastal environment. proprietary
USGS_SOFIA_eden_dem_cm_nov07_nc Everglades Depth Estimation Network (EDEN) November 2007 Digital Elevation Model for use with EDENapps CEOS_EXTRA STAC Catalog 1995-01-01 2007-12-31 -81.36353, 25.229605, -80.22176, 26.683613 https://cmr.earthdata.nasa.gov/search/concepts/C2231551925-CEOS_EXTRA.umm_json This is the 1st release of the third version of an Everglades Depth Estimation Network (EDEN) digital elevation model (DEM) generated from certified airborne height finder (AHF) and airboat collected ground surface elevations for the Greater Everglades Region. This version includes all data collected and certified by the USGS prior to the conclusion of the AHF collection process. It differs from the previous elevation model (EDEN_EM_JAN07) in that the modeled area of WCA3N (all the WCA3A area north of I-75) is increased while the modeled area of the Big Cypress National Preserve (BNCP) has been both refined and reduced to the region where standard error of cross-validation points falls below 0.16 meters. EDEN offers a consistent and documented dataset that can be used to guide large-scale field operations, to integrate hydrologic and ecological responses, and to support biological and ecological assessments that measure ecosystem responses to Comprehensive Everglades Restoration Plan. To produce historic and near-real time maps of water depths, the EDEN requires a system-wide DEM of the ground surface. This file is a modification of the eden dem released in October of 2007 (i.e., eden_em_oct07) in which the elevation values have been converted from meters (m) to centimeters(cm) for use by EDEN applications software. This file is intended specifically for use in the EDEN applications software. Aside from this difference in horizontal units, the following documentation applies. These data were specifically created for the development of water depth information using interpolated water surfaces from the EDEN stage data network. proprietary
@@ -16272,10 +16273,10 @@ USGS_arapbase_Version 1.0, July 22, 1998 COVERAGE ARAPBASE -- Structure contours
USGS_benchmark_1.0 Locations of NASQAN benchmark stations CEOS_EXTRA STAC Catalog 1990-01-01 1990-12-31 -127.042595, 27.19216, -69.387886, 48.367382 https://cmr.earthdata.nasa.gov/search/concepts/C2231550268-CEOS_EXTRA.umm_json This coverage was created for the 1990-91 National Water Summary. The coverage shows locations of NASQAN benchmark stations. Procedures_Used: The point coverage was created from data taken from U.S. Geological Survey computer files. proprietary
USGS_cir89_Version 1.0 Color-infrared composite of Landsat data for the Sarcobatus Flat area of the Death Valley regional flow system, Nevada and California, 1989 CEOS_EXTRA STAC Catalog 1989-06-21 1989-06-21 -117.216324, 36.997658, -116.66944, 37.40421 https://cmr.earthdata.nasa.gov/search/concepts/C2231554772-CEOS_EXTRA.umm_json "The data set was created to determine phreatophyte boundaries used in the report, ""Ground-water discharge determined from estimates of evapotranspiration, Death Valley regional flow system, Nevada and California"". The raster-based, color-infrared composite was derived from Landsat Thematic Mapper imagery data acquired during June 1989 for the Sarcobatus Flat area of the Death Valley regional flow system. The image is a single-channel, parallelepiped classification that when displayed using a 256-color color table shows a simulation of a color-infrared composite. The data set was used in determining phreatophyte boundaries for a ground-water evapotranspiration study. The raster-based, color-infrared composite (CIR) was derived from Landsat Thematic Mapper (TM) imagery data acquired during June 1989 for the Death Valley regional flow system, Nevada and California. The image is a single-channel, parallelepiped classification that when displayed using a 256-color color table shows a simulation of a color-infrared composite (Beverley and Penton, 1989). TM channels 2, 3, and 4 are used in the classification process. The wavelengths of these channels correspond to those used for a CIR composite. The data range of each channel is divided into eight divisions. The 512 possible combinations are then reduced to 256. A color table of red, green, and blue values is created for display of the image. Sixteen possible color values exist for each color. These values are scaled between 0 and 255. The image is reduced from more than 16 million colors to 256 colors. Reviews The CIR image for 1989 was checked for consistency and accuracy during the data processing. Two external reviews were done. The reviewers were asked to check metadata and other documentation files for completeness and accuracy. Reviewers also were asked to check the topological consistency, tolerances, projections, and geographic extent. The Landsat Entity-identification number is LT5040034008917210." proprietary
USGS_cira92_Version 1.0 Color-infrared composite of Landsat data for the Death Valley regional flow system, Nevada and California, 1992 CEOS_EXTRA STAC Catalog 1992-06-01 1992-06-13 -117.550385, 35.378323, -115.251015, 37.653557 https://cmr.earthdata.nasa.gov/search/concepts/C2231551442-CEOS_EXTRA.umm_json "This data set was created to determine phreatophyte boundaries for use in the report, ""Ground-water discharge determined from estimates of evapotranspiration, Death Valley regional flow system, Nevada and California"". The raster-based, color-infrared composite was derived from Landsat Thematic Mapper imagery data acquired during June 1992 for the Death Valley regional flow system. The image is a single-channel, parallelepiped classification that when displayed using a 256-color color table shows a simulation of a color-infrared composite. The data set was used in determining phreatophyte boundaries for a ground-water evapotranspiration study. The raster-based, color-infrared composite (CIR) was derived from Landsat Thematic Mapper (TM) imagery data acquired during June 1992 for the Death Valley ground-water flow system, Nevada and California. The image is a single-channel, parallelepiped classification that when displayed using a 256-color color table shows a simulation of a color-infrared composite (Beverley and Penton, 1989). TM channels 2, 3, and 4 are used in the classification process. The wavelengths of these channels correspond to those used for a CIR composite. The data range of each channel is divided into eight divisions. The 512 possible combinations are then reduced to 256. A color table of red, green, and blue values is created for display of the image. Sixteen possible color values exist for each color. These values are scaled between 0 and 255. The image is reduced from more than 16 million colors to 256 colors." proprietary
-USGS_cont1992 1992 Water-Table Contours of the Mojave River Ground-Water Basin, San Bernardino County, California ALL STAC Catalog 1970-01-01 -117.652695, 34.364513, -116.55357, 35.081955 https://cmr.earthdata.nasa.gov/search/concepts/C2231553864-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Mojave River Basin. The U.S. Geological Survey, in cooperation with the Mojave Water Agency, constructed a water-table map of the Mojave River ground-water basin for ground-water levels measured in November 1992. Water-level data were collected from approximately 300 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:125,000. The contour interval ranges from 3,200 to 1,600 feet above sea level. [Summary provided by the USGS.] proprietary
USGS_cont1992 1992 Water-Table Contours of the Mojave River Ground-Water Basin, San Bernardino County, California CEOS_EXTRA STAC Catalog 1970-01-01 -117.652695, 34.364513, -116.55357, 35.081955 https://cmr.earthdata.nasa.gov/search/concepts/C2231553864-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Mojave River Basin. The U.S. Geological Survey, in cooperation with the Mojave Water Agency, constructed a water-table map of the Mojave River ground-water basin for ground-water levels measured in November 1992. Water-level data were collected from approximately 300 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:125,000. The contour interval ranges from 3,200 to 1,600 feet above sea level. [Summary provided by the USGS.] proprietary
-USGS_cont1994 1994 Water-Table Contours of the Morongo Ground-Water Basin, San Bernardino County, California CEOS_EXTRA STAC Catalog 1970-01-01 -117.07194, 34.095333, -115.98976, 34.64026 https://cmr.earthdata.nasa.gov/search/concepts/C2231554677-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Morongo Basin. The U.S. Geological Survey constructed a water-table map of the Morongo ground-water basin for ground-water levels measured during the period January-October 1994. Water-level data were collected from 248 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:125,000. The contour interval ranges from 3,400 to 1,500 feet above sea level. [Summary provided by the USGS.] proprietary
+USGS_cont1992 1992 Water-Table Contours of the Mojave River Ground-Water Basin, San Bernardino County, California ALL STAC Catalog 1970-01-01 -117.652695, 34.364513, -116.55357, 35.081955 https://cmr.earthdata.nasa.gov/search/concepts/C2231553864-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Mojave River Basin. The U.S. Geological Survey, in cooperation with the Mojave Water Agency, constructed a water-table map of the Mojave River ground-water basin for ground-water levels measured in November 1992. Water-level data were collected from approximately 300 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:125,000. The contour interval ranges from 3,200 to 1,600 feet above sea level. [Summary provided by the USGS.] proprietary
USGS_cont1994 1994 Water-Table Contours of the Morongo Ground-Water Basin, San Bernardino County, California ALL STAC Catalog 1970-01-01 -117.07194, 34.095333, -115.98976, 34.64026 https://cmr.earthdata.nasa.gov/search/concepts/C2231554677-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Morongo Basin. The U.S. Geological Survey constructed a water-table map of the Morongo ground-water basin for ground-water levels measured during the period January-October 1994. Water-level data were collected from 248 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:125,000. The contour interval ranges from 3,400 to 1,500 feet above sea level. [Summary provided by the USGS.] proprietary
+USGS_cont1994 1994 Water-Table Contours of the Morongo Ground-Water Basin, San Bernardino County, California CEOS_EXTRA STAC Catalog 1970-01-01 -117.07194, 34.095333, -115.98976, 34.64026 https://cmr.earthdata.nasa.gov/search/concepts/C2231554677-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Morongo Basin. The U.S. Geological Survey constructed a water-table map of the Morongo ground-water basin for ground-water levels measured during the period January-October 1994. Water-level data were collected from 248 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:125,000. The contour interval ranges from 3,400 to 1,500 feet above sea level. [Summary provided by the USGS.] proprietary
USGS_cont1996 1996 Water-Table Contours of the Mojave River, the Morongo, and the Fort Irwin Ground-Water Basins, San Bernardino County, California ALL STAC Catalog 1970-01-01 -117.63461, 34.109745, -115.98707, 35.31552 https://cmr.earthdata.nasa.gov/search/concepts/C2231555091-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Mojave River, the Morongo and the Fort Irwin Ground-Water Basins. The U.S. Geological Survey constructed a water-table map of the Mojave River, the Morongo and the Fort Irwin Ground-Water Basins for ground-water levels measured during the period January-September 1996. Water-level data were collected from 632 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:175,512. The contour interval ranges from 3,400 to 1,550 feet above sea level. [Summary provided by the USGS.] proprietary
USGS_cont1996 1996 Water-Table Contours of the Mojave River, the Morongo, and the Fort Irwin Ground-Water Basins, San Bernardino County, California CEOS_EXTRA STAC Catalog 1970-01-01 -117.63461, 34.109745, -115.98707, 35.31552 https://cmr.earthdata.nasa.gov/search/concepts/C2231555091-CEOS_EXTRA.umm_json This data set consists of digital water-table contours for the Mojave River, the Morongo and the Fort Irwin Ground-Water Basins. The U.S. Geological Survey constructed a water-table map of the Mojave River, the Morongo and the Fort Irwin Ground-Water Basins for ground-water levels measured during the period January-September 1996. Water-level data were collected from 632 wells to construct the contours. The water-table contours were digitized from the paper map which was published at a scale of 1:175,512. The contour interval ranges from 3,400 to 1,550 feet above sea level. [Summary provided by the USGS.] proprietary
USGS_erf1_Version 1.2, August 01, 1999 ERF1 -- Enhanced River Reach File 1.2 CEOS_EXTRA STAC Catalog 1999-01-07 1999-01-07 -127.8169, 23.247017, -65.55541, 48.19323 https://cmr.earthdata.nasa.gov/search/concepts/C2231552175-CEOS_EXTRA.umm_json ERF1 was designed to be a digital data base of river reaches capable of supporting regional and national water-quality and river-flow modeling and transport investigations in the water-resources community. ERF1 has been recently used at the U.S. Geological Survey to support interpretations of stream water-quality monitoring network data (see Alexander and others, 1996; Smith and others, 1995). In these analyses, the reach network has been used to determine flow pathways between the sources of point and nonpoint pollutants (e.g., fertilizer use, municipal wastewater discharges) and downstream water-quality monitoring locations in support of predictive water-quality models of stream nutrient transport. The digital data set ERF1 includes enhancements to the U.S. Environmental Protection Agency's River Reach File 1 (RF1)to ensure the hydrologic integrity of the digital reach traces and to quantify the time of travel of river reaches and reservoirs [see U.S.EPA (1996) for a description of the original RF1]. Any use of trade, product, or firm names is for descriptive proprietary
@@ -16342,8 +16343,8 @@ USM_pCO2_0 University of Southern Mississippi (USM) - partial pressure of carbon
US_FOREST_FRAGMENTATION Forest Fragmentation in the United States CEOS_EXTRA STAC Catalog 1970-01-01 -128, 24, -65, 50 https://cmr.earthdata.nasa.gov/search/concepts/C2231549003-CEOS_EXTRA.umm_json "National Land Cover Data (NLCD) was reclassified into three categories: forest, other natural (e.g., grassland and wetland), and anthropogenic use (e.g., agricultural and urban). Three new grids were created, one for each edge type (forest, forest, forest natural, and forest anthropogenic). The values in these grids were calculated as the number of edges with the appropriate type in the window divided by the total number of forest edges, regardless of neighbor. These grids represented forest connectivity (forest forest edges), naturally caused forest fragmentation (forest natural edges), and human-caused forest fragmentation (forest anthropogenic edges). In the map, forest connectivity is displayed in green, natural fragmentation in blue, and human fragmentation in red. Pure green identifies areas where most or all forest edges are shared by another forest pixel. Pure red areas are where forest edges are largely shared with human land use. Pure blue areas show where most or all forest edges are shared with another natural land cover type. Different mixes of the three edge types can produce other colors. Two common examples in the map are yellow and cyan. Yellow identifies areas with roughly equal amounts of forest connectivity and anthropogenic fragmentation. Cyan is where forest connectivity and natural fragmentation are approximately equal. Black represents areas with no forest in the window, and white represents ignored areas, mostly water, as well as state boundaries. With few exceptions, forest fragmentation by other natural land cover types is confined to the western United States, while most human-caused forest fragmentation is in the East and Midwest. The yellow and red areas around Yellowstone in northwest Wyoming are a result of the wildfires in 1988. The burned areas are classified as ""transitional"" in the NLCD, which are treated as anthropogenic use. The Mississippi River valley was largely forested at one time but has been almost entirely converted to agricultural use, resulting in a display of black and red. Las Vegas, Nevada, is visible as a patch of red in the Mojave Desert due to an ""urban forest"" effect from trees planted by residents. Riparian corridors are highly visible in arid and developed areas, especially the West and Midwest. In arid areas, climate often confines trees to riparian zones that are displayed in shades of blue. In the intensely farmed Midwest, intact and restored riparian vegetation is depicted in yellow or red. Southern Atlantic coastal plain riparian zones are wider; forest is better connected and is shown in green." proprietary
US_MODIS_NDVI_1299_3 MODIS NDVI Data, Smoothed and Gap-filled, for the Conterminous US: 2000-2015 ORNL_CLOUD STAC Catalog 2000-01-01 2015-12-31 -129.89, 20.85, -62.56, 50.56 https://cmr.earthdata.nasa.gov/search/concepts/C2764637520-ORNL_CLOUD.umm_json This data set provides Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data, smoothed and gap-filled, for the conterminous US for the period 2000-01-01 through 2015-12-31. The data were generated using the NASA Stennis Time Series Product Tool (TSPT) to generate NDVI data streams from the Terra satellite (MODIS MOD13Q1 product) and Aqua satellite (MODIS MYD13Q1 product) instruments. TSPT produces NDVI data that are less affected by clouds and bad pixels. proprietary
US_MODIS_Veg_Parameters_1539_1 MODIS-derived Vegetation and Albedo Parameters for Agroecosystem-Climate Modeling ORNL_CLOUD STAC Catalog 2003-01-01 2010-12-31 -139.05, 15.15, -51.95, 49.15 https://cmr.earthdata.nasa.gov/search/concepts/C2517700524-ORNL_CLOUD.umm_json This dataset provides MODIS-derived leaf area index (LAI), stem area index (SAI), vegetation area fraction, dominant landcover category, and albedo parameters for the continental US (CONUS), parts of southern Canada, and Mexico at 30 km resolution. The data cover the period 2003-2010 and were developed to be used as surface input data for regional agroecosystem-climate models. MODIS Collection 5 products used to derive these parameters included the Terra yearly water mask, vegetation continuous field products, the combined Terra and Aqua yearly land-cover category (LCC) (MCD12Q1), 8-day composites for LAI (MCD15A2), and albedo parameter (MCD43B1) products. Please note that the MODIS Version 5 land data products used in this dataset have been superseded by Version 6 data products. proprietary
-UTC_1990countyboundaries 1990 County Boundaries of the United States ALL STAC Catalog 1972-01-01 1990-12-31 -177.1, 13.71, -61.48, 76.63 https://cmr.earthdata.nasa.gov/search/concepts/C2231550562-CEOS_EXTRA.umm_json This data set portrays the 1990 State and county boundaries of the United States, Puerto Rico, and the U.S. Virgin Islands. The data set was created by extracting county polygon features from the individual 1:2,000,000-scale State boundary Digital Line Graph (DLG) files produced by the U.S. Geological Survey. These files were then merged into a single file and the boundaries were modified to what they were in 1990. This is a revised version of the March 2000 data set. proprietary
UTC_1990countyboundaries 1990 County Boundaries of the United States CEOS_EXTRA STAC Catalog 1972-01-01 1990-12-31 -177.1, 13.71, -61.48, 76.63 https://cmr.earthdata.nasa.gov/search/concepts/C2231550562-CEOS_EXTRA.umm_json This data set portrays the 1990 State and county boundaries of the United States, Puerto Rico, and the U.S. Virgin Islands. The data set was created by extracting county polygon features from the individual 1:2,000,000-scale State boundary Digital Line Graph (DLG) files produced by the U.S. Geological Survey. These files were then merged into a single file and the boundaries were modified to what they were in 1990. This is a revised version of the March 2000 data set. proprietary
+UTC_1990countyboundaries 1990 County Boundaries of the United States ALL STAC Catalog 1972-01-01 1990-12-31 -177.1, 13.71, -61.48, 76.63 https://cmr.earthdata.nasa.gov/search/concepts/C2231550562-CEOS_EXTRA.umm_json This data set portrays the 1990 State and county boundaries of the United States, Puerto Rico, and the U.S. Virgin Islands. The data set was created by extracting county polygon features from the individual 1:2,000,000-scale State boundary Digital Line Graph (DLG) files produced by the U.S. Geological Survey. These files were then merged into a single file and the boundaries were modified to what they were in 1990. This is a revised version of the March 2000 data set. proprietary
UTC_TNgeologicmaps Geologic Maps of Tennessee CEOS_EXTRA STAC Catalog 1966-01-01 1966-12-31 -90.31191, 34.983253, -81.64822, 36.679295 https://cmr.earthdata.nasa.gov/search/concepts/C2231549514-CEOS_EXTRA.umm_json This data set is a digital representation of the printed 1:250,000 geologic maps from the Tennessee Department of Environment and Conservation, Division of Geology. The coverage was designed primarily to provide a more detailed geologic base than the 1:2,500,000 King and Beikman (1974). 1:24,000 scale coverage of the state is available for about 40 percent of the state. Formation names and geologic unit codes used in the coverage are from the Tennessee Division of Geology published maps and may not conform to USGS nomenclature. The Tennessee Division of Geology can be contacted at (615) 532-1500. proprietary
UTC_TRIfacilities Facilities in the Toxic Release Inventory CEOS_EXTRA STAC Catalog 1997-12-31 -127.61431, 23.24277, -65.505165, 51.523094 https://cmr.earthdata.nasa.gov/search/concepts/C2231553589-CEOS_EXTRA.umm_json This data set is a subset of the U.S. Environmental Protection Agency (USEPA) Envirofacts point data set which includes facilities included in the the Toxic Release Inventory. Information on total pounds of volatile organic compounds released in 1995 (from USEPA's Toxic Release Inventory CD-ROM) has been included. This data set is designed to locate or plot manufacturing facilities included in the Toxic Release Inventory and display or analysis of volatile organic compounds releases in pounds per year. The following are the volatile organic compounds (VOC's) selected to calculate the total releases at each facility. Not all of these chemicals actually appear in the TRI data set, but this list was used to select releases to sum for each facility. CAS-ID Chemical name > ---------- ---------------------------- > 1 630-20-6 1,1,1,2-Tetrachloroethane > 2 71-55-6 1,1,1-Trichloroethane > 3 79-34-5 1,1,2,2-Tetrachloroethane > 4 76-13-1 1,1,2-Trichloro-1,2,2-trifluoroethane > 5 79-00-5 1,1,2-Trichloroethane > 6 75-34-3 1,1-Dichloroethane > 7 75-35-4 1,1-Dichloroethene > 8 563-58-6 1,1-Dichloropropene > 9 87-61-6 1,2,3-Trichlorobenzene > 10 96-18-4 1,2,3-Trichloropropane > 11 120-82-1 1,2,4-Trichlorobenzene > 12 95-63-6 1,2,4-Trimethylbenzene > 13 96-12-8 1,2-Dibromo-3-chloropropane > 14 106-93-4 1,2-Dibromoethane > 15 95-50-1 1,2-Dichlorobenzene > 16 107-06-2 1,2-Dichloroethane > 17 78-87-5 1,2-Dichloropropane > 18 108-67-8 1,3,5-Trimethylbenzene > 19 541-73-1 1,3-Dichlorobenzene > 20 142-28-9 1,3-Dichloropropane > 21 106-46-7 1,4-Dichlorobenzene > 22 95-49-8 1-Chloro-2-methylbenzene > 23 106-43-4 1-Chloro-4-methylbenzene > 24 594-20-7 2,2-Dichloropropane > 25 71-43-2 Benzene > 26 108-86-1 Bromobenzene > 27 74-97-5 Bromochloromethane > 28 75-27-4 Bromodichloromethane > 29 74-83-9 Bromomethane > 30 108-90-7 Chlorobenzene > 31 75-00-3 Chloroethane > 32 75-01-4 Chloroethene > 33 74-87-3 Chloromethane > 34 124-48-1 Dibromochloromethane > 35 74-95-3 Dibromomethane > 36 75-71-8 Dichlorodifluoromethane > 37 75-09-2 Dichloromethane > 38 1330-20-7 Dimethylbenzenes > 39 100-42-5 Ethenylbenzene > 40 100-41-4 Ethylbenzene > 41 87-68-3 Hexachlorobutadiene > 42 98-82-8 Isopropylbenzene > 43 1634-04-4 Methyl tert-butyl ether > 44 108-88-3 Methylbenzene > 45 91-20-3 Naphthalene > 46 127-18-4 Tetrachloroethene > 47 56-23-5 Tetrachloromethane > 48 75-25-2 Tribromomethane > 49 79-01-6 Trichloroethene > 50 75-69-4 Trichlorofluoromethane > 51 67-66-3 Trichloromethane > 52 156-59-2 cis-1,2-Dichloroethene > 53 10061-01-5 cis-1,3-Dichloropropene > 54 104-51-8 n-Butylbenzene > 55 103-65-1 n-Propylbenzene > 56 99-87-6 p-Isopropyltoluene > 57 135-98-8 sec-Butylbenzene > 58 98-06-6 tert-Butylbenzene > 59 156-60-5 trans-1,2-Dichloroethene > 60 10061-02-6 trans-1,3-Dichloropropene Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this Federal Geographic Data Committee-compliant metadata file is intended to document the data set in nonproprietary form, as well as in ARC/INFO format, this metadata file may include some ARC/INFO-specific terminology. proprietary
UTC_USdams Major Dams in the United States CEOS_EXTRA STAC Catalog 1995-01-01 1996-12-31 -162.93422, 18.016077, -66.01461, 68.06759 https://cmr.earthdata.nasa.gov/search/concepts/C2231555196-CEOS_EXTRA.umm_json "This data set portrays major dams of the United States, including Puerto Rico and the U.S. Virgin Islands. The data set was created by extracting dams 50 feet or more in height, or with a normal storage capacity of 5,000 acre- feet or more, or with a maximum storage capacity of 25,000 acre-feet or more, from the 75,187 dams in the U.S. Army Corps of Engineers National Inventory of Dams. These data are intended for geographic display and analysis at the national level, and for large regional areas. The data should be displayed and analyzed at scales appropriate for 1:2,000,000-scale data. No responsibility is assumed by the U.S. Geological Survey in the use of these data. In the online, interactive National Atlas of the United States, at scales smaller than 1:4,850,000 the data is thinned for display purposes. For scales between 1: 4,850,000 and 1:22,000,000, dams are only shown if they have a height of 500 feet or more, or a normal storage capacity of 50,000 acre-feet or more, or a maximum storage capacity of 250,000 acre-feet or more (1173 dams). At scales smaller than 1:22,000,000, dams are only shown if they have a height of 5000 feet or more, or a normal storage capacity of 500,000 acre-feet or more, or a maximum storage capacity of 2,500,000 acre-feet or more (240 dams). The dams in this file were selected from the National Inventory of Dams (NID). First, a subset of the attributes contained in the NID was selected based on input from the Army Corps of Engineers. Using an ArcView query, the dams with a height of 50 feet or more were selected, along with the dams with a normal storage capacity of 5,000 acre-feet or more, and those with a maximum storage capacity of 25,000 acre-feet or more. (The International Committee on Large Dams considers dams over 50 feet to be large dams. The USGS Water Resources Division considers large reservoirs to be those with a normal storage capacity of 5,000 acre-feet or more, or with a maximum storage capacity of 25,000 acre-feet or more.) The resulting data set was converted to an ArcView shape file using the ""Convert to Shapefile"" command. 33 dams that fell outside the 50 States were deleted (1 in Guam, 1 in the Trust Territories, and 31 in Puerto Rico), and 78 dams without coordinates were also deleted. Several misspelled county names were corrected, and the entries in the FIPS_cnty (County FIPS) field were cleaned up. For all dams with a valid county name but no County FIPS, the FIPS code was added based on the listed county name. If two county names were given, the FIPS code used was for the first one listed, or for the county in the listed State. Where the county name was invalid or missing, the county was determined by comparing the dam location to the National Atlas counties file. If the dam fell on a State line, the county name and FIPS code used were those appropriate for the listed State. The shape file was converted to an Arc/Info coverage and then converted to NAD 83 for display purposes. The result was then converted back to shapefile format." proprietary
@@ -16656,8 +16657,8 @@ VMS_Bathy_Processing_1 Acoustic depth soundings collected on Australian Antarcti
VMS_Benthic_Photography_1 High resolution still photographs of the seafloor across the Mertz Glacier Region AU_AADC STAC Catalog 2011-01-04 2011-02-06 140, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214314096-AU_AADC.umm_json Geoscience Australia and the Australian Antarctic Division conducted a benthic community survey using underwater still photographs on the shelf around the Mertz Glacier region. The purpose of the work was to collect high resolution still photographs of the seafloor across the shelf to address three main objectives: 1. to investigate benthic community composition in the area previously covered by the Mertz Glacier tongue and to the east, an area previously covered by fast ice 2. to investigate benthic community composition (or lack thereof) in areas of known iceberg scours 3. to investigate the lateral extent of cold water coral communities in canyons along the shelf break. Benthic photos were captured using a Canon EOS 20D SLR 8 megapixel stills camera fitted with a Canon EF 35mm f1.4 L USM lens in a 2500m rated flat port anodised aluminium housing. Two Canon 580EX Speedlight strobes were housed in 6000m rated stainless steel housings with hemispherical acrylic domes. The camera and strobes were powered with a 28V 2.5Ah cyclone SLA battery pack fitted in the camera housing and connected using Brantner Wetconn series underwater connectors. The results were obtained with 100 ASA and a flash compensation value of +2/3 of a stop. The focus was set manually to 7m and the image was typically exposed at f2.8 and a shutter speed of 1/60 sec. The interval between photos was set to 10 or 15 seconds. The camera was fitted to either the CTD frame or the beam trawl frame and lowered to approximately 4-5 m from the bottom. Two laser pointers, set 50 cm apart, were used for scale. The camera was deployed at 93 stations, 7 using the beam trawl frame and 86 using the CTD frame. The stations were named by: 1. Camera deployment frame (e.g. CTD or beam trawl, BT) 2. Frame sequence number (e.g. CTD53) 3. Instrument (e.g. camera = CAM) 4. Sequence of camera deployments through the survey overall (e.g. first deployment = CAM01, second deployment = CAM02 etc). For example, BT5_CAM16 is the sixteenth camera deployment of the survey overall, and was the fifth deployment using the beam trawl frame. From the 93 stations, there were 75 successful camera deployments. There were no photos captured at 9 stations. This was due to the camera or strobes malfunctioning, the camera being too far from the bottom, or the camera or strobes being in the mud at the bottom. The photos at a further 9 stations are considered poor due to the camera being out of focus, the camera being a little too far from the bottom or because very few photos were captured of the bottom. The benthic photo will be used to document the fauna and communities associated with representative habitats in the study area. The post-cruise analysis of the benthic photos will involve recording seabed geology and biology (class or order, and whatever is significant for the habitat) for each image proprietary
VMS_FRRF_1 2010/11 VMS - Fast Repetition Rate Fluorometer (FRRF) sampling on the Aurora Australis ALL STAC Catalog 2011-01-04 2011-02-06 140, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214314029-AU_AADC.umm_json FRRF deployments were conducted at 22 sites in conjunction with ship stop times when the CTD was deployed. See event log for locations. Some underway FRRF sampling was conducted on the return voyage. This work was conducted as part of the VMS (Voyage Marine Science) voyage of the Aurora Australis in the 2010-2011 season. A report providing further details about the FRRF work is available as part of the download file. The download file also contains a word document (also included in the download file for metadata record ASAC_1307) explaining the data columns in the excel spreadsheets. proprietary
VMS_FRRF_1 2010/11 VMS - Fast Repetition Rate Fluorometer (FRRF) sampling on the Aurora Australis AU_AADC STAC Catalog 2011-01-04 2011-02-06 140, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214314029-AU_AADC.umm_json FRRF deployments were conducted at 22 sites in conjunction with ship stop times when the CTD was deployed. See event log for locations. Some underway FRRF sampling was conducted on the return voyage. This work was conducted as part of the VMS (Voyage Marine Science) voyage of the Aurora Australis in the 2010-2011 season. A report providing further details about the FRRF work is available as part of the download file. The download file also contains a word document (also included in the download file for metadata record ASAC_1307) explaining the data columns in the excel spreadsheets. proprietary
-VMS_Genomics_1 2010/11 VMS Geonomics sampling - data collected from the VMS (Voyage Marine Science) voyage of the Aurora Australis ALL STAC Catalog 2011-01-04 2011-02-06 140, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214314097-AU_AADC.umm_json Purpose of future metagenomic (DNA), metaproteomic (protein) and metatranscriptomic (RNA) analysis: For each sample, two drums (~200L each) of seawater were collected. Samples were taken from CTD sites, and surface samples (2m depth) taken at each of these sites. At most of these CTD sites, a deeper sample was taken according to the location of the DCM at that site. The 200L seawater is pumped through a 20 micron mesh to remove the largest particles, then the biomass is collected on three consecutive filters corresponding to decreasing pore size (3.0 microns, 0.8 microns, 0.1 microns). This is repeated for each sample using the second 200L of seawater to generate duplicates for each sample. The overall aim is to determine the identity of microbes present in the Southern Ocean, and what microbial metabolic processes are in operation. In other words: who is there, and what they are doing. Special emphasis was placed on the SR3 transect. Samples were collected as below. For each sample, a total of six filters were obtained (3x pore sizes, 2x replicates). Each filter is stored in a storage buffer in a 50mL tube, and placed at -80 degrees C for the remainder of the voyage. proprietary
VMS_Genomics_1 2010/11 VMS Geonomics sampling - data collected from the VMS (Voyage Marine Science) voyage of the Aurora Australis AU_AADC STAC Catalog 2011-01-04 2011-02-06 140, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214314097-AU_AADC.umm_json Purpose of future metagenomic (DNA), metaproteomic (protein) and metatranscriptomic (RNA) analysis: For each sample, two drums (~200L each) of seawater were collected. Samples were taken from CTD sites, and surface samples (2m depth) taken at each of these sites. At most of these CTD sites, a deeper sample was taken according to the location of the DCM at that site. The 200L seawater is pumped through a 20 micron mesh to remove the largest particles, then the biomass is collected on three consecutive filters corresponding to decreasing pore size (3.0 microns, 0.8 microns, 0.1 microns). This is repeated for each sample using the second 200L of seawater to generate duplicates for each sample. The overall aim is to determine the identity of microbes present in the Southern Ocean, and what microbial metabolic processes are in operation. In other words: who is there, and what they are doing. Special emphasis was placed on the SR3 transect. Samples were collected as below. For each sample, a total of six filters were obtained (3x pore sizes, 2x replicates). Each filter is stored in a storage buffer in a 50mL tube, and placed at -80 degrees C for the remainder of the voyage. proprietary
+VMS_Genomics_1 2010/11 VMS Geonomics sampling - data collected from the VMS (Voyage Marine Science) voyage of the Aurora Australis ALL STAC Catalog 2011-01-04 2011-02-06 140, -67, 150, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214314097-AU_AADC.umm_json Purpose of future metagenomic (DNA), metaproteomic (protein) and metatranscriptomic (RNA) analysis: For each sample, two drums (~200L each) of seawater were collected. Samples were taken from CTD sites, and surface samples (2m depth) taken at each of these sites. At most of these CTD sites, a deeper sample was taken according to the location of the DCM at that site. The 200L seawater is pumped through a 20 micron mesh to remove the largest particles, then the biomass is collected on three consecutive filters corresponding to decreasing pore size (3.0 microns, 0.8 microns, 0.1 microns). This is repeated for each sample using the second 200L of seawater to generate duplicates for each sample. The overall aim is to determine the identity of microbes present in the Southern Ocean, and what microbial metabolic processes are in operation. In other words: who is there, and what they are doing. Special emphasis was placed on the SR3 transect. Samples were collected as below. For each sample, a total of six filters were obtained (3x pore sizes, 2x replicates). Each filter is stored in a storage buffer in a 50mL tube, and placed at -80 degrees C for the remainder of the voyage. proprietary
VNP01_NRT_2 VIIRS/NPP Raw Radiances in Counts 6-Min L1A Swath NRT LANCEMODIS STAC Catalog 2022-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2208439292-LANCEMODIS.umm_json VIIRS/NPP Raw Radiances in Counts 6-Min L1A Swath - NRT product contains the unpacked, raw VIIRS science, calibration and engineering data; the extracted ephemeris and attitude data from the spacecraft diary packets; and the raw ADCS and bus-critical spacecraft telemetry data from those packets, with a few critical fields extracted. The shortname for this product is VNP01_NRT. For more information download VIIRS Level 1 Product User's Guide at https://oceancolor.gsfc.nasa.gov/docs/format/VIIRS_Level-1_DataProductUsersGuide.pdf file_naming_convention = VNP01_NRT.AYYYYDDD.HHMM.CCC.nc AYYYYDDD = Acquisition Year and Day of Year HHMM = Acquisition Hour and Minute CCC = Collection number nc = NetCDF5 proprietary
VNP02DNB_2 VIIRS/NPP Day/Night Band 6-Min L1B Swath 750 m LAADS STAC Catalog 2012-01-19 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2105091380-LAADS.umm_json The VIIRS/NPP Day/Night Band 6-Min L1B Swath 750 m product, short-name VNP02DNB, is a panchromatic Day-Night band (DNB) calibrated radiance product. The DNB is one of the M-bands with an at-nadir spatial resolution of 750 meters (across the entire scan). The panchromatic DNB’s spectral wavelength ranges from 0.5 µm to 0.9 µm. It facilitates measuring night lights, reflected solar/lunar lights with a large dynamic range between a low of a quarter moon illumination to the brightest daylight. More information is available at product page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/VNP02DNB/ proprietary
VNP02DNB_NRT_2 VIIRS/NPP Day/Night Band 6-Min L1B Swath 750m NRT LANCEMODIS STAC Catalog 2022-01-25 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2208367854-LANCEMODIS.umm_json The VIIRS/NPP Day/Night Band 6-Min L1B Swath SDR 750m Near Real Time (NRT) product, short-name VNP02DNB_NRT is among the VIIRS Level 1 and Level 2 swath products that are generated from the processing of 6 minutes of VIIRS data acquired during the S-NPP satellite overpass. The Day/Night band (DNB) is a panchromatic channel covering the wavelengths from 500 nm to 900 nm, and sensitive to visible and near-infrared from daylight down to the low-level radiation observed at night. The VIIRS DNB is much improved from previous products due in large part to its complicated continuous on-board calibration. In addition, new-moon Earth observations are used to estimate and remove stray light. These corrections are a first of its kind to provide on-orbit radiometric calibration. The corrections made to the DNB data are provided by the NASA VIIRS Characterization Support Team and are likely to continue to evolve given this new methodology. The spatial resolution of the instrument at viewing nadir is approximately 750 m for the DNB and the Moderate-resolution Bands and and 375m for the Imagery bands. The DNB is aggregated to maintain nearly constant horizontal spatial resolution across the swath. As the DNB is sensitive to nighttime radiation over the full lunar cycle, the incoming solar and lunar radiation must be properly modeled to calculate the reflectance. However, the DNB is sensitive to more sources of radiation than just the sun and moon. proprietary
@@ -16927,8 +16928,8 @@ WILKS_2018_Chatham_sedimenttraps_specieslist_3 Diatom and coccolithophore assemb
WIND_3DP 3-D Plasma and Energetic Particle Investigation on WIND ALL STAC Catalog 1994-11-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214615352-SCIOPS.umm_json The main purpose of the Wind spacecraft is to measure the incoming solar wind, magnetic fields and particles, although early on it will also observe the Earth's foreshock region. Wind, together with Geotail, Polar, SOHO, and Cluster projects, constitute a cooperative scientific satellite project designated the International Solar Terrestrial Physics (ISTP) program which aims at gaining improved understanding of the physics of solar terrestrial relations. This experiment is designed to measure the full three-dimensional distribution of suprathermal electrons and ions at energies from a few eV to over several hundred keV on the WIND spacecraft. Its high sensitivity, wide dynamic range, and good energy and angular resolution make it especially capable of detecting and characterizing the numerous populations of particles that are present in interplanetary space at energies above the bulk of the solar wind particles and below the energies typical of most cosmic rays. Data consists of ion moments, energy spectra, electron spectra, electron and ion omni directional energy spectra. Data are available from SSL at University of California, Berkeley (http://sprg.ssl.berkeley.edu/wind3dp/esahome.html) and at the NSSDC CDAWeb (http://cdaweb.gsfc.nasa.gov/cdaweb/) proprietary
WIND_3DP 3-D Plasma and Energetic Particle Investigation on WIND SCIOPS STAC Catalog 1994-11-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214615352-SCIOPS.umm_json The main purpose of the Wind spacecraft is to measure the incoming solar wind, magnetic fields and particles, although early on it will also observe the Earth's foreshock region. Wind, together with Geotail, Polar, SOHO, and Cluster projects, constitute a cooperative scientific satellite project designated the International Solar Terrestrial Physics (ISTP) program which aims at gaining improved understanding of the physics of solar terrestrial relations. This experiment is designed to measure the full three-dimensional distribution of suprathermal electrons and ions at energies from a few eV to over several hundred keV on the WIND spacecraft. Its high sensitivity, wide dynamic range, and good energy and angular resolution make it especially capable of detecting and characterizing the numerous populations of particles that are present in interplanetary space at energies above the bulk of the solar wind particles and below the energies typical of most cosmic rays. Data consists of ion moments, energy spectra, electron spectra, electron and ion omni directional energy spectra. Data are available from SSL at University of California, Berkeley (http://sprg.ssl.berkeley.edu/wind3dp/esahome.html) and at the NSSDC CDAWeb (http://cdaweb.gsfc.nasa.gov/cdaweb/) proprietary
WIR_98_4105 Major-Ion, Nutrient, and Trace-Element Concentrations in the Steamboat Creek Basin CEOS_EXTRA STAC Catalog 1996-09-09 1996-09-13 -122.7, 42.3, -122.5, 43.6 https://cmr.earthdata.nasa.gov/search/concepts/C2231554333-CEOS_EXTRA.umm_json In September 1996, a water-quality study was done by the U.S. Geological Survey, in coordination with the U.S. Forest Service, in headwater streams of Steamboat Creek, a tributary to the North Umpqua River Basin in southwestern Oregon. Field measurements were made in and surface-water and bottom-sediment samples were collected from three tributaries of Steamboat Creek-Singe Creek, City Creek, and Horse Heaven Creek-and at one site in Steamboat Creek upstream from where the three tributaries flow into Steamboat Creek. Water samples collected in Singe Creek had larger concentrations of most major-ion constituents and smaller concentrations of most nutrient constitu ents than was observed in the other three creeks. City Creek, Horse Heaven Creek, and Steamboat Creek had primarily calcium bicarbonate water, whereas Singe Creek had primarily a calcium sulfate water; the calcium sulfate water detected in Singe Creek, along with the smallest observed alkalinity and pH values, suggests that Singe Creek may be receiving naturally occurring acidic water. Of the 18 trace elements analyzed in filtered water samples, only 6 were detected-aluminum, barium, cobalt, iron, manganese, and zinc. All six of the trace elements were detected in Singe Creek, at concentrations generally larger than those observed in the other three creeks. Of the detected trace elements, only iron and zinc have chronic toxicity criteria established by the U.S. Environmental Protection Agency (USEPA) for the protection of aquatic life; none exceeded the USEPA criterion. Bottom-sediment concentrations of antimony, arsenic, cadmium, copper, lead, mercury, zinc, and organic carbon were largest in City Creek. In City Creek and Horse Heaven Creek, concentrations for 11 constituents--antimony, arsenic, cadmium, copper, lead, manganese (Horse Heaven Creek only), mercury, selenium, silver, zinc, and organic carbon (City Creek only)--exceeded concentrations considered to be enriched in streams of the nearby Willamette River Basin, whereas in Steamboat Creek only two trace elements--antimony and nickel--exceeded Willamette River enriched concentrations. Bottom-sediment concentrations for six of these constituents in City Creek and Horse Heaven Creek--arsenic, cadmium, copper, lead, mercury, and zinc--also exceeded interim Canadian threshold effect level (TEL) concentrations established for the protection of aquatic life, whereas only four constituents between Singe Creek and Steamboat Creek--arsenic, chromium, copper (Singe Creek only), and nickel--exceeded the TEL concentrations. The data set checked for the concentrations of major ions, nutrients, and trace elements in water and bottom sediments collected in the four tributaries during the low-flow conditions of September 9-13, 1996. Stream-water chemistry results were contrasted, and trace-element concentrations were compared with U.S. Environmental Protection Agency chronic aquatic life toxicity criteria. Bottom-sediment trace-element results were also contrasted and compared with concentrations considered to be enriched in streams of the nearby Willamette River Basin and to interim Canadian threshold level (TEL) concentrations established for the protection of aquatic life. The area of study was Headwater streams of Steamboat Creek, a tributary to the north Umpqua River Basin in southwestern Oregon Field measurements and surface-water and bottom-sediment samples at each of the four sites included streamflow, stream temperature, specific conductance, dissolved oxygen, pH, alkalinity, major ions in filtered water (8 constituents), low-level concentrations of trace elements in filtered water (18 elements), and trace elements and carbon in bottom sediment (47 elements). Stream temperature, specific conductance, dissolved oxygen, and pH were measured using a calibrated Hydrolab multiparameter unit. Because stream widths were less than 8 feet, field measurements were made only near the center of flow at 1 foot or less below water surface. The Hydrolab unit was calibrated at each site before and after sampling. Stream temperatures were recorded to the nearest 0.1 degree Centigrade; specific conductance to the nearest 1 microsiemen per centimeter at 25 degrees Centigrade ; dissolved oxygen to the nearest 0.1 milligrams per liter; and pH to the nearest 0.1 pH units. Measurements of streamflow were made in accordance with standard USGS procedures (Rantz and others, 1982). Alkalinity measurements were made on filtered water samples using an incremental titration method (Shelton, 1994), and results were reported to the nearest 1 milligram per liter as calcium carbonate (CaCO3). Water samples were collected using 1-liter narrow-mouth acid-rinsed polyethylene bottles from a minimum of eight verticals in the cross section, suing an equal-width-increment method described by Edwards and Glysson (1988), and composited into a 8-liter polyethylene acid-rinsed churn splitter. Sample and compositing containers were prerinsed with native water prior to sample collection. Water samples were collected using clean procedures as outlined by Horowitz and others (1994). Samples were chilled on ice from time of sample collection until analysis, except when samples were processed. Processing of the field samples was accomplished either in the mobile field laboratory or in an area suitably clean for carrying out the filtering and preservation procedures. Samples for major ions, nutrients, and trace elements in filtered water (operationally defined as dissolved) were passed through 0.45 micrometer pore-size capsule filters into polyethylene bottles using procedures outlined by Horowitz and others (1994). Filtered-water trace-element samples were preserved with 0.5 milliliter of ultra-pure nitric acid per 250 mL of sample; nutrient samples were placed in dark brown polyethylene bottles and were chilled for preservation. All chemical samples were shipped to the USGS National Water Quality Laboratory (NWQL) in Arvada, Colorado, for analysis according to methods outlined by Fishman (1993). The information for this metadata was taken from the Online Publications of the Oregon District at http://oregon.usgs.gov/pubs_dir/online_list.html . proprietary
-WISPMAWSON04-05_1 A GIS dataset of Wilson's storm petrel nests mapped in the Mawson region during the 2004-2005 season ALL STAC Catalog 2004-12-10 2005-04-25 62.18384, -67.68587, 63.40759, -67.47282 https://cmr.earthdata.nasa.gov/search/concepts/C1214314124-AU_AADC.umm_json Very little information is known about the distribution and abundance of Wilson's storm petrels at the regional and local scales. This dataset contains locations of Wilson's storm petrel nests, mapped in the Mawson region during 2004-2005 season. Location of nests were recorded with handheld Trimble Geoexplorer GPS receivers, differentially corrected and stored as an Arcview point shapefile(ESRI software). Descriptive information relating to each bird nest was recorded and a detailed description of data fields is provided in description of the shapefile. A text file also provide the attribute information (formatted for input into R statistical software). This work has been completed as part of ASAC project 2704 (ASAC_2704). Fields recorded Species Activity Type Entrances Slope Remnants Latitude Longitude Date Snow Eggchick Cavitysize Cavitydepth Distnn Substrate Comments SitedotID Aspect Firstfred proprietary
WISPMAWSON04-05_1 A GIS dataset of Wilson's storm petrel nests mapped in the Mawson region during the 2004-2005 season AU_AADC STAC Catalog 2004-12-10 2005-04-25 62.18384, -67.68587, 63.40759, -67.47282 https://cmr.earthdata.nasa.gov/search/concepts/C1214314124-AU_AADC.umm_json Very little information is known about the distribution and abundance of Wilson's storm petrels at the regional and local scales. This dataset contains locations of Wilson's storm petrel nests, mapped in the Mawson region during 2004-2005 season. Location of nests were recorded with handheld Trimble Geoexplorer GPS receivers, differentially corrected and stored as an Arcview point shapefile(ESRI software). Descriptive information relating to each bird nest was recorded and a detailed description of data fields is provided in description of the shapefile. A text file also provide the attribute information (formatted for input into R statistical software). This work has been completed as part of ASAC project 2704 (ASAC_2704). Fields recorded Species Activity Type Entrances Slope Remnants Latitude Longitude Date Snow Eggchick Cavitysize Cavitydepth Distnn Substrate Comments SitedotID Aspect Firstfred proprietary
+WISPMAWSON04-05_1 A GIS dataset of Wilson's storm petrel nests mapped in the Mawson region during the 2004-2005 season ALL STAC Catalog 2004-12-10 2005-04-25 62.18384, -67.68587, 63.40759, -67.47282 https://cmr.earthdata.nasa.gov/search/concepts/C1214314124-AU_AADC.umm_json Very little information is known about the distribution and abundance of Wilson's storm petrels at the regional and local scales. This dataset contains locations of Wilson's storm petrel nests, mapped in the Mawson region during 2004-2005 season. Location of nests were recorded with handheld Trimble Geoexplorer GPS receivers, differentially corrected and stored as an Arcview point shapefile(ESRI software). Descriptive information relating to each bird nest was recorded and a detailed description of data fields is provided in description of the shapefile. A text file also provide the attribute information (formatted for input into R statistical software). This work has been completed as part of ASAC project 2704 (ASAC_2704). Fields recorded Species Activity Type Entrances Slope Remnants Latitude Longitude Date Snow Eggchick Cavitysize Cavitydepth Distnn Substrate Comments SitedotID Aspect Firstfred proprietary
WLDAS_NOAHMP001_DA1_D1.0 WLDAS Noah-MP 3.6 Land Surface Model L4 Daily 0.01 degree x 0.01 degree Version D1.0 (WLDAS_NOAHMP001_DA1) at GES DISC GES_DISC STAC Catalog 1979-01-02 -124.925, 25.065, -89.025, 52.925 https://cmr.earthdata.nasa.gov/search/concepts/C2789781977-GES_DISC.umm_json The Western Land Data Assimilation System (WLDAS), developed at Goddard Space Flight Center (GSFC) and funded by the NASA Western Water Applications Office, provides water managers and stakeholders in the western United States with a long-term record of near-surface hydrology for use in drought assessment and water resources planning. WLDAS leverages advanced capabilities in land surface modeling and data assimilation to furnish a system that is customized for stakeholders’ needs in the region. WLDAS uses NASA’s Land Information System (LIS) to configure and drive the Noah Multiparameterization (Noah-MP) Land Surface Model (LSM) version 3.6 to simulate land surface states and fluxes. WLDAS uses meteorological observables from the North American Land Data Assimilation System (NLDAS-2) including precipitation, incoming shortwave and longwave radiation, near surface air temperature, humidity, wind speed, and surface pressure along with parameters such as vegetation class, soil texture, and elevation as inputs to a model that simulates land surface energy and water budget processes. Outputs of the model include soil moisture, snow depth and snow water equivalent, evapotranspiration, soil temperature, as well as derived quantities such as groundwater recharge and anomalies of the state variables. proprietary
WOCE91_Chlorophyll_1 Chlorophyll a data collected on the 1991 WOCE voyage of the Aurora Australis AU_AADC STAC Catalog 1991-10-08 1991-10-26 136.393, -62.294, 154.937, -45.183 https://cmr.earthdata.nasa.gov/search/concepts/C1214314037-AU_AADC.umm_json Chloropyll a data were collected along the WOCE transect on voyage 1 of the Aurora Australis, during October of 1991. These data were collected as part of ASAC project 40 (The role of antarctic marine protists in trophodynamics and global change and the impact of UV-B on these organisms). proprietary
WOES_Chlorophyll_1 Aurora Australis Voyage 9 (WOES) 1992-93 Chlorophyll a Data AU_AADC STAC Catalog 1993-03-12 1993-05-03 139.71167, -65.888, 155.11171, -43.22 https://cmr.earthdata.nasa.gov/search/concepts/C1214314038-AU_AADC.umm_json This dataset contains chlorophyll a data collected by the Aurora Australis on Voyage 7, 1992-1993 - the WOES (Wildlife Oceanography Ecosystem Survey) cruise. Samples were collected from March-May of 1993. These data were collected as part of ASAC project 40 (The role of antarctic marine protists in trophodynamics and global change and the impact of UV-B on these organisms). proprietary
@@ -16952,10 +16953,10 @@ WV04_Pan_L1B_1 WorldView-4 Level 1B Panchromatic Satellite Imagery CSDA STAC Cat
WV_LCC_SC_FSCA_1 Land Cover Classification, Snow Cover, and Fractional Snow-Covered Area Maps from Maxar WorldView Satellite Images V001 NSIDC_ECS STAC Catalog 2015-05-20 2019-05-05 -121.203708, 38.867847, -108.032283, 48.672717 https://cmr.earthdata.nasa.gov/search/concepts/C2695676729-NSIDC_ECS.umm_json This data set includes: (1) fine-scale snow and land cover maps from two mountainous study sites in the Western U.S., produced using machine-learning models trained to extract land cover data from WorldView-2 and WorldView-3 stereo panchromatic and multispectral images; (2) binary snow maps derived from the land cover maps; and (3) 30 m and 465 m fractional snow-covered area (fSCA) maps, produced via downsampling of the binary snow maps. The land cover classification maps feature between three and six classes common to mountainous regions and integral for accurate stereo snow depth mapping: illuminated snow, shaded snow, vegetation, exposed surfaces, surface water, and clouds. Also included are Landsat and MODSCAG fSCA map products. The source imagery for these data are the Maxar WorldView-2 and Maxar WorldView-3 Level-1B 8-band multispectral images, orthorectified and converted to top-of-atmosphere reflectance. These Level-1B images are available under the NGA NextView/EnhancedView license. proprietary
WYGISC_HYDRO100K 1:100,000-scale Hydrography for Wyoming (enhanced DLGs) SCIOPS STAC Catalog 1970-01-01 -111.36555, 40.944794, -103.783806, 44.99391 https://cmr.earthdata.nasa.gov/search/concepts/C1214614313-SCIOPS.umm_json The purpose of this data layer was to provide a base layer of water features at a statewide level for riparian/aquatic species distribution modeling for the Wyoming Gap Analysis project. However the data may also be used for a variety of other natural resources management/biological studies at the appropriate scale. Hydrographic features for Wyoming at 1:100,000-scale, including perennial and intermittent designations and Strahler stream order attributes for streams. Does not include man-made ditches, canals and aqueducts. The data was originally produced by USGS, a Digital Line Graph (DLG) product, though this product was enhanced (edgematched, some linework and attributes corrected, stream order attribute added). A subset of this dataset is also available for distribution, including only major streams (order 4 to 7) and major lakes and reservoirs. In order to reduce the size of this subset, the line segments were dissolved to remove unncessary segments. Both datasets are available in Arc export file and shapefile format for download Statewide and tiled data: there is one export file, which when imported into ARC/INFO, will contain one coverage with both polygon (lakes, reservoirs) and line (streams) topology and two feature attribute files (.PAT and .AAT) along with three additional attribute files containing descriptive information. In shapefile format, there will be two shapefiles (polygons and lines separated), with all attribute files in Dbase format. proprietary
WYGISC_HYDRO100K 1:100,000-scale Hydrography for Wyoming (enhanced DLGs) ALL STAC Catalog 1970-01-01 -111.36555, 40.944794, -103.783806, 44.99391 https://cmr.earthdata.nasa.gov/search/concepts/C1214614313-SCIOPS.umm_json The purpose of this data layer was to provide a base layer of water features at a statewide level for riparian/aquatic species distribution modeling for the Wyoming Gap Analysis project. However the data may also be used for a variety of other natural resources management/biological studies at the appropriate scale. Hydrographic features for Wyoming at 1:100,000-scale, including perennial and intermittent designations and Strahler stream order attributes for streams. Does not include man-made ditches, canals and aqueducts. The data was originally produced by USGS, a Digital Line Graph (DLG) product, though this product was enhanced (edgematched, some linework and attributes corrected, stream order attribute added). A subset of this dataset is also available for distribution, including only major streams (order 4 to 7) and major lakes and reservoirs. In order to reduce the size of this subset, the line segments were dissolved to remove unncessary segments. Both datasets are available in Arc export file and shapefile format for download Statewide and tiled data: there is one export file, which when imported into ARC/INFO, will contain one coverage with both polygon (lakes, reservoirs) and line (streams) topology and two feature attribute files (.PAT and .AAT) along with three additional attribute files containing descriptive information. In shapefile format, there will be two shapefiles (polygons and lines separated), with all attribute files in Dbase format. proprietary
-WYGISC_HYDRO24K 1:24,000-scale Hydrography for ortions Wyoming, various sources ALL STAC Catalog 1967-01-01 1971-12-31 -111, 41, -104, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1214614312-SCIOPS.umm_json "The purpose of this data layer is to provide a base layer of hydrography at the watershed scale for GIS display and analysis. The hydrography described by this metadata, including streams, lakes, reservoirs and"" ditches, came from three different sources, all at 1:24,000-scale:"" -USGS Digital Line Graphs -USFS Cartographic Feature File -digitized by Wyoming Water Resources Center off of paper topographic maps" proprietary
WYGISC_HYDRO24K 1:24,000-scale Hydrography for ortions Wyoming, various sources SCIOPS STAC Catalog 1967-01-01 1971-12-31 -111, 41, -104, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1214614312-SCIOPS.umm_json "The purpose of this data layer is to provide a base layer of hydrography at the watershed scale for GIS display and analysis. The hydrography described by this metadata, including streams, lakes, reservoirs and"" ditches, came from three different sources, all at 1:24,000-scale:"" -USGS Digital Line Graphs -USFS Cartographic Feature File -digitized by Wyoming Water Resources Center off of paper topographic maps" proprietary
-WYGISC_LANDUSE Agricultural Land Use of Wyoming SCIOPS STAC Catalog 1980-01-01 1982-12-31 -111.09, 40.95, -103.88, 45.107 https://cmr.earthdata.nasa.gov/search/concepts/C1214614317-SCIOPS.umm_json The purpose of this data layer is to provide a digital layer showing areas of agriculture and agricultural chemical use in Wyoming. This layer was designed to be applied in the Wyoming Ground-Water Vulnerability Mapping Project. This dataset represents croplands of Wyoming as interpreted from 1:58,200-scale National High Altitude Program (NHAP) color infrared aerial photography. The photos, which were taken in 1980-1982, were interpreted and land use designations were hand-drawn onto plots produced at the same scale as the photos, using a light table. The plots were then digitized as polygons into ARC/INFO 7.0.2. Valid polygons include irrigated croplands, non-irrigated croplands, urban lands, golf-courses, and non-agricultural lands. Golf courses boundaries, which have changed recently, were later updated with 1994 NAPP photos. proprietary
+WYGISC_HYDRO24K 1:24,000-scale Hydrography for ortions Wyoming, various sources ALL STAC Catalog 1967-01-01 1971-12-31 -111, 41, -104, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1214614312-SCIOPS.umm_json "The purpose of this data layer is to provide a base layer of hydrography at the watershed scale for GIS display and analysis. The hydrography described by this metadata, including streams, lakes, reservoirs and"" ditches, came from three different sources, all at 1:24,000-scale:"" -USGS Digital Line Graphs -USFS Cartographic Feature File -digitized by Wyoming Water Resources Center off of paper topographic maps" proprietary
WYGISC_LANDUSE Agricultural Land Use of Wyoming ALL STAC Catalog 1980-01-01 1982-12-31 -111.09, 40.95, -103.88, 45.107 https://cmr.earthdata.nasa.gov/search/concepts/C1214614317-SCIOPS.umm_json The purpose of this data layer is to provide a digital layer showing areas of agriculture and agricultural chemical use in Wyoming. This layer was designed to be applied in the Wyoming Ground-Water Vulnerability Mapping Project. This dataset represents croplands of Wyoming as interpreted from 1:58,200-scale National High Altitude Program (NHAP) color infrared aerial photography. The photos, which were taken in 1980-1982, were interpreted and land use designations were hand-drawn onto plots produced at the same scale as the photos, using a light table. The plots were then digitized as polygons into ARC/INFO 7.0.2. Valid polygons include irrigated croplands, non-irrigated croplands, urban lands, golf-courses, and non-agricultural lands. Golf courses boundaries, which have changed recently, were later updated with 1994 NAPP photos. proprietary
+WYGISC_LANDUSE Agricultural Land Use of Wyoming SCIOPS STAC Catalog 1980-01-01 1982-12-31 -111.09, 40.95, -103.88, 45.107 https://cmr.earthdata.nasa.gov/search/concepts/C1214614317-SCIOPS.umm_json The purpose of this data layer is to provide a digital layer showing areas of agriculture and agricultural chemical use in Wyoming. This layer was designed to be applied in the Wyoming Ground-Water Vulnerability Mapping Project. This dataset represents croplands of Wyoming as interpreted from 1:58,200-scale National High Altitude Program (NHAP) color infrared aerial photography. The photos, which were taken in 1980-1982, were interpreted and land use designations were hand-drawn onto plots produced at the same scale as the photos, using a light table. The plots were then digitized as polygons into ARC/INFO 7.0.2. Valid polygons include irrigated croplands, non-irrigated croplands, urban lands, golf-courses, and non-agricultural lands. Golf courses boundaries, which have changed recently, were later updated with 1994 NAPP photos. proprietary
WaterBalance_Daily_Historical_GRIDMET_1.5 Daily Historical Water Balance Products for the CONUS LPCLOUD STAC Catalog 1980-01-01 2023-12-31 -131.70607, 21.115301, -60.530453, 55.457306 https://cmr.earthdata.nasa.gov/search/concepts/C2674694066-LPCLOUD.umm_json This dataset provides daily historical Water Balance Model outputs from a Thornthwaite-type, single bucket model. Climate inputs to the model are from GridMet daily temperature and precipitation for the Continental United States (CONUS). The Water Balance Model output variables include the following: Potential Evapotranspiration (PET, mm), Actual Evapotranspiration (AET, mm), Moisture Deficit (Deficit, mm), Soil Water (soilwater, mm), Runoff (mm), Rain (mm), and Accumulated Snow Water Equivalent (accumswe, mm). The dataset covers the period from January 1 to December 31 for years 1980 through 2023 for the CONUS. Water Balance Model variables are provided as individual files, by variable and year, at a 1 km x 1 km spatial resolution and a daily temporal resolution. Data are in a North America Lambert Conformal Conic projection and are distributed in a standardized Climate and Forecast (CF)-compliant NetCDF file format. proprietary
WaterBalance_Monthly_Historical_GRIDMET_1.5 Monthly Historical Water Balance Products for the CONUS LPCLOUD STAC Catalog 1980-01-01 2023-12-31 -131.70607, 21.115301, -60.530453, 55.457306 https://cmr.earthdata.nasa.gov/search/concepts/C2674700048-LPCLOUD.umm_json This dataset provides daily historical Water Balance Model outputs from a Thornthwaite-type, single bucket model. Climate inputs to the model are from GridMet daily temperature and precipitation for the Continental United States (CONUS). The Water Balance Model output variables include the following: Potential Evapotranspiration (PET, mm), Actual Evapotranspiration (AET, mm), Moisture Deficit (Deficit, mm), Soil Water (soilwater, mm), Runoff (mm), Rain (mm), and Accumulated Snow Water Equivalent (accumswe, mm). The dataset covers the period from January 1 to December 31 for years 1980 through 2023 for the CONUS. Water Balance Model variables are provided as individual files, by variable and year, at a 1 km x 1 km spatial resolution and a daily temporal resolution. Data are in a North America Lambert Conformal Conic projection and are distributed in a standardized Climate and Forecast (CF)-compliant NetCDF file format. proprietary
WebbRosenzweig_548_1 Global Soil Texture and Derived Water-Holding Capacities (Webb et al.) ORNL_CLOUD STAC Catalog 1950-01-01 1996-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2216863033-ORNL_CLOUD.umm_json A standardized global data set of soil horizon thicknesses and textures (particle size distributions). proprietary
@@ -16968,49 +16969,49 @@ Wetland_Soil_CarbonStocks_WA_2249_1 Soil Organic Carbon and Wetland Intrinsic Po
Wetland_VegClassification_PAD_2069_1 ABoVE: Wetland Vegetation Classification for Peace-Athabasca Delta, Canada, 2019 ORNL_CLOUD STAC Catalog 2019-07-15 2019-09-15 -112.11, 58.21, -110.83, 59.14 https://cmr.earthdata.nasa.gov/search/concepts/C2308233855-ORNL_CLOUD.umm_json This dataset contains land cover classification focused on water and wetland vegetation communities over the Peace-Athabasca Delta, Canada. Four classification maps with 5-m resolution were derived various combinations of Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) acquired in July and September 2019, and a historical LiDAR archive data. The maps include 10 land cover classes, including open water, emergent aquatic vegetation types, terrestrial vegetation, and forest. Based on field data, the best performing model, which combined all three data sources, achieved an overall accuracy of 93.5%. The land cover maps are provided in GeoTIFF format along with polygons of AVIRIS-NG, UAVSAR, and LiDAR footprints in shapefile and KML formats. proprietary
Wetland_VegClassification_PAD_2069_1 ABoVE: Wetland Vegetation Classification for Peace-Athabasca Delta, Canada, 2019 ALL STAC Catalog 2019-07-15 2019-09-15 -112.11, 58.21, -110.83, 59.14 https://cmr.earthdata.nasa.gov/search/concepts/C2308233855-ORNL_CLOUD.umm_json This dataset contains land cover classification focused on water and wetland vegetation communities over the Peace-Athabasca Delta, Canada. Four classification maps with 5-m resolution were derived various combinations of Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) acquired in July and September 2019, and a historical LiDAR archive data. The maps include 10 land cover classes, including open water, emergent aquatic vegetation types, terrestrial vegetation, and forest. Based on field data, the best performing model, which combined all three data sources, achieved an overall accuracy of 93.5%. The land cover maps are provided in GeoTIFF format along with polygons of AVIRIS-NG, UAVSAR, and LiDAR footprints in shapefile and KML formats. proprietary
WhitePhenoregions_799_1 Phenoregions For Monitoring Vegetation Responses to Climate Change ORNL_CLOUD STAC Catalog 1982-01-01 1999-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784383305-ORNL_CLOUD.umm_json The overall purpose in this research was to identify the regions of the world best suited for long-term monitoring of biospheric responses to climate change, i.e., monitoring land surface phenology. The user is referred to White et al. [2005] for further details. Using global 8 km 1982 to 1999 Normalized Difference Vegetation Index (NDVI) data and an eight-element monthly climatology, we identified pixels consistently dominated by annual cycles and then created phenologically and climatically self-similar clusters, which we term phenoregions. We then ranked and screened each phenoregion as a function of landcover homogeneity and consistency, evidence of human impacts, and political diversity.This dataset contains material providing users with direct access to data used to construct the figures in White et al. [2005]. Users are referred to this reference for additional information. Data files include ASCII and binary versions of the image files for the 500 elemental phenoregions and the 136 final monitoring phenoregions (shown in figure below) and a corresponding .jpg map. Also included are the classification data in tabular ACSII format for each of the 500 elemental phenoregions.Selected monitoring phenoregions. Phenoregions with fewer than 100 pixels or dominated by crop, urban or barren landcover removed. The 136 remaining phenoregions are those passing the screening factors in Table 1 and are shown with normalized rankings by landcover. (From White et al., 2005) proprietary
-WhiteSpruce_Leaf_Traits_Alaska_2124_1 ABoVE: White Spruce Photosynthetic and Leaf Traits, Alaska and New York, 2017 ORNL_CLOUD STAC Catalog 2017-06-19 2017-07-20 -149.75, 41.4, -74.02, 67.99 https://cmr.earthdata.nasa.gov/search/concepts/C2636355463-ORNL_CLOUD.umm_json This dataset provides measurements of gas exchange (light response curves, Kok curves and ACi curves), leaf traits (carbon, nitrogen, and specific leaf area), leaf pigments (Chlorophyll a, Chlorophyll b and Carotenoids), the photochemical reflectance index (PRI), and average photosynthetic photon flux density as collected from hemispherical photographs. Data were collected on white spruce trees (Picea glauca (Moench) Voss) growing at the northern edge of the species' distribution in Alaska and at the southern edge of the species' distribution in Black Rock Forest (BRF), New York. Measurements were taken at high and low canopy positions on each tree at both sites during the 2017 growing season (2017-06-19 to 2017-07-20). Gas exchange, leaf trait, pigment and spectral measurements were obtained using a portable photosynthesis system (LI-6800, LI-COR, Lincoln, NE). Photochemical reflectance index was determined using a spectroradiometer, and hemispherical photographs were taken with a digital camera. These data were collected to better understand how vertical canopy gradients in photosynthetic physiology change from the southernmost to the northernmost range extremes of white spruce. The data are provided in comma-separated value (CSV) format. proprietary
WhiteSpruce_Leaf_Traits_Alaska_2124_1 ABoVE: White Spruce Photosynthetic and Leaf Traits, Alaska and New York, 2017 ALL STAC Catalog 2017-06-19 2017-07-20 -149.75, 41.4, -74.02, 67.99 https://cmr.earthdata.nasa.gov/search/concepts/C2636355463-ORNL_CLOUD.umm_json This dataset provides measurements of gas exchange (light response curves, Kok curves and ACi curves), leaf traits (carbon, nitrogen, and specific leaf area), leaf pigments (Chlorophyll a, Chlorophyll b and Carotenoids), the photochemical reflectance index (PRI), and average photosynthetic photon flux density as collected from hemispherical photographs. Data were collected on white spruce trees (Picea glauca (Moench) Voss) growing at the northern edge of the species' distribution in Alaska and at the southern edge of the species' distribution in Black Rock Forest (BRF), New York. Measurements were taken at high and low canopy positions on each tree at both sites during the 2017 growing season (2017-06-19 to 2017-07-20). Gas exchange, leaf trait, pigment and spectral measurements were obtained using a portable photosynthesis system (LI-6800, LI-COR, Lincoln, NE). Photochemical reflectance index was determined using a spectroradiometer, and hemispherical photographs were taken with a digital camera. These data were collected to better understand how vertical canopy gradients in photosynthetic physiology change from the southernmost to the northernmost range extremes of white spruce. The data are provided in comma-separated value (CSV) format. proprietary
-Wildfire_Effects_Spruce_Field_1595_1 ABoVE: Characterization of Burned and Unburned Spruce Forest Sites, Tanana, AK, 2017 ORNL_CLOUD STAC Catalog 2017-07-26 2017-07-28 -152.42, 65.1, -151.95, 65.23 https://cmr.earthdata.nasa.gov/search/concepts/C2162141870-ORNL_CLOUD.umm_json This dataset provides the results of field observations of soil characteristics and depth to permafrost, survey results for Composite Burn Index (CBI) determination, and Landsat-derived estimates of Relative Difference Normalized Burn Ratio (RdNBR) for 38 burned and unburned forest sites near Tanana, Alaska, in 2017. Forests in the study area, at the confluence of the Yukon and Tanana Rivers about 200 km west of Fairbanks, are predominately black spruce on wetter soils and white spruce on drier soils. The burned areas were from wildfires that occurred in the summer of 2015. proprietary
+WhiteSpruce_Leaf_Traits_Alaska_2124_1 ABoVE: White Spruce Photosynthetic and Leaf Traits, Alaska and New York, 2017 ORNL_CLOUD STAC Catalog 2017-06-19 2017-07-20 -149.75, 41.4, -74.02, 67.99 https://cmr.earthdata.nasa.gov/search/concepts/C2636355463-ORNL_CLOUD.umm_json This dataset provides measurements of gas exchange (light response curves, Kok curves and ACi curves), leaf traits (carbon, nitrogen, and specific leaf area), leaf pigments (Chlorophyll a, Chlorophyll b and Carotenoids), the photochemical reflectance index (PRI), and average photosynthetic photon flux density as collected from hemispherical photographs. Data were collected on white spruce trees (Picea glauca (Moench) Voss) growing at the northern edge of the species' distribution in Alaska and at the southern edge of the species' distribution in Black Rock Forest (BRF), New York. Measurements were taken at high and low canopy positions on each tree at both sites during the 2017 growing season (2017-06-19 to 2017-07-20). Gas exchange, leaf trait, pigment and spectral measurements were obtained using a portable photosynthesis system (LI-6800, LI-COR, Lincoln, NE). Photochemical reflectance index was determined using a spectroradiometer, and hemispherical photographs were taken with a digital camera. These data were collected to better understand how vertical canopy gradients in photosynthetic physiology change from the southernmost to the northernmost range extremes of white spruce. The data are provided in comma-separated value (CSV) format. proprietary
Wildfire_Effects_Spruce_Field_1595_1 ABoVE: Characterization of Burned and Unburned Spruce Forest Sites, Tanana, AK, 2017 ALL STAC Catalog 2017-07-26 2017-07-28 -152.42, 65.1, -151.95, 65.23 https://cmr.earthdata.nasa.gov/search/concepts/C2162141870-ORNL_CLOUD.umm_json This dataset provides the results of field observations of soil characteristics and depth to permafrost, survey results for Composite Burn Index (CBI) determination, and Landsat-derived estimates of Relative Difference Normalized Burn Ratio (RdNBR) for 38 burned and unburned forest sites near Tanana, Alaska, in 2017. Forests in the study area, at the confluence of the Yukon and Tanana Rivers about 200 km west of Fairbanks, are predominately black spruce on wetter soils and white spruce on drier soils. The burned areas were from wildfires that occurred in the summer of 2015. proprietary
+Wildfire_Effects_Spruce_Field_1595_1 ABoVE: Characterization of Burned and Unburned Spruce Forest Sites, Tanana, AK, 2017 ORNL_CLOUD STAC Catalog 2017-07-26 2017-07-28 -152.42, 65.1, -151.95, 65.23 https://cmr.earthdata.nasa.gov/search/concepts/C2162141870-ORNL_CLOUD.umm_json This dataset provides the results of field observations of soil characteristics and depth to permafrost, survey results for Composite Burn Index (CBI) determination, and Landsat-derived estimates of Relative Difference Normalized Burn Ratio (RdNBR) for 38 burned and unburned forest sites near Tanana, Alaska, in 2017. Forests in the study area, at the confluence of the Yukon and Tanana Rivers about 200 km west of Fairbanks, are predominately black spruce on wetter soils and white spruce on drier soils. The burned areas were from wildfires that occurred in the summer of 2015. proprietary
Wildfire_Impacts_Boreal_Ecosys_2359_1 Impacts of Wildfires on Boreal Forest Ecosystem Carbon Dynamics ORNL_CLOUD STAC Catalog 1986-01-01 2020-12-31 -166, 43.5, -53, 70 https://cmr.earthdata.nasa.gov/search/concepts/C3234724704-ORNL_CLOUD.umm_json This dataset contains simulations of net primary production (NPP), heterotrophic respiration (RH), net ecosystem production (NEP), and soil temperature data in North American boreal forests for the period 1986-2020. Data sources included historical fire sources and Landsat data. The delta Normalized Burn Ratio (dNBR), which can be used to represent burn severity for a fire, was calculated for each individual fire over the time period. The interactions between canopy, fire and soil thermal dynamics were modelled using a soil surface energy balance model incorporated into a previous Terrestrial Ecosystem Model (TEM). Using the revised TEM, two regional simulations were conducted with and without fire disturbance. Fire polygons were dissected into each unit with unique fire history and then intersected with each grid cell to measure fire impacts. The output values for each grid cell are the area-weighted mean of each fire polygon and unburned area within the cell. Two extra simulations without a canopy energy balance scheme were also conducted to quantify the impact of the canopy. Soil temperature was simulated with and without the canopy energy balance scheme in the model in addition to considering fire impacts. proprietary
-Wildfires_2014_NWT_Canada_1307_1 ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014 ORNL_CLOUD STAC Catalog 1997-07-07 2015-07-15 -121.6, 60.33, -110.68, 64.25 https://cmr.earthdata.nasa.gov/search/concepts/C2170968584-ORNL_CLOUD.umm_json This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites. proprietary
Wildfires_2014_NWT_Canada_1307_1 ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014 ALL STAC Catalog 1997-07-07 2015-07-15 -121.6, 60.33, -110.68, 64.25 https://cmr.earthdata.nasa.gov/search/concepts/C2170968584-ORNL_CLOUD.umm_json This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites. proprietary
+Wildfires_2014_NWT_Canada_1307_1 ABoVE: Burn Severity, Fire Progression, Landcover and Field Data, NWT, Canada, 2014 ORNL_CLOUD STAC Catalog 1997-07-07 2015-07-15 -121.6, 60.33, -110.68, 64.25 https://cmr.earthdata.nasa.gov/search/concepts/C2170968584-ORNL_CLOUD.umm_json This data set provides peatland landcover classification maps, fire progression maps, and vegetation community biophysical data collected from areas that were burned by wildfire in 2014 in the Northwest Territories, Canada. The peatland maps include peatland type (bog, fen, marsh, swamp) and level of biomass (open, forested). The fire progression maps enabled an assessment of wildfire progression rates at a daily time scale. Field data, collected in 2015, include an estimate of burn severity, woody seedling/sprouting data, soil moisture, and tree diameter and height of burned sites and similar vegetation characterization at landcover validation sites. proprietary
Wildfires_Date_of_Burning_1559_1.1 ABoVE: Wildfire Date of Burning within Fire Scars across Alaska and Canada, 2001-2019 ALL STAC Catalog 2001-01-01 2019-12-31 -178.84, 41.75, -53.83, 70.16 https://cmr.earthdata.nasa.gov/search/concepts/C2162122340-ORNL_CLOUD.umm_json This dataset provides estimates of wildfire progression represented by date of burning (DoB) within fire scars across Alaska and Canada for the period 2001-2019. Burn scar locations were obtained from two datasets: the Alaskan Interagency Coordination Center (AICC) and the Natural Resources Canada (NRC) databases. All scars within these databases were used in this study. The estimated DoB was derived using an algorithm for identifying the first fire occurrence from the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire detection product (MCD14ML, Collection 6) and to subsequently determine all dates of burning within fire scars. The DoB data are provided as polygons and map the daily progression of a fire within each burn scar. As a result, there is one polygon for each DoB detected within an identified burn scar boundary. The MODIS active fire points associated with the burn scar data are also provided. Data for the period 2001-2015 were first published in 2017 and data for the period 2016-2019 were added in January 2021. proprietary
Wildfires_Date_of_Burning_1559_1.1 ABoVE: Wildfire Date of Burning within Fire Scars across Alaska and Canada, 2001-2019 ORNL_CLOUD STAC Catalog 2001-01-01 2019-12-31 -178.84, 41.75, -53.83, 70.16 https://cmr.earthdata.nasa.gov/search/concepts/C2162122340-ORNL_CLOUD.umm_json This dataset provides estimates of wildfire progression represented by date of burning (DoB) within fire scars across Alaska and Canada for the period 2001-2019. Burn scar locations were obtained from two datasets: the Alaskan Interagency Coordination Center (AICC) and the Natural Resources Canada (NRC) databases. All scars within these databases were used in this study. The estimated DoB was derived using an algorithm for identifying the first fire occurrence from the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire detection product (MCD14ML, Collection 6) and to subsequently determine all dates of burning within fire scars. The DoB data are provided as polygons and map the daily progression of a fire within each burn scar. As a result, there is one polygon for each DoB detected within an identified burn scar boundary. The MODIS active fire points associated with the burn scar data are also provided. Data for the period 2001-2015 were first published in 2017 and data for the period 2016-2019 were added in January 2021. proprietary
Wildfires_NWT_Canada_1548_1 ABoVE: Burn Severity, Fire Progression, and Field Data, NWT, Canada, 2015-2016 ALL STAC Catalog 2015-05-20 2016-08-08 -135.54, 59.93, -106.76, 68.33 https://cmr.earthdata.nasa.gov/search/concepts/C2162122286-ORNL_CLOUD.umm_json This data set provides a fire progression map for year 2015 and measures of burn severity and vegetation community biophysical data collected from areas that were burned by wildfires in 2014 and 2015 in the Northwest Territories, Canada. Field data collected in 2016 include an estimate of burn severity, woody seedling/sprouting data, soil moisture, peat depth, thaw depth, and vegetation cover for selected sites. proprietary
Wildfires_NWT_Canada_1548_1 ABoVE: Burn Severity, Fire Progression, and Field Data, NWT, Canada, 2015-2016 ORNL_CLOUD STAC Catalog 2015-05-20 2016-08-08 -135.54, 59.93, -106.76, 68.33 https://cmr.earthdata.nasa.gov/search/concepts/C2162122286-ORNL_CLOUD.umm_json This data set provides a fire progression map for year 2015 and measures of burn severity and vegetation community biophysical data collected from areas that were burned by wildfires in 2014 and 2015 in the Northwest Territories, Canada. Field data collected in 2016 include an estimate of burn severity, woody seedling/sprouting data, soil moisture, peat depth, thaw depth, and vegetation cover for selected sites. proprietary
-Wildfires_NWT_Canada_2018_1703_1 ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2018 ORNL_CLOUD STAC Catalog 2018-08-12 2018-08-22 -117.43, 60.45, -113.42, 62.57 https://cmr.earthdata.nasa.gov/search/concepts/C2143403376-ORNL_CLOUD.umm_json This dataset provides vegetation community characteristics and biophysical data collected in 2018 from areas that were burned by wildfire in 2014 and 2015, and from nine unburned validation sites in the Northwest Territories, Canada. The data include vegetation inventories, ground cover, regrowth, tree diameter and height, and woody seedling/sprouting data at burned sites, and similar vegetation community characterization at unburned validation sites. Additional measurements included soil moisture, collected for validation of the UAVSAR airborne collection, and depth to frozen ground at the nine unburned sites. This 2018 fieldwork completes four years of field sampling at the wildfire areas. proprietary
Wildfires_NWT_Canada_2018_1703_1 ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2018 ALL STAC Catalog 2018-08-12 2018-08-22 -117.43, 60.45, -113.42, 62.57 https://cmr.earthdata.nasa.gov/search/concepts/C2143403376-ORNL_CLOUD.umm_json This dataset provides vegetation community characteristics and biophysical data collected in 2018 from areas that were burned by wildfire in 2014 and 2015, and from nine unburned validation sites in the Northwest Territories, Canada. The data include vegetation inventories, ground cover, regrowth, tree diameter and height, and woody seedling/sprouting data at burned sites, and similar vegetation community characterization at unburned validation sites. Additional measurements included soil moisture, collected for validation of the UAVSAR airborne collection, and depth to frozen ground at the nine unburned sites. This 2018 fieldwork completes four years of field sampling at the wildfire areas. proprietary
-Wildfires_NWT_Canada_2019_1900_1 ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2019 ORNL_CLOUD STAC Catalog 2018-08-16 2019-09-05 -117.43, 60.92, -113.02, 62.57 https://cmr.earthdata.nasa.gov/search/concepts/C2445465291-ORNL_CLOUD.umm_json This dataset provides vegetation community characteristics, soil moisture, and biophysical data collected in 2019 from 11 study areas, which contained 28 sites that were burned by wildfires in 2014 and 2015, and 14 unburned sites in the Northwest Territories (NWT), Canada. Burn sites included peatland and upland. These field data include vegetation inventories, ground cover, as well as diameter and height for trees and shrubs in the unburned sites. Similar data were collected for the unburned sites in the years 2015-18 and are available in related separate datasets. In 2019, the focus was on woody and non-woody seedling/sprouting regrowth data in the burned sites. Additional measurements collected at all sites included total peat depth, soil moisture, and active layer thickness (ALT). Soil moisture and ALT were collected for validation of the UAVSAR airborne collection and Radarsat-2 overpasses. This 2019 fieldwork completes five years of field sampling at the wildfire areas. proprietary
+Wildfires_NWT_Canada_2018_1703_1 ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2018 ORNL_CLOUD STAC Catalog 2018-08-12 2018-08-22 -117.43, 60.45, -113.42, 62.57 https://cmr.earthdata.nasa.gov/search/concepts/C2143403376-ORNL_CLOUD.umm_json This dataset provides vegetation community characteristics and biophysical data collected in 2018 from areas that were burned by wildfire in 2014 and 2015, and from nine unburned validation sites in the Northwest Territories, Canada. The data include vegetation inventories, ground cover, regrowth, tree diameter and height, and woody seedling/sprouting data at burned sites, and similar vegetation community characterization at unburned validation sites. Additional measurements included soil moisture, collected for validation of the UAVSAR airborne collection, and depth to frozen ground at the nine unburned sites. This 2018 fieldwork completes four years of field sampling at the wildfire areas. proprietary
Wildfires_NWT_Canada_2019_1900_1 ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2019 ALL STAC Catalog 2018-08-16 2019-09-05 -117.43, 60.92, -113.02, 62.57 https://cmr.earthdata.nasa.gov/search/concepts/C2445465291-ORNL_CLOUD.umm_json This dataset provides vegetation community characteristics, soil moisture, and biophysical data collected in 2019 from 11 study areas, which contained 28 sites that were burned by wildfires in 2014 and 2015, and 14 unburned sites in the Northwest Territories (NWT), Canada. Burn sites included peatland and upland. These field data include vegetation inventories, ground cover, as well as diameter and height for trees and shrubs in the unburned sites. Similar data were collected for the unburned sites in the years 2015-18 and are available in related separate datasets. In 2019, the focus was on woody and non-woody seedling/sprouting regrowth data in the burned sites. Additional measurements collected at all sites included total peat depth, soil moisture, and active layer thickness (ALT). Soil moisture and ALT were collected for validation of the UAVSAR airborne collection and Radarsat-2 overpasses. This 2019 fieldwork completes five years of field sampling at the wildfire areas. proprietary
+Wildfires_NWT_Canada_2019_1900_1 ABoVE: Post-Fire and Unburned Vegetation Community and Field Data, NWT, Canada, 2019 ORNL_CLOUD STAC Catalog 2018-08-16 2019-09-05 -117.43, 60.92, -113.02, 62.57 https://cmr.earthdata.nasa.gov/search/concepts/C2445465291-ORNL_CLOUD.umm_json This dataset provides vegetation community characteristics, soil moisture, and biophysical data collected in 2019 from 11 study areas, which contained 28 sites that were burned by wildfires in 2014 and 2015, and 14 unburned sites in the Northwest Territories (NWT), Canada. Burn sites included peatland and upland. These field data include vegetation inventories, ground cover, as well as diameter and height for trees and shrubs in the unburned sites. Similar data were collected for the unburned sites in the years 2015-18 and are available in related separate datasets. In 2019, the focus was on woody and non-woody seedling/sprouting regrowth data in the burned sites. Additional measurements collected at all sites included total peat depth, soil moisture, and active layer thickness (ALT). Soil moisture and ALT were collected for validation of the UAVSAR airborne collection and Radarsat-2 overpasses. This 2019 fieldwork completes five years of field sampling at the wildfire areas. proprietary
Willow_Veg_Plots_1368_1 Arctic Vegetation Plots in Willow Communities, North Slope, Alaska, 1997 ORNL_CLOUD STAC Catalog 1997-07-09 1997-08-17 -149.85, 68.03, -148.08, 70.19 https://cmr.earthdata.nasa.gov/search/concepts/C2170969823-ORNL_CLOUD.umm_json This data set provides environmental, soil, and vegetation data collected in July and August 1997 from 85 study plots in willow shrub communities located along a north-south transect from the Brooks Range to Prudhoe Bay on the North Slope of Alaska. Data includes the baseline plot information for vegetation, soils, and site factors for the study plots subjectively located in three broad habitat types across the glaciated landscape. Specific attributes include: dominant vegetation species, cover, indices, and biomass pools; soil chemistry, physical characteristics, moisture, and organic matter. This product brings together for easy reference all the available information collected from the plots that has been used for the classification, mapping, and analysis of geobotanical factors in the region and across Alaska. proprietary
WindSat-REMSS-L3U-v7.0.1a_7.0.1a GHRSST Level 3U Global Subskin Sea Surface Temperature version7.0.1a from the WindSat Polarimetric Radiometer on the Coriolis satellite POCLOUD STAC Catalog 2002-06-01 2020-10-19 -179.99, -39.06, 180, 39.01 https://cmr.earthdata.nasa.gov/search/concepts/C2036878925-POCLOUD.umm_json "The WindSat Polarimetric Radiometer, launched on January 6, 2003 aboard the Department of Defense Coriolis satellite, was designed to measure the ocean surface wind vector from space. It developed by the Naval Research Laboratory (NRL) Remote Sensing Division and the Naval Center for Space Technology for the U.S. Navy and the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Integrated Program Office (IPO). In addition to wind speed and direction, the instrument can also measure sea surface temperature, soil moisture, ice and snow characteristics, water vapor, cloud liquid water, and rain rate. Unlike previous radiometers, the WindSat sensor takes observations during both the forward and aft looking scans. This makes the WindSat geometry of the earth view swath quite different and significantly more complicated to work with than the other passive microwave sensors. The Remote Sensing Systems (RSS, or REMSS) WindSat products are the only dataset available that uses both the fore and aft look directions. By using both directions, a wider swath and more complicated swath geometry is obtained. RSS providers of these SST data for the Group for High Resolution Sea Surface Temperature (GHRSST) Project, performs a detailed processing of WindSat instrument data in two stages. The first stage produces a near-real-time (NRT) product (identified by ""rt"" within the file name) which is made as available as soon as possible. This is generally within 3 hours of when the data are recorded. Although suitable for many timely uses the NRT products are not intended to be archive quality. ""Final"" data (currently identified by ""v7.0.1a"" within the file name) are processed when RSS receives the atmospheric mode NCEP FNL analysis. The NCEP wind directions are particularly useful for retrieving more accurate SSTs and wind speeds. The final ""v7.0.1a"" products will continue to accumulate new swaths (half orbits) until the maps are full, generally within 7 days. The version with letter ""a"" refers to the file incompliance with GHRSST format." proprietary
-Wolves_Denning_Pups_Climate_1846_1 ABoVE: Wolf Denning Phenology and Reproductive Success, Alaska and Canada, 2000-2017 ALL STAC Catalog 2000-03-29 2017-08-31 -154.58, 52.97, -112.97, 67.84 https://cmr.earthdata.nasa.gov/search/concepts/C2143401778-ORNL_CLOUD.umm_json This dataset provides annual gray wolf (Canis lupus) denning spatial information and timing, associated climatic and phenologic metrics, and reproductive success (i.e., pup survival) in wolf populations across areas of western Canada and Alaska within the NASA ABoVE Core Domain. The study encompasses 18 years between the period 2000-2017. Wolves were captured from eight populations following standard animal care protocols and released with Global Positioning System (GPS) collars. Data from 388 wolves were used to estimate den initiation dates (n=227 dens of 106 packs) and reproductive success in the eight populations. Each population was monitored from 1 to 12 years between 2000 and 2017. Denning parturition phenology was measured each year as the number of calendar days from January 1st to the initiation date of each documented denning event. Reproductive success was determined as to whether pups survived through the end of August following a reproductive event. To evaluate the effect of climate factors on reproductive phenology, aggregated seasonal climate metrics for temperature, precipitation, and snow water equivalent based on three biological seasons for seasonal wolf home ranges were produced. Normalized Difference Vegetation Index (NDVI) time-series data were used to estimate phenological metrics such as the start of the growing season (SOS), length of the growing season (LOS), and time-integrated NDVI (tiNDVI), and were summarized for the populations' home range. proprietary
Wolves_Denning_Pups_Climate_1846_1 ABoVE: Wolf Denning Phenology and Reproductive Success, Alaska and Canada, 2000-2017 ORNL_CLOUD STAC Catalog 2000-03-29 2017-08-31 -154.58, 52.97, -112.97, 67.84 https://cmr.earthdata.nasa.gov/search/concepts/C2143401778-ORNL_CLOUD.umm_json This dataset provides annual gray wolf (Canis lupus) denning spatial information and timing, associated climatic and phenologic metrics, and reproductive success (i.e., pup survival) in wolf populations across areas of western Canada and Alaska within the NASA ABoVE Core Domain. The study encompasses 18 years between the period 2000-2017. Wolves were captured from eight populations following standard animal care protocols and released with Global Positioning System (GPS) collars. Data from 388 wolves were used to estimate den initiation dates (n=227 dens of 106 packs) and reproductive success in the eight populations. Each population was monitored from 1 to 12 years between 2000 and 2017. Denning parturition phenology was measured each year as the number of calendar days from January 1st to the initiation date of each documented denning event. Reproductive success was determined as to whether pups survived through the end of August following a reproductive event. To evaluate the effect of climate factors on reproductive phenology, aggregated seasonal climate metrics for temperature, precipitation, and snow water equivalent based on three biological seasons for seasonal wolf home ranges were produced. Normalized Difference Vegetation Index (NDVI) time-series data were used to estimate phenological metrics such as the start of the growing season (SOS), length of the growing season (LOS), and time-integrated NDVI (tiNDVI), and were summarized for the populations' home range. proprietary
+Wolves_Denning_Pups_Climate_1846_1 ABoVE: Wolf Denning Phenology and Reproductive Success, Alaska and Canada, 2000-2017 ALL STAC Catalog 2000-03-29 2017-08-31 -154.58, 52.97, -112.97, 67.84 https://cmr.earthdata.nasa.gov/search/concepts/C2143401778-ORNL_CLOUD.umm_json This dataset provides annual gray wolf (Canis lupus) denning spatial information and timing, associated climatic and phenologic metrics, and reproductive success (i.e., pup survival) in wolf populations across areas of western Canada and Alaska within the NASA ABoVE Core Domain. The study encompasses 18 years between the period 2000-2017. Wolves were captured from eight populations following standard animal care protocols and released with Global Positioning System (GPS) collars. Data from 388 wolves were used to estimate den initiation dates (n=227 dens of 106 packs) and reproductive success in the eight populations. Each population was monitored from 1 to 12 years between 2000 and 2017. Denning parturition phenology was measured each year as the number of calendar days from January 1st to the initiation date of each documented denning event. Reproductive success was determined as to whether pups survived through the end of August following a reproductive event. To evaluate the effect of climate factors on reproductive phenology, aggregated seasonal climate metrics for temperature, precipitation, and snow water equivalent based on three biological seasons for seasonal wolf home ranges were produced. Normalized Difference Vegetation Index (NDVI) time-series data were used to estimate phenological metrics such as the start of the growing season (SOS), length of the growing season (LOS), and time-integrated NDVI (tiNDVI), and were summarized for the populations' home range. proprietary
WorldView-1.full.archive.and.tasking_8.0 WorldView-1 full archive and tasking ESA STAC Catalog 2007-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336959-ESA.umm_json "WorldView-1 high resolution optical products are available as part of the Maxar Standard Satellite Imagery products from the QuickBird, WorldView-1/-2/-3/-4, and GeoEye-1 satellites. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section. In particular, WorldView-1 offers archive and tasking panchromatic products up to 0.50 m GSD resolution. Band Combination Data Processing Level Resolution Panchromatic Standard(2A)/View Ready STANDARD (OR2A) 50 cm, 30 cm HD View Ready Stereo 50 cm Map-Ready (Ortho) 1:12.000 Orthorectified 50 cm, 30 cm HD Native 50 cm resolution products are processed with MAXAR HD Technology to generate the 30 cm HD products: the initial special resolution (GSD) is unchanged but the HD technique increases the number of pixels and improves the visual clarity achieving aesthetically refined imagery with precise edges and well reconstructed details. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
WorldView-2.European.Cities_10.0 WorldView-2 European Cities ESA STAC Catalog 2010-07-20 2015-07-19 -19, -26, 35, 66 https://cmr.earthdata.nasa.gov/search/concepts/C1965336961-ESA.umm_json ESA, in collaboration with European Space Imaging, has collected this WorldView-2 dataset covering the most populated areas in Europe at 40 cm resolution. The products have been acquired between July 2010 and July 2015. proprietary
WorldView-2.full.archive.and.tasking_8.0 WorldView-2 full archive and tasking ESA STAC Catalog 2009-11-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336963-ESA.umm_json "WorldView-2 high resolution optical products are available as part of the Maxar Standard Satellite Imagery products from the QuickBird, WorldView-1/-2/-3/-4, and GeoEye-1 satellites. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section. In particular, WorldView-2 offers archive and tasking panchromatic products up to 0.46 m GSD resolution, and 4-Bands/8-Bands Multispectral products up to 1.84 m GSD resolution. Band Combination Data Processing Level Resolution Panchromatic and 4-bands Standard (2A)/View Ready Standard (OR2A) 15 cm HD, 30 cm HD, 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map-Ready (Ortho) 1:12.000 Orthorectified 15 cm HD, 30 cm HD, 30 cm, 40 cm, 50/60 cm 8-bands Standard(2A)/View Ready Standard (OR2A) 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map-Ready (Ortho) 1:12.000 Orthorectified 30 cm, 40 cm, 50/60 cm 4-Bands being an optional from: 4-Band Multispectral (BLUE, GREEN, RED, NIR1) 4-Band Pan-sharpened (BLUE, GREEN, RED, NIR1) 4-Band Bundle (PAN, BLUE, GREEN, RED, NIR1) 3-Bands Natural Colour (pan-sharpened BLUE, GREEN, RED) 3-Band Colored Infrared (pan-sharpened GREEN, RED, NIR1). 8-Bands being an optional from: 8-Band Multispectral (COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2) 8-Band Bundle (PAN, COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2). Native 30 cm and 50/60 cm resolution products are processed with MAXAR HD Technology to generate respectively the 15 cm HD and 30 cm HD products: the initial special resolution (GSD) is unchanged but the HD technique increases the number of pixels, improves the visual clarity and allows to obtain an aesthetically refined imagery with precise edges and well reconstructed details. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
WorldView-3.full.archive.and.tasking_8.0 WorldView-3 full archive and tasking ESA STAC Catalog 2014-09-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336965-ESA.umm_json "WorldView-3 high resolution optical products are available as part of the Maxar Standard Satellite Imagery products from the QuickBird, WorldView-1/-2/-3/-4, and GeoEye-1 satellites. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section. In particular, WorldView-3 offers archive and tasking panchromatic products up to 0.31m GSD resolution, 4-Bands/8-Bands products up to 1.24 m GSD resolution, and SWIR products up to 3.70 m GSD resolution. Band Combination Data Processing Level Resolution High Res Optical: Panchromatic and 4-bands Standard(2A)/View Ready Standard (OR2A) 15 cm HD, 30 cm HD, 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map Ready (Ortho) 1:12.000 Orthorectified 15 cm HD, 30 cm HD, 30 cm, 40 cm, 50/60 cm High Res Optical: 8-bands Standard(2A)/View Ready Standard (OR2A) 30 cm, 40 cm, 50/60 cm View Ready Stereo 30 cm, 40 cm, 50/60 cm Map Ready (Ortho) 1:12.000 Orthorectified 30 cm, 40 cm, 50/60 cm High Res Optical: SWIR Standard(2A)/View Ready Standard (OR2A) 3.7 m or 7.5 m (depending on the collection date) Map Ready (Ortho) 1:12.000 Orthorectified 4-Bands being an optional from: 4-Band Multispectral (BLUE, GREEN, RED, NIR1) 4-Band Pan-sharpened (BLUE, GREEN, RED, NIR1) 4-Band Bundle (PAN, BLUE, GREEN, RED, NIR1) 3-Bands Natural Colour (pan-sharpened BLUE, GREEN, RED) 3-Band Colored Infrared (pan-sharpened GREEN, RED, NIR1) 8-Bands being an optional from: 8-Band Multispectral (COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2) 8-Band Bundle (PAN, COASTAL, BLUE, GREEN, YELLOW, RED, RED EDGE, NIR1, NIR2) Native 30 cm and 50/60 cm resolution products are processed with MAXAR HD Technology to generate respectively the 15 cm HD and 30 cm HD products: the initial special resolution (GSD) is unchanged but the HD technique increases the number of pixels and improves the visual clarity achieving aesthetically refined imagery with precise edges and well reconstructed details. As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
WorldView-4.full.archive_7.0 WorldView-4 full archive ESA STAC Catalog 2016-12-01 2019-01-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2547572305-ESA.umm_json WorldView-4 high resolution optical products are available as part of the Maxar Standard Satellite Imagery products from the QuickBird, WorldView-1/-2/-3/-4, and GeoEye-1 satellites. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section. In particular, WorldView-4 offers archive panchromatic products up to 0.31m GSD resolution, and 4-Bands Multispectral products up to 1.24m GSD resolution Band Combination: Panchromatic and 4-bands Data Processing Level: STANDARD (2A) / VIEW READY STANDARD (OR2A), VIEW READY STEREO, MAP-READY (ORTHO) 1:12.000 Orthorectified Resolutions: 0.30 m, 0.40 m, 0.50 m. 0.60 m The options for 4-Bands are the following: • 4-Band Multispectral (BLUE, GREEN, RED, NIR1) • 4-Band Pan-sharpened (BLUE, GREEN, RED, NIR1) • 4-Band Bundle (PAN, BLUE, GREEN, RED, NIR1) • 3-Bands Natural Colour (pan-sharpened BLUE, GREEN, RED) • 3-Band Colored Infrared (pan-sharpened GREEN, RED, NIR1) The list of available archived data can be retrieved using the Image Library (https://www.euspaceimaging.com/image-library/) catalogue. proprietary
WorldView.ESA.archive_9.0 WorldView ESA archive ESA STAC Catalog 2009-02-07 2020-12-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689694-ESA.umm_json "The WorldView ESA archive is composed of products acquired by WorldView-1, -2, -3 and -4 satellites and requested by ESA supported projects over their areas of interest around the world Panchromatic, 4-Bands, 8-Bands and SWIR products are part of the offer, with the resolution at Nadir depicted in the table. Band Combination Mission GSD Resolution at Nadir GSD Resolution (20° off nadir) Panchromatic WV-1 50 cm 55 cm WV-2 46 cm 52 cm WV-3 31 cm 34 cm WV-4 31 cm 34 cm 4-Bands WV-2 1.84 m 2.4 m WV-3 1.24 m 1.38 m WV-4 1.24 m 1.38 m 8-Bands WV-2 1.84 m 2.4 m WV-3 1.24 m 1.38 m SWIR WV-3 3.70 m 4.10 m The 4-Bands includes various options such as Multispectral (separate channel for Blue, Green, Red, NIR1), Pan-sharpened (Blue, Green, Red, NIR1), Bundle (separate bands for PAN, Blue, Green, Red, NIR1), Natural Colour (pan-sharpened Blue, Green, Red), Coloured Infrared (pan-sharpened Green, Red, NIR). The 8-Bands being an option from Multispectral (COASTAL, Blue, Green, Yellow, Red, Red EDGE, NIR1, NIR2) and Bundle (PAN, COASTAL, Blue, Green, Yellow, Red, Red EDGE, NIR1, NIR2). The processing levels are: Standard (2A): normalised for topographic relief View Ready Standard: ready for orthorectification (RPB files embedded) View Ready Stereo: collected in-track for stereo viewing and manipulation (not available for SWIR) Map Scale (Ortho) 1:12,000 Orthorectified: additional processing unnecessary Spatial coverage: Check the spatial coverage of the collection on a _$$map$$ https://tpm-ds.eo.esa.int/smcat/WorldView/ available on the Third Party Missions Dissemination Service. The following table summarises the offered product types EO-SIP Product Type Band Combination Processing Level Missions WV6_PAN_2A Panchromatic (PAN) Standard/View Ready Standard WorldView-1 and 4 WV6_PAN_OR Panchromatic (PAN) View Ready Stereo WorldView-1 and 4 WV6_PAN_MP Panchromatic (PAN) Map Scale Ortho WorldView-1 and 4 WV1_PAN__2A Panchromatic (PAN) Standard/View Ready Standard WorldView-2 and 3 WV1_PAN__OR Panchromatic (PAN) View Ready Stereo WorldView-2 and 3 WV1_PAN__MP Panchromatic (PAN) Map Scale Ortho WorldView-2 and 3 WV1_4B__2A 4-Band (4B) Standard/View Ready Standard WorldView-2, 3 and 4 WV1_4B__OR 4-Band (4B) View Ready Stereo WorldView-2, 3 and 4 WV1_4B__MP 4-Band (4B) Map Scale Ortho WorldView-2, 3 and 4 WV1_8B_2A 8-Band (8B) Standard/View Ready Standard WorldView-2 and 3 WV1_8B_OR 8-Band (8B) View Ready Stereo WorldView-2 and 3 WV1_8B_MP 8-Band (8B) Map Scale Ortho WorldView-2 and 3 WV1_S8B__2A SWIR Standard/View Ready Standard WorldView-3 WV1_S8B__MP SWIR Map Scale Ortho WorldView-3 As per ESA policy, very high-resolution imagery of conflict areas cannot be provided." proprietary
-XAERDT_L2_ABI_G16_1 ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2019-01-01 2023-01-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859273114-LAADS.umm_json The ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G16 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-16 has been serving in the operational GOES-East position (near -75°W) since December 18, 2017. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G16 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G16 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G16 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_ABI_G16_1 ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS STAC Catalog 2019-01-01 2023-01-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859273114-LAADS.umm_json The ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G16 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-16 has been serving in the operational GOES-East position (near -75°W) since December 18, 2017. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G16 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G16 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G16 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
-XAERDT_L2_ABI_G17_1 ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS STAC Catalog 2019-01-01 2023-01-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859265967-LAADS.umm_json The ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G17 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-17 served in the operational GOES-West position (near -137°W), from February 12, 2019, through January 4, 2023. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G17 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G17 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G17 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
+XAERDT_L2_ABI_G16_1 ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2019-01-01 2023-01-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859273114-LAADS.umm_json The ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G16 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-16 has been serving in the operational GOES-East position (near -75°W) since December 18, 2017. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G16 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G16 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G16 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_ABI_G17_1 ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2019-01-01 2023-01-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859265967-LAADS.umm_json The ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G17 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-17 served in the operational GOES-West position (near -137°W), from February 12, 2019, through January 4, 2023. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G17 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G17 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G17 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
-XAERDT_L2_AHI_H08_1 AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859255251-LAADS.umm_json The AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H08 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-8 platform served in the operational Himawari position (near 140.7°E) between October 2014 and 13 December 2022. Himawari-9 replaced Himawari-8 and is currently operational. The Himawari-8/AHI collection record spans from January 2019 through 12th December 2022. The final 19 days of 2022 (December 13 through 31) are served by L2 products derived from the Himawari-9/AHI instrument. The XAERDT_L2_AHI_H08 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H08 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H08 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
+XAERDT_L2_ABI_G17_1 ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS STAC Catalog 2019-01-01 2023-01-02 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859265967-LAADS.umm_json The ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G17 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-17 served in the operational GOES-West position (near -137°W), from February 12, 2019, through January 4, 2023. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G17 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G17 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G17 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_AHI_H08_1 AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS STAC Catalog 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859255251-LAADS.umm_json The AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H08 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-8 platform served in the operational Himawari position (near 140.7°E) between October 2014 and 13 December 2022. Himawari-9 replaced Himawari-8 and is currently operational. The Himawari-8/AHI collection record spans from January 2019 through 12th December 2022. The final 19 days of 2022 (December 13 through 31) are served by L2 products derived from the Himawari-9/AHI instrument. The XAERDT_L2_AHI_H08 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H08 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H08 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
-XAERDT_L2_AHI_H09_1 AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2022-12-13 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859261579-LAADS.umm_json The AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H09 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-9 platform currently serves in the operational Himawari position (near 140.7°E) since it was launched November 2, 2016, and replaces Himawari-8. The Himawari-9/AHI collection record spans from 13th December 2022 through 31st December 2022. The XAERDT_L2_AHI_H09 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H09 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H09 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
+XAERDT_L2_AHI_H08_1 AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859255251-LAADS.umm_json The AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H08 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-8 platform served in the operational Himawari position (near 140.7°E) between October 2014 and 13 December 2022. Himawari-9 replaced Himawari-8 and is currently operational. The Himawari-8/AHI collection record spans from January 2019 through 12th December 2022. The final 19 days of 2022 (December 13 through 31) are served by L2 products derived from the Himawari-9/AHI instrument. The XAERDT_L2_AHI_H08 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H08 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H08 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_AHI_H09_1 AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS STAC Catalog 2022-12-13 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859261579-LAADS.umm_json The AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H09 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-9 platform currently serves in the operational Himawari position (near 140.7°E) since it was launched November 2, 2016, and replaces Himawari-8. The Himawari-9/AHI collection record spans from 13th December 2022 through 31st December 2022. The XAERDT_L2_AHI_H09 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H09 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H09 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
+XAERDT_L2_AHI_H09_1 AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km ALL STAC Catalog 2022-12-13 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859261579-LAADS.umm_json The AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H09 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-9 platform currently serves in the operational Himawari position (near 140.7°E) since it was launched November 2, 2016, and replaces Himawari-8. The Himawari-9/AHI collection record spans from 13th December 2022 through 31st December 2022. The XAERDT_L2_AHI_H09 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H09 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H09 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_MODIS_Aqua_1 MODIS/Aqua Dark Target Aerosol 5-Min L2 Swath 10 km LAADS STAC Catalog 2019-01-01 2023-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859238768-LAADS.umm_json The MODIS/Aqua Dark Target Aerosol 5-Min L2 Swath 10 km product, short-name XAERDT_L2_MODIS_Aqua is provided at 10-km spatial resolution (at-nadir) and a 5-minute cadence that typically yields about 140 granules over the daylit hours of a 24-hour period. The Aqua/MODIS L2 collection record spans from January 2019 through December 2022. The XAERDT_L2_MODIS_Aqua product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_MODIS_Aqua product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_MODIS_Aqua Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_MODIS_Terra_1 MODIS/Terra Dark Target Aerosol 5-Min L2 Swath 10 km LAADS STAC Catalog 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859248304-LAADS.umm_json The MODIS/Terra Dark Target Aerosol 5-Min L2 Swath 10 km product, short-name XAERDT_L2_MODIS_Terra is provided at 10-km spatial resolution (at-nadir) and a 5-minute cadence that typically yields about 140 granules over the daylit hours of a 24-hour period. The Terra/MODIS L2 collection record spans from January 2019 through December 2022. The XAERDT_L2_MODIS_Terra product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_MODIS_Terra product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_MODIS_Terra Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_VIIRS_NOAA20_1 VIIRS/NOAA20 Dark Target Aerosol L2 6-Min Swath 6 km LAADS STAC Catalog 2019-01-01 2023-05-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859228520-LAADS.umm_json The VIIRS/NOAA20 L2 Dark Target Aerosol 6-Min L2 Swath 6 km product, short-name XAERDT_L2_VIIRS_NOAA20 is provided at 6-km spatial resolution (at-nadir) and a 6-minute cadence that typically yields about 130 granules over the daylit hours of a 24-hour period. The NOAA20/VIIRS L2 collection record spans from January 2019 through December 2022. The XAERDT_L2_VIIRS_NOAA20 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_VIIRS_NOAA20 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_VIIRS_NOAA20 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
XAERDT_L2_VIIRS_SNPP_1 VIIRS/SNPP Dark Target Aerosol L2 6-Min Swath 6km LAADS STAC Catalog 2019-01-01 2023-05-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859232902-LAADS.umm_json The SNPP/VIIRS L2 Dark Target Aerosol 6-Min L2 Swath 6 km product, short-name XAERDT_L2_VIIRS_SNPP is provided at 6-km spatial resolution (at-nadir) and a 6-minute cadence that typically yields about 130 granules over the daylit hours of a 24-hour period. The SNPP/VIIRS L2 collection record spans from January 2019 through December 2022. The XAERDT_L2_VIIRS_SNPP product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_VIIRS_SNPP product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_VIIRS_SNPP Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ proprietary
Xingu_Albedo_Radiation_1622_1 Net Radiation and Albedo from MODIS for Xingu River Basin, Brazil, 2000-2012 ORNL_CLOUD STAC Catalog 2000-02-18 2012-11-16 -55.69, -15.07, -51.23, -9.57 https://cmr.earthdata.nasa.gov/search/concepts/C2764687115-ORNL_CLOUD.umm_json This dataset provides daily average land surface net radiation (Rnet) as an 8-day time series at approximately 0.5 km resolution for the upper Xingu River Basin in Mato Grosso, Brazil, from 2000-02-18 to 2012-11-16. The parameters needed to calculate Rnet, including albedo, downward shortwave radiation (RSnet), upward longwave radiation (RLnet[up]) and downward longwave radiation (RLnet[down]) were derived from MODIS products (MOD43A3, MOD11A2, MOD08E3) and local weather station data. Parameters were estimated under all sky conditions. These parameters are also provided for the Xingu Basin but at varying spatial and temporal resolutions. proprietary
-YKDelta_EnvChange_InfoExchange_1894_1 Alaska's Changing YK Delta: Knowledge Exchange between Elders and Geoscientists, 2018 ALL STAC Catalog 2018-11-14 2018-11-16 -166.55, 59.58, -159.48, 63.43 https://cmr.earthdata.nasa.gov/search/concepts/C2170972782-ORNL_CLOUD.umm_json This dataset provides a booklet documenting the discussions and outcomes from a knowledge-exchange meeting with Yup'ik elders from the Yukon-Kuskokwim Delta (YKD), western Alaska, community members, and natural scientist to discuss landscape and weather changes that have been observed in their homelands. The meeting was held during November 14-16, 2018. Yup'ik participants represented several YKD villages that occupy very different biophysical environments, and they have lifelong perspectives of environmental conditions and change that predate the era of Earth-observing satellites by many decades. Nearly 16 hours of discussion and testimonials from YKD elders were recorded during the meeting. The booklet is structured according to the environmental change processes that were discussed (e.g., coastal flooding, permafrost thaw, shrub expansion, climate change) and includes narrative summaries, quotations from participants, graphical illustrations, and examples of the field- and remote-sensing-based scientific findings, and map products developed as part of the larger ABoVE project. proprietary
YKDelta_EnvChange_InfoExchange_1894_1 Alaska's Changing YK Delta: Knowledge Exchange between Elders and Geoscientists, 2018 ORNL_CLOUD STAC Catalog 2018-11-14 2018-11-16 -166.55, 59.58, -159.48, 63.43 https://cmr.earthdata.nasa.gov/search/concepts/C2170972782-ORNL_CLOUD.umm_json This dataset provides a booklet documenting the discussions and outcomes from a knowledge-exchange meeting with Yup'ik elders from the Yukon-Kuskokwim Delta (YKD), western Alaska, community members, and natural scientist to discuss landscape and weather changes that have been observed in their homelands. The meeting was held during November 14-16, 2018. Yup'ik participants represented several YKD villages that occupy very different biophysical environments, and they have lifelong perspectives of environmental conditions and change that predate the era of Earth-observing satellites by many decades. Nearly 16 hours of discussion and testimonials from YKD elders were recorded during the meeting. The booklet is structured according to the environmental change processes that were discussed (e.g., coastal flooding, permafrost thaw, shrub expansion, climate change) and includes narrative summaries, quotations from participants, graphical illustrations, and examples of the field- and remote-sensing-based scientific findings, and map products developed as part of the larger ABoVE project. proprietary
+YKDelta_EnvChange_InfoExchange_1894_1 Alaska's Changing YK Delta: Knowledge Exchange between Elders and Geoscientists, 2018 ALL STAC Catalog 2018-11-14 2018-11-16 -166.55, 59.58, -159.48, 63.43 https://cmr.earthdata.nasa.gov/search/concepts/C2170972782-ORNL_CLOUD.umm_json This dataset provides a booklet documenting the discussions and outcomes from a knowledge-exchange meeting with Yup'ik elders from the Yukon-Kuskokwim Delta (YKD), western Alaska, community members, and natural scientist to discuss landscape and weather changes that have been observed in their homelands. The meeting was held during November 14-16, 2018. Yup'ik participants represented several YKD villages that occupy very different biophysical environments, and they have lifelong perspectives of environmental conditions and change that predate the era of Earth-observing satellites by many decades. Nearly 16 hours of discussion and testimonials from YKD elders were recorded during the meeting. The booklet is structured according to the environmental change processes that were discussed (e.g., coastal flooding, permafrost thaw, shrub expansion, climate change) and includes narrative summaries, quotations from participants, graphical illustrations, and examples of the field- and remote-sensing-based scientific findings, and map products developed as part of the larger ABoVE project. proprietary
Young_Russian_Forest_Map_1330_1 Distribution of Young Forests and Estimated Stand Age across Russia, 2012 ORNL_CLOUD STAC Catalog 2012-01-01 2012-12-31 -180, 32.86, 180, 87.24 https://cmr.earthdata.nasa.gov/search/concepts/C2773252554-ORNL_CLOUD.umm_json This data set provides the distribution of young forests (forests less than 27 years of age) and their estimated stand ages across the full extent of Russia at 500-m resolution for the year 2012. The distribution of young forests was modeled with MODIS 500-m records for 12- to 27-year-old forests and augmented with the 0- to 11-year-old forest distribution as aggregated from 30 m resolution contemporary Landsat imagery. proprietary
-ZZZ302 Alabama Remote Sensing Archive Multispectral Imagery of Alabama from Landsat and Skylab SCIOPS STAC Catalog 1972-01-01 1984-01-01 -92, 24, -80, 35 https://cmr.earthdata.nasa.gov/search/concepts/C1214584460-SCIOPS.umm_json Multispectral imagery of the state of Alabama is available from the Geological Survey of Alabama for the time period of 1972-1984. Imagery from the Landsat multispectral scanner (MSS) is available as prints or transparencies for all bands (with selected color composites avaliable) at an approximate scale of 1:1,000,000. MSS data is collected in four spectral bands ranging from 0.5 to 1.1 micrometer with a ground resolution of about 80m. Images available from Skylab 3 and 4 include 9 x 9 prints and transparencies at 1:750,000 (skylab 3) and 1:500,000 (skylab 4). These images were taken in 1973 and are along three tracks; northeast from New Orleans, LA to South Carolina, northeast from Pensacola, FL to Columbus, GA, and from Pearl River, Jackson MI to Pensacola, FL. The multispectral photographic facility onboard Skylab provided imagery in several wavelength bands ranging from 0.5 to 0.9 Micrometers. This camera system provided ground resolution of approximately 40 m in visible wavelengths to 75 m in the infrared. A variety of high and low altitude aircraft imagery of Alabama is also available from the Geological Survey of Alabama. Microfiche images of MSS/TM imagery of North America since 1986 (landsat browse imagery) are also available. Similar imagery for other locations and time periods is available from the Eros Data Center. proprietary
ZZZ302 Alabama Remote Sensing Archive Multispectral Imagery of Alabama from Landsat and Skylab ALL STAC Catalog 1972-01-01 1984-01-01 -92, 24, -80, 35 https://cmr.earthdata.nasa.gov/search/concepts/C1214584460-SCIOPS.umm_json Multispectral imagery of the state of Alabama is available from the Geological Survey of Alabama for the time period of 1972-1984. Imagery from the Landsat multispectral scanner (MSS) is available as prints or transparencies for all bands (with selected color composites avaliable) at an approximate scale of 1:1,000,000. MSS data is collected in four spectral bands ranging from 0.5 to 1.1 micrometer with a ground resolution of about 80m. Images available from Skylab 3 and 4 include 9 x 9 prints and transparencies at 1:750,000 (skylab 3) and 1:500,000 (skylab 4). These images were taken in 1973 and are along three tracks; northeast from New Orleans, LA to South Carolina, northeast from Pensacola, FL to Columbus, GA, and from Pearl River, Jackson MI to Pensacola, FL. The multispectral photographic facility onboard Skylab provided imagery in several wavelength bands ranging from 0.5 to 0.9 Micrometers. This camera system provided ground resolution of approximately 40 m in visible wavelengths to 75 m in the infrared. A variety of high and low altitude aircraft imagery of Alabama is also available from the Geological Survey of Alabama. Microfiche images of MSS/TM imagery of North America since 1986 (landsat browse imagery) are also available. Similar imagery for other locations and time periods is available from the Eros Data Center. proprietary
+ZZZ302 Alabama Remote Sensing Archive Multispectral Imagery of Alabama from Landsat and Skylab SCIOPS STAC Catalog 1972-01-01 1984-01-01 -92, 24, -80, 35 https://cmr.earthdata.nasa.gov/search/concepts/C1214584460-SCIOPS.umm_json Multispectral imagery of the state of Alabama is available from the Geological Survey of Alabama for the time period of 1972-1984. Imagery from the Landsat multispectral scanner (MSS) is available as prints or transparencies for all bands (with selected color composites avaliable) at an approximate scale of 1:1,000,000. MSS data is collected in four spectral bands ranging from 0.5 to 1.1 micrometer with a ground resolution of about 80m. Images available from Skylab 3 and 4 include 9 x 9 prints and transparencies at 1:750,000 (skylab 3) and 1:500,000 (skylab 4). These images were taken in 1973 and are along three tracks; northeast from New Orleans, LA to South Carolina, northeast from Pensacola, FL to Columbus, GA, and from Pearl River, Jackson MI to Pensacola, FL. The multispectral photographic facility onboard Skylab provided imagery in several wavelength bands ranging from 0.5 to 0.9 Micrometers. This camera system provided ground resolution of approximately 40 m in visible wavelengths to 75 m in the infrared. A variety of high and low altitude aircraft imagery of Alabama is also available from the Geological Survey of Alabama. Microfiche images of MSS/TM imagery of North America since 1986 (landsat browse imagery) are also available. Similar imagery for other locations and time periods is available from the Eros Data Center. proprietary
ZinkeSoil_221_1 Global Organic Soil Carbon and Nitrogen (Zinke et al.) ORNL_CLOUD STAC Catalog 1940-01-01 1986-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2216862657-ORNL_CLOUD.umm_json A compilation of worldwide soil carbon and nitrogen data for more than 3500 soil profiles. proprietary
Zinke_soil_683_1 LBA Regional Organic Soil Carbon and Nitrogen Data (Zinke et al.) ORNL_CLOUD STAC Catalog 1940-01-01 1984-12-31 -85, -25, -30, 10 https://cmr.earthdata.nasa.gov/search/concepts/C2777326924-ORNL_CLOUD.umm_json The data set contains a subset of a global organic soil carbon and nitrogen data set (Zinke et al. 1986). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The point data are available in three formats: a comma-delimited ASCII file (*.csv), an ESRI shapefile, and an ESRI export file (*.e00).The data for the global data set (Zinke et al. 1986) were obtained from soil surveys conducted by Zinke in 1965-1984 and from soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations. Many samples reported in the literature did not have uniform soil increments or bulk density determinations. Only soil profiles that had been sampled either to a meter in depth or to actual depth were included in this database from soil survey literature. When carbon content was known but bulk densities were absent from soil samples reported in the literature, densities were estimated by regression analysis on the basis of the relationship between organic carbon content and measured bulk density in 1800 soil profiles for which bulk densities were known.Further information can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/Zinke_soil/comp/zinke_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html. proprietary
ZoblerSoilDerived_540_1 Global Soil Types, 0.5-Degree Grid (Modified Zobler) ORNL_CLOUD STAC Catalog 1974-01-01 1982-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2216862776-ORNL_CLOUD.umm_json A global data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler's (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution. proprietary
@@ -17041,49 +17042,49 @@ aamhcpex_1 AAMH CPEX ALL STAC Catalog 2017-05-26 2017-07-16 154.716, 0.6408, -19
ab90030e26c54ba495b1cbec51e137e1_NA ESA Aerosol Climate Change Initiative (Aerosol_cci): Level 3 aerosol products from AATSR (ADV algorithm), Version 2.31 FEDEO STAC Catalog 2002-07-24 2012-04-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548142756-FEDEO.umm_json The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 3 daily and monthly gridded aerosol products from the AATSR instrument on the ENVISAT satellite, derived using the ADV algorithm, version 2.31. Data is available for the period from 2002 to 2012.For further details about these data products please see the linked documentation. proprietary
above-and-below-ground-herbivore-communities-along-elevation_1.0 Above- and below-ground herbivore communities along elevation ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.umm_json Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017. proprietary
above-and-below-ground-herbivore-communities-along-elevation_1.0 Above- and below-ground herbivore communities along elevation ALL STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.umm_json Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017. proprietary
-accessibility-of-the-swiss-forest-for-economic-wood-extraction_1.0 Accessibility of the Swiss forest for economic wood extraction (2021) ENVIDAT STAC Catalog 2023-01-01 2023-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081516-ENVIDAT.umm_json "Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport. A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination. Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the ""helicopter"" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based. Road transport was investigated using network analysis, based on the data set ""Forest access roads 2013"" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account. Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the ""helicopter"" category or transport with trucks under 26 tons). The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland. The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php) Input data used: - Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016). - NFI forest mask, 10 m resolution (2015) - Digital elevation model, 10m resolution (based on swissALTI3D 2016) - Slope map, 10m resolution (based on swissALTI3D 2016) - Soil suitability map, 10m resolution (based on soil suitability map BFS 2000) - Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)" proprietary
accessibility-of-the-swiss-forest-for-economic-wood-extraction_1.0 Accessibility of the Swiss forest for economic wood extraction (2021) ALL STAC Catalog 2023-01-01 2023-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081516-ENVIDAT.umm_json "Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport. A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination. Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the ""helicopter"" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based. Road transport was investigated using network analysis, based on the data set ""Forest access roads 2013"" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account. Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the ""helicopter"" category or transport with trucks under 26 tons). The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland. The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php) Input data used: - Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016). - NFI forest mask, 10 m resolution (2015) - Digital elevation model, 10m resolution (based on swissALTI3D 2016) - Slope map, 10m resolution (based on swissALTI3D 2016) - Soil suitability map, 10m resolution (based on soil suitability map BFS 2000) - Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)" proprietary
-accum-measurements-domec-traverse-1982_1 Accumulation Measurements from Pioneerskaya to Dome C, 1982-84 AU_AADC STAC Catalog 1982-01-01 1984-12-31 124.5, -78.5, 93, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311710-AU_AADC.umm_json Initial accumulation levels measured on traverse in 1982/83, and re-measurement of some poles on the 1983/84 traverse. These documents have been archived in the records store at the Australian Antarctic Division. proprietary
+accessibility-of-the-swiss-forest-for-economic-wood-extraction_1.0 Accessibility of the Swiss forest for economic wood extraction (2021) ENVIDAT STAC Catalog 2023-01-01 2023-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081516-ENVIDAT.umm_json "Two raster maps (10m resolution) of: I) the most suitable extraction method for wood in the Swiss forest, and II) the overall suitability of the Swiss forest for economic wood extraction and transport. A modern forest road system is important for the efficient management of forests. In order to assess the current forest accessibility in Switzerland on a comprehensive basis, the entire Swiss forest was investigated using a consistent methodology. In our model, wood extraction from the stand to the road and on-road transport are analysed in combination. Suitable extraction methods for each forest parcel (10m x 10m) were determined using an approach in which ground-based, cable-based and air-based transport are distinguished. First, the areas for ground- and cable-based extraction were delineated. The trafficability of the forest areas was assessed based on the terrain and soil characteristics; trafficable areas also had to be connected to a forest road. To evaluate the suitability for cable-yarding (up to a maximum distance of 1500 m), terrain and possible obstacles (e.g., power lines) were considered. The remaining forest area, which was not suitable for either ground-based or cable-based methods, was assigned to the ""helicopter"" category. As a result of this analysis, a map of the most suitable skidding method for each plot could be created. When several methods were possible for a parcel, the priority was ground-based over cable-based over air-based. Road transport was investigated using network analysis, based on the data set ""Forest access roads 2013"" from the Swiss National Forest Inventory (NFI), which contains information on width and weight limits of roads in the forest and up to the superordinate main road network. Thus, in addition to the distance, the largest type of vehicle allowed on the respective removal route could also be taken into account. Based on the extraction method and the weight limits for on-road transport, the forest area was divided into three categories: 1) meets the requirements for efficient forest management (all forest parcels with ground-based extraction method or mobile cable-yarding, transport weight limit at least 28 tons); 2) limited suitability for efficient forest management; and 3) not suitable for efficient forest management (forest parcels in the ""helicopter"" category or transport with trucks under 26 tons). The resulting maps cannot provide an accurate classification for each forest parcel. Missing or incorrect roads in the road dataset, insufficient information on ground trafficability or other local factors, the limitation to only three possible extraction systems, and failure to account for anchor trees, extraction methods changing over small distances, and unrealistically short cable-yarding distances can cause the model results to deviate from the assessment by an expert with knowledge of the local conditions. Also, protected areas were not excluded and harvesting intensity was not taken into account. The advantage of the method is that consistent criteria are used for the entire Swiss forest, making the results comparable throughout Switzerland. The data are managed at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) and are available to third parties on request. (NFI data policy: https://www.lfi.ch/dienstleist/daten.php) Input data used: - Forest road dataset of the NFI4 (only truck roads from 3.0 m width and 26 t carrying capacity) (2016). - NFI forest mask, 10 m resolution (2015) - Digital elevation model, 10m resolution (based on swissALTI3D 2016) - Slope map, 10m resolution (based on swissALTI3D 2016) - Soil suitability map, 10m resolution (based on soil suitability map BFS 2000) - Obstacles for cable lines, 10m resolution (buildings, major roads, power lines, railroads, based on swissTLM3D 2016)" proprietary
accum-measurements-domec-traverse-1982_1 Accumulation Measurements from Pioneerskaya to Dome C, 1982-84 ALL STAC Catalog 1982-01-01 1984-12-31 124.5, -78.5, 93, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311710-AU_AADC.umm_json Initial accumulation levels measured on traverse in 1982/83, and re-measurement of some poles on the 1983/84 traverse. These documents have been archived in the records store at the Australian Antarctic Division. proprietary
+accum-measurements-domec-traverse-1982_1 Accumulation Measurements from Pioneerskaya to Dome C, 1982-84 AU_AADC STAC Catalog 1982-01-01 1984-12-31 124.5, -78.5, 93, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311710-AU_AADC.umm_json Initial accumulation levels measured on traverse in 1982/83, and re-measurement of some poles on the 1983/84 traverse. These documents have been archived in the records store at the Australian Antarctic Division. proprietary
accumulation-movement-markers-mirny-domec_1 Detailed Notes on Accumulation/Movement Markers, Mirny-Dome C AU_AADC STAC Catalog 1977-01-01 1978-12-31 124.5, -78.5, 93, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311711-AU_AADC.umm_json Detailed notes about each of the markers used for movement (and accumulation) measurements along the Mirny-Dome C traverse line. Includes processing notes from the JMR position analysis. These documents have been archived in the records store at the Australian Antarctic Division. proprietary
accumulation_lawdome_1960_1 Accumulation Measurements, Law Dome 1959-1960 AU_AADC STAC Catalog 1959-01-01 1960-12-31 110, -67, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214305674-AU_AADC.umm_json A collection of information on the position and measurements of snow accumulation via accumulation stakes placed on Law Dome in 1959, and measured over 1959 and 1960. These documents have been archived at the Australian Antarctic Division. proprietary
accumulation_lawdome_1960_1 Accumulation Measurements, Law Dome 1959-1960 ALL STAC Catalog 1959-01-01 1960-12-31 110, -67, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214305674-AU_AADC.umm_json A collection of information on the position and measurements of snow accumulation via accumulation stakes placed on Law Dome in 1959, and measured over 1959 and 1960. These documents have been archived at the Australian Antarctic Division. proprietary
-aces1am_1 ACES Aircraft and Mechanical Data ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.umm_json The ACES Aircraft and Mechanical Data consist of aircraft (e.g. pitch, roll, yaw) and mechanical (e.g. aircraft engine speed, tail commands, fuel levels) data recorded by the Altus II Unmanned Aerial Vehicle (Altus II UAV) system during the Altus Cumulus Electrification Study (ACES) based at the Naval Air Facility Key West in Florida. ACES aimed to provide extensive observations of the cloud electrification process and its effects by using the Altus II UAV to collect cloud top observations of thunderstorms. The campaign also worked to validate satellite lightning measurements. The Altus II aircraft and mechanical data files are available from July 10 through August 30, 2002 in MATLAB data format (.mat). proprietary
aces1am_1 ACES Aircraft and Mechanical Data GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.umm_json The ACES Aircraft and Mechanical Data consist of aircraft (e.g. pitch, roll, yaw) and mechanical (e.g. aircraft engine speed, tail commands, fuel levels) data recorded by the Altus II Unmanned Aerial Vehicle (Altus II UAV) system during the Altus Cumulus Electrification Study (ACES) based at the Naval Air Facility Key West in Florida. ACES aimed to provide extensive observations of the cloud electrification process and its effects by using the Altus II UAV to collect cloud top observations of thunderstorms. The campaign also worked to validate satellite lightning measurements. The Altus II aircraft and mechanical data files are available from July 10 through August 30, 2002 in MATLAB data format (.mat). proprietary
+aces1am_1 ACES Aircraft and Mechanical Data ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.umm_json The ACES Aircraft and Mechanical Data consist of aircraft (e.g. pitch, roll, yaw) and mechanical (e.g. aircraft engine speed, tail commands, fuel levels) data recorded by the Altus II Unmanned Aerial Vehicle (Altus II UAV) system during the Altus Cumulus Electrification Study (ACES) based at the Naval Air Facility Key West in Florida. ACES aimed to provide extensive observations of the cloud electrification process and its effects by using the Altus II UAV to collect cloud top observations of thunderstorms. The campaign also worked to validate satellite lightning measurements. The Altus II aircraft and mechanical data files are available from July 10 through August 30, 2002 in MATLAB data format (.mat). proprietary
aces1cont_1 ACES CONTINUOUS DATA V1 GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847043-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August, 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloudelectrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from seven instruments: the Slow/Fast antenna, Electric Field Mill, Dual Optical Pulse Sensor, Searchcoil Magnetometer, Accelerometers, Gerdien Conductivity Probe, and the Fluxgate Magnetometer. Data consists of sensor reads at 50HZ throughout the flight from all 64 channels. proprietary
aces1cont_1 ACES CONTINUOUS DATA V1 ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847043-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August, 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloudelectrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from seven instruments: the Slow/Fast antenna, Electric Field Mill, Dual Optical Pulse Sensor, Searchcoil Magnetometer, Accelerometers, Gerdien Conductivity Probe, and the Fluxgate Magnetometer. Data consists of sensor reads at 50HZ throughout the flight from all 64 channels. proprietary
-aces1efm_1 ACES ELECTRIC FIELD MILL V1 GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data from Electric Field Mills, which yield information about the atmospheric electrical fields above the instruments. proprietary
aces1efm_1 ACES ELECTRIC FIELD MILL V1 ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data from Electric Field Mills, which yield information about the atmospheric electrical fields above the instruments. proprietary
+aces1efm_1 ACES ELECTRIC FIELD MILL V1 GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data from Electric Field Mills, which yield information about the atmospheric electrical fields above the instruments. proprietary
aces1log_1 ACES LOG DATA GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977853903-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of log data from each flight, and yields instrument and aircraft status throughout the flight. proprietary
aces1log_1 ACES LOG DATA ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977853903-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of log data from each flight, and yields instrument and aircraft status throughout the flight. proprietary
-aces1time_1 ACES TIMING DATA ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August or 2002, ACES researchers overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of timing data used for the experiment. When used it provides: syncclock_time = time found at the syncclock (VSI-SYnCCLOCK-32) in seconds from first file name, syncclock_m_time = time found at the syncclock (VSI-SYnCCLOCK-32) in Matlab dateform format, system_time = system time in seconds from first file name, system_m_time = system time in dateform format, gps_time = time found at the GPS unit in seconds from first file name, gps_m_time = time found at GPS unit in dateform, cmos_time = time found at the computer CMOS in seconds from first file name, cmos_m_time = time found at the computer CMOS in dateform. proprietary
aces1time_1 ACES TIMING DATA GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August or 2002, ACES researchers overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of timing data used for the experiment. When used it provides: syncclock_time = time found at the syncclock (VSI-SYnCCLOCK-32) in seconds from first file name, syncclock_m_time = time found at the syncclock (VSI-SYnCCLOCK-32) in Matlab dateform format, system_time = system time in seconds from first file name, system_m_time = system time in dateform format, gps_time = time found at the GPS unit in seconds from first file name, gps_m_time = time found at GPS unit in dateform, cmos_time = time found at the computer CMOS in seconds from first file name, cmos_m_time = time found at the computer CMOS in dateform. proprietary
-aces1trig_1 ACES TRIGGERED DATA GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued. proprietary
+aces1time_1 ACES TIMING DATA ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August or 2002, ACES researchers overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of timing data used for the experiment. When used it provides: syncclock_time = time found at the syncclock (VSI-SYnCCLOCK-32) in seconds from first file name, syncclock_m_time = time found at the syncclock (VSI-SYnCCLOCK-32) in Matlab dateform format, system_time = system time in seconds from first file name, system_m_time = system time in dateform format, gps_time = time found at the GPS unit in seconds from first file name, gps_m_time = time found at GPS unit in dateform, cmos_time = time found at the computer CMOS in seconds from first file name, cmos_m_time = time found at the computer CMOS in dateform. proprietary
aces1trig_1 ACES TRIGGERED DATA ALL STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued. proprietary
+aces1trig_1 ACES TRIGGERED DATA GHRC_DAAC STAC Catalog 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.umm_json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued. proprietary
acoustic_charts_v6_1994_95_1 Acoustic Sounder Charts from Australian Antarctic Division Voyage 6 1994/95 (BANGSS) ALL STAC Catalog 1995-02-06 1995-04-12 60, -69.393, 147.473, -42.882 https://cmr.earthdata.nasa.gov/search/concepts/C1214311712-AU_AADC.umm_json Acoustic sounder charts were collected at six locations during Australian Antarctic Division Voyage 6 1994/95 (BANGSS) using the Kongsberg EA200 Echo Sounder on the Aurora Australis. BANGSS is an acronym for Big ANtarctic Geological and Seismic Survey. The voyage began on 6 February 1995 and finished on 12 April 1995. Each chart is labelled with information about when and where the data was collected: date, time, latitude and longitude. The charts provide a profile of the sea floor and have a time axis with numbers in the following format. the first two digits are the day the next two digits are the month the next five digits are the time (UTC) the last ten digits are the maximum value on the depth axis eg 2402005 360000000500 means 24 February 5:36 UTC and the maximum value on the depth axis is 500 metres See a Related URL for a link to information about the voyage including the voyage report. proprietary
acoustic_charts_v6_1994_95_1 Acoustic Sounder Charts from Australian Antarctic Division Voyage 6 1994/95 (BANGSS) AU_AADC STAC Catalog 1995-02-06 1995-04-12 60, -69.393, 147.473, -42.882 https://cmr.earthdata.nasa.gov/search/concepts/C1214311712-AU_AADC.umm_json Acoustic sounder charts were collected at six locations during Australian Antarctic Division Voyage 6 1994/95 (BANGSS) using the Kongsberg EA200 Echo Sounder on the Aurora Australis. BANGSS is an acronym for Big ANtarctic Geological and Seismic Survey. The voyage began on 6 February 1995 and finished on 12 April 1995. Each chart is labelled with information about when and where the data was collected: date, time, latitude and longitude. The charts provide a profile of the sea floor and have a time axis with numbers in the following format. the first two digits are the day the next two digits are the month the next five digits are the time (UTC) the last ten digits are the maximum value on the depth axis eg 2402005 360000000500 means 24 February 5:36 UTC and the maximum value on the depth axis is 500 metres See a Related URL for a link to information about the voyage including the voyage report. proprietary
-acoustic_doppler_current_profiler_data_-_2010 Acoustic Doppler Current Profiler Data - 2010 ALL STAC Catalog 2010-08-21 2010-09-17 -156, 70, -154, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214602088-SCIOPS.umm_json "Acoustic Doppler current profiler data were collected using a RD Instruments, 300 kHz ADCP that was mounted on an acoustic sled and towed alongside the R/V Annika Marie. Deployment was somewhat limited by weather, with higher sea states precluding use of the instrument. Data were processed by Frank Bahr at the Woods Hole Oceanographic Institution. Two files are included: A matlab file and a .zip file containing ascii files for each deployement. 2.) ascii format. The .mat file sos2010_dt.mat contains all deployments in the structure vm_data.
The format is described in a text variable ""readme"" contained in sos2010_dt.mat 2.) ascii format.
The data are also presented in ascii, with one data file per deployment, with files zipped together in to sos2010dt_ascii.zip.
The first line of each file gives the center depth of the ADCP bins in meters.
Note that both the bin depths as well as the number of bins may change
between deployments.
It is followed by one line per ADCP profile, listing
- profile time as year/month/day hour:min:sec,
- profile time in 2010 decimal days (noon on Jan 1 equals decimal day 0.5)
- longitude, latitude in decimal degrees
- N values of zonal velocity, positive eastward, where N is the number of bins
- N values of meridional velocity, positive northward
""Bad"" data are marked with the flag value 999.99." proprietary
acoustic_doppler_current_profiler_data_-_2010 Acoustic Doppler Current Profiler Data - 2010 SCIOPS STAC Catalog 2010-08-21 2010-09-17 -156, 70, -154, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214602088-SCIOPS.umm_json "Acoustic Doppler current profiler data were collected using a RD Instruments, 300 kHz ADCP that was mounted on an acoustic sled and towed alongside the R/V Annika Marie. Deployment was somewhat limited by weather, with higher sea states precluding use of the instrument. Data were processed by Frank Bahr at the Woods Hole Oceanographic Institution. Two files are included: A matlab file and a .zip file containing ascii files for each deployement. 2.) ascii format. The .mat file sos2010_dt.mat contains all deployments in the structure vm_data.
The format is described in a text variable ""readme"" contained in sos2010_dt.mat 2.) ascii format.
The data are also presented in ascii, with one data file per deployment, with files zipped together in to sos2010dt_ascii.zip.
The first line of each file gives the center depth of the ADCP bins in meters.
Note that both the bin depths as well as the number of bins may change
between deployments.
It is followed by one line per ADCP profile, listing
- profile time as year/month/day hour:min:sec,
- profile time in 2010 decimal days (noon on Jan 1 equals decimal day 0.5)
- longitude, latitude in decimal degrees
- N values of zonal velocity, positive eastward, where N is the number of bins
- N values of meridional velocity, positive northward
""Bad"" data are marked with the flag value 999.99." proprietary
-acoustic_doppler_current_profiler_data_-_2011 Acoustic Doppler Current Profiler Data - 2011 SCIOPS STAC Catalog 2011-08-22 2011-09-13 -156, 70, -154, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214600594-SCIOPS.umm_json "Acoustic Doppler current profiler data were collected using a RD Instruments, 300 kHz ADCP that was mounted on an acoustic sled and towed alongside the R/V Annika Marie. Deployment was somewhat limited by weather, with higher sea states precluding use of the instrument. Data were processed by Frank Bahr at the Woods Hole Oceanographic Institution. Three files are included: A matlab file and .zip file and .tar files containing ascii files for each deployement. 1.) Matlab format. The .mat file sos2011_dt.mat contains all deployments in the structure vm_data.
The format is described in a text variable ""readme"" contained in sos2010_dt.mat 2.) ascii format.
The data are also presented in ascii, with one data file per deployment, with files zipped together in to sos2011dt_ascii.zip or sos2011dt_asc.tar.
The first line of each file gives the center depth of the ADCP bins in meters.
Note that both the bin depths as well as the number of bins may change
between deployments.
It is followed by one line per ADCP profile, listing
- profile time as year/month/day hour:min:sec,
- profile time in 2010 decimal days (noon on Jan 1 equals decimal day 0.5)
- longitude, latitude in decimal degrees
- N values of zonal velocity, positive eastward, where N is the number of bins
- N values of meridional velocity, positive northward
""Bad"" data are marked with the flag value 999.99." proprietary
+acoustic_doppler_current_profiler_data_-_2010 Acoustic Doppler Current Profiler Data - 2010 ALL STAC Catalog 2010-08-21 2010-09-17 -156, 70, -154, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214602088-SCIOPS.umm_json "Acoustic Doppler current profiler data were collected using a RD Instruments, 300 kHz ADCP that was mounted on an acoustic sled and towed alongside the R/V Annika Marie. Deployment was somewhat limited by weather, with higher sea states precluding use of the instrument. Data were processed by Frank Bahr at the Woods Hole Oceanographic Institution. Two files are included: A matlab file and a .zip file containing ascii files for each deployement. 2.) ascii format. The .mat file sos2010_dt.mat contains all deployments in the structure vm_data.
The format is described in a text variable ""readme"" contained in sos2010_dt.mat 2.) ascii format.
The data are also presented in ascii, with one data file per deployment, with files zipped together in to sos2010dt_ascii.zip.
The first line of each file gives the center depth of the ADCP bins in meters.
Note that both the bin depths as well as the number of bins may change
between deployments.
It is followed by one line per ADCP profile, listing
- profile time as year/month/day hour:min:sec,
- profile time in 2010 decimal days (noon on Jan 1 equals decimal day 0.5)
- longitude, latitude in decimal degrees
- N values of zonal velocity, positive eastward, where N is the number of bins
- N values of meridional velocity, positive northward
""Bad"" data are marked with the flag value 999.99." proprietary
acoustic_doppler_current_profiler_data_-_2011 Acoustic Doppler Current Profiler Data - 2011 ALL STAC Catalog 2011-08-22 2011-09-13 -156, 70, -154, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214600594-SCIOPS.umm_json "Acoustic Doppler current profiler data were collected using a RD Instruments, 300 kHz ADCP that was mounted on an acoustic sled and towed alongside the R/V Annika Marie. Deployment was somewhat limited by weather, with higher sea states precluding use of the instrument. Data were processed by Frank Bahr at the Woods Hole Oceanographic Institution. Three files are included: A matlab file and .zip file and .tar files containing ascii files for each deployement. 1.) Matlab format. The .mat file sos2011_dt.mat contains all deployments in the structure vm_data.
The format is described in a text variable ""readme"" contained in sos2010_dt.mat 2.) ascii format.
The data are also presented in ascii, with one data file per deployment, with files zipped together in to sos2011dt_ascii.zip or sos2011dt_asc.tar.
The first line of each file gives the center depth of the ADCP bins in meters.
Note that both the bin depths as well as the number of bins may change
between deployments.
It is followed by one line per ADCP profile, listing
- profile time as year/month/day hour:min:sec,
- profile time in 2010 decimal days (noon on Jan 1 equals decimal day 0.5)
- longitude, latitude in decimal degrees
- N values of zonal velocity, positive eastward, where N is the number of bins
- N values of meridional velocity, positive northward
""Bad"" data are marked with the flag value 999.99." proprietary
+acoustic_doppler_current_profiler_data_-_2011 Acoustic Doppler Current Profiler Data - 2011 SCIOPS STAC Catalog 2011-08-22 2011-09-13 -156, 70, -154, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214600594-SCIOPS.umm_json "Acoustic Doppler current profiler data were collected using a RD Instruments, 300 kHz ADCP that was mounted on an acoustic sled and towed alongside the R/V Annika Marie. Deployment was somewhat limited by weather, with higher sea states precluding use of the instrument. Data were processed by Frank Bahr at the Woods Hole Oceanographic Institution. Three files are included: A matlab file and .zip file and .tar files containing ascii files for each deployement. 1.) Matlab format. The .mat file sos2011_dt.mat contains all deployments in the structure vm_data.
The format is described in a text variable ""readme"" contained in sos2010_dt.mat 2.) ascii format.
The data are also presented in ascii, with one data file per deployment, with files zipped together in to sos2011dt_ascii.zip or sos2011dt_asc.tar.
The first line of each file gives the center depth of the ADCP bins in meters.
Note that both the bin depths as well as the number of bins may change
between deployments.
It is followed by one line per ADCP profile, listing
- profile time as year/month/day hour:min:sec,
- profile time in 2010 decimal days (noon on Jan 1 equals decimal day 0.5)
- longitude, latitude in decimal degrees
- N values of zonal velocity, positive eastward, where N is the number of bins
- N values of meridional velocity, positive northward
""Bad"" data are marked with the flag value 999.99." proprietary
active_layer_arcss_grid_atqasuk_alaska_2010 Active Layer ARCSS grid Atqasuk, Alaska 2010 ALL STAC Catalog 2010-07-10 2010-08-16 -156, 70, -158, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214602289-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's long depth probe was used (orange tape on the handle). Data have been corrected by subtracting 3 cm from measurements made in the field to account for the missing tip of the probe. proprietary
active_layer_arcss_grid_atqasuk_alaska_2010 Active Layer ARCSS grid Atqasuk, Alaska 2010 SCIOPS STAC Catalog 2010-07-10 2010-08-16 -156, 70, -158, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214602289-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's long depth probe was used (orange tape on the handle). Data have been corrected by subtracting 3 cm from measurements made in the field to account for the missing tip of the probe. proprietary
-active_layer_arcss_grid_atqasuk_alaska_2011 Active Layer ARCSS grid Atqasuk, Alaska 2011 SCIOPS STAC Catalog 2011-06-17 2011-08-12 -157, 70, -156, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600393-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Atqasuk, Alaska during the 2011 summer field season. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's CALM depth probe was used to take the measurements. proprietary
active_layer_arcss_grid_atqasuk_alaska_2011 Active Layer ARCSS grid Atqasuk, Alaska 2011 ALL STAC Catalog 2011-06-17 2011-08-12 -157, 70, -156, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600393-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Atqasuk, Alaska during the 2011 summer field season. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's CALM depth probe was used to take the measurements. proprietary
+active_layer_arcss_grid_atqasuk_alaska_2011 Active Layer ARCSS grid Atqasuk, Alaska 2011 SCIOPS STAC Catalog 2011-06-17 2011-08-12 -157, 70, -156, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600393-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Atqasuk, Alaska during the 2011 summer field season. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's CALM depth probe was used to take the measurements. proprietary
active_layer_arcss_grid_atqasuk_alaska_2012 Active Layer ARCSS grid Atqasuk, Alaska 2012 SCIOPS STAC Catalog 2012-06-09 2012-08-18 -156, 70, -157, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214601993-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Atqasuk, Alaska during the 2012 summer field season. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's CALM depth probe was used to take the measurements. proprietary
active_layer_arcss_grid_atqasuk_alaska_2012 Active Layer ARCSS grid Atqasuk, Alaska 2012 ALL STAC Catalog 2012-06-09 2012-08-18 -156, 70, -157, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214601993-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Atqasuk, Alaska during the 2012 summer field season. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from E2-E6 and J2-J6. The SEL lab's CALM depth probe was used to take the measurements. proprietary
-active_layer_arcss_grid_barrow_alaska_2010 Active Layer ARCSS grid Barrow, Alaska 2010 SCIOPS STAC Catalog 2010-06-30 2010-08-11 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600590-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's long depth probe was used (orange tape on the handle). Data have been corrected by subtracting 3 cm from measurements made in the field to account for the missing tip of the probe. proprietary
active_layer_arcss_grid_barrow_alaska_2010 Active Layer ARCSS grid Barrow, Alaska 2010 ALL STAC Catalog 2010-06-30 2010-08-11 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600590-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's long depth probe was used (orange tape on the handle). Data have been corrected by subtracting 3 cm from measurements made in the field to account for the missing tip of the probe. proprietary
+active_layer_arcss_grid_barrow_alaska_2010 Active Layer ARCSS grid Barrow, Alaska 2010 SCIOPS STAC Catalog 2010-06-30 2010-08-11 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600590-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's long depth probe was used (orange tape on the handle). Data have been corrected by subtracting 3 cm from measurements made in the field to account for the missing tip of the probe. proprietary
active_layer_arcss_grid_barrow_alaska_2011 Active Layer ARCSS grid Barrow, Alaska 2011 SCIOPS STAC Catalog 2011-06-14 2011-07-25 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600390-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's CALM depth probe was used. Depth was measured on the probe as the distance from the frozen active layer to the top of the surface of the vegetation. If water was present, then it was measured to the top of the biomass. proprietary
active_layer_arcss_grid_barrow_alaska_2011 Active Layer ARCSS grid Barrow, Alaska 2011 ALL STAC Catalog 2011-06-14 2011-07-25 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600390-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's CALM depth probe was used. Depth was measured on the probe as the distance from the frozen active layer to the top of the surface of the vegetation. If water was present, then it was measured to the top of the biomass. proprietary
-active_layer_arcss_grid_barrow_alaska_2012 Active Layer ARCSS grid Barrow, Alaska 2012 SCIOPS STAC Catalog 2012-06-09 2012-08-18 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600333-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's CALM depth probe was used. Depth was measured on the probe as the distance from the frozen active layer to the top of the surface of the vegetation. If water was present, then it was measured to the top of the biomass. proprietary
active_layer_arcss_grid_barrow_alaska_2012 Active Layer ARCSS grid Barrow, Alaska 2012 ALL STAC Catalog 2012-06-09 2012-08-18 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600333-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's CALM depth probe was used. Depth was measured on the probe as the distance from the frozen active layer to the top of the surface of the vegetation. If water was present, then it was measured to the top of the biomass. proprietary
+active_layer_arcss_grid_barrow_alaska_2012 Active Layer ARCSS grid Barrow, Alaska 2012 SCIOPS STAC Catalog 2012-06-09 2012-08-18 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600333-SCIOPS.umm_json Active Layer measurements were taken on a 30 plot subset within the ARCSS Grid in Barrow, Alaska. Each measurement was taken on the north eastern most corner of each plot. The chosen subset was located from D2-D7 and H2-H7. The SEL lab's CALM depth probe was used. Depth was measured on the probe as the distance from the frozen active layer to the top of the surface of the vegetation. If water was present, then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_atqasuk_alaska_2011 Active Layer NIMS grid Atqasuk, Alaska 2011 SCIOPS STAC Catalog 2011-06-05 2011-08-12 -156, 70, -157, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600341-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Atqasuk, Alaska throughout the 2011 summer field season. UTEP SELs CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_atqasuk_alaska_2011 Active Layer NIMS grid Atqasuk, Alaska 2011 ALL STAC Catalog 2011-06-05 2011-08-12 -156, 70, -157, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600341-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Atqasuk, Alaska throughout the 2011 summer field season. UTEP SELs CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_atqasuk_alaska_2012 Active Layer NIMS grid Atqasuk, Alaska 2012 SCIOPS STAC Catalog 2012-06-09 2012-08-18 -156, 70, -157, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600318-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Atqasuk, Alaska throughout the 2012 summer field season. UTEP SEL's CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_atqasuk_alaska_2012 Active Layer NIMS grid Atqasuk, Alaska 2012 ALL STAC Catalog 2012-06-09 2012-08-18 -156, 70, -157, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214600318-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Atqasuk, Alaska throughout the 2012 summer field season. UTEP SEL's CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
-active_layer_nims_grid_barrow_alaska_2011 Active Layer NIMS grid Barrow, Alaska 2011 SCIOPS STAC Catalog 2011-06-14 2011-08-09 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214602385-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Barrow, Alaska throughout the 2011 summer field season. UTEP SEL’s CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_barrow_alaska_2011 Active Layer NIMS grid Barrow, Alaska 2011 ALL STAC Catalog 2011-06-14 2011-08-09 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214602385-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Barrow, Alaska throughout the 2011 summer field season. UTEP SEL’s CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
+active_layer_nims_grid_barrow_alaska_2011 Active Layer NIMS grid Barrow, Alaska 2011 SCIOPS STAC Catalog 2011-06-14 2011-08-09 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214602385-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Barrow, Alaska throughout the 2011 summer field season. UTEP SEL’s CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_barrow_alaska_2012 Active Layer NIMS grid Barrow, Alaska 2012 SCIOPS STAC Catalog 2012-06-09 2012-08-18 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600541-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Barrow, Alaska throughout the 2012 summer field season. UTEP SELs CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
active_layer_nims_grid_barrow_alaska_2012 Active Layer NIMS grid Barrow, Alaska 2012 ALL STAC Catalog 2012-06-09 2012-08-18 -156.6, 71, -156.5, 71.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214600541-SCIOPS.umm_json Active Layer measurements were taken at each NIMS (Networked Info-mechanical Systems) grid plot in Barrow, Alaska throughout the 2012 summer field season. UTEP SELs CALM depth probe was used to take measurements. Depth was measured on the probe as the distance from frozen active layer to the top surface of the vegetation. If water was present then it was measured to the top of the biomass. proprietary
ada968fd392d49fbbb07ac84eeb23ac6_NA ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Zachariae Glacier between 2017-06-25 and 2017-08-10, generated using Sentinel-2 data, v1.1 FEDEO STAC Catalog 2017-06-24 2017-08-10 -80, 60, -10, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548142710-FEDEO.umm_json This dataset contains an optical ice velocity time series and seasonal product of the Zachariae Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-06-25 and 2017-08-10. It has been produced as part of the ESA Greenland Ice Sheet CCI project.The data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid. The product was generated by S[&]T Norway. proprietary
@@ -17091,8 +17092,8 @@ adaptive_long-term_fasting_in_land_and_ice-bound_polar_bears_data_table Adaptive
adaptive_long-term_fasting_in_land_and_ice-bound_polar_bears_data_table Adaptive long-term fasting in land and ice-bound polar bears: Data Table SCIOPS STAC Catalog 2008-01-01 2011-12-31 -155, 70, -122, 80 https://cmr.earthdata.nasa.gov/search/concepts/C1214602399-SCIOPS.umm_json The datasets in the data table have been collected as part of a project to understand how reduced sea ice cover in the Arctic will impact polar bear populations. Bears that stay ashore in summer have almost no access to food and tend to be inactive. Those that stay on the ice, however, have continued access to prey and make extensive movements. Over a three year period, scientists from the University of Wyoming and the U. S. Geological Service followed the movements of bears in both habitats and monitored their body temperature, muscle condition, blood chemistry, and metabolism. The physiological data will be added to spatially-explicit individual-based population models to predict population response to reduced ice cover. proprietary
adcp_2 Aurora Australis Southern Ocean ADCP data AU_AADC STAC Catalog 1994-12-13 1999-09-07 75, -69, 165, -41 https://cmr.earthdata.nasa.gov/search/concepts/C1214311719-AU_AADC.umm_json Acoustic Doppler current profiler (ADCP) measurements from a hull mounted 150 kHz narrow band ADCP unit were collected in the Southern Ocean from 1994 to 1999, on the following cruises: au9404, au9501, au9604, au9601, au9701, au9706, au9807 and au9901. The fields in this dataset are: Currents bottom depth cruise number ship speed time velocity GPS proprietary
add104f4c4454b629dbc7648efaa1b50_NA ESA Ozone Climate Change Initiative (Ozone CCI): ODIN/SMR (544.6 GHz) Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1 FEDEO STAC Catalog 2001-01-01 2013-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548142584-FEDEO.umm_json This dataset comprises gridded limb ozone monthly zonal mean profiles from the ODIN/SMR (544.6 GHz) instrument. The data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.The monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file âESACCI-OZONE-L3-LP-MZM-SMR_ODIN-544_6_GHz-2008-fv0001.ncâ contains monthly zonal mean data for ODIN/SMR at 544.6GHz in 2008. proprietary
-adpe-aat-census_1 Adelie penguin census from records from 1931 to 2007 AAT region AU_AADC STAC Catalog 1931-02-13 2006-12-08 38.2, -69.6, 89.5, -65.8 https://cmr.earthdata.nasa.gov/search/concepts/C1214311746-AU_AADC.umm_json A catalogue of adelie penguin colony census records from 1931 to 2007 and limited geographically to the Australian Antarctic Territory (AAT). The present set is from 40E to Gaussberg (89E). The census records have been collected and compiled from a literature search. proprietary
adpe-aat-census_1 Adelie penguin census from records from 1931 to 2007 AAT region ALL STAC Catalog 1931-02-13 2006-12-08 38.2, -69.6, 89.5, -65.8 https://cmr.earthdata.nasa.gov/search/concepts/C1214311746-AU_AADC.umm_json A catalogue of adelie penguin colony census records from 1931 to 2007 and limited geographically to the Australian Antarctic Territory (AAT). The present set is from 40E to Gaussberg (89E). The census records have been collected and compiled from a literature search. proprietary
+adpe-aat-census_1 Adelie penguin census from records from 1931 to 2007 AAT region AU_AADC STAC Catalog 1931-02-13 2006-12-08 38.2, -69.6, 89.5, -65.8 https://cmr.earthdata.nasa.gov/search/concepts/C1214311746-AU_AADC.umm_json A catalogue of adelie penguin colony census records from 1931 to 2007 and limited geographically to the Australian Antarctic Territory (AAT). The present set is from 40E to Gaussberg (89E). The census records have been collected and compiled from a literature search. proprietary
adu_birp Animal Demography Unit - The Birds in Reserves Project (BIRP) CEOS_EXTRA STAC Catalog 1906-02-05 2007-05-20 16.46, -34.77, 32.86, -22.61 https://cmr.earthdata.nasa.gov/search/concepts/C2232477691-CEOS_EXTRA.umm_json BIRP is a joint project of BirdLife South Africa (BLSA), and the Animal Demography Unit (ADU), based at the University of Cape Town (UCT). The basic purpose of BIRP is to compile a comprehensive catalogue of the species of birds which occur and breed in South Africa’s many protected areas. A database of this kind will help to identify the species which are as yet not adequately protected and will also provide the managers of protected areas with information useful in setting management policies. proprietary
adu_cwac Animal Demography Unit - Coordinated Waterbird Counts (CWAC) CEOS_EXTRA STAC Catalog 1983-07-15 2006-09-30 16.46, -34.72, 32.88, -22.22 https://cmr.earthdata.nasa.gov/search/concepts/C2232477679-CEOS_EXTRA.umm_json The Coordinated Waterbird Counts (CWAC) project was launched in 1992. The objective of CWAC is to monitor South Africa's waterbird populations and the conditions of the wetlands which are important for waterbirds. This is being done by means of a programme of regular mid-summer and mid-winter censuses at a large number of South African wetlands. Regular six-monthly counts are conducted; however, we do encourage counters to survey their wetlands on a more regular basis as this provides better data. CWAC currently monitors over 400 wetlands around the country on a regular basis, and furthermore curates waterbird data for close to 600 wetlands. proprietary
adu_safring Animal Demography Unit - South African Bird Ringing Unit (SAFRING) CEOS_EXTRA STAC Catalog 1899-12-30 2004-12-31 -76.33, -71.9, 73.5, 72.25 https://cmr.earthdata.nasa.gov/search/concepts/C2232477669-CEOS_EXTRA.umm_json The South African Bird Ringing Unit (SAFRING) administers bird ringing in southern Africa, supplying rings, ringing equipment and services to volunteer and professional ringers in South Africa and neighbouring countries. All ringing records are curated by SAFRING, which is an essential arm of the Animal Demography Unit. Contact is maintained by the SAFRING Project Coordinator with all ringers (banders in North American or Australian terminology). The Bird Ringing Scheme in South Africa was initiated in 1948, so 1998 saw the 50th anniversary of the scheme. During this period over 1.7 million birds of 852 species were ringed. There have been a total of 16 800 ring recoveries since the inception of the scheme. This gives an overall recovery rate for rings in southern Africa of marginally less than 1%, averaged across all species. This probability varies enormously across species. proprietary
@@ -17102,23 +17103,23 @@ aerial_mosaics_macquarie_2017_2 Aerial photograph mosaics of The Isthmus at Macq
aerial_mosaics_macquarie_2017_2 Aerial photograph mosaics of The Isthmus at Macquarie Island, January and February 2017 AU_AADC STAC Catalog 2017-01-15 2017-02-15 158.874, -54.506, 158.954, -54.483 https://cmr.earthdata.nasa.gov/search/concepts/C1437176029-AU_AADC.umm_json One vertical and two oblique mosaics of The Isthmus at Macquarie Island were created from aerial photographs taken with a UAV (Unmanned Aerial Vehicle) during the course of Australian Antarctic Science Project 4340 in January and February 2017. The oblique mosaics include Wireless Hill and the northern end of the island's plateau. One oblique mosaic is a view from the eastern side of The Isthmus and the other is a view from the western side of The Isthmus. The photographs were taken by Murray Hamilton of the University of Adelaide using a DJI Phantom 3 Advanced UAV (under Monash University's Operators Certificate) which he was using to make temperature and humidity observations. They were taken when the UAV was waiting to descend and measure a temperature profile. The measuring instrument needed some time for the temperature to equilibrate after a rapid ascent. The photographs were taken by rotating the craft, taking snapshots every few tens of degrees. Hugin software was used to create the mosaics. The photographs for the vertical mosaic were taken on 15 January 2017 and the photographs for the oblique mosaics were taken on 7 February 2017 (view from east) and 15 February 2017 (view from west). The vertical mosaic was produced at the request of the Building Services Supervisor at the station. proprietary
aerial_photo_sea_ice_1 Aerial photographs of sea ice flown by the Australian Antarctic Division ALL STAC Catalog 2003-09-10 -58.2, -69.67, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1214305646-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during the following voyages: Australian Antarctic Division voyage 1 2003/04 - Antarctic Remote Ice Sensing Experiment (ARISE); Alfred Wegener Institute Ice Station Polarstern (ISPOL) voyage 2004/05; and Australian Antarctic Division voyage 1 2007/08 - Sea Ice Physics and Ecosystems Experiment (SIPEX). Voyage dates: ARISE: 10 Sep 2003 to 31 Oct 2003 ISPOL: 6 Nov 2004 to 19 Jan 2005 SIPEX: 29 Aug 2007 to 16 Oct 2007 SIPEX II: 25 Sep 2012 to 6 Nov 2012 The child records include the urls of web pages with information about these voyages, urls for requesting for the photographs and urls for downloading information about the photographs. proprietary
aerial_photo_sea_ice_1 Aerial photographs of sea ice flown by the Australian Antarctic Division AU_AADC STAC Catalog 2003-09-10 -58.2, -69.67, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1214305646-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during the following voyages: Australian Antarctic Division voyage 1 2003/04 - Antarctic Remote Ice Sensing Experiment (ARISE); Alfred Wegener Institute Ice Station Polarstern (ISPOL) voyage 2004/05; and Australian Antarctic Division voyage 1 2007/08 - Sea Ice Physics and Ecosystems Experiment (SIPEX). Voyage dates: ARISE: 10 Sep 2003 to 31 Oct 2003 ISPOL: 6 Nov 2004 to 19 Jan 2005 SIPEX: 29 Aug 2007 to 16 Oct 2007 SIPEX II: 25 Sep 2012 to 6 Nov 2012 The child records include the urls of web pages with information about these voyages, urls for requesting for the photographs and urls for downloading information about the photographs. proprietary
-aerial_photo_sea_ice_ARISE_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the ARISE voyage in 2003 ALL STAC Catalog 2003-09-10 2003-10-31 109.1, -66.7, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611591-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during Australian Antarctic Division voyage 1 2003/04 - Antarctic Remote Ice Sensing Experiment (ARISE), 10 Sep 2003 to 31 Oct 2003. The Related URLs in this metadata record include the urls of web pages with information about the voyage, urls for requesting for the photographs and urls for downloading information about the photographs. The ARISE aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. The collection can be searched in the Australian Antarctic Data Centre's Aerial Photograph Catalogue - see Related URLs. Select ARISE from the Aerial Photography Series picklist. Preview images of the photos may be viewed using this search. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. The flight lines and photo centres for ARISE are available for download as shapefiles - see metadata record ID: aerial_photo_sea_ice_shapefiles. proprietary
aerial_photo_sea_ice_ARISE_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the ARISE voyage in 2003 AU_AADC STAC Catalog 2003-09-10 2003-10-31 109.1, -66.7, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611591-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during Australian Antarctic Division voyage 1 2003/04 - Antarctic Remote Ice Sensing Experiment (ARISE), 10 Sep 2003 to 31 Oct 2003. The Related URLs in this metadata record include the urls of web pages with information about the voyage, urls for requesting for the photographs and urls for downloading information about the photographs. The ARISE aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. The collection can be searched in the Australian Antarctic Data Centre's Aerial Photograph Catalogue - see Related URLs. Select ARISE from the Aerial Photography Series picklist. Preview images of the photos may be viewed using this search. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. The flight lines and photo centres for ARISE are available for download as shapefiles - see metadata record ID: aerial_photo_sea_ice_shapefiles. proprietary
-aerial_photo_sea_ice_ISPOL_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the ISPOL voyage in 2004 ALL STAC Catalog 2004-11-06 2005-01-19 -58.2, -69.67, -55.2, -67.57 https://cmr.earthdata.nasa.gov/search/concepts/C1292611592-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during the voyage, Alfred Wegener Institute Ice Station Polarstern (ISPOL) voyage 2004/05, 6 Nov 2004 to 19 Jan 2005. Flights were conducted around the edges of a triangular array of drifting buoys each transmitting GPS location. Flights throughout the experiment show changes in the surface properties (floe size, extent of surface flooding) with time. See the metadata record 'AAD buoy data collected during ISPOL 2004, Western Weddell Sea' for more information on the ISPOL project. The Related URLs in this metadata record include the urls of web pages with information about the voyage, urls for requesting for the photographs and urls for downloading information about the photographs. The ISPOL aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. The collection can be searched in the Australian Antarctic Data Centre's Aerial Photograph Catalogue - see Related URLs. Select ISPOL from the Aerial Photography Series picklist. Preview images of the photos may be viewed using this search. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. The flight lines and photo centres for ISPOL are available for download as shapefiles - see metadata record ID: aerial_photo_sea_ice_shapefiles. proprietary
+aerial_photo_sea_ice_ARISE_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the ARISE voyage in 2003 ALL STAC Catalog 2003-09-10 2003-10-31 109.1, -66.7, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611591-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during Australian Antarctic Division voyage 1 2003/04 - Antarctic Remote Ice Sensing Experiment (ARISE), 10 Sep 2003 to 31 Oct 2003. The Related URLs in this metadata record include the urls of web pages with information about the voyage, urls for requesting for the photographs and urls for downloading information about the photographs. The ARISE aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. The collection can be searched in the Australian Antarctic Data Centre's Aerial Photograph Catalogue - see Related URLs. Select ARISE from the Aerial Photography Series picklist. Preview images of the photos may be viewed using this search. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. The flight lines and photo centres for ARISE are available for download as shapefiles - see metadata record ID: aerial_photo_sea_ice_shapefiles. proprietary
aerial_photo_sea_ice_ISPOL_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the ISPOL voyage in 2004 AU_AADC STAC Catalog 2004-11-06 2005-01-19 -58.2, -69.67, -55.2, -67.57 https://cmr.earthdata.nasa.gov/search/concepts/C1292611592-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during the voyage, Alfred Wegener Institute Ice Station Polarstern (ISPOL) voyage 2004/05, 6 Nov 2004 to 19 Jan 2005. Flights were conducted around the edges of a triangular array of drifting buoys each transmitting GPS location. Flights throughout the experiment show changes in the surface properties (floe size, extent of surface flooding) with time. See the metadata record 'AAD buoy data collected during ISPOL 2004, Western Weddell Sea' for more information on the ISPOL project. The Related URLs in this metadata record include the urls of web pages with information about the voyage, urls for requesting for the photographs and urls for downloading information about the photographs. The ISPOL aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. The collection can be searched in the Australian Antarctic Data Centre's Aerial Photograph Catalogue - see Related URLs. Select ISPOL from the Aerial Photography Series picklist. Preview images of the photos may be viewed using this search. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. The flight lines and photo centres for ISPOL are available for download as shapefiles - see metadata record ID: aerial_photo_sea_ice_shapefiles. proprietary
-aerial_photo_sea_ice_SIPEX_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the SIPEX voyage in 2007 ALL STAC Catalog 2007-08-29 2007-10-16 109.1, -66.7, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611658-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during Australian Antarctic Division voyage 1 2007/08 - Sea Ice Physics and Ecosystems Experiment (SIPEX). Voyage dates: SIPEX: 29 Aug 2007 to 16 Oct 2007 The Related URLs in this metadata record include the urls of web pages with information about these voyages, urls for requesting for the photographs and urls for downloading information about the photographs. Some of the SIPEX aerial photographs were taken at ice stations. Refer to the metadata record 'An integrated study of processes linking sea ice and biological ecosystem elements off East Antarctica during winter', Entry ID: ASAC_2767, for information about the ice stations. The metadata record 'RAPPLS Surveys (Radar, Aerial Photography, Pyrometer, and Laser Scanning system) made during the SIPEX II voyage of the Aurora Australis, 2012', Entry ID: SIPEX_II_RAPPLS, describes the aerial photography conducted on SIPEX II, 13 Sep 2012 to 15 Nov 2012. proprietary
+aerial_photo_sea_ice_ISPOL_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the ISPOL voyage in 2004 ALL STAC Catalog 2004-11-06 2005-01-19 -58.2, -69.67, -55.2, -67.57 https://cmr.earthdata.nasa.gov/search/concepts/C1292611592-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during the voyage, Alfred Wegener Institute Ice Station Polarstern (ISPOL) voyage 2004/05, 6 Nov 2004 to 19 Jan 2005. Flights were conducted around the edges of a triangular array of drifting buoys each transmitting GPS location. Flights throughout the experiment show changes in the surface properties (floe size, extent of surface flooding) with time. See the metadata record 'AAD buoy data collected during ISPOL 2004, Western Weddell Sea' for more information on the ISPOL project. The Related URLs in this metadata record include the urls of web pages with information about the voyage, urls for requesting for the photographs and urls for downloading information about the photographs. The ISPOL aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. The collection can be searched in the Australian Antarctic Data Centre's Aerial Photograph Catalogue - see Related URLs. Select ISPOL from the Aerial Photography Series picklist. Preview images of the photos may be viewed using this search. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. The flight lines and photo centres for ISPOL are available for download as shapefiles - see metadata record ID: aerial_photo_sea_ice_shapefiles. proprietary
aerial_photo_sea_ice_SIPEX_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the SIPEX voyage in 2007 AU_AADC STAC Catalog 2007-08-29 2007-10-16 109.1, -66.7, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611658-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during Australian Antarctic Division voyage 1 2007/08 - Sea Ice Physics and Ecosystems Experiment (SIPEX). Voyage dates: SIPEX: 29 Aug 2007 to 16 Oct 2007 The Related URLs in this metadata record include the urls of web pages with information about these voyages, urls for requesting for the photographs and urls for downloading information about the photographs. Some of the SIPEX aerial photographs were taken at ice stations. Refer to the metadata record 'An integrated study of processes linking sea ice and biological ecosystem elements off East Antarctica during winter', Entry ID: ASAC_2767, for information about the ice stations. The metadata record 'RAPPLS Surveys (Radar, Aerial Photography, Pyrometer, and Laser Scanning system) made during the SIPEX II voyage of the Aurora Australis, 2012', Entry ID: SIPEX_II_RAPPLS, describes the aerial photography conducted on SIPEX II, 13 Sep 2012 to 15 Nov 2012. proprietary
+aerial_photo_sea_ice_SIPEX_1 Aerial photographs of sea ice flown by the Australian Antarctic Division on the SIPEX voyage in 2007 ALL STAC Catalog 2007-08-29 2007-10-16 109.1, -66.7, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611658-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during Australian Antarctic Division voyage 1 2007/08 - Sea Ice Physics and Ecosystems Experiment (SIPEX). Voyage dates: SIPEX: 29 Aug 2007 to 16 Oct 2007 The Related URLs in this metadata record include the urls of web pages with information about these voyages, urls for requesting for the photographs and urls for downloading information about the photographs. Some of the SIPEX aerial photographs were taken at ice stations. Refer to the metadata record 'An integrated study of processes linking sea ice and biological ecosystem elements off East Antarctica during winter', Entry ID: ASAC_2767, for information about the ice stations. The metadata record 'RAPPLS Surveys (Radar, Aerial Photography, Pyrometer, and Laser Scanning system) made during the SIPEX II voyage of the Aurora Australis, 2012', Entry ID: SIPEX_II_RAPPLS, describes the aerial photography conducted on SIPEX II, 13 Sep 2012 to 15 Nov 2012. proprietary
aerial_photo_sea_ice_shapefiles_1 Flight lines and photo centres of aerial photographs of sea ice flown by the Australian Antarctic Division on the ARISE and ISPOL voyages in 2003 and 2004 AU_AADC STAC Catalog 2003-09-10 2005-01-19 -58.2, -69.67, 118.85, -64.03 https://cmr.earthdata.nasa.gov/search/concepts/C1292611653-AU_AADC.umm_json The Australian Antarctic Division acquired aerial photographs of sea ice from helicopters using a digital Nikon D1X digital camera during the following voyages: Australian Antarctic Division voyage 1 2003/04 - Antarctic Remote Ice Sensing Experiment (ARISE); Alfred Wegener Institute Ice Station Polarstern (ISPOL) voyage 2004/05. Voyage dates: ARISE: 10 Sep 2003 to 31 Oct 2003 ISPOL: 6 Nov 2004 to 19 Jan 2005 The ARISE and ISPOL aerial photographs of sea ice are part of the Australian Antarctic Data Centre's collection of aerial photographs which is described by the metadata record 'The collection of aerial photographs held by the Australian Antarctic Data Centre' with Entry ID: aerial_photo_gis. Digital flight lines and photo centres representing the runs along which the photographs were taken and the centres of the photographs are the basis of the catalogue. proprietary
-aerial_photographs_from_columbia_glacier_1976-2010 Aerial Photographs from Columbia Glacier, 1976-2010 SCIOPS STAC Catalog 1976-07-24 2011-06-15 -146.895, 61.22, -146.895, 61.22 https://cmr.earthdata.nasa.gov/search/concepts/C1214600568-SCIOPS.umm_json Aerial stereophotography missions were flown at least once every year over the Columbia Glacier in 1976-2010, and documented further in the Aerial Inventory. Flight data include all existing scans of the large format diapositives and their derived data products from 2002-2010.
This dataset consists of scanned aerial diapositives in high resolution from a photogrammetric scanner and low resolution JPEG previews. The data are collected into TAR files by year. Data gathered during 2002-2003 are collected into TAR files by day and part (e.g. 20020826_01.tar).
proprietary
aerial_photographs_from_columbia_glacier_1976-2010 Aerial Photographs from Columbia Glacier, 1976-2010 ALL STAC Catalog 1976-07-24 2011-06-15 -146.895, 61.22, -146.895, 61.22 https://cmr.earthdata.nasa.gov/search/concepts/C1214600568-SCIOPS.umm_json Aerial stereophotography missions were flown at least once every year over the Columbia Glacier in 1976-2010, and documented further in the Aerial Inventory. Flight data include all existing scans of the large format diapositives and their derived data products from 2002-2010.
This dataset consists of scanned aerial diapositives in high resolution from a photogrammetric scanner and low resolution JPEG previews. The data are collected into TAR files by year. Data gathered during 2002-2003 are collected into TAR files by day and part (e.g. 20020826_01.tar).
proprietary
+aerial_photographs_from_columbia_glacier_1976-2010 Aerial Photographs from Columbia Glacier, 1976-2010 SCIOPS STAC Catalog 1976-07-24 2011-06-15 -146.895, 61.22, -146.895, 61.22 https://cmr.earthdata.nasa.gov/search/concepts/C1214600568-SCIOPS.umm_json Aerial stereophotography missions were flown at least once every year over the Columbia Glacier in 1976-2010, and documented further in the Aerial Inventory. Flight data include all existing scans of the large format diapositives and their derived data products from 2002-2010.
This dataset consists of scanned aerial diapositives in high resolution from a photogrammetric scanner and low resolution JPEG previews. The data are collected into TAR files by year. Data gathered during 2002-2003 are collected into TAR files by day and part (e.g. 20020826_01.tar).
proprietary
aerial_rpa_nov2016_1 Aerial photographs of Davis and Heidemann Valley taken with Remotely Piloted Aircraft, November 2016 AU_AADC STAC Catalog 2016-11-07 2016-11-20 77.9619, -68.5811, 78.0131, -68.5731 https://cmr.earthdata.nasa.gov/search/concepts/C1367275166-AU_AADC.umm_json The Australian Antarcic Division (AAD) contracted Helicopter Resources to fly remotely piloted aircraft (RPA) on Voyage 1 2016/17. The RPA were used to take aerial photographs for sea ice reconnaisance from the RSV Aurora Australis, aerial photographs of Davis, aerial photographs for building roof inspections at Davis and aerial photographs of part of Heidemann Valley. Video was also recorded from the RSV Aurora Australis and of Heidemann Valley. The flights over Heidemann Valley were done at the request of the AAD's Antarctic Modernisation Taskforce. The roof inspections were done at the request of the AAD's Infrastructure section. The following can be downloaded or requested from this metadata record by AAD staff only (see Related URLs): 1 A report prepared by Doug Thost, the chief RPA pilot; 2 The aerial photographs of Davis and Heidemann Valley; and 3 Some panoramas created from aerial photographs taken at Davis. The AAD's Multimedia section have a copy of the videos. The AAD's Infrastructure section have a copy of the aerial photographs taken for roof inspections. See the report for further details. proprietary
aerial_rpa_nov2016_1 Aerial photographs of Davis and Heidemann Valley taken with Remotely Piloted Aircraft, November 2016 ALL STAC Catalog 2016-11-07 2016-11-20 77.9619, -68.5811, 78.0131, -68.5731 https://cmr.earthdata.nasa.gov/search/concepts/C1367275166-AU_AADC.umm_json The Australian Antarcic Division (AAD) contracted Helicopter Resources to fly remotely piloted aircraft (RPA) on Voyage 1 2016/17. The RPA were used to take aerial photographs for sea ice reconnaisance from the RSV Aurora Australis, aerial photographs of Davis, aerial photographs for building roof inspections at Davis and aerial photographs of part of Heidemann Valley. Video was also recorded from the RSV Aurora Australis and of Heidemann Valley. The flights over Heidemann Valley were done at the request of the AAD's Antarctic Modernisation Taskforce. The roof inspections were done at the request of the AAD's Infrastructure section. The following can be downloaded or requested from this metadata record by AAD staff only (see Related URLs): 1 A report prepared by Doug Thost, the chief RPA pilot; 2 The aerial photographs of Davis and Heidemann Valley; and 3 Some panoramas created from aerial photographs taken at Davis. The AAD's Multimedia section have a copy of the videos. The AAD's Infrastructure section have a copy of the aerial photographs taken for roof inspections. See the report for further details. proprietary
-aerial_surveys_vestfold_2017-18_1 Aerial surveys of Davis station and an area of the Vestfold Hills to the north-east of the station 2017/18 ALL STAC Catalog 2017-11-19 2018-01-31 77.8923, -68.6067, 78.2235, -68.4809 https://cmr.earthdata.nasa.gov/search/concepts/C1542262550-AU_AADC.umm_json "Three aerial surveys were flown by Helicopter Resources Pty Ltd for the Australian Antarctic Division's Antarctic Modernisation Taskforce during the 2017/18 field season. The photography was done from a helicopter and covered Davis station and an area of the Vestfold Hills to the north-east of the station. The first survey conducted on 19 November 2017 covered an inner higher resolution area with flying heights approximately 300 to 400 metres above sea level. The second survey conducted on 20 November 2017 covered a more extensive area at lower resolution with flying heights approximately 800 metres above sea level. The third survey was conducted on 31 January 2018 over a similar area to the first survey with flying heights approximately 300 to 400 metres above sea level. The report on the third survey states ""As a general comment, in comparison to Survey 1, this survey was flown more accurately, in better lighting conditions, with less snow cover, and by all statistical metrics has resulted in a higher quality survey overall."" The spatial extents given in this metadata record are for the second survey. For each survey there is zip file with a report and the following products generated from the survey data: (i) an orthophoto; (ii) a Digital Surface Model (DSM); and (iii) contours generated from the DSM. The products are stored in the UTM zone 44S coordinate system, based on the horizontal datum ITRF2000. Elevations are in metres above Mean Sea Level. There is also a separate zip file with the aerial photographs from the three surveys and a spreadsheet with latitude and longitude for each photo centre. Ground control points were used to constrain the DSM for each survey. One metre by one metre cross markers were set out across the survey area prior to the aerial surveys being flown. The centre of each cross was surveyed by Australian Defence Force surveyors Sam Kelly and Warwick Cox. Some permanent survey marks were used as an independent check of the overall accuracy of the DSM." proprietary
aerial_surveys_vestfold_2017-18_1 Aerial surveys of Davis station and an area of the Vestfold Hills to the north-east of the station 2017/18 AU_AADC STAC Catalog 2017-11-19 2018-01-31 77.8923, -68.6067, 78.2235, -68.4809 https://cmr.earthdata.nasa.gov/search/concepts/C1542262550-AU_AADC.umm_json "Three aerial surveys were flown by Helicopter Resources Pty Ltd for the Australian Antarctic Division's Antarctic Modernisation Taskforce during the 2017/18 field season. The photography was done from a helicopter and covered Davis station and an area of the Vestfold Hills to the north-east of the station. The first survey conducted on 19 November 2017 covered an inner higher resolution area with flying heights approximately 300 to 400 metres above sea level. The second survey conducted on 20 November 2017 covered a more extensive area at lower resolution with flying heights approximately 800 metres above sea level. The third survey was conducted on 31 January 2018 over a similar area to the first survey with flying heights approximately 300 to 400 metres above sea level. The report on the third survey states ""As a general comment, in comparison to Survey 1, this survey was flown more accurately, in better lighting conditions, with less snow cover, and by all statistical metrics has resulted in a higher quality survey overall."" The spatial extents given in this metadata record are for the second survey. For each survey there is zip file with a report and the following products generated from the survey data: (i) an orthophoto; (ii) a Digital Surface Model (DSM); and (iii) contours generated from the DSM. The products are stored in the UTM zone 44S coordinate system, based on the horizontal datum ITRF2000. Elevations are in metres above Mean Sea Level. There is also a separate zip file with the aerial photographs from the three surveys and a spreadsheet with latitude and longitude for each photo centre. Ground control points were used to constrain the DSM for each survey. One metre by one metre cross markers were set out across the survey area prior to the aerial surveys being flown. The centre of each cross was surveyed by Australian Defence Force surveyors Sam Kelly and Warwick Cox. Some permanent survey marks were used as an independent check of the overall accuracy of the DSM." proprietary
-aerosol-data-davos-wolfgang_1.0 Aerosol Data Davos Wolfgang ALL STAC Catalog 2020-01-01 2020-01-01 9.853594, 46.835577, 9.853594, 46.835577 https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.umm_json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. proprietary
+aerial_surveys_vestfold_2017-18_1 Aerial surveys of Davis station and an area of the Vestfold Hills to the north-east of the station 2017/18 ALL STAC Catalog 2017-11-19 2018-01-31 77.8923, -68.6067, 78.2235, -68.4809 https://cmr.earthdata.nasa.gov/search/concepts/C1542262550-AU_AADC.umm_json "Three aerial surveys were flown by Helicopter Resources Pty Ltd for the Australian Antarctic Division's Antarctic Modernisation Taskforce during the 2017/18 field season. The photography was done from a helicopter and covered Davis station and an area of the Vestfold Hills to the north-east of the station. The first survey conducted on 19 November 2017 covered an inner higher resolution area with flying heights approximately 300 to 400 metres above sea level. The second survey conducted on 20 November 2017 covered a more extensive area at lower resolution with flying heights approximately 800 metres above sea level. The third survey was conducted on 31 January 2018 over a similar area to the first survey with flying heights approximately 300 to 400 metres above sea level. The report on the third survey states ""As a general comment, in comparison to Survey 1, this survey was flown more accurately, in better lighting conditions, with less snow cover, and by all statistical metrics has resulted in a higher quality survey overall."" The spatial extents given in this metadata record are for the second survey. For each survey there is zip file with a report and the following products generated from the survey data: (i) an orthophoto; (ii) a Digital Surface Model (DSM); and (iii) contours generated from the DSM. The products are stored in the UTM zone 44S coordinate system, based on the horizontal datum ITRF2000. Elevations are in metres above Mean Sea Level. There is also a separate zip file with the aerial photographs from the three surveys and a spreadsheet with latitude and longitude for each photo centre. Ground control points were used to constrain the DSM for each survey. One metre by one metre cross markers were set out across the survey area prior to the aerial surveys being flown. The centre of each cross was surveyed by Australian Defence Force surveyors Sam Kelly and Warwick Cox. Some permanent survey marks were used as an independent check of the overall accuracy of the DSM." proprietary
aerosol-data-davos-wolfgang_1.0 Aerosol Data Davos Wolfgang ENVIDAT STAC Catalog 2020-01-01 2020-01-01 9.853594, 46.835577, 9.853594, 46.835577 https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.umm_json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. proprietary
-aerosol-data-weissfluhjoch_1.0 Aerosol Data Weissfluhjoch ALL STAC Catalog 2020-01-01 2020-01-01 9.806475, 46.832964, 9.806475, 46.832964 https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.umm_json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. proprietary
+aerosol-data-davos-wolfgang_1.0 Aerosol Data Davos Wolfgang ALL STAC Catalog 2020-01-01 2020-01-01 9.853594, 46.835577, 9.853594, 46.835577 https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.umm_json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. proprietary
aerosol-data-weissfluhjoch_1.0 Aerosol Data Weissfluhjoch ENVIDAT STAC Catalog 2020-01-01 2020-01-01 9.806475, 46.832964, 9.806475, 46.832964 https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.umm_json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. proprietary
+aerosol-data-weissfluhjoch_1.0 Aerosol Data Weissfluhjoch ALL STAC Catalog 2020-01-01 2020-01-01 9.806475, 46.832964, 9.806475, 46.832964 https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.umm_json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. proprietary
aerosol_properties_725_1 SAFARI 2000 Physical and Chemical Properties of Aerosols, Dry Season 2000 ORNL_CLOUD STAC Catalog 2000-08-17 2000-09-13 5, -35, 60, 5 https://cmr.earthdata.nasa.gov/search/concepts/C2789011485-ORNL_CLOUD.umm_json SAFARI 2000 provided an opportunity to study aerosol particles produced by savanna burning. We used analytical transmission electron microscopy (TEM), including energy-dispersive X-ray spectrometry (EDS) and electron energy-loss spectroscopy (EELS), to study aerosol particles from several smoke and haze samples and from a set of cloud samples. These aerosol particle samples were collected using the University of Washington Convair CV-580 research aircraft (Posfai et al., 2003). proprietary
aes5davg_236_1 BOREAS AES Five-day Averaged Surface Meteorological and Upper Air Data ORNL_CLOUD STAC Catalog 1976-01-01 1997-01-01 -107.87, 52.17, -97.83, 57.35 https://cmr.earthdata.nasa.gov/search/concepts/C2807614663-ORNL_CLOUD.umm_json Contains 5-day averages of hourly and daily data from 23 meteorological stations across Canada along with full-resolution upper air measurements from 1 station in The Pas, Manitoba. proprietary
aes_upl1_238_1 BOREAS AFM-05 Level-1 Upper Air Network Data, R1 ORNL_CLOUD STAC Catalog 1993-08-16 1996-10-22 -111, 50.09, -93.5, 59.98 https://cmr.earthdata.nasa.gov/search/concepts/C2812433046-ORNL_CLOUD.umm_json Contains basic upper-air parameters collected by the AFM-05 team from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. proprietary
@@ -17142,8 +17143,8 @@ agricultural-biogas-plants-to-foster-circular-economy-and-bioenergy_1.0 Agricult
agricultural-biogas-plants-to-foster-circular-economy-and-bioenergy_1.0 Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using substance and energy flow analysis ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081749-ENVIDAT.umm_json "Supplementary material for the publication "" Agricultural biogas plants as a hub to foster circular economy and bioenergy: An assessment using material substance and energy flow analysis"" Burg, V., b, Rolli, C., Schnorf, V., Scharfy, D., Anspach, V., Bowman, G. Today's agro-food system is typically based on linear fluxes (e.g. mineral fertilizers importation), when a circular approach should be privileged. The production of biogas as a renewable energy source and digestate, used as an organic fertilizer, is essential for the circular economy in the agricultural sector. This study investigates the current utilization of wet biomass in agricultural anaerobic digestion plants in Switzerland in terms of mass, nutrients, and energy flows, to see how biomass use contributes to circular economy and climate change mitigation through the substitution effect of mineral fertilizers and fossil fuels. We quantify the system and its benefits in details and examine future developments of agricultural biogas plants using different scenarios. Our results demonstrate that agricultural anaerobic digestion could be largely increased, as it could provide ten times more biogas by 2050, while saving significant amounts of mineral fertilizer and GHG emissions." proprietary
air_methane_lawdome_1 Dated Readings For Air Composition And Methane From Law Dome Ice Core AU_AADC STAC Catalog 1988-01-01 1993-12-31 112.8, -66.771, 112.81, -66.77 https://cmr.earthdata.nasa.gov/search/concepts/C1214311761-AU_AADC.umm_json "This work was completed as part of ASAC project 757 (ASAC_757). This file comprises three main records compiled for publication in the following: V. Morgan, M. Delmotte, T. van Ommen, J. Jouzel, J. Chappellaz, S. Woon, V. Masson-Delmotte and D. Raynaud. Relative Timing of Deglacial Climate Events in Antarctica and Greenland, Science, 13 September 2002, Vol 297 (5588), pp. 1862-1864, DOI: 10.1126/science.1074257. Supporting Material - http://www.sciencemag.org/cgi/content/full/sci;297/5588/1862/DC1 Law Dome is a small (200 km in diameter) ice sheet located at the edge of the Indian Ocean sector of East Antarctica. The core site, near the summit of Law Dome (66 degrees 46'S, 112 degrees 48'E), is characterised by a high rate of accumulation (late Holocene average, 0.68 m ice equivalent per year) that results in an ice core with a highly tapered time scale in which the Holocene represents some 93% of the ice thickness of 1200 m. However, the full Law Dome isotopic record generally matches the long records from Vostok and Byrd to at least 80 ka, indicating that the record is continuous and undisturbed over this period. The Law Dome record is suited to gas-synchronisation studies because the high accumulation rate and consequent rapid burial give a small age difference (Delta age) between trapped air and the older enclosing ice. Derivation of an age scale for the Law Dome core, is based upon a Dansgaard- Johnsen flow model (S1) matched to the observed layer thinning (S2). Continuously sampled seasonal cycles down to ~1/3 ice-thickness (~1ky) and spot measurements of seasonal layers to ~85% ice-thickness (~4 ky) constrain the ice-flow model through this period in which mean accumulation is assumed to be free of large trends. Chronological control in the lower portion of the ice-sheet prior to 4 ky is through ties to other records. For the period of discussion, namely 10 ky to 17 ky, ties at 9.6 ky, 11.0 ky, 11.6 ky, 12.5 ky, 12.8 ky, 14.3 ky and 16.3 ky, are obtained by matching air composition changes with those of GRIP. The 9.6 ky tie is obtained by matching to d18O of air in GRIP (S3) and GISP2 (S4) data, and the remainder synchronise with the Byrd and GRIP CH4 records (S5). Dust concentration data also provide additional constraints on the 16.3 ky tie. Beyond 16.3 ky control is by a tie at 32 ky (based on both dust and d18Oice matched to the Byrd ice core (S6) on the GRIP timescale (S5)). The mean temporal resolution of the LD isotope data is ~24y through this period. The air-composition age-ties require Delta age computations for sequencing events within the LD record and for synchronisation of the chronology with GRIP. The high accumulation at DSS results in a particularly small Delta age value. The modern difference between ice-age and gas-age is 60 plus or minus 2 years for methane (S7). Note that at such low Delta age values, the diffusive mixing time from the free atmosphere down to seal-off depth becomes significant and must be accounted for; in the case of CH4 this is ~8 years (S7). The absolute chronology derived for the LD record has contributions from both the LD and GRIP Delta age errors, but the relative timing between the LD CH4 and water isotope (d18Oice) signals is only uncertain to within the small errors associated with LD Delta age. While the present-day trapping age at LD is small, lower temperatures and accumulation rates during the deglaciation lead to longer trapping times. To estimate Delta age under past conditions, we use a model (S8) to compute trapping age from accumulation and temperature (this model agrees with precise experimentally determined present day values). Since we have no direct indicators for palaeoaccumulation and palaeotemperature, we adopt two scenarios that use alternative estimation methods. Estimation of palaeotemperature from the isotope data in both scenarios is by application of a calibration slope, ""Beta ppt/degrees C"". For the young chronology, which has minimum Delta age, the commonly applied spatial slope of Beta=0.67 ppt/degrees C is used, giving relatively warm temperatures. The default chronology uses a long-term temporal calibration (S9) for Law Dome, Beta=0.44 ppt/degrees C. This estimate, which is seasonally derived, gives greater temperature sensitivity for isotopic changes than the spatial slope. The use of this lower value for Beta is supported by direct comparisons between annual averages in d18O and temperature at the site and elsewhere on Law Dome. Over several years to a few decades, these yield coefficients of typically ~0.33 ppt/degrees C. We adopt the value 0.44 ppt/degrees C as a conservative choice, based on a longer-term calibration and because the incorporation of seasonal sea-ice variations may better capture glacial-to- Holocene environmental shifts. Estimation of palaeoaccumulation for the young chronology is via the commonly applied method (see, e.g. S5) that scales modern accumulation-rate using the derivative of saturation vapour-pressure versus temperature relationship (also using Beta=0.67 ppt/degrees C). This method explicitly assumes no non-thermodynamic changes to moisture transport during climate variations (such as, e.g., atmospheric circulation changes) that may be important at this near-coastal location. Our alternative palaeoaccumulation estimate used for the default chronology assumes that the flow-model is correct and infers accumulation from the known age-intervals between the gas ties. This leads to considerably larger changes in accumulation which may nonetheless be understandable given the distinctively high Holocene precipitation regime that prevails at Law Dome. In addition, dust concentration data show a larger LGM to Holocene decrease at LD than Vostok. If relative flux changes at the two sites are similar, then the exaggerated dilution at LD is consistent with a large interglacial accumulation shift. Trapped gas measurements were made in France: CH4 measurements at LGGE, Grenoble and d18Oair measurements at LSCE, Saclay. Both analyses were conducted using a wet extraction procedure to release the air of the ice and followed by an injection into a gas chromatograph (CH4 measurement) or by a mass spectrometer isotopic analysis (d18Oair measurements). Both analyses were conducted using established procedures (S10,S11). The methane analytical uncertainty is plus or minus 20 ppbv with values were obtained on a single measurement (in which the sample was exhausted) and are presented on the LGGE scale which differs slightly from the NOAA scale but is well calibrated against it: LGGE = 1.02*NOAA (S12). The d18Oair values arise from means of duplicate measurements (except for one point with an obvious experimental problem, 1127.492 m depth). The analytical precision for d18Oair is around 0.05 ppt with a mean reproducibility of about 0.1 ppt. d18Oice measurements were made in Hobart and have an analytical precision of approximately 0.1 ppt. The results are expressed using the conventional reference of VSMOW (Vienna Standard Mean Ocean Water). Supporting References and Notes S1. W. Dansgaard, S. J. Johnsen, J. Glaciol., 8, 215 (1969). S2. V. Morgan et al., J. Glaciol., 43, 3 (1997). S3. M. Cross, (Compiler) Greenland summit ice cores CD-ROM. Boulder, CO: National Snow and Ice Data Center in association with the World Data Center for Paleoclimatology at NOAA-NGDC, and the Institute of Arctic and Alpine Research (1997). S4. M. Bender et al., Nature 372, 663-666 (1994). S5. T. Blunier, et al., Nature 394, 739 (1998). S6. S. J. Johnsen, W. Dansgaard, H. B. Clausen, C. C. Langway, Nature, 235, 429 (1972). S7. D. M. Etheridge et al., J. Geophys. Res., 101, 4115 (1996). S8. J.-M. Barnola, P. Pimienta, D. Raynaud, Y. S. Korotkevich, Tellus Ser. B, 43, 83 (1991). S9. T. D. van Ommen, V. Morgan, J. Geophys. Res., 102, 9351 (1997). S10. J. Chappellaz, et al., J. Geophys. Res., 102, 15987, (1997). S11. B. Malaize, Analyse isotopique de l'oxygene de l'air piege dans les glaces de l'Antarctique et du Groenland: correlation inter-hemispheriques et effet Dole, PhD thesis, University Paris 6, (1998). S12. T. Sowers et al, J. Geophys. Res., 102, 26527, (1997)." proprietary
air_sea_gas_exchange_xdeg_1208_1 ISLSCP II Air-Sea Carbon Dioxide Gas Exchange ORNL_CLOUD STAC Catalog 1995-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2785340637-ORNL_CLOUD.umm_json This data set contains the calculated net ocean-air carbon dioxide (CO2) flux and sea-air CO2 partial pressure (pCO2) difference. The estimates are based on approximately one million measurements made for the pCO2 in surface waters of the global ocean since the International Geophysical Year, 1956-1959. Only the ocean water pCO2 values measured using direct gas-seawater equilibration methods were used. The results represent the climatological distributions under non-El Nino conditions. Since the measurements were made in different years, during which the atmospheric pCO2 was increasing, they were corrected to a single reference year (arbitrarily chosen to be 1995) on the basis of the following assumptions: -Surface waters in subtropical gyres mix vertically at slow rates with subsurface waters due to the presence of strong stratification at the base of the mixed layer. This will allow a long contact time with the atmosphere to exchange CO2. Therefore, their CO2 chemistry tends to follow the atmospheric CO2 increase. Accordingly, the pCO2 measured in a given month and year is corrected to the same month of the reference year 1995 using changes in the atmospheric CO2 concentration occurred during this period.-Oceanic pCO2 measurements made after the beginning of 1979 have been corrected to 1995 using the atmospheric CO2 concentration data from the GLOBALVIEW-CO2 database (2000), in which the zonal mean atmospheric concentrations (for each 0.05 in sine of latitude) within the planetary boundary layer are summarized for each month since 1979 to 2000.-Pre-1979 oceanic pCO2 data were corrected to 1979 using the annual mean trend for the global mean atmospheric CO2 concentration constructed from the Mauna Loa data of Keeling and Whorf (2000), and then from 1979 to 1995 using the GLOBALVIEW-CO2 database. -Measurements for pCO2 made in the following areas have been corrected for the time of observation; 45 degrees N, 50 degrees S, in the Atlantic Ocean, north of 50 degrees S in the Indian Ocean, 40 degrees N, 50 degrees S in the western Pacific west of the date line, and 40 degrees N, 60 degrees S, in the eastern Pacific east of the date line. proprietary
-air_temperature_observations_in_the_arctic_1979-2004 Air Temperature Observations in the Arctic 1979-2004 ALL STAC Catalog 1979-01-01 2005-12-01 -180, 14.5, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600622-SCIOPS.umm_json The statistics of surface air temperature observations obtained from buoys, manned drifting stations, and meteorological land stations in the Arctic during 1979-2004 are analyzed. Although the basic statistics agree with what has been published in various climatologies, the seasonal correlation length scales between the observations are shorter than the annual correlation length scales, especially during summer when the inhomogeneity between the ice-covered ocean and the land is most apparent. During autumn, winter, and spring, the monthly mean correlation length scales are approximately constant at about 1000 km; during summer, the length scales are much shorter, i.e. as low as 300 km. These revised scales are particularly important in the optimal interpolation of data on surface air temperature (SAT) and are used in the analysis of an improved SAT dataset called IABP/POLES. Compared to observations from land stations and the Russian North Pole drift stations, the IABP/POLES dataset has higher correlations and lower rms errors than previous SAT fields and provides better temperature estimates, especially during summer in the marginal ice zones. In addition, the revised correlation length scales allow data taken at interior land stations to be included in the optimal interpretation analysis without introducing land biases to grid points over the ocean. The new analysis provides 12-hour fields of air temperatures on a 100-km rectangular grid for all land and ocean areas of the Arctic region for the years 1979-2004. proprietary
air_temperature_observations_in_the_arctic_1979-2004 Air Temperature Observations in the Arctic 1979-2004 SCIOPS STAC Catalog 1979-01-01 2005-12-01 -180, 14.5, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600622-SCIOPS.umm_json The statistics of surface air temperature observations obtained from buoys, manned drifting stations, and meteorological land stations in the Arctic during 1979-2004 are analyzed. Although the basic statistics agree with what has been published in various climatologies, the seasonal correlation length scales between the observations are shorter than the annual correlation length scales, especially during summer when the inhomogeneity between the ice-covered ocean and the land is most apparent. During autumn, winter, and spring, the monthly mean correlation length scales are approximately constant at about 1000 km; during summer, the length scales are much shorter, i.e. as low as 300 km. These revised scales are particularly important in the optimal interpolation of data on surface air temperature (SAT) and are used in the analysis of an improved SAT dataset called IABP/POLES. Compared to observations from land stations and the Russian North Pole drift stations, the IABP/POLES dataset has higher correlations and lower rms errors than previous SAT fields and provides better temperature estimates, especially during summer in the marginal ice zones. In addition, the revised correlation length scales allow data taken at interior land stations to be included in the optimal interpretation analysis without introducing land biases to grid points over the ocean. The new analysis provides 12-hour fields of air temperatures on a 100-km rectangular grid for all land and ocean areas of the Arctic region for the years 1979-2004. proprietary
+air_temperature_observations_in_the_arctic_1979-2004 Air Temperature Observations in the Arctic 1979-2004 ALL STAC Catalog 1979-01-01 2005-12-01 -180, 14.5, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600622-SCIOPS.umm_json The statistics of surface air temperature observations obtained from buoys, manned drifting stations, and meteorological land stations in the Arctic during 1979-2004 are analyzed. Although the basic statistics agree with what has been published in various climatologies, the seasonal correlation length scales between the observations are shorter than the annual correlation length scales, especially during summer when the inhomogeneity between the ice-covered ocean and the land is most apparent. During autumn, winter, and spring, the monthly mean correlation length scales are approximately constant at about 1000 km; during summer, the length scales are much shorter, i.e. as low as 300 km. These revised scales are particularly important in the optimal interpolation of data on surface air temperature (SAT) and are used in the analysis of an improved SAT dataset called IABP/POLES. Compared to observations from land stations and the Russian North Pole drift stations, the IABP/POLES dataset has higher correlations and lower rms errors than previous SAT fields and provides better temperature estimates, especially during summer in the marginal ice zones. In addition, the revised correlation length scales allow data taken at interior land stations to be included in the optimal interpretation analysis without introducing land biases to grid points over the ocean. The new analysis provides 12-hour fields of air temperatures on a 100-km rectangular grid for all land and ocean areas of the Arctic region for the years 1979-2004. proprietary
airmoss_chamela_mexico USGS AirMOSS - Chamela, Mexico USGS_LTA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567952-USGS_LTA.umm_json North American ecosystems are critical components of the global carbon cycle, exchanging large amounts of carbon dioxide and other gases with the atmosphere. Net ecosystem exchange (NEE) quantifies these carbon fluxes, but current continental-scale estimates contain high levels of uncertainty. Root-zone soil moisture (RZSM) and its spatial and temporal hetergeneity influence NEE and contribute as much as 60-80 percent to the uncertainty. Energy and CO2 Fluxes have been monitored from 1997 to 2007 using Bowen Ratio technique, and since spring of 2004 with eddy covariance. proprietary
airscm3b_448_1 BOREAS RSS-16 Level-3b DC-8 AIRSAR CM Images ORNL_CLOUD STAC Catalog 1993-08-12 1995-07-31 -110.05, 50.57, -94.08, 59.34 https://cmr.earthdata.nasa.gov/search/concepts/C2929127558-ORNL_CLOUD.umm_json Satellite and aircraft SAR data used in conjunction with various ground measurements to determine the moisture regime of the boreal forest. The NASA JPL AIRSAR is a side-looking imaging radar system that utilizes the SAR principle to obtain high-resolution images that represent the radar backscatter of the imaged surface at different frequencies and polarizations. The information contained in each pixel of the AIRSAR data represents the radar backscatter for all possible combinations of horizontal and vertical transmit and receive polarizations (i.e., HH, HV, VH, and VV). proprietary
airscpex_1 Atmospheric Infrared Sounder (AIRS) CPEX GHRC_DAAC STAC Catalog 2017-05-11 2017-07-16 -130.881382, -18.2515803, -14.6008026, 64.1143891 https://cmr.earthdata.nasa.gov/search/concepts/C2721994875-GHRC_DAAC.umm_json The Atmospheric Infrared Sounder (AIRS) CPEX dataset contains products obtained from the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. These data were collected in support of the NASA Convective Processes Experiment (CPEX) field campaign. The CPEX field campaign took place in the North Atlantic-Gulf of Mexico-Caribbean Sea region and conducted a total of sixteen DC-8 missions from May through June 2017. The CPEX campaign collected data to help explain convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data are available from May 11, 2017 through July 16, 2017 and are available in HDF-4 format. proprietary
@@ -17154,8 +17155,8 @@ alaska_census_regional_database Alaska Census Regional Database ALL STAC Catalog
alaska_census_regional_database Alaska Census Regional Database SCIOPS STAC Catalog 1970-01-01 2000-01-01 -129, 50, 169, 71 https://cmr.earthdata.nasa.gov/search/concepts/C1214602419-SCIOPS.umm_json 1970-2000 decennial census results by 27 census areas conformed to 2000 Census geography. Dataset consists of 611 variables covering demography, employment, education, income, mobility, and housing. proprietary
alaskan_air_ground_snow_and_soil_temperatures__1998-2005 Alaskan Air Ground Snow and Soil Temperatures 1998-2005 ALL STAC Catalog 1998-08-29 2007-11-30 -164.761, 64.919, -148.6, 70.439 https://cmr.earthdata.nasa.gov/search/concepts/C1214600491-SCIOPS.umm_json This data set contains air and ground temperature measurements collected from three different regions, each with multiple sites. The regions sampled are North Slope, Council, and Ivotuk. Early measurements were taken as part of the Land-Atmosphere-Ice Interactions - Arctic Transitions in the Land-Atmosphere System (LAII-ATLAS) program. The research project was funded by the Arctic System Sciences (ARCSS) Program, grant numbers OPP-9721347, OPP-9870635, and OPP-9732126 proprietary
alaskan_air_ground_snow_and_soil_temperatures__1998-2005 Alaskan Air Ground Snow and Soil Temperatures 1998-2005 SCIOPS STAC Catalog 1998-08-29 2007-11-30 -164.761, 64.919, -148.6, 70.439 https://cmr.earthdata.nasa.gov/search/concepts/C1214600491-SCIOPS.umm_json This data set contains air and ground temperature measurements collected from three different regions, each with multiple sites. The regions sampled are North Slope, Council, and Ivotuk. Early measurements were taken as part of the Land-Atmosphere-Ice Interactions - Arctic Transitions in the Land-Atmosphere System (LAII-ATLAS) program. The research project was funded by the Arctic System Sciences (ARCSS) Program, grant numbers OPP-9721347, OPP-9870635, and OPP-9732126 proprietary
-albedo_line_snow_depths Albedo Line Snow Depths SCIOPS STAC Catalog 2009-04-27 2009-04-28 -157, 71, -156, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214600343-SCIOPS.umm_json Snow depth measurements recorded every half meter along the transects used for albedo measurements using a GPS magnaprobe. Included in the file are latitude, longitude, and snow depth. The first set of columns are at the south site, the second set are at the north site. Note that the south site was surveyed first along the line every half meter, and then a large dune field north of the line was extensively surveyed. Data Citation: Eicken, H., R. Gradinger, T. Heinrichs, M. Johnson, A. Lovecraft, and M. Sturm. (Nov. 29, 2009, Updated May 9, 2012). Albedo Line Snow Depths (SIZONET). UCAR/NCAR - CISL - ACADIS. http://dx.doi.org/10.5065/D6057CV2 proprietary
albedo_line_snow_depths Albedo Line Snow Depths ALL STAC Catalog 2009-04-27 2009-04-28 -157, 71, -156, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214600343-SCIOPS.umm_json Snow depth measurements recorded every half meter along the transects used for albedo measurements using a GPS magnaprobe. Included in the file are latitude, longitude, and snow depth. The first set of columns are at the south site, the second set are at the north site. Note that the south site was surveyed first along the line every half meter, and then a large dune field north of the line was extensively surveyed. Data Citation: Eicken, H., R. Gradinger, T. Heinrichs, M. Johnson, A. Lovecraft, and M. Sturm. (Nov. 29, 2009, Updated May 9, 2012). Albedo Line Snow Depths (SIZONET). UCAR/NCAR - CISL - ACADIS. http://dx.doi.org/10.5065/D6057CV2 proprietary
+albedo_line_snow_depths Albedo Line Snow Depths SCIOPS STAC Catalog 2009-04-27 2009-04-28 -157, 71, -156, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1214600343-SCIOPS.umm_json Snow depth measurements recorded every half meter along the transects used for albedo measurements using a GPS magnaprobe. Included in the file are latitude, longitude, and snow depth. The first set of columns are at the south site, the second set are at the north site. Note that the south site was surveyed first along the line every half meter, and then a large dune field north of the line was extensively surveyed. Data Citation: Eicken, H., R. Gradinger, T. Heinrichs, M. Johnson, A. Lovecraft, and M. Sturm. (Nov. 29, 2009, Updated May 9, 2012). Albedo Line Snow Depths (SIZONET). UCAR/NCAR - CISL - ACADIS. http://dx.doi.org/10.5065/D6057CV2 proprietary
ali_etm_tandem_821_1 SAFARI 2000 ALI/ETM+ Tandem Image Pair for Skukuza, South Africa, May 2001 ORNL_CLOUD STAC Catalog 2001-05-30 2001-05-30 30.76, -25.5, 33.12, -23.59 https://cmr.earthdata.nasa.gov/search/concepts/C2789740161-ORNL_CLOUD.umm_json A tandem pair of Advanced Land Imager (ALI) and Landsat Enhanced Thematic Mapper Plus (ETM+) scenes covering the same part of Kruger National Park (KNP), South Africa (including the Skukuza tower site and rest camp), were acquired about a minute apart on May 30, 2001. The ALI is one of three instruments aboard NASA's first New Millennium Program Earth Observing 1 (EO-1) satellite. ALI is a technology validation testbed that employs novel wide-angle optics and a highly integrated multispectral and panchromatic spectroradiometer.The tandem pair was produced to evaluate the differences between ALI and ETM+ and determine if technology similar to that of the ALI is suitable for future land imaging that will continue the observations begun by the Landsat satellites in 1972.The ALI and ETM+ images are false color composites combining shortwave infrared, near infrared, and visible wavelengths, displayed as red, green, and blue, respectively. Dense vegetation appears green. The similarity of the images demonstrates the ability of the ALI to produce data comparable to ETM+. Several SAFARI 2000 field campaigns conducted in KNP provided ground-based data needed to evaluate measurements from the satellite sensors.Each band is stored as an individual binary file. A metadata file accompanies each set of ALI and ETM+ band files to document the path and row number, sample and line counts, band file names, and sun azimuth and elevation angles. There is also a calibration parameter file that was used for 1R processing. proprietary
allADCP_GB Acoustic Doppler Current Profiler (ADCP) observations, Georges Bank area, April-June 1995, GLOBEC. SCIOPS STAC Catalog 1995-04-25 1995-06-16 -68, 40.5, -67, 41.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214155092-SCIOPS.umm_json Acoustic Doppler Current Profiler (ADCP) observations, were collected from the R/V Seward Johnson on two cruises to the Georges Bank region, April-June 1995. Three different ADCP units were used: two broadband at 150 and 600 kHz, and one narrowband at 150 kHz. The broadband 150 kHz unit was used at anchor stations with data reported at hourly intervals. The broad-band 600 kHz and narrow-band 150 kHz units collected data in the along track mode with data reported at five minute intervals. For each time interval, the u and v components of currents are reported at uniform depth intervals throughout the water column. Ship cruise dates R/V Seward Johnson 9506 1995 04 25 1995 05 02 R/V Seward Johnson 9508 1995 06 06 1995 06 16 proprietary
allADCP_GB Acoustic Doppler Current Profiler (ADCP) observations, Georges Bank area, April-June 1995, GLOBEC. ALL STAC Catalog 1995-04-25 1995-06-16 -68, 40.5, -67, 41.5 https://cmr.earthdata.nasa.gov/search/concepts/C1214155092-SCIOPS.umm_json Acoustic Doppler Current Profiler (ADCP) observations, were collected from the R/V Seward Johnson on two cruises to the Georges Bank region, April-June 1995. Three different ADCP units were used: two broadband at 150 and 600 kHz, and one narrowband at 150 kHz. The broadband 150 kHz unit was used at anchor stations with data reported at hourly intervals. The broad-band 600 kHz and narrow-band 150 kHz units collected data in the along track mode with data reported at five minute intervals. For each time interval, the u and v components of currents are reported at uniform depth intervals throughout the water column. Ship cruise dates R/V Seward Johnson 9506 1995 04 25 1995 05 02 R/V Seward Johnson 9508 1995 06 06 1995 06 16 proprietary
@@ -17186,12 +17187,12 @@ ams_cs93_403_1 BOREAS/AES Campbell Scientific 15-minute Surface Meteorological D
ams_cs94_404_1 BOREAS/AES Campbell Scientific 15-minute Surface Meteorological Data: 1994 ORNL_CLOUD STAC Catalog 1994-01-01 1994-12-31 -108.52, 50.95, -94.7, 58.18 https://cmr.earthdata.nasa.gov/search/concepts/C2808090015-ORNL_CLOUD.umm_json Contains data from 1994 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS. proprietary
ams_cs95_405_1 BOREAS/AES Campbell Scientific 15-minute Surface Meteorological Data: 1995 ORNL_CLOUD STAC Catalog 1995-01-01 1995-12-31 -108.52, 50.95, -94.7, 58.18 https://cmr.earthdata.nasa.gov/search/concepts/C2808090046-ORNL_CLOUD.umm_json Contains data from 1995 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS. proprietary
ams_cs96_406_1 BOREAS/AES Campbell Scientific 15-minute Surface Meteorological Data: 1996 ORNL_CLOUD STAC Catalog 1996-01-01 1996-12-31 -108.52, 50.95, -94.7, 58.18 https://cmr.earthdata.nasa.gov/search/concepts/C2808090091-ORNL_CLOUD.umm_json Contains data from 1996 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS. proprietary
-amsua15sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15 ALL STAC Catalog 1998-08-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NOAA-15 was the first spacecraft to fly AMSU. Launched on 13 May 1998, NOAA-15 is in a sun synchronous near polar orbit. proprietary
amsua15sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15 GHRC_DAAC STAC Catalog 1998-08-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NOAA-15 was the first spacecraft to fly AMSU. Launched on 13 May 1998, NOAA-15 is in a sun synchronous near polar orbit. proprietary
+amsua15sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15 ALL STAC Catalog 1998-08-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NOAA-15 was the first spacecraft to fly AMSU. Launched on 13 May 1998, NOAA-15 is in a sun synchronous near polar orbit. proprietary
amsua16sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-16 ALL STAC Catalog 2001-05-27 2009-07-30 -180, -89.91, 180, 89.73 https://cmr.earthdata.nasa.gov/search/concepts/C1979956366-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). Launched on 21 September 2000, NOAA-16 is in a sun synchronous near polar orbit. proprietary
amsua16sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-16 GHRC_DAAC STAC Catalog 2001-05-27 2009-07-30 -180, -89.91, 180, 89.73 https://cmr.earthdata.nasa.gov/search/concepts/C1979956366-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). Launched on 21 September 2000, NOAA-16 is in a sun synchronous near polar orbit. proprietary
-amsua17sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-17 GHRC_DAAC STAC Catalog 2002-07-21 2003-12-13 -180, -89.575, 180, 89.629 https://cmr.earthdata.nasa.gov/search/concepts/C1979975136-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Third Advanced Microwave Sounding Unit-A was launched on NOAA-17 on 24 June 2002 from Vandenberg AFB, California on a Titan II booster. proprietary
amsua17sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-17 ALL STAC Catalog 2002-07-21 2003-12-13 -180, -89.575, 180, 89.629 https://cmr.earthdata.nasa.gov/search/concepts/C1979975136-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Third Advanced Microwave Sounding Unit-A was launched on NOAA-17 on 24 June 2002 from Vandenberg AFB, California on a Titan II booster. proprietary
+amsua17sp_1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-17 GHRC_DAAC STAC Catalog 2002-07-21 2003-12-13 -180, -89.575, 180, 89.629 https://cmr.earthdata.nasa.gov/search/concepts/C1979975136-GHRC_DAAC.umm_json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Third Advanced Microwave Sounding Unit-A was launched on NOAA-17 on 24 June 2002 from Vandenberg AFB, California on a Titan II booster. proprietary
anezet-analysing-net-zero-transformations_1.0 ANEZET: Analysing Net-Zero Transformations ENVIDAT STAC Catalog 2023-01-01 2023-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081289-ENVIDAT.umm_json We have analysed past transformations in Switzerland in four environmental domains, with the aim to draw conclusions for current challenges, such as the net‐zero transformation. The data comprise transcripts of interviews with experts in the field of biodiversity, forests, landscape and natural hazard research. proprietary
angle-of-repose-of-snow_1.0 Angle of repose experiments with natural and spherical snow ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814625-ENVIDAT.umm_json Angle of repose experiments were performed with different snow types at temperatures between -2 and -40°C. They were used to examine granular snow dynamics on the grain-scale with focus on the role of grain shape and cohesion. The angle of repose was observed by sieving snow onto a round, freestanding base until a stationary heap was formed. This dataset consists of 1) the images of the experimental heaps that were taken to determine the angle of repose, 2) one binary 3D micro computed tomography image of each snow type. The CT images were taken with the SLF micro-CT40 to characterize snow properties and grain shape. The experiments with natural snow types (rounded and faceted grains) and spherical model snow allowed for an examination of the differences in granular properties between natural grain shapes and spherical particles in view of Discrete Element Modelling. With the chosen temperatures, the effect of sintering could be observed that increases the angle of repose with increasing temperature. proprietary
ant_dist_1 Antarctic Distances AU_AADC STAC Catalog 1996-11-01 1996-11-01 45, -90, 160, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214311734-AU_AADC.umm_json Spreadsheet of distances between Antarctic locations (eg. Mawson Station, Prince Edward Island) and world locations (eg. Melbourne, Santiago). proprietary
@@ -17201,17 +17202,17 @@ antarctic_circumpolar_current_fronts_1 Fronts of the Antarctic Circumpolar Curre
antarctic_single_frames USGS Antarctic Single Frame Records USGS_LTA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567558-USGS_LTA.umm_json Antarctic Single Frame Records are a collection of aerial photographs over Antarctica from the United States Antarctic Resource Center (USARC) and the British Antarctic Survey (BAS) dating from 1946 to 2000. The Antarctic Single Frame Records collection includes black-and-white, natural color and color infrared images with a photographic scale ranging from 1:1,000 to 1:64,000. proprietary
anthropogenic-change-and-net-n-mineralization_1.0 Anthropogenic change and soil net N mineralization ENVIDAT STAC Catalog 2020-01-01 2020-01-01 158.90625, -54.9776137, -132.1875, 61.2702328 https://cmr.earthdata.nasa.gov/search/concepts/C2789814650-ENVIDAT.umm_json This dataset contains all data on which the following publication below is based. Paper Citation: Risch Anita C., Zimmermann, Stefan, Moser, Barbara, Schütz, Martin, Hagedorn, Frank, Firn, Jennifer, Fay, Philip A., Adler, Peter B., Biederman, Lori A., Blair, John M., Borer, Elizabeth T., Broadbent, Arthur A.D., Brown, Cynthia S., Cadotte, Marc W., Caldeira, Maria C., Davies, Kendi F., di Virgilio, Augustina, Eisenhauer, Nico, Eskelinen, Anu, Knops, Johannes M.H., MacDougall, Andrew S., McCulley, Rebecca L., Melbourne, Brett A., Moore, Joslin L., Power, Sally A., Prober, Suzanne M., Seabloom, Eric W., Siebert, Julia, Silveira, Maria L. , Speziale, Karina L., Stevens, Carly J., Tognetti, Pedro M., Virtanen, Risto, Yahdjian, Laura, Ochoa-Hueso, Raul (accepted). Global impacts of fertilization and herbivore removal on soil net nitrogen mineralization are modulated by local climate and soil properties. Global Change Biology Please cite this paper together with the citation for the datafile. We assessed how the removal of mammalian herbivores (Fence) and fertilization with growth-limiting nutrients (N, P, K, plus nine essential macro- and micronutrients; NPK) individually, and in combination (NPK+Fence), affected potential and realized soil net Nmin across 22 natural and semi-natural grasslands on five continents. Our sites spanned a comprehensive range of climatic and edaphic conditions found across the grassland biome. We focused on grasslands, because they cover 40-50% of the ice-free land surface and provide vital ecosystem functions and services. They are particularly important for forage production and C sequestration. Worldwide, grasslands store approximately 20-30% of the Earth’s terrestrial C, most of it in the soil (Schimel, 1995; White et al., 2000). proprietary
aoci0bil_281_1 BOREAS Level-0 AOCI Imagery: Digital Counts in BIL Format ORNL_CLOUD STAC Catalog 1994-07-21 1994-07-21 -105.91, 52.98, -104.93, 54.46 https://cmr.earthdata.nasa.gov/search/concepts/C2927616228-ORNL_CLOUD.umm_json The level-0 AOCI imagery, along with the other remotely sensed images, was collected to provide spatially extensive information about radiant energy over the primary BOREAS study areas. The AOCI was the only remote sensing instrument flown with wavelength bands specific to the investigation of various aquatic parameters such as chlorophyll content and turbidity. proprietary
-apr3cpex_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX ALL STAC Catalog 2017-05-27 2017-06-24 -96.0262, 16.8091, -69.2994, 28.9042 https://cmr.earthdata.nasa.gov/search/concepts/C2409563129-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment (CPEX) aircraft field campaign. CPEX collected data to help answer questions about convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data files are available from May 27, 2017 through June 24, 2017 in a HDF-5 file, with associated browse imagery in JPG format. proprietary
apr3cpex_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX GHRC_DAAC STAC Catalog 2017-05-27 2017-06-24 -96.0262, 16.8091, -69.2994, 28.9042 https://cmr.earthdata.nasa.gov/search/concepts/C2409563129-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment (CPEX) aircraft field campaign. CPEX collected data to help answer questions about convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data files are available from May 27, 2017 through June 24, 2017 in a HDF-5 file, with associated browse imagery in JPG format. proprietary
-apr3cpexaw_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW ALL STAC Catalog 2021-08-20 2021-09-04 -80.7804, 11.8615, -45.6417, 34.046 https://cmr.earthdata.nasa.gov/search/concepts/C2269541013-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment – Aerosols & Winds (CPEX-AW) field campaign. CPEX-AW was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix. These data files are available from August 20, 2021 through September 4, 2021 in a MatLab file, with associated browse files in JPEG format. proprietary
+apr3cpex_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX ALL STAC Catalog 2017-05-27 2017-06-24 -96.0262, 16.8091, -69.2994, 28.9042 https://cmr.earthdata.nasa.gov/search/concepts/C2409563129-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment (CPEX) aircraft field campaign. CPEX collected data to help answer questions about convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data files are available from May 27, 2017 through June 24, 2017 in a HDF-5 file, with associated browse imagery in JPG format. proprietary
apr3cpexaw_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW GHRC_DAAC STAC Catalog 2021-08-20 2021-09-04 -80.7804, 11.8615, -45.6417, 34.046 https://cmr.earthdata.nasa.gov/search/concepts/C2269541013-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment – Aerosols & Winds (CPEX-AW) field campaign. CPEX-AW was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix. These data files are available from August 20, 2021 through September 4, 2021 in a MatLab file, with associated browse files in JPEG format. proprietary
+apr3cpexaw_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW ALL STAC Catalog 2021-08-20 2021-09-04 -80.7804, 11.8615, -45.6417, 34.046 https://cmr.earthdata.nasa.gov/search/concepts/C2269541013-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-AW dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment – Aerosols & Winds (CPEX-AW) field campaign. CPEX-AW was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix. These data files are available from August 20, 2021 through September 4, 2021 in a MatLab file, with associated browse files in JPEG format. proprietary
apr3cpexcv_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-CV ALL STAC Catalog 2022-09-02 2022-09-30 -89.6733315, 1.7593585, -14.8189435, 39.1985524 https://cmr.earthdata.nasa.gov/search/concepts/C2708951073-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-CV dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross-section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment – Cabo Verde (CPEX-CV) field campaign. The NASA CPEX-CV field campaign will be based out of Sal Island, Cabo Verde from August through September 2022. The campaign is a continuation of CPEX – Aerosols and Winds (CPEX-AW) and was conducted aboard the NASA DC-8 aircraft equipped with remote sensors and dropsonde-launch capability that will allow for the measurement of tropospheric aerosols, winds, temperature, water vapor, and precipitation. The overarching CPEX-CV goal was to investigate atmospheric dynamics, marine boundary layer properties, convection, the dust-laden Saharan Air Layer, and their interactions across various spatial scales to improve understanding and predictability of process-level lifecycles in the data-sparse tropical East Atlantic region. These data files are available from September 2, 2022, through September 30, 2022, in netCDF-4 format, with associated browse imagery in JPG format. proprietary
apr3cpexcv_1 Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-CV GHRC_DAAC STAC Catalog 2022-09-02 2022-09-30 -89.6733315, 1.7593585, -14.8189435, 39.1985524 https://cmr.earthdata.nasa.gov/search/concepts/C2708951073-GHRC_DAAC.umm_json The Airborne Precipitation Radar 3rd Generation (APR-3) CPEX-CV dataset consists of radar reflectivity, Doppler velocity for all bands, linear depolarization ratio Ku-band, and normalized radar cross-section measurements at Ka- and Ku- bands data collected by the APR-3 onboard the NASA DC-8 aircraft. These data were gathered during the Convective Processes Experiment – Cabo Verde (CPEX-CV) field campaign. The NASA CPEX-CV field campaign will be based out of Sal Island, Cabo Verde from August through September 2022. The campaign is a continuation of CPEX – Aerosols and Winds (CPEX-AW) and was conducted aboard the NASA DC-8 aircraft equipped with remote sensors and dropsonde-launch capability that will allow for the measurement of tropospheric aerosols, winds, temperature, water vapor, and precipitation. The overarching CPEX-CV goal was to investigate atmospheric dynamics, marine boundary layer properties, convection, the dust-laden Saharan Air Layer, and their interactions across various spatial scales to improve understanding and predictability of process-level lifecycles in the data-sparse tropical East Atlantic region. These data files are available from September 2, 2022, through September 30, 2022, in netCDF-4 format, with associated browse imagery in JPG format. proprietary
apuimpacts_1 Autonomous Parsivel Unit (APU) IMPACTS GHRC_DAAC STAC Catalog 2020-01-15 2020-02-29 -75.5894, 37.919, -75.3588, 38.2064 https://cmr.earthdata.nasa.gov/search/concepts/C1995564696-GHRC_DAAC.umm_json The Autonomous Parsivel Unit (APU) IMPACTS data were collected in support of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. The IMPACTS field campaign addressed providing observations critical to understanding the mechanisms of snowband formation, organization, and evolution, examining how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands, and improving snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. This dataset consists of precipitation data including precipitation amount, precipitation rate, reflectivity in Rayleigh regime, liquid water content, drop diameter, and drop concentration. Data are available in ASCII format from January 15, 2020 through February 29, 2020. proprietary
area_of_shrub_forest-123_1.0 Area of shrub forest ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814712-ENVIDAT.umm_json All plots classified as shrub forest according to the NFI forest definition. __Citation:__ > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_ proprietary
arthropod-biomass-abundance-species-richness-trends-limpach_1.0 Arthropod biomass, abundance and species richness trends over 32 years in the agricultural Limpach valley, Switzerland ENVIDAT STAC Catalog 2020-01-01 2020-01-01 7.3819542, 47.0815787, 7.528553, 47.1334543 https://cmr.earthdata.nasa.gov/search/concepts/C2789814758-ENVIDAT.umm_json Recent publications about declines in arthropod biomass, abundance and species diversity raise concerns and call for measures. Agricultural intensification is likely one cause for the negative trends. But rare long-term arthropod surveys conceal trends in arthropod communities in agricultural land. Here, we report about a standardized sampling of arthropod fauna in a Swiss agricultural landscape, repeated over 32 years (1987, 1997 and 2019). We sampled 8 sites covering 4 semi-natural and agricultural habitat types. Four trap types were used to capture a wide range of flying and ground dwelling arthropods between May and July. Over the three sampling periods, 58’255 specimens of 1’343 species were analysed. Mean arthropod biomass, abundance and species richness per trap was significantly higher in 2019 than in prior years and gamma diversity of the study area was highest in 2019. Biomass and abundance increased stronger in the flight traps than in the pitfall traps. The implementation of agri-environmental schemes has improved habitat quality since 1993, while landscape composition and pesticide and fertilizer use remained stable over the study period, both contributing to the findings. The results of this study contrast with outcomes of comparable investigations and highlight the importance of further long-term investigations on arthropod dynamics. Data are provided on request to contact person against bilateral agreement. proprietary
-asas Advanced Solid-state Array Spectroradiometer (ASAS) USGS_LTA STAC Catalog 1988-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566261-USGS_LTA.umm_json The Advanced Solid-state Array Spectroradiometer (ASAS) data collection contains data collected by the ASAS sensor flown aboard NASA aircraft. A fundamental use of ASAS data is to characterize and understand the directional variability in solar energy scattered by various land surface cover types (e.g.,crops, forests, prairie grass, snow, or bare soil). The sensor's Bidirectional Reflectance Distribution Function determines the variation in the reflectance of a surface as a function of both the view zenith angle and solar illumination angle. The ASAS sensor is a hyperspectral, multiangle, airborne remote sensing instrument maintained and operated by the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The ASAS instrument is mounted on the underside of either NASA C-130 or NASA P-3 aircraft and is capable of off-nadir pointing from approximately 70 degrees forward to 55 degrees aft along the direction of flight. The aircraft is flown at an altitude of 5000 - 6000 meters (approximately 16,000 - 20,000 ft.). Data in the ASAS collection primarily cover areas over the continental United States, but some ASAS data are also available over areas in Canada and western Africa. The ASAS data were collected between 1988 and 1994. proprietary
asas Advanced Solid-state Array Spectroradiometer (ASAS) ALL STAC Catalog 1988-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566261-USGS_LTA.umm_json The Advanced Solid-state Array Spectroradiometer (ASAS) data collection contains data collected by the ASAS sensor flown aboard NASA aircraft. A fundamental use of ASAS data is to characterize and understand the directional variability in solar energy scattered by various land surface cover types (e.g.,crops, forests, prairie grass, snow, or bare soil). The sensor's Bidirectional Reflectance Distribution Function determines the variation in the reflectance of a surface as a function of both the view zenith angle and solar illumination angle. The ASAS sensor is a hyperspectral, multiangle, airborne remote sensing instrument maintained and operated by the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The ASAS instrument is mounted on the underside of either NASA C-130 or NASA P-3 aircraft and is capable of off-nadir pointing from approximately 70 degrees forward to 55 degrees aft along the direction of flight. The aircraft is flown at an altitude of 5000 - 6000 meters (approximately 16,000 - 20,000 ft.). Data in the ASAS collection primarily cover areas over the continental United States, but some ASAS data are also available over areas in Canada and western Africa. The ASAS data were collected between 1988 and 1994. proprietary
+asas Advanced Solid-state Array Spectroradiometer (ASAS) USGS_LTA STAC Catalog 1988-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566261-USGS_LTA.umm_json The Advanced Solid-state Array Spectroradiometer (ASAS) data collection contains data collected by the ASAS sensor flown aboard NASA aircraft. A fundamental use of ASAS data is to characterize and understand the directional variability in solar energy scattered by various land surface cover types (e.g.,crops, forests, prairie grass, snow, or bare soil). The sensor's Bidirectional Reflectance Distribution Function determines the variation in the reflectance of a surface as a function of both the view zenith angle and solar illumination angle. The ASAS sensor is a hyperspectral, multiangle, airborne remote sensing instrument maintained and operated by the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The ASAS instrument is mounted on the underside of either NASA C-130 or NASA P-3 aircraft and is capable of off-nadir pointing from approximately 70 degrees forward to 55 degrees aft along the direction of flight. The aircraft is flown at an altitude of 5000 - 6000 meters (approximately 16,000 - 20,000 ft.). Data in the ASAS collection primarily cover areas over the continental United States, but some ASAS data are also available over areas in Canada and western Africa. The ASAS data were collected between 1988 and 1994. proprietary
asas_l1b_562_1 BOREAS RSS-02 Level-1b ASAS Image Data: At-sensor Radiance in BSQ Format ORNL_CLOUD STAC Catalog 1994-04-19 1996-07-20 -106.32, 53.24, -97.23, 56.25 https://cmr.earthdata.nasa.gov/search/concepts/C2813527156-ORNL_CLOUD.umm_json The BOREAS RSS-02 team used the ASAS instrument, mounted on the NASA C-130 aircraft, to create at-sensor radiance images of various sites as a function of spectral wavelength, view geometry (combinations of view zenith angle, view azimuth angle, solar zenith angle, and solar azimuth angle), and altitude. The level-1b ASAS images of the BOREAS study areas were collected from April to September 1994 and March to July 1996. proprietary
asasrefl_287_1 BOREAS RSS-02 Extracted Reflectance Factors Derived from ASAS Imagery ORNL_CLOUD STAC Catalog 1994-05-24 1996-07-20 -106.2, 53.24, -104.62, 53.99 https://cmr.earthdata.nasa.gov/search/concepts/C2813382300-ORNL_CLOUD.umm_json Contains calculated bidirectional reflectance factor means derived from extractions of C130-based ASAS measurements made during BOREAS. proprietary
ascatcpex_1 Advanced Scatterometer (ASCAT) CPEX GHRC_DAAC STAC Catalog 2017-05-24 2017-07-16 160.241, 3.9062, -25.0958, 42.5176 https://cmr.earthdata.nasa.gov/search/concepts/C2428509185-GHRC_DAAC.umm_json The Advanced Scatterometer (ASCAT) CPEX dataset consists of ice probability, wind speed, and wind direction estimates collected by the ASCAT. The ASCAT is onboard the MetOp-A and MetOp-B satellites and uses radar to measure the electromagnetic backscatter from the wind-roughened ocean surface, from which data on wind speed and direction can be derived. These data were gathered during the Convective Processes Experiment (CPEX) field campaign. CPEX collected data to help answer questions about convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data files are available from May 24, 2017 through July 16, 2017 in netCDF-3 format. proprietary
@@ -17221,8 +17222,8 @@ aspas_asmas_aat_3 Antarctic Specially Protected Areas and Antarctic Specially Ma
asrb-dav_1.0 ASRB_DAV: Shortwave and longwave radiation measurements (2 min) in Davos Dorf ENVIDAT STAC Catalog 2017-01-01 2017-01-01 9.84827, 46.81277, 9.84827, 46.81277 https://cmr.earthdata.nasa.gov/search/concepts/C2789814851-ENVIDAT.umm_json Incoming and outgoing shortwave and longwave 2 min radiation measurements in Davos Dorf, CH. ### References 1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019. 2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf. proprietary
asrb-vf_1.0 ASRB_WFJVF: Shortwave and longwave radiation measurements (2 min) at the Weissfluhjoch research site, Davos ENVIDAT STAC Catalog 2016-01-01 2016-01-01 9.809204, 46.829631, 9.809204, 46.829631 https://cmr.earthdata.nasa.gov/search/concepts/C2789814947-ENVIDAT.umm_json Incoming and outgoing shortwave and longwave 2 min radiation measurements at the Weissfluhjoch research site, Davos, CH. The experimental site at the Weissfluhjoch (WFJ, 46.83 N, 9.81 E) is located at an altitude of 2540 m in the Swiss Alps near Davos. During the winter months, almost all precipitation falls as snow at this altitude. As a consequence, a continuous seasonal snow cover builds up every winter, with a maximum snow height ranging from 153–366 cm over the period 1934–2012. The measurement site is located in an almost flat part of a southeast oriented slope. ### References 1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019. 2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf. proprietary
asrb-wfj_1.0 ASRB_WFJ: Shortwave and longwave radiation measurements (2 min) at the Weissfluhjoch research site, Davos ENVIDAT STAC Catalog 2017-01-01 2017-01-01 9.809204, 46.829631, 9.809204, 46.829631 https://cmr.earthdata.nasa.gov/search/concepts/C2789814987-ENVIDAT.umm_json Corrected incoming and outgoing shortwave and longwave 2 min radiation measurements at the Weissfluhjoch summit, Davos, CH. ### References 1. Marty, C., Philipona, R., Frohlich, C., Ohmura, A.. Altitude dependence of surface radiation fluxes and cloud forcing in the alps: results from the alpine surface radiation budget network. 2002. Theoretical and Applied Climatology. Volume 72. Issue 3-4. 137-155. http://dx.doi.org/10.1007/s007040200019. 10.1007/s007040200019. 2. Christoph Marty. Surface Radiation, Cloud Forcing and Greenhouse Effect in the Alps. 2000. Institute fuer Klimaforschung ETH. Zuercher Klima-Schriften. Volume 79. http://e-collection.library.ethz.ch/eserv/eth:23491/eth-23491-01.pdf. proprietary
-aster_1 Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster) satellite image data held by the Australian Antarctic Data Centre ALL STAC Catalog 2000-10-08 -180, -90, 180, -53 https://cmr.earthdata.nasa.gov/search/concepts/C1214313130-AU_AADC.umm_json Advanced Spaceborne Thermal Emission and Reflection Radiometer. Level 1A and level 1B data. The L1A data are reconstructed, unprocessed instrument data at full resolution. It consists of the image data, the radiometric coefficients, the geometric coefficients and other auxiliary data without applying the coefficients to the image data. The L1B data have these coefficents applied for radiometric calibration and geometric resampling. There are approximately 2500 scenes available. Of these, over 3/5 of theme are level 1B data. Search the Satellite Image Catalogue for more information using the link included. proprietary
aster_1 Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster) satellite image data held by the Australian Antarctic Data Centre AU_AADC STAC Catalog 2000-10-08 -180, -90, 180, -53 https://cmr.earthdata.nasa.gov/search/concepts/C1214313130-AU_AADC.umm_json Advanced Spaceborne Thermal Emission and Reflection Radiometer. Level 1A and level 1B data. The L1A data are reconstructed, unprocessed instrument data at full resolution. It consists of the image data, the radiometric coefficients, the geometric coefficients and other auxiliary data without applying the coefficients to the image data. The L1B data have these coefficents applied for radiometric calibration and geometric resampling. There are approximately 2500 scenes available. Of these, over 3/5 of theme are level 1B data. Search the Satellite Image Catalogue for more information using the link included. proprietary
+aster_1 Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster) satellite image data held by the Australian Antarctic Data Centre ALL STAC Catalog 2000-10-08 -180, -90, 180, -53 https://cmr.earthdata.nasa.gov/search/concepts/C1214313130-AU_AADC.umm_json Advanced Spaceborne Thermal Emission and Reflection Radiometer. Level 1A and level 1B data. The L1A data are reconstructed, unprocessed instrument data at full resolution. It consists of the image data, the radiometric coefficients, the geometric coefficients and other auxiliary data without applying the coefficients to the image data. The L1B data have these coefficents applied for radiometric calibration and geometric resampling. There are approximately 2500 scenes available. Of these, over 3/5 of theme are level 1B data. Search the Satellite Image Catalogue for more information using the link included. proprietary
aster_global_dem ASTER Global DEM USGS_LTA STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567908-USGS_LTA.umm_json ASTER is capable of collecting in-track stereo using nadir- and aft-looking near infrared cameras. Since 2001, these stereo pairs have been used to produce single-scene (60- x 60-kilomenter (km)) digital elevation models (DEM) having vertical (root-mean-squared-error) accuracies generally between 10- and 25-meters (m). The methodology used by Japan's Sensor Information Laboratory Corporation (SILC) to produce the ASTER GDEM involves automated processing of the entire ASTER Level-1A archive. Stereo-correlation is used to produce over one million individual scene-based ASTER DEMs, to which cloud masking is applied to remove cloudy pixels. All cloud-screened DEMS are stacked and residual bad values and outliers are removed. Selected data are averaged to create final pixel values, and residual anomalies are corrected before partitioning the data into 1 degree (°) x 1° tiles. The ASTER GDEM covers land surfaces between 83°N and 83°S and is comprised of 22,702 tiles. Tiles that contain at least 0.01% land area are included. The ASTER GDEM is distributed as Geographic Tagged Image File Format (GeoTIFF) files with geographic coordinates (latitude, longitude). The data are posted on a 1 arc-second (approximately 30–m at the equator) grid and referenced to the 1984 World Geodetic System (WGS84)/ 1996 Earth Gravitational Model (EGM96) geoid. proprietary
atlas_buildings_gis_1 Differential GPS survey of the Atlas Cove ANARE Station ruins on Heard Island AU_AADC STAC Catalog 2000-01-01 2000-02-28 73.3, -53.1, 73.5, -53 https://cmr.earthdata.nasa.gov/search/concepts/C1214313143-AU_AADC.umm_json Alistair Grinbergs (Heritage Officer) was on Heard island in January and February 2000) as part of the 2000 ANARE, to make an assessment of the heritage value of the old ANARE station ruins. This GPS survey data of the corners of buildings and other artefacts will form part of the record of the station site, together with drawings and other measurements. The assessment will be used to formulate a conservation management plan for the site. proprietary
atlas_cove_photos_1 Atlas Cove Terrestrial Photos - historic ANARE Base AU_AADC STAC Catalog 2008-03-26 2008-03-26 73.391, -53.02, 73.394, -53.018 https://cmr.earthdata.nasa.gov/search/concepts/C1214313131-AU_AADC.umm_json Photographs and photo locations of the historic Australian National Antarctic Research Expedition (ANARE) base at Atlas Cove on Heard Island. The station was established 11 December 1947 and was closed down on 9 March 1955. Photos were taken in March of 2008 by Kerry Steinberner during a visit to Heard Island. The map used to locate the images is described in the following metadata record: Topographic Survey at Atlas Cove, Heard Island, November 2000 [atlas_survey2000_gis] The images include shots of the remains of ANARE buildings, vehicles, tanks, debris, fences, artefacts and flora. The dataset includes a copy of the images, an excel spreadsheet cataloguing the images, and shapefiles showing the image locations. proprietary
@@ -17269,8 +17270,8 @@ avalanche-fatalities-european-alps-1969-2015_1.0 Avalanche fatalities in the Eur
avalanche-fatalities-per-calendar-year-since-1936_1.0 Number of avalanche fatalities per calendar year in Switzerland since 1937 ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814645-ENVIDAT.umm_json Attention: this data is not updated after 2022 anymore. This dataset contains the statistics on the number of avalanche fatalities per **calendar year** in Switzerland. The data collection commences with the beginning of the year 1937. After the completion of a hydrological year, which is the standard way avalanche fatalities are summarized in Switzerland and ends on the 30th of September, the new data is appended to the existing dataset. If you require annual statistics per hydrological year, please download the data from here: [https://www.envidat.ch/dataset/avalanche-fatalities-switzerland-1936] The following information is contained (by column and column title): - year - number of fatalities in the backcountry (=tour) - number of fatalities in terrain close to ski areas (=offpiste, away from open and secured ski runs) - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors) - number of fatalities in or around buildings or in settlements (= buildings) - sum (of all four categories) The definitions for these four categories, as described in the guidelines to the avalanche accident database are: __tour:__ activities include back-country ski, snowboard or snow-shoe touring __offpiste:__ access from ski area, generally from the top of a skilift with short hiking distances __transportation.corridors__ (Techel et al., 2016): people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams) __buildings__ (Techel et al., 2016): people inside or just outside buildings, and workers on high alpine building sites proprietary
avalanche-fatalities-switzerland-1936_1.0 Number of avalanche fatalities per hydrological year in Switzerland since 1936-1937 ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814658-ENVIDAT.umm_json Attention: this data is not updated after 2022 anymore. This dataset contains the statistics on the number of avalanche fatalities per hydrological year in Switzerland. The data set commences with the beginning of the hydrological year 1936/37 on 01/10/1936. After the completion of a hydrological year, the new data is appended to the existing dataset. The following information is contained (by column and column title): - hydrological year - number of fatalities in the backcountry (=tour) - number of fatalities in terrain close to ski areas (=offpiste) - number of fatalities on transportation corridors including ski runs, roads, railway lines (=transportation.corridors) - number of fatalities in or around buildings or in settlements (= buildings) - sum (of all four categories) The definition for these four categories as described in the guidelines to the avalanche accident database: **tour**: activities include back-country ski, snowboard or snow-shoe touring **offpiste**: access from ski area, generally from the top of a skilift with short hiking distances **transportation.corridors** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )): people travelling or recreating on open or temporarily closed transportation corridors (e.g. a road user or a skier on a ski run) and people working on open or closed transportation corridors (e.g. maintenance crews on roads, professional rescue teams) **buildings** ([Techel et al., 2016](http://www.geogr-helv.net/71/147/2016/ )): people inside or just outside buildings, and workers on high alpine building sites proprietary
avalanche-prediction-snowpack-simulations_1.0 Data-set for prediction of natural dry-snow avalanche activity and avalanche size using physics-based snowpack simulations ENVIDAT STAC Catalog 2023-01-01 2023-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081494-ENVIDAT.umm_json The data set contained in this repository was used in the analysis by Mayer et al. (2023): Mayer, S. I., Techel, F., Schweizer, J., and van Herwijnen, A.: Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations, EGUsphere, https://doi.org/10.5194/egusphere-2023-646, 2023. proprietary
-avapsimpacts_1 Advanced Vertical Atmospheric Profiling System Dropsondes (AVAPS) IMPACTS ALL STAC Catalog 2020-01-12 2023-02-28 -77.815, 33.54, -65.44, 44.17 https://cmr.earthdata.nasa.gov/search/concepts/C2004708338-GHRC_DAAC.umm_json The Advanced Vertical Atmospheric Profiling System (AVAPS) IMPACTS dataset consists of vertical atmospheric profile measurements collected by the Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes released from the NASA P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. AVAPS uses a Global Positioning System (GPS) dropsonde to measure atmospheric state parameters (temperature, humidity, wind speed/direction, pressure) and location in 3-dimensional space during the dropsonde’s descent. The AVAPS dataset files are available from January 12, 2020, through February 28, 2023, in ASCII-ict format. proprietary
avapsimpacts_1 Advanced Vertical Atmospheric Profiling System Dropsondes (AVAPS) IMPACTS GHRC_DAAC STAC Catalog 2020-01-12 2023-02-28 -77.815, 33.54, -65.44, 44.17 https://cmr.earthdata.nasa.gov/search/concepts/C2004708338-GHRC_DAAC.umm_json The Advanced Vertical Atmospheric Profiling System (AVAPS) IMPACTS dataset consists of vertical atmospheric profile measurements collected by the Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes released from the NASA P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. AVAPS uses a Global Positioning System (GPS) dropsonde to measure atmospheric state parameters (temperature, humidity, wind speed/direction, pressure) and location in 3-dimensional space during the dropsonde’s descent. The AVAPS dataset files are available from January 12, 2020, through February 28, 2023, in ASCII-ict format. proprietary
+avapsimpacts_1 Advanced Vertical Atmospheric Profiling System Dropsondes (AVAPS) IMPACTS ALL STAC Catalog 2020-01-12 2023-02-28 -77.815, 33.54, -65.44, 44.17 https://cmr.earthdata.nasa.gov/search/concepts/C2004708338-GHRC_DAAC.umm_json The Advanced Vertical Atmospheric Profiling System (AVAPS) IMPACTS dataset consists of vertical atmospheric profile measurements collected by the Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes released from the NASA P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. AVAPS uses a Global Positioning System (GPS) dropsonde to measure atmospheric state parameters (temperature, humidity, wind speed/direction, pressure) and location in 3-dimensional space during the dropsonde’s descent. The AVAPS dataset files are available from January 12, 2020, through February 28, 2023, in ASCII-ict format. proprietary
avhrr_822_1 SAFARI 2000 AVHRR Daily Site (1.5 km) and 15-Day Regional (1.5- and 6-km) Imagery ORNL_CLOUD STAC Catalog 1998-07-01 2000-10-31 8.73, -35.26, 43.2, -7.49 https://cmr.earthdata.nasa.gov/search/concepts/C2804805089-ORNL_CLOUD.umm_json The Global Inventory Mapping and Modeling (GIMMS) group at NASA/GSFC provided SAFARI 2000 with remotely sensed satellite data products at the site and regional level. These AVHRR data contain two main sets of data: site extracts of SAFARI core sites (Mongu, Etosha, Kasungu, Maun, Skukuza, and Tshane), and regional 15-day composites from sets of single-day images. These AVHRR data contain four main sets of data:1.5 km daily site extracts of SAFARI core sites (2000)1.5 km 15-day composites of SAFARI core sites (1998-2000)1.5 km 15-day composites of the southern African region (Mar, Sept 2000)6 km 15-day composites of the southern African region (1998-2000)The primary data layers for site extracts and regional composites are fire pixel counts and maximum NDVI. The fire product is different for the daily and for the composited products (see readme file) and a fire product is not included in the 1.5 km regional data set. NDVI composite-associated data layers for the regional data sets include land surface temperature, reflectance, solar zenith angle, view zenith angle, and relative azimuth angle. NDVI composite-associated data layers for the site extracts include these same variables as well as brightness temperature, fire mask composite, latitude, and longitude. The data are stored in binary image format files. There is a metadata file for each site and date/compositing period, in ASCII format. proprietary
avhrr_albedo_1995_xdeg_928_1 ISLSCP II AVHRR Albedo and BRDF, 1995 ORNL_CLOUD STAC Catalog 1995-02-01 1995-07-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784840966-ORNL_CLOUD.umm_json This Albedo and BRDF (Bidirectional Reflectance Distribution Function) data set contains three files containing BRDF parameters, white- sky albedo and black-sky albedo at solar noon for three bands ((350-680nm, 680-3000nm, and 350-30000nm)derived from AVHRR (Advanced Very High Resolution Radiometer). These data are available at spatial resolutions of quarter, half, and one degree. Black-sky albedo (direct beam contribution) and white-sky (Completely diffuse contribution) can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon. proprietary
avhrrl3b_481_1 BOREAS Level-3b AVHRR-LAC Imagery: Scaled At-Sensor Radiance in LGSOWG Format ORNL_CLOUD STAC Catalog 1994-01-30 1996-09-18 -111, 50.09, -93.5, 59.98 https://cmr.earthdata.nasa.gov/search/concepts/C2929133860-ORNL_CLOUD.umm_json Data acquired from the AVHRR instrument on the NOAA-9, -11, -12, and -14 satellites were processed and archived. A few winter acquisitions are available, but the archive contains primarily growing season imagery. These gridded, at-sensor radiance image data cover the period of 30-Jan-1994 to 18-Sep-1996. Geographically, the data cover the entire 1000 km x 1000 km BOREAS Region. proprietary
@@ -17303,8 +17304,8 @@ bb9fdc41-1a19-4793-aca1-a6f5f28d592d_NA TerraSAR-X - Staring Spotlight Images (T
bds_dragonfly A Checklist of British and Irish Dragonfly Species ALL STAC Catalog 1998-01-01 -8.41, 49.49, 2.39, 59.07 https://cmr.earthdata.nasa.gov/search/concepts/C1214611738-SCIOPS.umm_json "Dragonflies are among the most ancient of living creatures. Fossil records, clearly recognisable as dragonflies, go back to Carboniferous times which means that they date back almost 300 million years, predating pterodactyls by 100 million years and birds by some 150 million. It would he tragic if, after surviving such an unimaginable number of years, it should be our generation that witnesses the decline of these fascinating and beautiful insects. The British Dragonfly Society maintains a checklist of British and Irish dragonflies. This checklist includes all British and Irish species including migrants, vagrants and species now believed extinct in the British Isles. The species name provides a link to a photograph where available. Information was obtained from ""http://www.british-dragonflies.org.uk/content/uk-species""." proprietary
bds_dragonfly A Checklist of British and Irish Dragonfly Species SCIOPS STAC Catalog 1998-01-01 -8.41, 49.49, 2.39, 59.07 https://cmr.earthdata.nasa.gov/search/concepts/C1214611738-SCIOPS.umm_json "Dragonflies are among the most ancient of living creatures. Fossil records, clearly recognisable as dragonflies, go back to Carboniferous times which means that they date back almost 300 million years, predating pterodactyls by 100 million years and birds by some 150 million. It would he tragic if, after surviving such an unimaginable number of years, it should be our generation that witnesses the decline of these fascinating and beautiful insects. The British Dragonfly Society maintains a checklist of British and Irish dragonflies. This checklist includes all British and Irish species including migrants, vagrants and species now believed extinct in the British Isles. The species name provides a link to a photograph where available. Information was obtained from ""http://www.british-dragonflies.org.uk/content/uk-species""." proprietary
beaver_sat_1 Beaver Lake Satellite Image and Topographic Double-sided Map 1:100 000 AU_AADC STAC Catalog 1990-05-01 1990-05-31 67, -71, 69, -70 https://cmr.earthdata.nasa.gov/search/concepts/C1214313272-AU_AADC.umm_json Double-sided satellite image and topographic map of Beaver Lake, Antarctica. These maps were produced for the Australian Antarctic Division by AUSLIG (now Geoscience Australia) Commercial, in Australia, in 1990. Both maps are at a scale of 1:100 000. The satellite image map was produced from SPOT 1 and LANDSAT 5 TM scenes. It is projected on a Transverse Mercator projection, and shows glaciers/ice shelves, stations/bases and gives some historical text information. The map has both geographical and UTM co-ordinates. Contours on the topographic map were derived from Russian maps (values have not been verified.) This map is also projected on a transverse mercator projection, and shows traverses/routes/foot track charts, bases/stations, glaciers/ice shelves, survey marks, and gives some historical text information. proprietary
-bech_nest_locations_1 Adelie Penguin nest locations on Bechervaise Island ALL STAC Catalog 2000-02-01 2000-02-22 62.8084, -67.5879, 62.8152, -67.5863 https://cmr.earthdata.nasa.gov/search/concepts/C1214313158-AU_AADC.umm_json This dataset represents the locations of Adelie Penguin nests in colonies K, L and Q on Bechervaise Island, Holme Bay, Antarctica. Attributes include colony, nest number and tag colour. The dataset contains three files - an image file and two zip files. The image file, mapping_grid.jpg, is a diagram showing the grid used for plotting the colony L nest locations. The zip file, bech_penguin_nests.zip, contains shapefiles representing the Adelie Penguin nest locations, Bechervaise Island. The zip file, transform_nests_colonyL.zip, provides further information about the georeferencing of the colony L nest locations. proprietary
bech_nest_locations_1 Adelie Penguin nest locations on Bechervaise Island AU_AADC STAC Catalog 2000-02-01 2000-02-22 62.8084, -67.5879, 62.8152, -67.5863 https://cmr.earthdata.nasa.gov/search/concepts/C1214313158-AU_AADC.umm_json This dataset represents the locations of Adelie Penguin nests in colonies K, L and Q on Bechervaise Island, Holme Bay, Antarctica. Attributes include colony, nest number and tag colour. The dataset contains three files - an image file and two zip files. The image file, mapping_grid.jpg, is a diagram showing the grid used for plotting the colony L nest locations. The zip file, bech_penguin_nests.zip, contains shapefiles representing the Adelie Penguin nest locations, Bechervaise Island. The zip file, transform_nests_colonyL.zip, provides further information about the georeferencing of the colony L nest locations. proprietary
+bech_nest_locations_1 Adelie Penguin nest locations on Bechervaise Island ALL STAC Catalog 2000-02-01 2000-02-22 62.8084, -67.5879, 62.8152, -67.5863 https://cmr.earthdata.nasa.gov/search/concepts/C1214313158-AU_AADC.umm_json This dataset represents the locations of Adelie Penguin nests in colonies K, L and Q on Bechervaise Island, Holme Bay, Antarctica. Attributes include colony, nest number and tag colour. The dataset contains three files - an image file and two zip files. The image file, mapping_grid.jpg, is a diagram showing the grid used for plotting the colony L nest locations. The zip file, bech_penguin_nests.zip, contains shapefiles representing the Adelie Penguin nest locations, Bechervaise Island. The zip file, transform_nests_colonyL.zip, provides further information about the georeferencing of the colony L nest locations. proprietary
beech_stress_thresholds_1.0 Stress thresholds of mature European beech trees ENVIDAT STAC Catalog 2020-01-01 2020-01-01 6.5368652, 45.9799133, 9.7009277, 47.6044342 https://cmr.earthdata.nasa.gov/search/concepts/C2789814551-ENVIDAT.umm_json This data set contains the data presented in the figures 1-6 in Walthert et al. (2020): From the comfort zone to crown dieback: sequence of physiological stress thresholds in mature European beech trees across progressive drought. Science of the Total Environment. DOI: 10.1016/j.scitotenv.2020.141792. A detailed methodical description of the data can be found in the Material and Methods section of the paper. Drought responses of mature trees are still poorly understood making it difficult to predict species distributions under a warmer climate. Using mature European beech (Fagus sylvatica L.), a widespread and economically important tree species in Europe, we aimed at developing an empirical stress-level scheme to describe its physiological response to drought. We analysed effects of decreasing soil and leaf water potential on soil water uptake, stem radius, native embolism, early defoliation and crown dieback with comprehensive measurements from overall nine hydrologically distinct beech stands across Switzerland, including records from the exceptional 2018 drought and the 2019/2020 post-drought period. Based on the observed responses to decreasing water potential we derived the following five stress levels: I (predawn leaf water potential >-0.4 MPa): no detectable hydraulic limitations; II (-0.4 to -1.3): persistent stem shrinkage begins and growth ceases; III (-1.3 to -2.1): onset of native embolism and defoliation; IV (-2.1 to -2.8): onset of crown dieback; V (<-2.8): transpiration ceases and crown dieback is >20%. Our scheme provides, for the first time, quantitative thresholds regarding the physiological downregulation of mature European beech trees under drought and therefore synthesises relevant and fundamental information for process-based species distribution models. Moreover, our study revealed that European beech is drought vulnerable, because it still transpires considerably at high levels of embolism and because defoliation occurs rather as a result of embolism than preventing embolism. During the 2018 drought, an exposure to the stress levels III-V of only one month was long enough to trigger substantial crown dieback in beech trees on shallow soils. On deep soils with a high water holding capacity, in contrast, water reserves in deep soil layers prevented drought stress in beech trees. This emphasises the importance to include local data on soil water availability when predicting the future distribution of European beech. proprietary
bender2020_1.0 Changes in climatology, snow cover and ground temperatures at high alpine locations in Switzerland (Bender et al. 2020) ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.7568359, 45.7828484, 10.7336426, 48 https://cmr.earthdata.nasa.gov/search/concepts/C2789814563-ENVIDAT.umm_json This dataset includes all data and simulation files presented in the publication: Bender et al. 2020. Changes in climatology, snow cover and ground temperatures at high alpine locations, DOI: 10.3389/feart.2020.00100. This includes: * meteorological forcing, * climate change timeries and * simulation files together with * snow depth * ground temperature __Please refer to the following publication for further details which should be cited when using this dataset:__ __Bender et al. 2020. Changes in climatology, snow cover and ground temperatures at high alpine locations, DOI: 10.3389/feart.2020.00100.__ proprietary
beryllium_10be_isotopes_lawdome_1 High resolution studies of cosmogenic beryllium isotopes (10Be) at Law Dome AU_AADC STAC Catalog 2013-03-01 2013-03-31 112.80535, -66.7059, 112.80534, -66.7058 https://cmr.earthdata.nasa.gov/search/concepts/C1214571598-AU_AADC.umm_json "Energy from the Sun drives the Earth's climate system but this energy varies: there is an 11 year solar cycle and the Sun's intensity has varied over longer timescales. Reconstructing how the Sun's output has varied in past times is crucial to understanding the Earth's past climate which is key to predicting future climate change. Naturally-occurring radioactive isotopes such as 7Be and 10Be are produced in the Earth's atmosphere by cosmic rays, at a rate controlled by the activity of the Sun, and are layered in ice sheets, thus providing a means of reconstructing past solar output. 3 x 3"" PICO firn cores were drilled immediately in front of snow pit. The 3 pico cores were sampled at 14cm intervals and the sections combined resulting in 16 samples. Some length was lost during transit, especially in the top cores. It was assumed that the lost length was from the breaks in the core as the ends rubbed against each other during transport, and was evenly lost from each break, using the field notes to help. The bottom of each core was assumed to be the lengths as measured in the field. The samples were placed in a melting jar with carrier and left to melt overnight. ~10mL of the samples were retained for water isotope analysis. The samples were filtered and pumped onto cation columns." proprietary
@@ -17355,8 +17356,8 @@ breeding_success_BI_1 Adelie penguin breeding success for Bechervaise Island, Ma
breeding_success_BI_1 Adelie penguin breeding success for Bechervaise Island, Mawson AU_AADC STAC Catalog 1990-10-01 2005-02-01 62.8055, -67.5916, 62.825, -67.5861 https://cmr.earthdata.nasa.gov/search/concepts/C1214313363-AU_AADC.umm_json Adelie penguin breeding success records for Bechervaise Island, Mawson since 1990-91. Data include counts of occupied nests and chick counts when either 2/3 of the nests have creched or when all nests have creched. Breeding success values are calculated as the number of chicks per occupied nest. Breeding Success = the number of chicks raised to fledging per nest with eggs Breeding success is calculated from four different whole island counts: 1) the number of incubating nests (i.e. the number of nest with eggs) - 'incubating nest count' 2) the number of brooding nests (i.e. the number of nests brooding chicks) - 'brooding chick count' 3) the number of chicks present when 2/3 of the nests have creched their chicks - '2/3-creche count' 4) the number of chicks present when all the nests have creche their chicks - 'fully-creche count' Each colony on the island is manually counted by field observers, using 'counters', three times each. Counts within 10% of each other are used to average the number of nests or chicks for each colony and then in later calculations to determine breeding success. Incubating nest counts are conducted on or about 2nd December; Brooding chick counts are conducted on or about the 7th January; 2/3-creche counts on or about the 19th January; and Fully-creche chick counts on or about 26th January. Whole island 2/3-creche and fully-creche chick count dates are determined from calculating when 2/3 and all study nests in the census area (study colonies) have creche their chicks. This work was completed as part of ASAC Project 2205, Adelie penguin research and monitoring in support of the CCAMLR Ecosystem Monitoring Project. The fields in this dataset are: Year Breeding success Occupied nests proprietary
brok_5k_gis_1 Broknes Peninsula 1:5000 Topographic GIS Dataset AU_AADC STAC Catalog 1994-11-03 1994-11-17 76.2, -69.4333, 76.4333, -69.3333 https://cmr.earthdata.nasa.gov/search/concepts/C1214313345-AU_AADC.umm_json Broknes Peninsula, Larsemann Hills, 1:5000 GIS dataset. This dataset has been superseded by the datasets described by the metadata records: 'Larsemann Hills - Mapping from aerial photography captured February 1998' and 'Larsemann Hills - Mapping from Landsat 7 imagery captured January 2000'. These data have been archived as they have been superseded. proprietary
broknes_lake_catchments_gis_1 Lake catchments on Broknes, Larsemann Hills AU_AADC STAC Catalog 1997-05-06 2001-08-14 76.285, -69.4193, 76.42, -69.3698 https://cmr.earthdata.nasa.gov/search/concepts/C1214313378-AU_AADC.umm_json Catchment boundaries of the the lakes on Broknes, Larsemann Hills. These catchments were generated using the FLOWDIRECTION and BASINS routines in the GRID module of ArcInfo GIS. proprietary
-bromwich_0337948_1 A 45-Y Hindcast of Antarctic Surface Mass Balance Using Polar MM5 ALL STAC Catalog 1979-01-01 2002-08-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214586989-SCIOPS.umm_json This 3-year project (June 2004-May 2007) was funded by the National Science Foundation's Office of Polar Programs (Glaciology). We employed the Polar MM5 to model variability and change in the surface mass balance (the net accumulation of moisture) over Antarctica in recent decades. Available here are annually and seasonally resolved grids of atmospheric data simulated by Polar MM5 for the period Jan 1979-Aug 2002. The ERA-40 dataset provided the initial and boundary conditions for the simulations. The burden of validating the data provided is the responsibility of anyone choosing to download it. MODEL CONFIGURATION: The Polar MM5 simulations were performed on a 121 x 121 polar stereographic grid covering the Antarctic and centered over the South Pole. The model resolution is 60-km in each horizontal direction. Vertically, the domain contains 32 sigma levels ranging from the surface to 10 hPa. Atmospheric data (U,V,T,Q,P) and sea surface temperatures were provided by ERA-40. 25-km resolution daily sea ice concentration grids were provided by the National Snow and Ice Data Center to determine fractional ice coverage over ocean gridpoints. The model topography was interpolated from the 1-km resolution digital elevation model of Liu et al. (2001). Images of the model domain, topography and land use specifications can be found here. More information on the physics in Polar MM5 can be found on the Polar MM5 Webpage, http://polarmet.mps.ohio-state.edu/PolarMet/pmm5.html Please reference the following publication if you use the data in a publication: Monaghan, A. J., D. H. Bromwich, and S.-H. Wang, 2006: Recent trends in Antarctic snow accumulation from Polar MM5. Philosophical Trans. Royal. Soc. A, 364, 1683-1708. proprietary
bromwich_0337948_1 A 45-Y Hindcast of Antarctic Surface Mass Balance Using Polar MM5 SCIOPS STAC Catalog 1979-01-01 2002-08-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214586989-SCIOPS.umm_json This 3-year project (June 2004-May 2007) was funded by the National Science Foundation's Office of Polar Programs (Glaciology). We employed the Polar MM5 to model variability and change in the surface mass balance (the net accumulation of moisture) over Antarctica in recent decades. Available here are annually and seasonally resolved grids of atmospheric data simulated by Polar MM5 for the period Jan 1979-Aug 2002. The ERA-40 dataset provided the initial and boundary conditions for the simulations. The burden of validating the data provided is the responsibility of anyone choosing to download it. MODEL CONFIGURATION: The Polar MM5 simulations were performed on a 121 x 121 polar stereographic grid covering the Antarctic and centered over the South Pole. The model resolution is 60-km in each horizontal direction. Vertically, the domain contains 32 sigma levels ranging from the surface to 10 hPa. Atmospheric data (U,V,T,Q,P) and sea surface temperatures were provided by ERA-40. 25-km resolution daily sea ice concentration grids were provided by the National Snow and Ice Data Center to determine fractional ice coverage over ocean gridpoints. The model topography was interpolated from the 1-km resolution digital elevation model of Liu et al. (2001). Images of the model domain, topography and land use specifications can be found here. More information on the physics in Polar MM5 can be found on the Polar MM5 Webpage, http://polarmet.mps.ohio-state.edu/PolarMet/pmm5.html Please reference the following publication if you use the data in a publication: Monaghan, A. J., D. H. Bromwich, and S.-H. Wang, 2006: Recent trends in Antarctic snow accumulation from Polar MM5. Philosophical Trans. Royal. Soc. A, 364, 1683-1708. proprietary
+bromwich_0337948_1 A 45-Y Hindcast of Antarctic Surface Mass Balance Using Polar MM5 ALL STAC Catalog 1979-01-01 2002-08-31 -180, -90, 180, -60 https://cmr.earthdata.nasa.gov/search/concepts/C1214586989-SCIOPS.umm_json This 3-year project (June 2004-May 2007) was funded by the National Science Foundation's Office of Polar Programs (Glaciology). We employed the Polar MM5 to model variability and change in the surface mass balance (the net accumulation of moisture) over Antarctica in recent decades. Available here are annually and seasonally resolved grids of atmospheric data simulated by Polar MM5 for the period Jan 1979-Aug 2002. The ERA-40 dataset provided the initial and boundary conditions for the simulations. The burden of validating the data provided is the responsibility of anyone choosing to download it. MODEL CONFIGURATION: The Polar MM5 simulations were performed on a 121 x 121 polar stereographic grid covering the Antarctic and centered over the South Pole. The model resolution is 60-km in each horizontal direction. Vertically, the domain contains 32 sigma levels ranging from the surface to 10 hPa. Atmospheric data (U,V,T,Q,P) and sea surface temperatures were provided by ERA-40. 25-km resolution daily sea ice concentration grids were provided by the National Snow and Ice Data Center to determine fractional ice coverage over ocean gridpoints. The model topography was interpolated from the 1-km resolution digital elevation model of Liu et al. (2001). Images of the model domain, topography and land use specifications can be found here. More information on the physics in Polar MM5 can be found on the Polar MM5 Webpage, http://polarmet.mps.ohio-state.edu/PolarMet/pmm5.html Please reference the following publication if you use the data in a publication: Monaghan, A. J., D. H. Bromwich, and S.-H. Wang, 2006: Recent trends in Antarctic snow accumulation from Polar MM5. Philosophical Trans. Royal. Soc. A, 364, 1683-1708. proprietary
brownbay_bathy_dem_1 A bathymetric Digital Elevation Model (DEM) of Brown Bay, Windmill Islands ALL STAC Catalog 1997-02-01 2000-02-05 110.54, -66.281, 110.548, -66.279 https://cmr.earthdata.nasa.gov/search/concepts/C1214308318-AU_AADC.umm_json This dataset is a Digital Elevation Model (DEM) of Brown Bay, Windmill Islands and contours and bathymetric contours derived from the DEM. The data are stored in a UTM zone 49 projection. They were created by interpolation of point data using Kriging. The input point data comprised soundings and terrestrial contour vertices. THE DATA ARE NOT FOR NAVIGATION PURPOSES. proprietary
brownbay_bathy_dem_1 A bathymetric Digital Elevation Model (DEM) of Brown Bay, Windmill Islands AU_AADC STAC Catalog 1997-02-01 2000-02-05 110.54, -66.281, 110.548, -66.279 https://cmr.earthdata.nasa.gov/search/concepts/C1214308318-AU_AADC.umm_json This dataset is a Digital Elevation Model (DEM) of Brown Bay, Windmill Islands and contours and bathymetric contours derived from the DEM. The data are stored in a UTM zone 49 projection. They were created by interpolation of point data using Kriging. The input point data comprised soundings and terrestrial contour vertices. THE DATA ARE NOT FOR NAVIGATION PURPOSES. proprietary
bryophyte-observer-bias_1.0 Greater observer expertise leads to higher estimates of bryophyte species richness ENVIDAT STAC Catalog 2024-01-01 2024-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226081769-ENVIDAT.umm_json This dataset contains bryophyte species count data and information about the observers bryophyte expertise for 2332 relevés conducted from 2011 to 2021 on 10-m2 plots in a long-term monitoring program in Switzerland. Plots were situated in raised bogs and fens of national importance, which were distributed across the whole country. The majority of the plots is represented by two relevés as sites are revisited every six years. The dataset was used in the paper mentioned below to test if species richness estimates differed among categories of observer expertise. Moser T, Boch S, Bedolla A, Ecker KT, Graf UH, Holderegger R, Küchler H, Pichon NA, Bergamini A (2024) Greater observer expertise leads to higher estimates of bryophyte species richness. _Journal of Vegetation Science_. (submitted) proprietary
@@ -17373,8 +17374,8 @@ c0b9f42f-640a-44e0-9080-7e80081942c9_NA MERIS - Water Parameters - North Sea, Da
c183044b88734442b6d37f5c4f6b0092_NA ESA Aerosol Climate Change Initiative (Aerosol_cci): Level 3 aerosol products from AATSR (ensemble product), Version 2.6 FEDEO STAC Catalog 2002-01-01 2012-04-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548143201-FEDEO.umm_json The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 3 daily, monthly and yearly gridded aerosol products from the AATSR instrument on the ENVISAT satellite. The data is an uncertainty-weighted ensemble of the outputs of three separate algorithms (the SU, ADV, and ORAC algorithms.) This product is version 2.6 of the ensemble product. Data is provided for the period 2002 to 2012. In the early period, it also contains data from the ATSR-2 instrument on the ERS-2 satellite. A separate ATSR-2 product covering the period 1995-2001 is also available, and together these form a continuous timeseries from 1995-2012.For further details about these data products please see the documentation. proprietary
c241e665-5175-4c26-b0cd-f0dfee32afdb Earthquakes events from ANSS 1970-March 2011 CEOS_EXTRA STAC Catalog 1970-01-02 2011-04-01 -180, -58, 180, 85.03594 https://cmr.earthdata.nasa.gov/search/concepts/C2232847370-CEOS_EXTRA.umm_json This dataset includes earthqakes events with magnitudes higher than 5.0 as reported by the Advanced national Seismic System (ANSS) Catalogue over the period 1970 - March 2011. UNEP/GRID-Europe processed the intensity buffer of each event following a methodology developped in GRAVITY I and II (http://www.grid.unep.ch/product/publication/download/ew_gravity1.pdf and http://www.grid.unep.ch/product/publication/download/ew_gravity2.pdf). Credit: Earthquakes events (USGS/ANSS), Intensity buffers UNEP/GRID-Europe. Attributes descriptions: EV_ID: Event ID ISO3YEAR: Country and year ISO3: Country ISO3 ID_NAT: Event ID and ISO3 ID_CAT: ANSS ID YEAR: Year START_DATE: Year, Month and Day (YYYYMMDD) MAG: Earthquake magnitude DEPTH: Earthquake depth (kilometer) RADIUS_M: Buffer radius following Gravity I and II methodology (meter) LATITUDE: Latitude (decimal degrees) proprietary
c2af8764c84744de87a69db7fecf7af9_NA ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 06.1 FEDEO STAC Catalog 1991-08-05 2020-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548142704-FEDEO.umm_json The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.The v06.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.The data set should be cited using the following references:1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-20192. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001 proprietary
-c2d1361c3fcbc6c7b60b35791f7bbc45bf8079dc 3 year daily average solar exposure map Mali 3Km GRAS January 2008-2011 ALL STAC Catalog 1970-01-01 -15, 8, 5, 28 https://cmr.earthdata.nasa.gov/search/concepts/C1214603977-SCIOPS.umm_json This map contains the 3 year (2008-2011) daily average solar exposure (in Kmh/m2/day) with a resolution of 3Km for Mali for January. proprietary
c2d1361c3fcbc6c7b60b35791f7bbc45bf8079dc 3 year daily average solar exposure map Mali 3Km GRAS January 2008-2011 SCIOPS STAC Catalog 1970-01-01 -15, 8, 5, 28 https://cmr.earthdata.nasa.gov/search/concepts/C1214603977-SCIOPS.umm_json This map contains the 3 year (2008-2011) daily average solar exposure (in Kmh/m2/day) with a resolution of 3Km for Mali for January. proprietary
+c2d1361c3fcbc6c7b60b35791f7bbc45bf8079dc 3 year daily average solar exposure map Mali 3Km GRAS January 2008-2011 ALL STAC Catalog 1970-01-01 -15, 8, 5, 28 https://cmr.earthdata.nasa.gov/search/concepts/C1214603977-SCIOPS.umm_json This map contains the 3 year (2008-2011) daily average solar exposure (in Kmh/m2/day) with a resolution of 3Km for Mali for January. proprietary
c4_percent_1deg_932_1 ISLSCP II C4 Vegetation Percentage ORNL_CLOUD STAC Catalog 1993-01-01 1998-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784880272-ORNL_CLOUD.umm_json The photosynthetic composition (C3 or C4) of vegetation on the land surface is essential for accurate simulations of biosphere-atmosphere exchanges of carbon, water, and energy. C3 and C4 plants have different responses to light, temperature, CO2, and nitrogen; they also differ in physiological functions like stomatal conductance and isotope fractionation. A fine-scale distribution of these plant types is essential for earth science modeling.The C4 percentage is determined from data sets that describe the continuous distribution of plant growth forms (i.e., the percent of a grid cell covered by herbaceous or woody vegetation), climate classifications, the fraction of a grid cell covered in croplands, and national crop type harvest area statistics. The staff from the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II have made the original data set consistent with the ISLSCP-2 land/water mask. This data set contains a single file in ArcInfo ASCIIGRID format.This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets. proprietary
c4a7495d-6275-4169-8ceb-59cfaa2dd09b_NA METOP GOME-2 - Water Vapour (H2O) - Global FEDEO STAC Catalog 2007-01-23 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2207458016-FEDEO.umm_json The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational H2O total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total H2O column is retrieved from GOME solar backscattered measurements in the red wavelength region (614-683.2 nm), using the Differential Optical Absorption Spectroscopy (DOAS) method. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/ proprietary
c4aaero_1 CAMEX-4 AEROSONDE V1 GHRC_DAAC STAC Catalog 2001-08-19 2001-09-10 -81.4325, 30.2039, -80.649, 30.5738 https://cmr.earthdata.nasa.gov/search/concepts/C1979080632-GHRC_DAAC.umm_json The CAMEX-4 Aerosonde dataset contains temperature, humidity, and atmospheric pressure measurements collected to study the boundary layer below levels where traditional hurricane reconnasissance aircaft fly. The Aerosonde is an unmanned aerial vehicle with a wingspan of 2.9 meters (~9 feet) weighing approximately 14 kg (~31 lbs). Carrying a payload of air pressure, temperature and humidity probes, the aircraft can fly at altitudes from near the surface to 21,000 feet at speeds of 50-95 mph for periods of up to 30 hours. Controlled by dual computers and navigated by GPS, the Aerosonde is designed to economically collect meteorological data over a wide area. proprietary
@@ -17426,11 +17427,11 @@ calibgas_500_1 BOREAS Calibration Gas Standards ORNL_CLOUD STAC Catalog 1994-05-
canopychem_422_1 Seedling Canopy Chemistry, 1992-1993 (ACCP) ORNL_CLOUD STAC Catalog 1992-11-06 1993-03-15 -122.05, 37.4, -122.05, 37.4 https://cmr.earthdata.nasa.gov/search/concepts/C2776831590-ORNL_CLOUD.umm_json The nitrogen and chlorophyll concentrations of constructed Douglas-fir and bigleaf maple seedling canopies were determined. Canopy reflectance spectra were measured before foliage samples were collected. proprietary
canopyspec_423_1 Seedling Canopy Reflectance Spectra, 1992-1993 (ACCP) ORNL_CLOUD STAC Catalog 1992-11-06 1993-03-15 -122.05, 37.4, -122.05, 37.4 https://cmr.earthdata.nasa.gov/search/concepts/C2776849767-ORNL_CLOUD.umm_json The reflectance spectra of Douglas-fir and bigleaf maple seedling canopies were measured. Canopies varied in fertilizer treatment and leaf area density respectively. proprietary
capeden_management_gis_1 Cape Denison Management Zone GIS Dataset AU_AADC STAC Catalog 2004-01-01 2004-12-31 142.651, -67.014, 142.691, -67.003 https://cmr.earthdata.nasa.gov/search/concepts/C1214313393-AU_AADC.umm_json This GIS dataset is comprised of the boundary of the Visual Protection Zone at Cape Denison, Antarctica. The data were created for the Management Plan for Historic Site and Monument No 77 and Antarctic Specially Managed Area (ASMA) No 3 produced by the Australian Antarctic Division in 2004. The data are formatted according to the SCAR Feature Catalogue and are available for download (see Related URLS). proprietary
-capeden_sat_ikonos_1 A georeferenced high resolution satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast acquired on 26, 31 January 2001 AU_AADC STAC Catalog 2001-01-26 2001-01-31 142.5153, -67.0697, 143.03, -66.9478 https://cmr.earthdata.nasa.gov/search/concepts/C1214313394-AU_AADC.umm_json The following was done by a contractor for the Australian Antarctic Division: A satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast was created by combining parts of three satellite images acquired by the Ikonos satellite. Two of the images were acquired on 26 January 2001 and the third image was acquired on 31 January 2001. The multispectral component of the mosaic was then (i) pan sharpened to increase the resolution from 4 metres to 1 metre; and (ii) georeferenced. See the Quality section for details about the satellite images and the georeferencing. The georeferenced mosaic is stored in two parts. See the Satellite Image Catalogue entries in Related URLs for details. Three satellite image maps were produced from the georeferenced mosaic. See the SCAR Map Catalogue entries in Related URLs for details. proprietary
capeden_sat_ikonos_1 A georeferenced high resolution satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast acquired on 26, 31 January 2001 ALL STAC Catalog 2001-01-26 2001-01-31 142.5153, -67.0697, 143.03, -66.9478 https://cmr.earthdata.nasa.gov/search/concepts/C1214313394-AU_AADC.umm_json The following was done by a contractor for the Australian Antarctic Division: A satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast was created by combining parts of three satellite images acquired by the Ikonos satellite. Two of the images were acquired on 26 January 2001 and the third image was acquired on 31 January 2001. The multispectral component of the mosaic was then (i) pan sharpened to increase the resolution from 4 metres to 1 metre; and (ii) georeferenced. See the Quality section for details about the satellite images and the georeferencing. The georeferenced mosaic is stored in two parts. See the Satellite Image Catalogue entries in Related URLs for details. Three satellite image maps were produced from the georeferenced mosaic. See the SCAR Map Catalogue entries in Related URLs for details. proprietary
+capeden_sat_ikonos_1 A georeferenced high resolution satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast acquired on 26, 31 January 2001 AU_AADC STAC Catalog 2001-01-26 2001-01-31 142.5153, -67.0697, 143.03, -66.9478 https://cmr.earthdata.nasa.gov/search/concepts/C1214313394-AU_AADC.umm_json The following was done by a contractor for the Australian Antarctic Division: A satellite image mosaic of Cape Denison, Mackellar Islands and part of the George V Land Coast was created by combining parts of three satellite images acquired by the Ikonos satellite. Two of the images were acquired on 26 January 2001 and the third image was acquired on 31 January 2001. The multispectral component of the mosaic was then (i) pan sharpened to increase the resolution from 4 metres to 1 metre; and (ii) georeferenced. See the Quality section for details about the satellite images and the georeferencing. The georeferenced mosaic is stored in two parts. See the Satellite Image Catalogue entries in Related URLs for details. Three satellite image maps were produced from the georeferenced mosaic. See the SCAR Map Catalogue entries in Related URLs for details. proprietary
carabid-beetles-in-forests_2.0 Carabid beetles in forests ENVIDAT STAC Catalog 2019-01-01 2019-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814572-ENVIDAT.umm_json Carabidae data from all historic up to the recent projects (21.10.2019) of WSL, collected with various methods in forests of different types. Version 2 ('FIDO_global_extract 2019-11-22_18-11-24 WSL-Forest-Carabidae') contains additional data field PROJ_FALLENBEZEICHNUNG. Data are provided on request to contact person against bilateral agreement. proprietary
-casey_alk_clones_1 Alkane mono-oxygenase genes from marine sediment near Casey ALL STAC Catalog 2001-12-01 2001-12-25 110.3, -66.35, 110.35, -66.3 https://cmr.earthdata.nasa.gov/search/concepts/C1214313396-AU_AADC.umm_json This dataset consists of 67 DNA sequences of the alkane mono-oxygenase gene. The sequence data are in FASTA format which can be opened with word-processing as well as sequence analysis software. The clone library was created using the primers described by Kloos et al. (2006, Journal Microbiological Methods 66:486-496) F: AAYACNGCNCAYGARCTNGGNCAYAA and R:GCRTGRTGRTCNGARTGNCGYTG. The library was created from a marine sediment sample that was part of the SRE4 marine biodegradation experiment in O'Brien bay near Casey station. The sample used was from the sediment exposed to Special Antarctic Blend diesel 5-weeks after the time of deployment. These data were collected as part of AAS project 2672 - Pathways of alkane biodegradation in antarctic and subantarctic soils and sediments. proprietary
casey_alk_clones_1 Alkane mono-oxygenase genes from marine sediment near Casey AU_AADC STAC Catalog 2001-12-01 2001-12-25 110.3, -66.35, 110.35, -66.3 https://cmr.earthdata.nasa.gov/search/concepts/C1214313396-AU_AADC.umm_json This dataset consists of 67 DNA sequences of the alkane mono-oxygenase gene. The sequence data are in FASTA format which can be opened with word-processing as well as sequence analysis software. The clone library was created using the primers described by Kloos et al. (2006, Journal Microbiological Methods 66:486-496) F: AAYACNGCNCAYGARCTNGGNCAYAA and R:GCRTGRTGRTCNGARTGNCGYTG. The library was created from a marine sediment sample that was part of the SRE4 marine biodegradation experiment in O'Brien bay near Casey station. The sample used was from the sediment exposed to Special Antarctic Blend diesel 5-weeks after the time of deployment. These data were collected as part of AAS project 2672 - Pathways of alkane biodegradation in antarctic and subantarctic soils and sediments. proprietary
+casey_alk_clones_1 Alkane mono-oxygenase genes from marine sediment near Casey ALL STAC Catalog 2001-12-01 2001-12-25 110.3, -66.35, 110.35, -66.3 https://cmr.earthdata.nasa.gov/search/concepts/C1214313396-AU_AADC.umm_json This dataset consists of 67 DNA sequences of the alkane mono-oxygenase gene. The sequence data are in FASTA format which can be opened with word-processing as well as sequence analysis software. The clone library was created using the primers described by Kloos et al. (2006, Journal Microbiological Methods 66:486-496) F: AAYACNGCNCAYGARCTNGGNCAYAA and R:GCRTGRTGRTCNGARTGNCGYTG. The library was created from a marine sediment sample that was part of the SRE4 marine biodegradation experiment in O'Brien bay near Casey station. The sample used was from the sediment exposed to Special Antarctic Blend diesel 5-weeks after the time of deployment. These data were collected as part of AAS project 2672 - Pathways of alkane biodegradation in antarctic and subantarctic soils and sediments. proprietary
casey_aws_1 Automatic Weather Station Data from Casey AU_AADC STAC Catalog 1996-04-11 110, -66, 110, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214313356-AU_AADC.umm_json The automatic weather stations at the Australian stations (Casey, Davis, Macquarie Island, and Mawson) were installed by the Bureau of Meteorology. They collect information on the following (in the following units): date Time hh:mm wind speed knots wind direction degrees air temperature degrees celsius relative humidity percent air pressure hPa Times are in UT. Measurements are made at 4 metres. The fields in this dataset are: date time (hh:mm) wind speed (knots) wind direction (degrees) air temperature (degrees celsius) relative humidity (percent) air pressure (hPa) More current data are provided at the AWS data page at the provided URL. A download file is available from the provided URL which provides information about the locations where wind measurements at Casey have been made. The information was provided to David Smith of the Australian Antarctic Data Centre by Phil Smart of the Hobart office of the Bureau of Meteorology in February 2009. David added the coordinates and the information about their origin. proprietary
casey_biopiles_DSM_2013_1 Digital Surface Model of the biopiles and nearby area at Casey, derived from aerial photographs taken with an Unmanned Aerial Vehicle (UAV), 10 February 2013 AU_AADC STAC Catalog 2013-02-10 2013-02-10 110.5211, -66.2822, 110.5261, -66.2808 https://cmr.earthdata.nasa.gov/search/concepts/C1214308483-AU_AADC.umm_json The Digital Surface Model (DSM) was created by Dr Arko Lucieer of TerraLuma (http://www.terraluma.net/) and the University of Tasmania for the Terrestrial and Nearshore Ecosystems research group at the Australian Antarctic Division (TNE/AAD). An orthophoto was also created. See the metadata record 'Orthophoto of the biopiles and nearby area at Casey, derived from aerial photographs taken with an Unmanned Aerial Vehicle (UAV), 10 February 2013' with ID 'casey_biopiles_ortho_2013'. The products were requested for Australian Antarctic Science Project 4036: Remediation of petroleum contaminants in the Antarctic and subantarctic. The products were created from digital photos taken on the 10th February, 2013, with a Canon EOS 550D from a Mikrokopter Oktokopter piloted by Arko Lucieer and Zybnek Malenovsky. The products were georeferenced to ground control points surveyed using differential GPS by Dr Daniel Wilkins of TNE/AAD. Raw photo metadata: ISO-400, Focal Length 20mm, f/6.3 Exposure Time 1/1250 sec. Horizontal Datum: ITRF2000. proprietary
casey_ice_coring_1979_1 Casey Ice Coring Program - Operations and Data Report, 1979 AU_AADC STAC Catalog 1979-01-01 1980-12-31 110, -67, 115, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214308486-AU_AADC.umm_json A handwritten copy of the 1979 report on ice core drilling on Law Dome (final draft?) Includes detailed notes on methods and equipment, as well as data for inclination, temperature and diameters of boreholes for several sites (SGF, SGP, SGB, BHQ), and results of measurements from S2. proprietary
@@ -17473,8 +17474,8 @@ chlorophyll_65-02_1 Long-term variation of surface phytoplankton chlorophyll a i
chm-hp-4rtm_1.0 Forest canopy structure data for radiation and snow modelling (CH/FIN) ENVIDAT STAC Catalog 2020-01-01 2020-01-01 9.871859, 46.845432, 26.6365886, 67.366827 https://cmr.earthdata.nasa.gov/search/concepts/C2789814990-ENVIDAT.umm_json This dataset contains forest canopy structure data acquired in a spruce forest at Laret, Switzerland, and a pine forest at Sodankylä, Finland. Data include: * Hemispherical photographs taken at transect intersection points of 13 experimental plots (40x40m each) * a Canopy Height Model (tree height map) derived by rasterizing airborne LiDAR data, encompassing the entire simulation domain at Laret (150'000 m2) These data provide the necessary basis for creating canopy structure datasets to be used as input to the forest snow snow model FSM2. These datasets, the model input derivatives and the radiation and snow modelling are described in detail in the following publication: _Mazzotti, G., Webster, C., Essery, R., and Jonas, T. (2021) Improving the physical representation of forest snow processes in coarse-resolution models: lessons learned from upscaling hyper-resolution simulations. Water Resources Research 57, e2020WR029064. [doi: 10.1029/2020WR029064](https://doi.org/10.1029/2020WR029064)_ This publication must be cited when using the data. ### See also: For additional information on the FSM2 model, see the corresponding [GitHub repository](https://github.com/GiuliaMazzotti/FSM2/tree/hyres_enhanced_canopy) The datasets and the model have also been used in _Mazzotti et al. (2020) Process-level evaluation of a hyper-resolution forest snow model using distributed multi-sensor observations. [doi: 10.1029/2020WR027572](https://doi.org/10.1029/2020WR027572) proprietary
climate-change-scenarios-at-hourly-resolution_1.0 Dataset for: Climate change scenarios at hourly time-step over Switzerland from an enhanced temporal downscaling approach ENVIDAT STAC Catalog 2021-01-01 2021-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814547-ENVIDAT.umm_json In fall 2019, a new set of climate change scenarios has been released for Switzerland, the CH2018 dataset (www.climate-scenarios.ch). The data are provided at daily resolution. We produced from the CH2018 dataset a new set of climate change scenarios temporally downscaled at hourly resolution. In addition, we extended this dataset integrating the meteorological stations from the Inter-Cantonal Measurement and Information System (IMIS) network, an alpine network of automatic meteorological stations operated by the WSL Institute for Snow and Avalanche Research SLF. The extension to the IMIS network is obtained using a Quantile Mapping approach in order to perform a spatial transfer of the CH2018 scenarios from the location of the MeteoSwiss stations to the location of the IMIS stations. The temporal downscaling is performed using an enhanced Delta-Change approach. This approach is based on objective criteria for assessing the quality of the determined delta and downscaled time series. In addition, this method also fixes a flaw of common quantile mapping methods (such as used in the CH2018 dataset for spatial downscaling) related to the decrease of correlation between different variables. The idea behind the delta change approach is to take the main seasonal signal (and mean) from climate change scenarios at daily resolution and to map it to a historical time series at hourly resolution in order to modify the historical time series. The obtained time series exhibit the same seasonal signal as the original climate change time series, while it keeps the sub-daily cycle from the historical time series. The applied methods (Quantile Mapping and Delta-Change) have limitations in correctly representing statistically extreme events and changes in the frequency of discontinuous events such as precipitation. In addition, the sub-daily cycle in the data is inherited from the historical time series, so there is no information of the climate change signal in this sub-daily cycle. A careful reading of the paper accompanying the dataset is necessary to understand the limitations and scope of application of this new dataset. This material is distributed under CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/legalcode). proprietary
climate_iceberg_1 Antarctic CRC and Australian Antarctic Division Climate Data Set - Australian iceberg observations AU_AADC STAC Catalog 1978-12-13 2001-03-20 -160, -70, 45, -40 https://cmr.earthdata.nasa.gov/search/concepts/C1214313409-AU_AADC.umm_json This dataset contains iceberg observations collected routinely on Australian National Antarctic Research Expeditions (ANARE) by Antarctic expeditioners on a volunteer basis. The observations were made each austral summer from the 1978/1979 season until the 2000/2001 season. Data included voyage number, date, time, latitude, longitude, sea ice concentration, water temperature, total icebergs, number of icebergs in each width category, the width to height ratio of selected larger tabular icebergs. It was been compiled and presented on the web by the Glaciology program of the Antarctic CRC (now ACE CRC). proprietary
-climate_pressure_1 ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air pressure AU_AADC STAC Catalog 1901-01-01 1998-12-31 -180, -80, 180, -17 https://cmr.earthdata.nasa.gov/search/concepts/C1214313319-AU_AADC.umm_json This dataset consists of tabulations of mean monthly surface air pressure for most occupied stations in Antarctic and the Southern Ocean. Some South Pacific Island stations are also included, along with a few continent based stations. The data have been collected from various climate sources world wide, and spans varying years ranging between 1901 and 2002. proprietary
climate_pressure_1 ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air pressure ALL STAC Catalog 1901-01-01 1998-12-31 -180, -80, 180, -17 https://cmr.earthdata.nasa.gov/search/concepts/C1214313319-AU_AADC.umm_json This dataset consists of tabulations of mean monthly surface air pressure for most occupied stations in Antarctic and the Southern Ocean. Some South Pacific Island stations are also included, along with a few continent based stations. The data have been collected from various climate sources world wide, and spans varying years ranging between 1901 and 2002. proprietary
+climate_pressure_1 ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air pressure AU_AADC STAC Catalog 1901-01-01 1998-12-31 -180, -80, 180, -17 https://cmr.earthdata.nasa.gov/search/concepts/C1214313319-AU_AADC.umm_json This dataset consists of tabulations of mean monthly surface air pressure for most occupied stations in Antarctic and the Southern Ocean. Some South Pacific Island stations are also included, along with a few continent based stations. The data have been collected from various climate sources world wide, and spans varying years ranging between 1901 and 2002. proprietary
climate_sea_ice_1 Antarctic CRC and Australian Antarctic Division Climate Data Set - Northern extent of Antarctic sea ice AU_AADC STAC Catalog 1973-01-18 1996-12-19 -180, -80, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1214313423-AU_AADC.umm_json This dataset contains the digitisation of one U.S. Navy/NOAA Joint Ice Facility sea ice extent and concentration map monthly to give the latitude and longitude of the northern extent of the Antarctic sea ice. Maps were produced weekly, but have been digitised monthly, since distribution began in January 1973 (except August 1985), until December 1996. Maps were digitised at each 10 degrees of longitude, and the longitude, distance from the south pole to the northern edge of the sea ice at that longitude, and latitude of that edge is given, as well as the mean distance and latitude for that map. Summary tabulations (sea ice northern extent latitudes at each 10 degree of longitude each year, grouped by month) and mean monthly sea ice extent statistics are also available. proprietary
climate_temps_1 ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air temperatures ALL STAC Catalog 1901-01-01 2002-12-31 -180, -80, 180, -17 https://cmr.earthdata.nasa.gov/search/concepts/C1214313410-AU_AADC.umm_json This dataset consists of tabulations of mean monthly surface air temperature for most occupied stations in Antarctic and the Southern Ocean. Some South Pacific Island stations are also included, along with a few continent based stations. The data have been collected from various climate sources world wide, and spans varying years ranging between 1901 and 2002. proprietary
climate_temps_1 ACE CRC and Australian Antarctic Division Climate Data Set - Mean monthly surface air temperatures AU_AADC STAC Catalog 1901-01-01 2002-12-31 -180, -80, 180, -17 https://cmr.earthdata.nasa.gov/search/concepts/C1214313410-AU_AADC.umm_json This dataset consists of tabulations of mean monthly surface air temperature for most occupied stations in Antarctic and the Southern Ocean. Some South Pacific Island stations are also included, along with a few continent based stations. The data have been collected from various climate sources world wide, and spans varying years ranging between 1901 and 2002. proprietary
@@ -17589,8 +17590,8 @@ distribution-maps-of-permanent-grassland-habitats-for-switzerland_1.0 Distributi
diversity-of-ground-beetles-and-spiders-as-well-as-cynipid-oak-gall-formation_1.0 Diversity of ground beetles and spiders as well as cynipid oak gall formation on irrigated and non-irrigated plots in a dry mixed Scots pine forest ENVIDAT STAC Catalog 2022-01-01 2022-01-01 7.6136971, 46.3021928, 7.6136971, 46.3021928 https://cmr.earthdata.nasa.gov/search/concepts/C2789814550-ENVIDAT.umm_json In the dry Pfynwald forest a long-term experiment of WSL was initiated in 2003 with a set of irrigated and non-irrigated plots. Forest Entomologie WSL made several investigations, one of them on the effect of irrigation (or conversely of drought) on the biodiversity of epigaeic arthropods such as ground beetles and spiders. In addition, its effects were also assessed by counting galls formed by gall wasps on pubescent oak. proprietary
diversity_of_woody_species-36_1.0 Diversity of woody species ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814561-ENVIDAT.umm_json Index based on the number of tree and shrub species starting at 12 cm dbh in the upper layer and the occurrence of especially ecologically valuable tree and shrub species starting at 12 cm dbh in the upper layer. __Citation:__ > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_ proprietary
dlhimpacts_1 Diode Laser Hygrometer (DLH) IMPACTS GHRC_DAAC STAC Catalog 2023-01-13 2023-02-28 -95.243, 35.753, -67.878, 48.237 https://cmr.earthdata.nasa.gov/search/concepts/C3247876662-GHRC_DAAC.umm_json The Diode Laser Hygrometer (DLH) dataset is comprised of water vapor mixing ratio measurements as well as relative humidities (both concerning liquid water and ice) which are derived from the water vapor mixing ratio and ambient static temperature and pressure provided by the TAMMS instrument suite. These measurements were made using two separate DLH instruments installed on the NASA P-3B research aircraft, and the data from these instruments were combined to provide the best combination of accuracy, dynamic range, and data coverage. The two DLH instruments are (1) the zenith-mounted system which utilizes an optical path between the zenith port and the aircraft’s vertical tail, and (2) the short-path system, which utilizes an optical path between two fuselage-mounted fins. This dataset was measured during the 2023 campaign of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) Earth Venture Suborbital 3 project. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S. Atlantic Coast (2020-2023). The project aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to advance prediction capabilities significantly. The DLH data files are available for flights from January 13, 2023, through February 28, 2023, and are in the ASCII format. proprietary
-doi:10.25921/sta3-3b95_Not Applicable 2014-2015 Untrawlable Habitat Strategic Initiative (UHSI) Video and Still Imagery Data Collection NOAA_NCEI STAC Catalog 2014-09-08 2015-05-08 -84.4, 27.7, -83.4, 29.7 https://cmr.earthdata.nasa.gov/search/concepts/C2107094639-NOAA_NCEI.umm_json The data collection deals with the optical data (i.e., video and still imagery) collected by natural light stereo cameras mounted on a MOdular Underwater Sampling System (MOUSS). The data collection consists of natively collected still images (5 frames per second) as well as the full length video and video segments that were created from original still images. Video annotations exist for the video segments; annotations are currently housed within a spreadsheet. The purpose was to execute a testbed study designed to evaluate the performance of transitional advanced technologies. All data are spatially located in the Florida Middle Grounds in the Gulf of Mexico. proprietary
doi:10.25921/sta3-3b95_Not Applicable 2014-2015 Untrawlable Habitat Strategic Initiative (UHSI) Video and Still Imagery Data Collection ALL STAC Catalog 2014-09-08 2015-05-08 -84.4, 27.7, -83.4, 29.7 https://cmr.earthdata.nasa.gov/search/concepts/C2107094639-NOAA_NCEI.umm_json The data collection deals with the optical data (i.e., video and still imagery) collected by natural light stereo cameras mounted on a MOdular Underwater Sampling System (MOUSS). The data collection consists of natively collected still images (5 frames per second) as well as the full length video and video segments that were created from original still images. Video annotations exist for the video segments; annotations are currently housed within a spreadsheet. The purpose was to execute a testbed study designed to evaluate the performance of transitional advanced technologies. All data are spatially located in the Florida Middle Grounds in the Gulf of Mexico. proprietary
+doi:10.25921/sta3-3b95_Not Applicable 2014-2015 Untrawlable Habitat Strategic Initiative (UHSI) Video and Still Imagery Data Collection NOAA_NCEI STAC Catalog 2014-09-08 2015-05-08 -84.4, 27.7, -83.4, 29.7 https://cmr.earthdata.nasa.gov/search/concepts/C2107094639-NOAA_NCEI.umm_json The data collection deals with the optical data (i.e., video and still imagery) collected by natural light stereo cameras mounted on a MOdular Underwater Sampling System (MOUSS). The data collection consists of natively collected still images (5 frames per second) as well as the full length video and video segments that were created from original still images. Video annotations exist for the video segments; annotations are currently housed within a spreadsheet. The purpose was to execute a testbed study designed to evaluate the performance of transitional advanced technologies. All data are spatially located in the Florida Middle Grounds in the Gulf of Mexico. proprietary
doi:10.25921/v3a2-m248_Not Applicable Archival and Discovery of November 27, 1945 Tsunami Event on Marigrams NOAA_NCEI STAC Catalog 1945-11-15 1945-12-01 66.97, 24.804, 66.97, 24.804 https://cmr.earthdata.nasa.gov/search/concepts/C2105865668-NOAA_NCEI.umm_json These water level data were digitized from a scanned marigram image associated with the tsunami event of 1945-11-27 at a tide gauge located at Karachi, Pakistan, and referenced to station datum. The Karachi marigram is one of the two instrumental records existing of the 1945 Makran tsunami and spans most of the 16 days between November 15 and December 1. The original Karachi analog record belongs to the Survey of India (SOI) and was collected and digitized by the National Institute of Oceanography (NIO) and Indian National Center for Ocean Information Services (INCOIS) for use in the publication of a few scientific papers. This digital marigram scan was reformatted into the accompanying digital, numerical time series by the Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO. Acknowledgement of SOI, NIO, and INCOIS should be included in any future scientific works using this record. proprietary
doi:10.7289/V51R6NQJ_Not Applicable Archival and Discovery of May 22, 1960 Tsunami Event on Marigrams NOAA_NCEI STAC Catalog 1960-05-18 1960-05-27 144.6539, 8.966667, -149.426667, 60.12 https://cmr.earthdata.nasa.gov/search/concepts/C2105865673-NOAA_NCEI.umm_json NOAA National Centers for Environmental Information have more than 3,000 tsunami marigram (tide gauge) records in both image and paper format. The majority of these tsunami marigram records were scanned to high-resolution digital tiff images during the NOAA Climate Data Modernization Program (CDMP). There still remain shelves full of deteriorating paper records that are in need of rescue reformatting to scanned images before they are lost. The 1946 tsunami is one of four 20th century tsunami events which are historically important but data during each reside only on the marigram records. The 1946 tsunami was the impetus for establishment of the Pacific Tsunami Warning Center after impact to the Hawaiian Islands. The 1952, 1960, and 1964 tsunamis were each generated by three of the greatest of all recorded earthquakes. The 1960 tsunami, in particular, was generated by the largest earthquake ever recorded, a magnitude 9.5 off the central coast of Chile. Measurements of these tsunamis are expected to provide researchers with important information linking earthquake rupture to tsunami generation and propagation characteristics. All data reformatted as part of this project will be brought into compliance with NOAA Data Directives and meet the requirements for Data Management, Discoverability, Accessibility, Documentation, Readability, and Data Preservation and Stewardship as per the Big Earth Data Initiative (BEDI). BEDI is designed to promote interoperability of Earth observation data across Federal agencies, systems and platforms through the improvement of data management practices and increased discoverability, accessibility, and usability of data collections. proprietary
doi:10.7289/V54X564T_Not Applicable Archival and Discovery of May 16, 1968 Tsunami Event on Marigrams NOAA_NCEI STAC Catalog 1968-05-13 1968-05-19 141, 13.4387, -124.18333, 41.745 https://cmr.earthdata.nasa.gov/search/concepts/C2105865675-NOAA_NCEI.umm_json NOAA National Centers for Environmental Information have more than 3,000 tsunami marigram (tide gauge) records in both image and paper format. The majority of these tsunami marigram records were scanned to high-resolution digital tiff images during the NOAA Climate Data Modernization Program (CDMP). There still remain shelves full of deteriorating paper records that are in need of rescue reformatting to scanned images before they are lost. As a follow-up to a successful 2016 BEDI project resulting in the archival and discovery of data held on marigrams during four large tsunamis (1946, 1952, 1960, 1964), marigrams from five additional tsunami events in 1854, 1883, 1896, 1933, and 1968 have been digitized. These additional five tsunami events were generated in both the Pacific and Indian Oceans and are rarely cited in research due to lack of data access. The five tsunami events proposed here for reformat, archive, and discovery in 2017 reside only on these same paper marigram records. Each of these datasets are of great importance as very little digital data exists from tsunamis that occurred during this time period, particularly those prior to the turn of the 20th Century. These events are not only historically important but with new research into tsunami probabilities, are statistically important as well. Similar to seismic hazard analyses, the tsunami community is now focused on tsunami recurrence rates through probabilistic tsunami hazard analysis to support land-use and construction decision-making. As a result, measurements of these tsunamis are not only expected to provide researchers with important information linking earthquake rupture to tsunami generation and propagation characteristics, but will add a significant number of tsunami data points to recurrence rates calculations. All data reformatted as part of this project will be brought into compliance with NOAA Data Directives and meet the requirements for Data Management, Discoverability, Accessibility, Documentation, Readability, and Data Preservation and Stewardship as per the Big Earth Data Initiative (BEDI). BEDI is designed to promote interoperability of Earth observation data across Federal agencies, systems and platforms through the improvement of data management practices and increased discoverability, accessibility, and usability of data collections. proprietary
@@ -17632,8 +17633,8 @@ ecmwf_met_1deg_1222_1 ISLSCP II ECMWF Near-Surface Meteorology Parameters ORNL_C
ecological-properties-of-urban-ecosystems-biodiversity-dataset-of-zurich_1.0 Ecological properties of urban ecosystems. Biodiversity dataset of Zurich ENVIDAT STAC Catalog 2020-01-01 2020-01-01 8.4639359, 47.3297483, 8.6026382, 47.4276227 https://cmr.earthdata.nasa.gov/search/concepts/C2789814615-ENVIDAT.umm_json Richness, site occurrence and abundance data of bees, beetles, birds, hoverflies, net-wingeds, true bugs, snails, spiders, milipides, wasps collected in the city of Zurich using different sampling techniques, and the environmental variables for each sampling site. Data are provided on request to contact person against bilateral agreement. proprietary
ecosystem-coupling-and-multifunctionality-exclosure-experiment_1.0 Ecosystem coupling and multifunctionality - exclosure experiment ENVIDAT STAC Catalog 2018-01-01 2018-01-01 10.0270844, 46.59481, 10.3951263, 46.7662842 https://cmr.earthdata.nasa.gov/search/concepts/C2789814632-ENVIDAT.umm_json "This dataset contains all data on which the following publication below is based. __Paper Citation:__ > Risch AC, Ochoa-Hueso R, van der Putten WH, Bump JK, Busse MD, Frey B, Gwiazdowicz DJ, Page-Dumroese DS, Vandegehuchte ML, Zimmermann S, Schütz M. Size-dependent loss of aboveground animals differentially affects grassland ecosystem coupling and functions. 2018. Nature Communications 9: 3684. [doi: 10.1038/s41467-018-06105-4](https://doi.org/10.1038/s41467-018-06105-4). Please cite this paper together with the citation for the datafile. #Methods ##Study sites The experimental exclosure setups were installed within the SNP (IUCN category Ia preserve; Dudley 2008), in south-eastern Switzerland. The park covers 172 km2 of forests and subalpine and alpine grasslands along with scattered rock outcrops and scree slopes. The entire area has been protected from human impact (no hunting, fishing, camping or off-trail hiking) since 1914. Large, fairly homogenous patches of short- and tall-grass vegetation, which originate from different historical management and grazing regimes, cover the park’s subalpine grasslands entirely. Short-grass vegetation developed in areas where cattle used to rest (nutrient input) prior to the park’s foundation (14th century to 1914) (Schütz and others 2003, 2006) and is dominated by lawn grass species such as Festuca rubra L., Briza media L. and Agrostis capillaris L. (Schütz and others 2003, 2006). Today, this vegetation type is intensively grazed by diverse vertebrate and invertebrate communities that inhabit the park and consume up to 60% of the available biomass (Risch and others 2013). Tall-grass vegetation developed where cattle formerly grazed, but did not rest, and is dominated by rather nutrient-poor tussocks of Carex sempervirens Vill. and Nardus stricta L. (Schütz and others 2003, 2006). This vegetation type receives considerably less grazing, with only roughly 20% of the biomass consumed (Risch and others 2013). Consequently, the two vegetation types together represent a long-term trajectory of changes in grazing regimes. Underlying bedrock of all grasslands is dolomite, which renders these grasslands rather poor in nutrients regardless of former and current land-use regimes. ##Experimental design To progressively exclude aboveground vertebrate and invertebrate animals, we established 18 size-selective exclosure setups (nine in short-grass, nine in tall-grass vegetation) distributed over six subalpine grasslands across the SNP (Risch and others 2013, 2015). Elevation differences of exclosure locations did not exceed 350 m (between 1975 and 2300 m a.s.l.). The exclosures were established immediately after snowmelt in spring 2009 and were left in place for five consecutive growing seasons (until end of 2013). They were, however, temporarily dismantled every fall (late October after first snowfall) to protect them from avalanches. They were re-established in the same location every spring immediately after snowmelt. Each size-selective exclosure setup consisted of five plots (2 x 3 m) that progressively excluded aboveground vertebrates and invertebrates from large to small. The plots are labelled according to the guilds that had access to them “L/M/S/I”, “M/S/I”, “S/I”, “I”, “None”; L = large mammals, M = medium mammals, S = small mammals, I = invertebrates, None = no animals had access. As we only had permission to have the experimental setup in place for five consecutive growing seasons, the experiment had to be completely dismantled in the late fall of 2013 and all material removed from the SNP. Our exclosure design was aimed at excluding mammalian herbivores, but naturally also excluded the few medium and small mammalian predators, as well as the entire aboveground invertebrate food web. A total of 26 large to small mammal species can be found in the SNP, but large apex predators are missing (wolf, bear, lynx) . Reptiles, amphibians and birds are scarce to absent in the subalpine grasslands under study. Only two reptile species occur in the park and they are confined to rocky areas that warm up enough for them to survive. One frog species spawns in an isolated pond far from our grasslands. Only three bird species occasionally feed on the subalpine grasslands. Using game cameras (Moultrie 6MP Game Spy I-60 Infrared Digital Game Camera, Moultrie Feeders, Alabaster, AL, USA), we did observe that the medium- and small-sized mammals (marmot/hares and mice) were not afraid to enter the fences and feed on their designated plots. We never spotted reptiles, amphibians or birds on camera. We distinguished between 59 higher aboveground-dwelling invertebrate taxa that our size-selective exclosures excluded (see also methods for aboveground-dwelling invertebrates below). The “L/M/S/I” plot (not fenced) was located at least 5 m from the 2.1 m tall and 7 x 9 m large main electrical fence that enclosed the other four plots. The bottom wire of this fence was mounted at 0.5 m height and was not electrified to enable safe access for medium and small mammals, while fencing out the large ones. Within each main fence, we randomly established four 2 x 3 m plots separated by 1-m wide walkways from one another and from the main fence line: 1) the “M/S/I” plots were unfenced, allowing access to all but the large mammals; 2) the “S/I” plots (10 x 10 cm electrical mesh fence) excluded all medium-sized mammals. Note that the bottom 10 cm of this fence remained non-electrified to enable safe access for small mammals; 3) the “I” plots (2 x 2 cm metal mesh fence) excluded all mammals. We double-folded the mesh at the bottom 50 cm to reduce the mesh size to smaller than 1 x 1 cm openings; and 4) the “None” plots were surrounded by a 1 m tall mosquito net (1.5 x 2 mm) to exclude all animals. The top of the plot was covered with a mosquito-meshed wooden frame mounted to the corner posts (roof). We treated these plots a few times with biocompatible insecticide (Clean kill original, Eco Belle GmbH, Waldshut-Tiengen, Germany) to remove insects that might have entered during data collection or that hatched from the soil, but amounts were negligible and did not impact soil moisture conditions within these plots. To assess whether the design of the “None” exclosure (mesh and roof) affected the response variables within the plots and, therefore, influenced the results, we established an additional six “micro-climate control” exclosures (one in each of the six grasslands) (Risch and others 2013, 2015). These exclosures were built as the “None” exclosures but were open at the bottom (20 cm) of the 3-m side of the fence facing away from the prevailing wind direction to allow invertebrates to enter. A 20-cm high and 3-m long strip of metal mesh was used to block access to small mammals. Thus, this construction allowed a comparable micro-climate to the “None” plots, but also a comparable feeding pressure by invertebrates to the “I” plots. We compared various properties within these exclosures against one another to assess if our construction altered the conditions in the “None” plots. We showed that differences in plant (e.g., vegetation height, aboveground biomass) and soil properties (e.g., soil temperature, moisture) found between the “I” and the “None” treatments were not due to the construction of the “None” exclosure, but a function of animal exclusions, although the amount of UV light reaching the plant canopy was significantly reduced (Risch and others 2013). ##Aboveground invertebrate sampling Aboveground invertebrates were sampled with two different methods to capture both ground- and plant-dwelling organisms: 1) we randomly placed two pitfall traps (67 mm in diameter, covered with a roof) filled with 20% propylene glycol in one 1 x 1 m subplot of the 2 x 3 m treatment plots in spring 2013 (May) and emptied them every two weeks until late September 2013 (Vandegehuchte and others 2017b, 2018). A pitfall trap consisted of a plastic cylinder (13 cm depth, 6.75 cm diameter). Within each cylinder we placed a 100 ml plastic vial with outer diameter 6.70 cm and on top of the cylinder we placed a plastic funnel to guide the invertebrates into the vials. Each trap was cover with a cone-shaped and transparent plastic roof to protect the trap from rain (Vandegehuchte and others 2017b, 2018). Note that in the “None” plots only one trap was placed as control to check for effectiveness of the exclosure. 2) We vacuumed all invertebrates from a 60 x 60 cm area on another 1 x 1 m subplot with a suction sampler (Vortis, Burkhard manufacturing CO, Ltd., Rickmansworth, Hertfordshire, UK) every month from June to September 2013 (Vandegehuchte and others 2017b, 2018). For this purpose, we quickly placed a square plastic frame (60 x 60 x 40 cm) with a closable mosquito mesh sleeve attached to the top edge into the plot from the outside. The suction sample was then inserted into through the sleeve and operated for 45 s to collect the invertebrates (Vandegehuchte and others 2017b, 2018). We sorted the ≈100 000 individuals collected with both methods by hand and identified each individual morphologically to the lowest taxonomic level feasible (59 taxa, including orders, suborders, subfamilies, families; phylum for Mollusca). These taxa belonged to the following feeding types: 19 herbivores, 16 detritivores, 9 predators, 8 mixed feeders, 5 omnivores and 2 non-classified feeders (or not feeding as adults) (Vandegehuchte and others 2017b). We summed the numbers from the two pitfall traps and the suction sampling over the course of the 2013 season to represent the aboveground invertebrate abundance and community composition of a plot. Note: we did not specifically attempt to catch flying invertebrates with e.g., sticky traps, thus a few flying insects may have been missed with our vacuum sampling approach. ##Sampling of plant properties The vascular plant species composition was assessed at peak biomass every summer (July) by estimating the frequency of occurrence of each species with the pin count method in each plot (Frank and McNaughton 1990). A total of 172 taxa occurred within our 90 plots and we calculated plant species richness for each plot separately. We used the 2013 data in this study. Plant quality was assessed every year in July and September; here we use plant quality at the end of the experiment (September 2013). Two 10 x 100 cm wide strips of vegetation per plot were clipped, combined, dried at 65°C, and ground (Pulverisette 16, Fritsch, Idar-Oberstein, Germany) to pass through a 0.5 mm sieve. Twenty randomly selected samples across all treatments were analysed for N (Leco TruSpec Analyser, Leco, St. Joseph, Michigan, USA) (Vandegehuchte and others 2015). Nitrogen concentrations of the other samples were then estimated from models established for the experiment and the entire SNP relating Fourier transform-near infrared reflectance (FT-NIR) spectra to the measured values of N using a multi-purpose FT-NIR spectrometer (Bruker Optics, Fällanden, Switzerland) (Vandegehuchte and others 2015). Root biomass was sampled every fall by collecting five 2.2 cm diameter x 10 cm deep soil samples (Giddings Machine Company, Windsor, CO, USA) per plot (450 samples year-1). The samples were dried at 30 °C and roots were sorted from the sample by hand. We sorted each sample for 1 h which allowed to retrieve over 90% of all roots present in the samples (Risch and others 2013). The roots were then dried at 65 °C for 48 and weighed to the nearest mg. We averaged the values per plot and used the 2013 data only in this study. ##Sampling of edaphic communities In 2009, 2010, and 2011 we collected three composited soil samples (5 cm diameter x 10 cm depth; AMS Samplers, American Falls, ID, USA) and assessed bacterial community structure using T-RFLP profiling (Liu and others 1997; Blackwood and others 2003; Hodel and others 2014). We detected a total of 89 operational taxonomic units (OTUs). These values are in accordance with other studies reporting OTU richness (Wirthner and others 2011; Zumsteg and others 2012; Meola and others 2014) using T-RFLP profiling, a method that detects the most abundant, and thus likely, the most relevant, taxa. We averaged the data over the three years of collections for our calculations. Microbial biomass carbon (MBC) was determined with the substrate-induced method (Anderson and Domsch 1978) every fall (September) between 2009 and 2013 by collecting three mineral soil samples (5 cm diameter × 10 cm mineral soil core, AMS Samplers, American Falls, ID, USA). The three samples were combined (90 samples for each sampling year), immediately put on ice, taken to the laboratory, passed through a 2-mm sieve and stored at 4°C. Again, we only used the 2013 data in this study. Soil samples (5 cm diameter x 10 cm depth) to extract soil arthropods were collected in June, July, and August 2011 with a soil corer lined with a plastic sleeve to ensure an undisturbed sample (total of 270 samples). The plastic line core was immediately sealed on both ends using cling film and put into a cooler. All plots were sampled within three days and the extraction of arthropods started the evening of the sampling day using a high-gradient Tullgren funnel apparatus (Crossley and Blair 1991; Vandegehuchte and others 2015). Samples were kept in the extractor for four days and the soil arthropods were collected in 95% ethanol. All individuals were counted and each individual was identified morphologically to the lowest level feasible [76 taxa, including orders, suborders, subfamilies, families (Protura, Thysanoptera, Aphidina, Psylina, Coleoptera, Brachycera, Nematocera, Auchenorryncha, Heteroptera, Formicidae); sub-phylum for Myriapoda, for Acari and Collembola also including morpho-species). Note that we also included larval stages (nine of the 76 taxa) (Vandegehuchte and others 2015). All data were summed over the season. A detailed species list for mites and collembolans is published (Vandegehuchte and others 2017a) [https://doi.org/10.1371/journal.pone.0118679.s001]. Earthworms are rare in the SNP and therefore were not included. We collected eight random 2.2 cm diameter x 10 cm deep soil cores from each plot in September 2013 to determine the soil nematode community composition. The samples were mixed and the nematodes were extracted from 100 ml of fresh soil using Oostenbrink elutriators (Oostenbrink 1960). All nematodes in a 1 ml of the 10 ml extract were counted, a minimum of 150 individuals sample-1 were identified to genus or family level using (Bongers 1988), the numbers of all nematodes were extrapolated to the entire sample and expressed for a 100 g dry sample. In total we identified 63 genus or family levels (Vandegehuchte and others 2015). The list of all the nematodes found is published (Vandegehuchte and others 2015) [http://www.oikosjournal.org/appendix/oik-03341] or DOI: [doi: 10.1111/oik.03341]. We are aware that sampling soil microbes from 2009 to 2011 and soil arthropods in 2011 was not ideal, but we are positive that this does not bias the results. Most of the parameters measured in our experiment either already showed a treatment response after the first growing season (e.g., plant biomass) or did not respond over the entire time experiment (e.g., microbial biomass C). The microbial community composition (2009 – 2011) was highly influenced by inter-annual differences in temperature and precipitation, but did not differ between treatments or vegetation types (Hodel and others 2014). We therefore felt comfortable using the 2009 through 2011 data for describing the soil microbial community in our experimental treatments. Similarly, we are positive that our soil arthropod data are representative. We did assess soil arthropods in August 2012 and found no differences to the August 2011 data. However, we did not feel comfortable combining the 2011 June, July, August data with only August data for 2012 for our analyses. ##Sampling of soil properties We collected three soil samples (5 cm diameter x 10 cm depth) in each plot in September 2013 after removing the vegetation. First, we collected the top layer of mineral soil rich in organic matter, the surface organic layer or rhizosphere, typically 1 to 3 cm in depth with a soil corer (AMS Samples, American Falls, Idaho, USA). Second, we collected a 10 cm mineral soil core beneath this surface layer. The cores for each layer were composited, dried at 65 °C for 48 h and fine-ground to pass a 0.5 mm screen. We then analysed all samples for total C using a Leco TruSpec Analyser (Leco, St. Joseph, Michigan, USA). Mineral soil pH was measured potentiometrically in 1:2 soil:CaCl2 solution with an equilibration time of 30 min. Soil net N mineralisation was assessed during the 2013 growing season (Risch and others 2015). For this purpose, we randomly collected a 5 cm diameter x10 cm deep soil sample with a soil corer (AMS Samples, American Falls, Idaho, USA) after clipping the vegetation in June 2013. After weighing and sieving (4 mm mesh) the soil, we extracted a 20 g subsample in 1 mol l-1 KCl for 1.5 h on an end-over-end shaker and thereafter filtered it through ashless folded filter paper (DF 5895 150, ALBET LabScience, Hahnenmühle FineArt GmbH, Dassel, Germany). From these filtrates NO3- concentrations were measured colorimetrically (Norman and Stucki 1981) and NH4+with flow injection analysis (FIAS 300, Perkin Elmer, Waltham Massachusetts, USA) (Risch and others 2015). We dried the rest of the sample 105 °C to constant mass to determine fine,fraction bulk density. A second soil sample was collected within each plot in June 2013 with a corer lined with a 5 x 13 cm aluminium cylinder. The corer was driven 11.5 cm deep into the soil so that the top 1.5 cm of the cylinder remained empty. Into this space we placed a polyester bag (250 µm) filled an ion-exchanger resin to capture the incoming N. The bag was filled with a 1:1 mixture of acidic and alkaline exchanger resin (ion-exchanger I KA/ion exchanger IIIAA, Merck AG, Darmstadt, Germany). We then removed 1.5 cm soil at the bottom of the cylinder and placed a second resin exchanger bag into this space to capture the N leached from the soil column. To assure that the exchange resin was saturated with H+ and Cl- prior to filling the bags, the mixture was stirred with 1.2 ml l-1 HCl for 1 h and then rinsed with demineralized water until the electrical conductivity of the water reached 5 µm cm-1. The cylinder with the resin bags in place was reinserted into the soil with the top flush to the soil surface and incubated for three months. We recollected the cylinders in September 2013. Each resin bag and 20 g of sieved soil (4 mm mesh) from each cylinder were then separately extracted with KCl and NO3- and NH4+ concentrations were measured. Nitrate and NH4+ concentrations of all samples were then converted to a content basis by multiplying their values with fine fraction bulk density. Net N mineralisation was thereafter calculated as the difference between the N content of the samples collected at the end of the three-month incubation (including the N extracted from the bottom resin bag) and the N content at the beginning of the incubation (Risch and others 2015). Soil CO2 emissions were measured every two weeks between 0900 and 1700 hrs from early May through late September 2013 with a PP-Systems SRC-1 soil respiration chamber (15 cm high, 10 cm diameter; closed circuit) attached to a PP-Systems EGM-4 infrared gas analyser (PP-Systems, Amesbury, MA, USA) on two locations per plot (Risch and others 2013). The chamber was placed on randomly placed, permanently installed PVC collars (10 cm diameter) driven 5 cm into the soil at the beginning of the study (Risch and others 2013). Freshly germinated plants growing within the collars were removed prior to each measurement to avoid measuring plant respiration or photosynthesis. The two measurements collected per plot and sampling date were averaged. Soil moisture (with time domain reflectometry; Field-Scout TDR-100, Spectrum Technologies, Plainfield, Illionois, USA) and temperature (with a waterproof digital pocket thermometer; Barnstead International, Dubuque, Iowa, USA) were measured at five random locations per plot every two weeks during the growing seasons during the experiment for the 0 to 10 cm depth (Risch and others 2013, 2015). As soil moisture and soil temperature were highly negatively correlated (Risch and others 2013), we only used soil moisture for this study. We used plot-level averages of all values available to capture soil moisture variability during the five years of the experiment. The results remained unchanged when we only used soil moisture from the 2013 growing season. ##Numeral calculations and statistical analyses Ecosystem coupling. We conducted principal component analyses (PCAs; unscaled) at the complete dataset level using the abundances of each taxonomical entity to describe each of the five different communities used in this study: aboveground-dwelling invertebrates, vascular plants, soil microorganisms, soil arthropods and soil nematodes. We retained the first two components (PCA axis 1 and PCA axis 2) of each analysis as we found them to adequately represent the temporal and spatial variability of our 90 treatment plots in previous studies55,67. Together they explained a total of 71.70% of the variation for aboveground invertebrates, 44.36% for plants, 44.85% for soil microorganisms, 61.85% for soil arthropods and 77.19% for soil nematodes. In addition, we used soil pH and soil organic C content as a proxy for soil chemical properties, soil bulk density as a proxy for soil physical properties and soil moisture (negatively correlated with soil temperature) as a proxy for soil micro-climatic conditions for an overall total of fourteen constituents. We calculated ecosystem coupling9 for each exclosure treatment within each vegetation type (i.e., 2 5 treatment combinations in total) as an integrated measure of pairwise ecological interactions between ecosystem constituents representing ecological communities and the soil abiotic environment. These ecological interactions are defined by non-parametric Spearman rank correlation analyses between two constituents, excluding interactions involving two abiotic constituents (e.g., soil pH vs. soil moisture) and interactions between the first (PC1) and second (PC2) component of each community type, as these are orthogonal by definition. Interactions between abiotic constituents were excluded from the analyses because the focus of our study was on communities and how they interact with one another and their surrounding environment; therefore, including abiotic-abiotic interactions was not of interest here. Given that the effectiveness of our experimental design resulted in that no community composition data of aboveground-dwelling invertebrates was available for the “None” plots (all animals excluded), only thirteen instead of fourteen constituents were included in the ecosystem coupling calculations for this treatment. The complete absence of aboveground invertebrates represents the most extreme case of disturbance between aboveground animal communities and the rest of the ecosystem constituents. This may have resulted in a slight overestimation of ecosystem coupling for these plots. Average ecosystem coupling was calculated as follows: Ecosystem coupling= where Xi is the absolute Coupling was calculated value of the Spearman’s rho coefficient of the ith correlation for each treatment within each vegetation type (i.e., based on nine replicates each), considering and n is the number of pairwise comparisons considered (n = a total of 80; interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment). Coupling was calculated for each treatment within each vegetation type (i.e., based on nine replicates each), considering a total of 80 interactions (56 in the case of the “None” treatment). We considered a total of 40 biotic-biotic interactions (i.e., concerning two community-level principal components such as plants and microbes; 24 in the case of the “None” treatment) and 40 abiotic-biotic (i.e., concerning one community-level principal component and one abiotic factor, e.g., plant community and soil properties; 32 in the case of the “None” treatment). To establish whether constituents were significantly and positively coupled within treatments (i.e., the average of their correlation coefficients were greater than in a null model where correlation only happens by chance), we calculated one-tailed p-values based on permutation tests with 999 permutations. We considered six ecosystem functions and process rates commonly used to assess ecosystem functioning (Meyer and others 2015; Manning and others 2018). Plant N content represents a measure of forage quality, while plant richness has been shown to stabilise biomass production, thus allowing the system to respond to changes in herbivory. Soil net N mineralisation, soil respiration, root biomass, and microbial biomass represent fluxes or stocks of energy. For all functions and processes higher values represent higher functioning (Manning and others 2018). All these variables were measured in the last year of the experiment (2013). We then quantified ecosystem multifunctionality using the multiple threshold approach (Byrnes and others 2014; Manning and others 2018), which considers the number of functions that are above a certain threshold, over a series of threshold values (typically 10-99%) that are defined based on the maximum value of each function. We weighted all our functions equally for these calculations (Manning and others 2018). The number of functions in a plot with values higher than a given threshold value for the respective function is summed up. The sum represents ecosystem multifunctionality for that plot. Given that choosing any particular threshold as a measure of ecosystem multifunctionality is arbitrary, we calculated the average of thresholds from 10-90% (in 10% intervals) as a more integrated representation of ecosystem multifunctionality. We used Pearson correlations to explore the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and ecosystem multifunctionality by calculating the slopes of all relationships between ecosystem coupling and multifunctionality for all thresholds between 10 and 99%. We also related ecosystem coupling with the average of multifunctionality at thresholds between 30-80% as explained before and considered this correlation as a robust indication of the type of association between these two variables. In addition, we explored the relationships between ecosystem coupling (all interactions, biotic-biotic interactions, abiotic-biotic interactions involving above- and belowground constituents, and all interactions, biotic-biotic interactions, abiotic-biotic interactions involving belowground constituents only) and individual ecosystem functions. The effects of exclosures and vegetation type on individual functions and multifunctionality were evaluated using linear mixed effects models ('lme' function of the nlme package), with exclosure and vegetation type as fixed effects and fence as a random factor. All statistical analyses and numerical calculations were done in R version 3.4.0 (R Core Team 2016). #References - Anderson J, Domsch K. 1978. A physiological method for the quantitative measurement of microbial biomass in soil. Soil Biol Biochem 10:215–21. - Blackwood CB, Marsh T, Kim S-H, Paul EA. 2003. 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Oikos 57:57–60. - Haynes AG, Schütz M, Buchmann N, Page-Dumroese DS, Busse MD, Risch AC. 2014. Linkages between grazing history and herbivore exclusion on decomposition rates in mineral soils of subalpine grasslands. Plant Soil 374. - Hodel M, Schütz M, Vandegehuchte ML, Frey B, Albrecht M, Busse MD, Risch AC. 2014. Does the aboveground herbivore assemblage influence soil bacterial community composition and richness in subalpine grasslands? Microb Ecol 68:584–95. - Liu WT, Marsh TL, Cheng H, Forney LJ. 1997. Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microbiol 63:4516–22. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC168770/ - Manning P, van der Plas F, Soliveres S, Allan E, Maestre FT, Mace G, Whittingham MJ, Fischer M. 2018. Redefining ecosystem multifunctionality. Nat Ecol Evol 2:427–36. https://doi.org/10.1038/s41559-017-0461-7 - Meola M, Lazzaro A, Zeyer J. 2014. Diversity, resistance and resilience of the bacterial communities at two alpine glacier forefields after a reciprocal soil transplantation. Environ Microbiol 16:1918–34. https://onlinelibrary.wiley.com/doi/abs/10.1111/1462-2920.12435 - Meyer ST, Koch C, Weisser WW. 2015. Towards a standardized Rapid Ecosystem Function Assessment (REFA). Trends Ecol Evol 30:390–7. http://www.sciencedirect.com/science/article/pii/S0169534715000968 - Norman R., Stucki JW. 1981. The determination of nitrate and nitrite in soil extracts by ultraviolet spectrophotometry. Soil Sci Soc Am J 45:347–53. - Ochoa-Hueso R. 2016. Non-linear disruption of ecological interactions in response to nitrogen deposition. Ecology 87:2802–2814. - Oostenbrink M. 1960. Estimating nematode populations by some selected methods. In: Sasser NJ, Jenkins WR, editors. Nematology. Chapel Hill, NC, USA: University of North Carolina Press. pp 85–101. - R Core Team. 2016. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing - Risch AC, Haynes AG, Busse MD, Filli F, Schütz M. 2013. The response of soil CO2 fluxes to progressively excluding vertebrate and invertebrate herbivores depends on ecosystem type. Ecosystems 16:1192–202. - Risch AC, Schütz M, Vandegehuchte ML, Van Der Putten WH, Duyts H, Raschein U, Gwiazdowicz DJ, Busse MD, Page-Dumroese DS, Zimmermann S. 2015. Aboveground vertebrate and invertebrate herbivore impact on net N mineralization in subalpine grasslands. Ecology 96:3312–22. - Schütz M, Risch AC, Achermann G, Thiel-Egenter C, Page-Dumroese DS, Jurgensen MF, Edwards PJ. 2006. Phosphorus translocation by red deer on a subalpine grassland in the Central European Alps. Ecosystems 9:624–633. - Schütz M, Risch AC, Leuzinger E, Krüsi BO, Achermann G. 2003. Impact of herbivory by red deer (Cervus elaphus L.) on patterns and processes in subalpine grasslands in the Swiss National Park. For Ecol Manage 181:177–88. - Vandegehuchte ML, van der Putten WH, Duyts H, Schütz M, Risch AC. 2017a. Aboveground mammal and invertebrate exclusions cause consistent changes in soil food webs of two subalpine grassland types, but mechanisms are system-specific. Oikos 126:212–23. - Vandegehuchte ML, Raschein U, Schütz M, Gwiazdowicz DJ, Risch AC. 2015. Indirect short- and long-term effects of aboveground invertebrate and vertebrate herbivores on soil microarthropod communities. PLoS One 10:e0118679. - Vandegehuchte ML, Schütz M, de Schaetzen F, Risch AC. 2017b. Mammal-induced trophic cascades in invertebrate food webs are modulated by grazing intensity in subalpine grassland. J Anim Ecol 86:1434–46. - Vandegehuchte ML, Trivellone V, Schütz M, Firn J, de Schaetzen F, Risch AC. 2018. Mammalian herbivores affect leafhoppers associated with specific plant functional types at different timescales. Funct Ecol 32:545–55. - Wirthner S, Frey B, Busse MD, Schütz M, Risch AC. 2011. Effects of wild boar (Sus scrofa L.) rooting on the bacterial community structure in mixed-hardwood forest soils in Switzerland. Eur J Soil Biol 47:296–302. http://dx.doi.org/10.1016/j.ejsobi.2011.07.003 - Zumsteg A, Luster J, Göransson H, Smittenberg RH, Brunner I, Bernasconi SM, Zeyer J, Frey B. 2012. Bacterial, Archaeal and Fungal Succession in the Forefield of a Receding Glacier. Microb Ecol 63:552–64. https://doi.org/10.1007/s00248-011-9991-8" proprietary
ecosystem_roots_1deg_929_1 ISLSCP II Ecosystem Rooting Depths ORNL_CLOUD STAC Catalog 1995-02-01 1995-07-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784847849-ORNL_CLOUD.umm_json The goal of this study was to predict the global distribution of plant rooting depths based on data about global aboveground vegetation structure and climate. Vertical root distributions influence the fluxes of water, carbon, and soil nutrients and the distribution and activities of soil fauna. Roots transport nutrients and water upwards, but they are also pathways for carbon and nutrient transport into deeper soil layers and for deep water infiltration. Roots also affect the weathering rates of soil minerals. For calculating such processes on a global scale, data on vertical root distributions are needed as inputs to global biogeochemistry and vegetation models. In the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS), rooting depth and vertical soil characteristics were the most important factors explaining scatter for simulated transpiration among 14 land-surface models. Recently, the Terrestrial Observation Panel for Climate of the Global Climate Observation System (GCOS) identified the 95% rooting depth as a key variable needed to quantify the interactions between the climate, soil, and plants, stating that the main challenge was to find the correlation between rooting depth and soil and climate features (GCOS/GTOS Terrestrial Observation Panel for Climate 1997). In response to this challenge, a data set of vertical rooting depths was collected from the literature in order to construct maps of global ecosystem rooting depths.The parameters included in these data sets are estimates for the soil depths containing 50% and 95% of all roots, termed 50% and 95% rooting depths (D50 and D95, respectively). Together, these variables can be used to calculate estimates for vertical root distributions, using a logistic equation provided in this documentation. The data represent mean ecosystem rooting depths for 1 by 1 degree grid cells. Related data sets: The ORNL DAAC offers related data sets by Jackson et al. (2003), Gordon and Jackson (2003), Schenk and Jackson (2003), and Gill and Jackson (2003).This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets. proprietary
-ecousm1 A comparative study on floral ecology between Malaysia and Antarctica SCIOPS STAC Catalog 1970-01-01 110.32, -66.28, 110.32, -66.28 https://cmr.earthdata.nasa.gov/search/concepts/C1214621680-SCIOPS.umm_json The major objectives of this project are as follows: 1. To determine the composition and distribution of algal flora from a wide range of habitats, which provide a conductive niche for algal population in Antarctica. 2. To compare the Antarctic and tropical algal flora, in order to determine the degree of species endemism based on evolutionary process. 3. To study the important role of habitat specificity in determining the composition of diatom assemblages. 4. To test the utility and suitability of diatom community structure as indicators of environmental stress. This is done by: 1. Conducting an ecological survey of microalgal distribution at Australian Antarctic station sites by looking into several types of habitat. 2. Identifying the microalgae samples collected based on morphology using light microscopy and SEM. 3. Comparing the algae community, structure and distribution from the tropics. The principal milestones of the project are as follows: 1. Information of microalgal distribution at several sites in Antarctica. 2. Collection of microalgae cultures. 3. Completion of identification of Antarctic microalgae. In collaboration with the Australian Antarctic Division (AAD) we have gone on an expeditions to Australian Antarctic Station of Casey and Davis. Collection of samples was made from various sources such as water, snow and soil and we have established a list of microalgae species in our collection. Comparative studies on the species diversity and distribution with tropical microalgae communities are being conducted. Physiological studies are currently in progress. proprietary
ecousm1 A comparative study on floral ecology between Malaysia and Antarctica ALL STAC Catalog 1970-01-01 110.32, -66.28, 110.32, -66.28 https://cmr.earthdata.nasa.gov/search/concepts/C1214621680-SCIOPS.umm_json The major objectives of this project are as follows: 1. To determine the composition and distribution of algal flora from a wide range of habitats, which provide a conductive niche for algal population in Antarctica. 2. To compare the Antarctic and tropical algal flora, in order to determine the degree of species endemism based on evolutionary process. 3. To study the important role of habitat specificity in determining the composition of diatom assemblages. 4. To test the utility and suitability of diatom community structure as indicators of environmental stress. This is done by: 1. Conducting an ecological survey of microalgal distribution at Australian Antarctic station sites by looking into several types of habitat. 2. Identifying the microalgae samples collected based on morphology using light microscopy and SEM. 3. Comparing the algae community, structure and distribution from the tropics. The principal milestones of the project are as follows: 1. Information of microalgal distribution at several sites in Antarctica. 2. Collection of microalgae cultures. 3. Completion of identification of Antarctic microalgae. In collaboration with the Australian Antarctic Division (AAD) we have gone on an expeditions to Australian Antarctic Station of Casey and Davis. Collection of samples was made from various sources such as water, snow and soil and we have established a list of microalgae species in our collection. Comparative studies on the species diversity and distribution with tropical microalgae communities are being conducted. Physiological studies are currently in progress. proprietary
+ecousm1 A comparative study on floral ecology between Malaysia and Antarctica SCIOPS STAC Catalog 1970-01-01 110.32, -66.28, 110.32, -66.28 https://cmr.earthdata.nasa.gov/search/concepts/C1214621680-SCIOPS.umm_json The major objectives of this project are as follows: 1. To determine the composition and distribution of algal flora from a wide range of habitats, which provide a conductive niche for algal population in Antarctica. 2. To compare the Antarctic and tropical algal flora, in order to determine the degree of species endemism based on evolutionary process. 3. To study the important role of habitat specificity in determining the composition of diatom assemblages. 4. To test the utility and suitability of diatom community structure as indicators of environmental stress. This is done by: 1. Conducting an ecological survey of microalgal distribution at Australian Antarctic station sites by looking into several types of habitat. 2. Identifying the microalgae samples collected based on morphology using light microscopy and SEM. 3. Comparing the algae community, structure and distribution from the tropics. The principal milestones of the project are as follows: 1. Information of microalgal distribution at several sites in Antarctica. 2. Collection of microalgae cultures. 3. Completion of identification of Antarctic microalgae. In collaboration with the Australian Antarctic Division (AAD) we have gone on an expeditions to Australian Antarctic Station of Casey and Davis. Collection of samples was made from various sources such as water, snow and soil and we have established a list of microalgae species in our collection. Comparative studies on the species diversity and distribution with tropical microalgae communities are being conducted. Physiological studies are currently in progress. proprietary
ect-and-rb-data-switzerland_1.0 ECT and RB data Switzerland ENVIDAT STAC Catalog 2020-01-01 2020-01-01 6.6500243, 45.8050626, 10.5831297, 47.4867706 https://cmr.earthdata.nasa.gov/search/concepts/C2789814654-ENVIDAT.umm_json "The data set contains the data used in the publication ""On snow stability interpretation of Extended Column Test results"" by Techel et. al. (2020), published in Natural Hazards Earth System Sciences." proprietary
edc_landcover_xdeg_930_1 ISLSCP II IGBP DISCover and SiB Land Cover, 1992-1993 ORNL_CLOUD STAC Catalog 1986-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2784854847-ORNL_CLOUD.umm_json This data set describes the geographic distributions of 17 classes of land cover based on the International Geosphere-Biosphere DISCover land cover legend (Loveland and Belward 1997) and the 15 classes of the SiB model processed at the USGS EROS Data Center (EDC). Specifically, the resampled DISCover datasets were derived from the 1km DISCover data set compiled by the USGS. The 1km data sets for each classification scheme were aggregated to 1, 0.5 and 0.25 degree spatial resolutions for this ISLSCP II data collection. Each layer of the aggregated products corresponds to a single DISCover land cover category and the values represent the percentage of the coarse resolution cell (1 degree, etc...)occupied by that land cover category. The dominant class data show the land cover category that occupies the majority of the cell and is derived from the percentage files for each cover type. The objective of this study was to create a land cover map derived from 1 kilometer AVHRR data using a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids for the International Satellite Land Surface Climatology Project (ISLSCP) data initiative II. During this re-processing, the original EDC land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by global modelers and others. This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets. proprietary
edgar_atmos_emissions_1deg_1022_1 ISLSCP II EDGAR 3 Gridded Greenhouse and Ozone Precursor Gas Emissions ORNL_CLOUD STAC Catalog 1970-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2785350291-ORNL_CLOUD.umm_json The EDGAR (Emission Database for Global Atmospheric Research) database project is a comprehensive task carried out jointly by the National Institute for Public Health (RIVM) and the Netherlands Organization for Applied Scientific Research (TNO) and stores global emission inventories of direct and indirect greenhouse gases from anthropogenic sources including halocarbons and aerosols both on a per country and region basis as well as on a grid (see http://www.rivm.nl/edgar/). For the ISLSCP Initiative II data collection, gridded global annual anthropogenic emissions for the greenhouse gases CO2, CH4, N2O are provided on a 1.0 degree by 1.0 degree grid for the years 1970, 1980, 1990, and 1995 and for the tropospheric ozone precursor gases CO, NOx, NMVOC (Non-Methane Volatile Organic Compounds) and SO2 for the years 1990 and 1995. There are 2 *.zip data files with this data set. proprietary
@@ -17678,8 +17679,8 @@ envidat-lwf-30_2019-03-06 EC-5 soil water content measurement LWF ENVIDAT STAC C
envidat-lwf-31_2019-03-06 MPS-2 soil water matric potential LWF ENVIDAT STAC Catalog 2019-01-01 2019-01-01 7.85832, 46.29688, 7.85832, 46.29688 https://cmr.earthdata.nasa.gov/search/concepts/C2789815159-ENVIDAT.umm_json Continuous measurement of soil matrix potential at 15, 50 and 80 cm depth with Decagon MPS-2 sensors ### Purpose: ### Improve the available data for the calibration or validation of the water cycle modells, i.e. the determination of the water flux needed for calculating the leaching fluxes. proprietary
envidat-lwf-32_2019-03-06 MPS-2 on LWF Visp to survey 2017 mortality wave ENVIDAT STAC Catalog 2019-01-01 2019-01-01 7.85832, 46.29688, 7.85832, 46.29688 https://cmr.earthdata.nasa.gov/search/concepts/C2789815187-ENVIDAT.umm_json Continuous measurement of soil matrix potential at 15, 50 and 100 cm depth with Decagon MPS-2 sensors 1 m N, SE and SW from the stem of 3 threes within much and 3 trees within few shrubs ### Purpose: ### Explore the effect of shrubs on the water availability for pine trees in Visp. proprietary
envidat-lwf-33_2019-03-06 TDR Pfynwald ENVIDAT STAC Catalog 2019-01-01 2019-01-01 7.61211, 46.30279, 7.61211, 46.30279 https://cmr.earthdata.nasa.gov/search/concepts/C2789815214-ENVIDAT.umm_json Continuous measurement of soil water content at one control and in one irrigated plot in 10, 40 and 60 cm depth (4 replications) with TDR (Tektronix 1502B cable tester, Beaverton, OR, US). ### Purpose: ### Monitoring of the soil water content ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) proprietary
-envidat-lwf-34_2019-03-06 10-HS Pfynwald ENVIDAT STAC Catalog 2019-01-01 2019-01-01 7.61211, 46.30279, 7.61211, 46.30279 https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.umm_json Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) proprietary
envidat-lwf-34_2019-03-06 10-HS Pfynwald ALL STAC Catalog 2019-01-01 2019-01-01 7.61211, 46.30279, 7.61211, 46.30279 https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.umm_json Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) proprietary
+envidat-lwf-34_2019-03-06 10-HS Pfynwald ENVIDAT STAC Catalog 2019-01-01 2019-01-01 7.61211, 46.30279, 7.61211, 46.30279 https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.umm_json Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) proprietary
envidat-lwf-36_2019-03-06 Passive sampling of O3 LWF ENVIDAT STAC Catalog 2019-01-01 2019-01-01 6.29085, 45.86141, 10.23009, 47.6837 https://cmr.earthdata.nasa.gov/search/concepts/C2789815256-ENVIDAT.umm_json Measuring air pollutants in forests is important for evaluating the risk for vegetation in areas not covered by conventional air quality monitoring networks. Ozone measurements are carried out at LWF, applying the harmonized methodologies from UNECE/ICP Forests and running under the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. Data are also collected on ozone-induced visible symptoms and other ecosystem properties such as tree growth, nutrition, and biodiversity, as well as climate. This makes this long-term monitoring data series essential for impact assessment and air pollution modelling. ### Purpose: ### Ozone risk assessment: Measurements of mean ozone concentrations with passive samplers (passam ag). ### Manual Citation: ### * Schaub M, Calatayud V, Ferretti M, Brunialti G, Lövblad G, Krause G, Sanz MJ, 2016: Part XV: Monitoring of Air Quality. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 11 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual) ### Paper Citation: ### * Schaub M, Häni M, Calatayud V, Ferretti M, Gottardini E (2018) ICP Forests Brief No 3 - Ozone concentrations are decreasing but exposure remains high in European forests. Programme Co-ordinating Centre of ICP Forests, Thu¨nen Institute of Forest Ecosystems. [doi: 10.3220/ICP1525258743000](https://icp-forests.org/pdf/ICPForestsBriefNo2.pdf) * Cailleret M, Ferretti M, Gessler A, Rigling A, Schaub M (2018) Ozone effects on European forest growth – towards an integrative approach. Journal of Ecology. [doi:10.1111/1365-2745.12941](http://doi.org/10.1111/1365-2745.12941) * Calatayud V, Diéguez JJ, Sicard P, Schaub M, De Marco A (2016) Testing approaches for calculating stomatal ozone fluxes from passive sampler. Science of the Total Environment. [doi:10.1016/j.scitotenv.2016.07.155](http://doi.org/10.1016/j.scitotenv.2016.07.155) * Calatayud V and Schaub M (2013) Methods for Measuring Gaseous Air Pollutants in Forests. In: Marco Ferretti and Richard Fischer (Eds). Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia, Vol 12, DENS, UK: Elsevier, 2013, pp. 375-384. [doi:10.1016/B978-0-08-098222-9.00019-4](http://doi.org/10.1016/B978-0-08-098222-9.00019-4) proprietary
envidat-lwf-37_2019-03-06 Continuous measurement of O3 LWF ENVIDAT STAC Catalog 2019-01-01 2019-01-01 6.65804, 45.86141, 9.06707, 47.6837 https://cmr.earthdata.nasa.gov/search/concepts/C2789815274-ENVIDAT.umm_json Measuring air pollutants in forests is important for evaluating the risk for vegetation in areas not covered by conventional air quality monitoring networks. Ozone measurements are carried out at LWF, applying the harmonized methodologies from UNECE/ICP Forests and running under the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. Data are also collected on ozone-induced visible symptoms and other ecosystem properties such as tree growth, nutrition, and biodiversity, as well as climate. This makes this long-term monitoring data series essential for impact assessment and air pollution modelling. ### Purpose: ### Ozone risk assessment: Continuous measurements of ozone concentrations ### Manual Citation: ### * Schaub M, Calatayud V, Ferretti M, Brunialti G, Lövblad G, Krause G, Sanz MJ, 2016: Part XV: Monitoring of Air Quality. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 11 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual) ### Paper Citation: ### * Schaub M, Häni M, Calatayud V, Ferretti M, Gottardini E (2018) ICP Forests Brief No 3 - Ozone concentrations are decreasing but exposure remains high in European forests. Programme Co-ordinating Centre of ICP Forests, Thu¨nen Institute of Forest Ecosystems. [doi: 10.3220/ICP1525258743000](https://icp-forests.org/pdf/ICPForestsBriefNo2.pdf) * Cailleret M, Ferretti M, Gessler A, Rigling A, Schaub M (2018) Ozone effects on European forest growth – towards an integrative approach. Journal of Ecology. [doi:10.1111/1365-2745.12941](https://doi.org/10.1111/1365-2745.12941) * Calatayud V and Schaub M (2013) Methods for Measuring Gaseous Air Pollutants in Forests. In: Marco Ferretti and Richard Fischer (Eds). Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia, Vol 12, DENS, UK: Elsevier, 2013, pp. 375-384. [doi:10.1016/B978-0-08-098222-9.00019-4](https://doi.org/10.1016/B978-0-08-098222-9.00019-4) proprietary
envidat-lwf-38_2019-03-06 Symptoms of O3 injuries LWF ENVIDAT STAC Catalog 2019-01-01 2019-01-01 6.29085, 46.02261, 10.23009, 47.6837 https://cmr.earthdata.nasa.gov/search/concepts/C2789815286-ENVIDAT.umm_json Measuring air pollutants in forests is important for evaluating the risk for vegetation in areas not covered by conventional air quality monitoring networks. Ozone-induced symptoms are being assessed at LWF, applying the harmonized methodologies from UNECE/ICP Forests and running under the 1999 Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone. Data are also collected on ozone concentrations and other ecosystem properties such as tree growth, nutrition, and biodiversity, as well as climate. This makes this long-term monitoring data series essential for impact assessment and air pollution modelling. ### Purpose: ### Ozone risk assessment, i.e. to investigate relationships between ozone exposures and ozone-induced, visible symptoms ### Manual Citation: ### * Schaub M, Calatayud V, Ferretti M, Brunialti G, Lövblad G, Krause G, Sanz MJ, 2016: Part VIII: Monitoring of Ozone Injury. In: UNECE ICP Forests Programme Co-ordinating Centre (ed.): Manual on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests. Thünen Institute of Forest Ecosystems, Eberswalde, Germany, 14 p. + Annex [http://icp-forests.net/page/icp-forests-manual](http://icp-forests.net/page/icp-forests-manual) ### Paper Citation: ### * Schaub M, Häni M, Calatayud V, Ferretti M, Gottardini E (2018) ICP Forests Brief No 3 - Ozone concentrations are decreasing but exposure remains high in European forests. Programme Co-ordinating Centre of ICP Forests, Thu¨nen Institute of Forest Ecosystems. [doi: 10.3220/ICP1525258743000](https://icp-forests.org/pdf/ICPForestsBriefNo2.pdf) * Schaub M and Calatayud V (2013) Assessment of Visible Foliar Injury Induced by Ozone. In: Marco Ferretti and Richard Fischer (Eds). Forest Monitoring: Methods for Terrestrial Investigations in Europe with an Overview of North America and Asia, Vol 12, DENS, UK: Elsevier, 2013, pp. 205-221. ISBN: 9780080982229. [doi: 10.1016/B978-0-08-098222-9.00011-X](https://doi.org/10.1016/B978-0-08-098222-9.00011-X) proprietary
@@ -17784,24 +17785,24 @@ fiber-bundle-model-for-snow-failure_1.0 Fiber Bundle Model for snow failure and
field-observations-of-snow-instabilities_1.0 Field observations of snow instabilities ENVIDAT STAC Catalog 2021-01-01 2021-01-01 9.7084808, 46.6864249, 10.0174713, 46.8979737 https://cmr.earthdata.nasa.gov/search/concepts/C2789815084-ENVIDAT.umm_json This data set includes 589 snow profile observations including a rutschblock test, observations of signs of instability and an assessment of the local avalanche danger level, mainly recorded in the region of Davos (eastern Swiss Alps) during the winter seasons 2001-2002 to 2018-2019. These data were analyzed and results published by Schweizer et al. (2021). They characterized the avalanche danger levels based on signs of instability (whumpfs, shooting cracks, recent avalanches), snow stability class and new snow height. The data are provided in a csv file (589 records); the variables are described in the corresponding read-me file. These data are the basis of the following publication: Schweizer, J., Mitterer, C., Reuter, B., and Techel, F.: Avalanche danger level characteristics from field observations of snow instability, Cryosphere, 15, 3293-3315, https://doi.org/10.5194/tc-15-3293-2021, 2021. ### Acknowlegements Many of the data were recorded by SLF observers and staff members, among those Roland Meister, Stephan Harvey, Lukas Dürr, Marcia Phillips, Christine Pielmeier and Thomas Stucki. Their contribution is gratefully acknowledged. proprietary
fieldsunp_65_1 Optical Thickness Data: Ground (OTTER) ORNL_CLOUD STAC Catalog 1990-02-22 1991-06-10 -123.95, 44.29, -121.33, 45.07 https://cmr.earthdata.nasa.gov/search/concepts/C2804770437-ORNL_CLOUD.umm_json Field sunphotometer data collected on 8/13-15/90 used to provide quantitative atmospheric correction to remotely sensed data of forest reflectance and radiance proprietary
fieldwork_lawdome_1964_1 Field work results carried out on Law Dome and Wilkes Land, 1964 AU_AADC STAC Catalog 1964-01-01 1964-12-31 110, -70, 115, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214313469-AU_AADC.umm_json A collection of notes and field data collected in traverse work on Law Dome/Wilkes Land in 1964. Includes data on gravity, air pressure (barometric levelling), air temperature, wind, snow accumulation stakes, ice movement. Also includes results from S2 pit measurements. proprietary
-fife_AF_dtrnd_nae_3_1 Aircraft Flux-Detrended: NRCC (FIFE) ORNL_CLOUD STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968494372-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_dtrnd_nae_3_1 Aircraft Flux-Detrended: NRCC (FIFE) ALL STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968494372-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
-fife_AF_dtrnd_ncar_5_1 Aircraft Flux-Detrended: Univ. Col. (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968514600-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
+fife_AF_dtrnd_nae_3_1 Aircraft Flux-Detrended: NRCC (FIFE) ORNL_CLOUD STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968494372-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_dtrnd_ncar_5_1 Aircraft Flux-Detrended: Univ. Col. (FIFE) ALL STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968514600-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
+fife_AF_dtrnd_ncar_5_1 Aircraft Flux-Detrended: Univ. Col. (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968514600-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_dtrnd_wyo_4_1 Aircraft Flux-Detrended: U of Wy. (FIFE) ALL STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968504925-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_dtrnd_wyo_4_1 Aircraft Flux-Detrended: U of Wy. (FIFE) ORNL_CLOUD STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968504925-ORNL_CLOUD.umm_json Detrended boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_filtr_nae_6_1 Aircraft Flux-Filtered: NRCC (FIFE) ALL STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968516479-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_filtr_nae_6_1 Aircraft Flux-Filtered: NRCC (FIFE) ORNL_CLOUD STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968516479-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
-fife_AF_filtr_ncar_8_1 Aircraft Flux-Filtered: Univ. Col. (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968522986-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_filtr_ncar_8_1 Aircraft Flux-Filtered: Univ. Col. (FIFE) ALL STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968522986-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
+fife_AF_filtr_ncar_8_1 Aircraft Flux-Filtered: Univ. Col. (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968522986-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_filtr_wyo_7_1 Aircraft Flux-Filtered: U of Wy. (FIFE) ALL STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968521064-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_filtr_wyo_7_1 Aircraft Flux-Filtered: U of Wy. (FIFE) ORNL_CLOUD STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968521064-ORNL_CLOUD.umm_json Filtered boundary layer fluxes recorded on aircraft flights over the Konza proprietary
fife_AF_raw_nae_9_1 Aircraft Flux-Raw: NRCC (FIFE) ORNL_CLOUD STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968531540-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
fife_AF_raw_nae_9_1 Aircraft Flux-Raw: NRCC (FIFE) ALL STAC Catalog 1987-06-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968531540-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
fife_AF_raw_ncar_11_1 Aircraft Flux-Raw: Univ. Col. (FIFE) ALL STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968534531-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
fife_AF_raw_ncar_11_1 Aircraft Flux-Raw: Univ. Col. (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968534531-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
-fife_AF_raw_wyo_10_1 Aircraft Flux-Raw: U of Wy. (FIFE) ALL STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968533497-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
fife_AF_raw_wyo_10_1 Aircraft Flux-Raw: U of Wy. (FIFE) ORNL_CLOUD STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968533497-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
+fife_AF_raw_wyo_10_1 Aircraft Flux-Raw: U of Wy. (FIFE) ALL STAC Catalog 1987-08-11 1989-10-31 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2968533497-ORNL_CLOUD.umm_json Raw (unmodified) boundary layer fluxes recorded on aircraft flights over Konza proprietary
fife_atmos_brut_drv_14_1 Atmos. Profile: Std. Press. Level (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-08-12 -96.56, 39.12, -96.56, 39.12 https://cmr.earthdata.nasa.gov/search/concepts/C2978502225-ORNL_CLOUD.umm_json Derived (5mb interval) radiosonde observations from Wilf Brutsaert's data proprietary
fife_atmos_brut_son_15_1 Atmospheric Profiles: Brutsaert (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-08-12 -96.56, 39.12, -96.56, 39.12 https://cmr.earthdata.nasa.gov/search/concepts/C2979919747-ORNL_CLOUD.umm_json Radiosonde observations from Wilf Brutsaert proprietary
fife_atmos_lidar_ht_17_1 Boundary Layer Heights: LIDAR (FIFE) ORNL_CLOUD STAC Catalog 1987-06-30 1989-10-31 -96.54, 39.07, -96.54, 39.07 https://cmr.earthdata.nasa.gov/search/concepts/C2979931759-ORNL_CLOUD.umm_json Height of the mixed layer gas for each LIDAR shot in volume scan, then averaged proprietary
@@ -17827,8 +17828,8 @@ fife_biology_soil_gas_106_1 Soil Gas Fluxes Using Soil Cores (FIFE) ORNL_CLOUD S
fife_biology_veg_biop_135_1 Vegetation Biophysical Data (FIFE) ORNL_CLOUD STAC Catalog 1987-05-26 1989-08-18 -96.61, 38.98, -96.45, 39.12 https://cmr.earthdata.nasa.gov/search/concepts/C2980707152-ORNL_CLOUD.umm_json Measurements of leaf area index and biomass of different canopy components proprietary
fife_biology_veg_ref_137_1 Vegetation Species Reference (FIFE) ORNL_CLOUD STAC Catalog 1989-10-31 1989-10-31 -97, 39, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2980719966-ORNL_CLOUD.umm_json LTER species names, codes, types, and other reference information proprietary
fife_biology_veg_spec_136_1 Vegetation Species Data (FIFE) ORNL_CLOUD STAC Catalog 1984-05-07 1989-08-18 -96.61, 38.98, -96.45, 39.12 https://cmr.earthdata.nasa.gov/search/concepts/C2980708363-ORNL_CLOUD.umm_json Species composition data, by site and date proprietary
-fife_hydrology_strm_15m_1_1 15 Minute Stream Flow Data: USGS (FIFE) ALL STAC Catalog 1984-12-25 1988-03-04 -96.6, 39.1, -96.6, 39.1 https://cmr.earthdata.nasa.gov/search/concepts/C2977827088-ORNL_CLOUD.umm_json USGS 15 minute stream flow data for Kings Creek on the Konza Prairie proprietary
fife_hydrology_strm_15m_1_1 15 Minute Stream Flow Data: USGS (FIFE) ORNL_CLOUD STAC Catalog 1984-12-25 1988-03-04 -96.6, 39.1, -96.6, 39.1 https://cmr.earthdata.nasa.gov/search/concepts/C2977827088-ORNL_CLOUD.umm_json USGS 15 minute stream flow data for Kings Creek on the Konza Prairie proprietary
+fife_hydrology_strm_15m_1_1 15 Minute Stream Flow Data: USGS (FIFE) ALL STAC Catalog 1984-12-25 1988-03-04 -96.6, 39.1, -96.6, 39.1 https://cmr.earthdata.nasa.gov/search/concepts/C2977827088-ORNL_CLOUD.umm_json USGS 15 minute stream flow data for Kings Creek on the Konza Prairie proprietary
fife_hydrology_strm_day_119_1 Stream Flow Daily Data: USGS (FIFE) ORNL_CLOUD STAC Catalog 1979-04-01 1988-09-02 -97, 39, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2980681974-ORNL_CLOUD.umm_json USGS daily stream flow data for Kings Creek on the Konza Prairie proprietary
fife_hydrology_strm_st_120_1 Stream Flow Storm Data (FIFE) ORNL_CLOUD STAC Catalog 1987-01-01 1988-01-01 -96.58, 39.07, -96.56, 39.09 https://cmr.earthdata.nasa.gov/search/concepts/C2980689463-ORNL_CLOUD.umm_json USGS stream flow during storm events around Kings Creek on the Konza Prairie proprietary
fife_optical_ot_brug_62_1 Optical Thickness Data: Bruegge (FIFE) ORNL_CLOUD STAC Catalog 1987-05-30 1989-08-08 -96.62, 38.98, -96.54, 39.12 https://cmr.earthdata.nasa.gov/search/concepts/C2980489715-ORNL_CLOUD.umm_json Optical thickness data from Dr. Carol Bruegge, JPL proprietary
@@ -17871,8 +17872,8 @@ fife_sur_met_hday_met_39_1 Historic Daily Meteorology Data (FIFE) ORNL_CLOUD STA
fife_sur_met_hmon_met_40_1 Historic Monthly Meteorology Data (FIFE) ORNL_CLOUD STAC Catalog 1858-01-01 1989-12-01 -102, 37, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2980078028-ORNL_CLOUD.umm_json Manhattan, KS. average rainfall measurements for every month since January 1858 proprietary
fife_sur_met_ncdc_sur_122_1 Surface Meteorology Data: NCDC (FIFE) ORNL_CLOUD STAC Catalog 1988-10-01 1989-10-31 -97.87, 37.62, -95.48, 40.85 https://cmr.earthdata.nasa.gov/search/concepts/C2980787683-ORNL_CLOUD.umm_json NCDC surface meteorology data for 1989 proprietary
fife_sur_met_noaa_sur_58_1 NOAA Regional Surface Data (FIFE) ORNL_CLOUD STAC Catalog 1985-07-02 1988-10-23 -97, 39, -95, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2980450611-ORNL_CLOUD.umm_json Hourly surface weather reports collected by NESDIS for stations near FIFE proprietary
-fife_sur_met_rain_30m_2_1 30 Minute Rainfall Data (FIFE) ALL STAC Catalog 1987-05-29 1987-10-26 -96.6, 39.08, -96.55, 39.11 https://cmr.earthdata.nasa.gov/search/concepts/C2977893818-ORNL_CLOUD.umm_json 30 minute rainfall data for the Konza Prairie proprietary
fife_sur_met_rain_30m_2_1 30 Minute Rainfall Data (FIFE) ORNL_CLOUD STAC Catalog 1987-05-29 1987-10-26 -96.6, 39.08, -96.55, 39.11 https://cmr.earthdata.nasa.gov/search/concepts/C2977893818-ORNL_CLOUD.umm_json 30 minute rainfall data for the Konza Prairie proprietary
+fife_sur_met_rain_30m_2_1 30 Minute Rainfall Data (FIFE) ALL STAC Catalog 1987-05-29 1987-10-26 -96.6, 39.08, -96.55, 39.11 https://cmr.earthdata.nasa.gov/search/concepts/C2977893818-ORNL_CLOUD.umm_json 30 minute rainfall data for the Konza Prairie proprietary
fife_sur_met_rain_day_29_1 Daily Rainfall Data (FIFE) ORNL_CLOUD STAC Catalog 1982-04-27 1989-12-30 -96.61, 39.07, -96.55, 39.11 https://cmr.earthdata.nasa.gov/search/concepts/C2980036855-ORNL_CLOUD.umm_json Daily rainfall data, by site & date proprietary
fife_sur_refl_gem_helo_38_1 Gemma Helicopter Data (FIFE) ORNL_CLOUD STAC Catalog 1989-08-04 1989-08-12 -96.61, 38.98, -96.45, 39.19 https://cmr.earthdata.nasa.gov/search/concepts/C2980074218-ORNL_CLOUD.umm_json Spectral reflected radiances measured with Russian GEMMA spectrometer from a helicopter proprietary
fife_sur_refl_irt_grnd_72_1 Radiant Temperature Ground Data (FIFE) ORNL_CLOUD STAC Catalog 1989-06-15 1989-08-11 -96.55, 39.05, -96.54, 39.09 https://cmr.earthdata.nasa.gov/search/concepts/C2980521154-ORNL_CLOUD.umm_json Surface temperatures collected w/ Everest Infrared Temperature Transducer proprietary
@@ -17904,8 +17905,8 @@ flowering-plants-angiospermae-in-urban-green-areas-in-five-european-cities_1.0 F
fltrepepoch_1 Flight Reports EPOCH GHRC_DAAC STAC Catalog 2017-07-27 2017-08-31 -130, 10, -80, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2175817241-GHRC_DAAC.umm_json The Flight Reports EPOCH dataset consists of flight number, purpose of flight, and flight hours logged during the East Pacific Origins and Characteristics of Hurricanes (EPOCH) project. EPOCH was a NASA program manager training opportunity directed at training NASA young scientists in conceiving, planning, and executing a major airborne science field program. The goals of the EPOCH project were to sample tropical cyclogenesis or intensification of an Eastern Pacific hurricane and to train the next generation of NASA Airborne Science Program leadership. The mission reports are available from July 27, 2017 through August 31, 2017 in PDF format. proprietary
flu-a-bh_1.0 Processed permafrost borehole data (2394 m asl), Fluelapass A, Switzerland ENVIDAT STAC Catalog 2016-01-01 2016-01-01 9.9451, 46.7479, 9.9451, 46.7479 https://cmr.earthdata.nasa.gov/search/concepts/C2789815125-ENVIDAT.umm_json Processed ground temperature measurements at the Fluelapass permafrost borehole A (FLU_0102) in canton Graubunden, Switzerland. The borehole is located at 2394 m asl on a moderate (26°) North-east slope (45°). The surface material is talus and borehole depth is 23 m. Thermistors used YSI 44006. Year of drilling 2002. This borehole is part of the Swiss Permafrost network, PERMOS (www.permos.ch). Contact phillips@slf.ch for details of processing applied. proprietary
fluxnet_point_1029_1 ISLSCP II Carbon Dioxide Flux at Harvard Forest and Northern BOREAS Sites ORNL_CLOUD STAC Catalog 1992-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2785312311-ORNL_CLOUD.umm_json This International Satellite Land Surface Climatology Project (ISLSCP II) data set, ISLSCP II Carbon Dioxide Flux at Harvard Forest and Northern BOREAS Sites, contains gapp-filled flux and meterological data for half-hourly, daily, weekly, monthly, and annual time intervals presented for each site and year. The 1992-1995 Harvard Forest, MA site, and the 1994-95 Old Black Spruce, Alberta, Canada site are members of the FLUXNET global network of micrometeorological towers that use eddy covariance methods to measure the excahanges of carbon dioxide (CO2), water vapor, and energy between terrestrial ecosystem and atmosphere. proprietary
-foraging_trip_duration_BI_1 Adelie penguin foraging trip duration, Bechervaise Island, Mawson AU_AADC STAC Catalog 1991-10-01 2005-02-01 62.8055, -67.5916, 62.825, -67.5861 https://cmr.earthdata.nasa.gov/search/concepts/C1214308557-AU_AADC.umm_json Adelie penguin foraging trip duration records for Bechervaise Island, Mawson since 1991-92. Data include average male and female foraging trip durations for both the guard and creche stages of the breeding season. Data based on records of tagged birds crossing the APMS for in and out crossings. Durations determined from difference between out and in crossings in conjunction with nest census records. Data included only for birds which were known to be foraging for a live chick. This work was completed as part of ASAC Project 2205, Adelie penguin research and monitoring in support of the CCAMLR Ecosystem Monitoring Project. The fields in this dataset are: Year trip duration (hours) Mean , standard error, count and standard deviation for male and female foraging trips during guard and creche stages of the breeding season. proprietary
foraging_trip_duration_BI_1 Adelie penguin foraging trip duration, Bechervaise Island, Mawson ALL STAC Catalog 1991-10-01 2005-02-01 62.8055, -67.5916, 62.825, -67.5861 https://cmr.earthdata.nasa.gov/search/concepts/C1214308557-AU_AADC.umm_json Adelie penguin foraging trip duration records for Bechervaise Island, Mawson since 1991-92. Data include average male and female foraging trip durations for both the guard and creche stages of the breeding season. Data based on records of tagged birds crossing the APMS for in and out crossings. Durations determined from difference between out and in crossings in conjunction with nest census records. Data included only for birds which were known to be foraging for a live chick. This work was completed as part of ASAC Project 2205, Adelie penguin research and monitoring in support of the CCAMLR Ecosystem Monitoring Project. The fields in this dataset are: Year trip duration (hours) Mean , standard error, count and standard deviation for male and female foraging trips during guard and creche stages of the breeding season. proprietary
+foraging_trip_duration_BI_1 Adelie penguin foraging trip duration, Bechervaise Island, Mawson AU_AADC STAC Catalog 1991-10-01 2005-02-01 62.8055, -67.5916, 62.825, -67.5861 https://cmr.earthdata.nasa.gov/search/concepts/C1214308557-AU_AADC.umm_json Adelie penguin foraging trip duration records for Bechervaise Island, Mawson since 1991-92. Data include average male and female foraging trip durations for both the guard and creche stages of the breeding season. Data based on records of tagged birds crossing the APMS for in and out crossings. Durations determined from difference between out and in crossings in conjunction with nest census records. Data included only for birds which were known to be foraging for a live chick. This work was completed as part of ASAC Project 2205, Adelie penguin research and monitoring in support of the CCAMLR Ecosystem Monitoring Project. The fields in this dataset are: Year trip duration (hours) Mean , standard error, count and standard deviation for male and female foraging trips during guard and creche stages of the breeding season. proprietary
forclim_4.0 ForClim ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815136-ENVIDAT.umm_json "ForClim is a cohort-based model that was developed to analyze successional pathways of various forest types in Central Europe. Following the standard approach of gap models ForClim simulates the establishment; growth and mortality of trees on multiple independent patches (typically n = 200) in annual time steps to derive regional-scale stand dynamics. ForClim is currently parameterized for ca. 180 tree species dominant of temperate forests worldwide. The model has been tested comprehensively for the representation of natural forest dynamics of temperate forests of the Northern Hemisphere, with an emphasis on European forests. ForClim may be freely used under the terms of the ""GNU GENERAL PUBLIC LICENSE v3"" license. ![alt text](https://www.envidat.ch/dataset/a049e6ad-caac-492a-9771-90856c48ed03/resource/e1c9f03a-2e55-444b-afee-fa1f7f50dee0/download/forclim_4submodels.jpg ""ForClim structure"")" proprietary
forecast-avalanche-danger-level-european-alps-2011-2015_1.0 Forecast avalanche danger level European Alps 2011 - 2015 ENVIDAT STAC Catalog 2018-01-01 2018-01-01 4.8779297, 43.2761391, 16.2597656, 48.179762 https://cmr.earthdata.nasa.gov/search/concepts/C2789815158-ENVIDAT.umm_json This dataset contains the data used in the publication by Techel et al., 2018 _Spatial consistency and bias in avalanche forecasts - a case study in the European Alps_ (Nat Haz Earth Syst Sci). For details on the data please refer to this publication. The dataset contains the following: - shape files for the warning regions in the Alps - highest forecast danger level for each warning region and day proprietary
forecomon-proceedings_v14 Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings. FORECOMON 2021 - the 9th forest ecosystem monitoring conference. 7–9 June 2021, Birmensdorf, Switzerland ENVIDAT STAC Catalog 2021-01-01 2021-01-01 8.4549183, 47.3607533, 8.4549183, 47.3607533 https://cmr.earthdata.nasa.gov/search/concepts/C2789815176-ENVIDAT.umm_json Forest monitoring to assess forest functioning under air pollution and climate change. Proceedings. FORECOMON 2021 - the 9th forest ecosystem monitoring conference. 7-9 June 2021, WSL, Birmensdorf, Switzerland The goal of FORECOMON 2021 is to highlight the extensive ICP Forests data series on forest growth, phenology and leaf area index, biodiversity and ground vegetation, foliage and litter fall, ambient air quality, deposition, meteorology, soil and crown condition. We combine novel modeling and assessment approaches and integrate long-term trends to assess air pollution and climate effects on European forests and related ecosystem services. Latest results and conclusions from local scale to European scale studies will be presented and discussed. Copyright © 2021 by WSL, Birmensdorf The authors are responsible for the content of their contribution. proprietary
@@ -18242,8 +18243,8 @@ geodata_2207 Livestock Production Index Base 1999-2001 - Total CEOS_EXTRA STAC C
geodata_2208 Cereals - Area Harvested CEOS_EXTRA STAC Catalog 1961-01-01 2009-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232849210-CEOS_EXTRA.umm_json Cereals also includes other cereals such as mixed grains and buckwheat. Crop production data refer to the actual harvested production from the field or orchard and gardens, excluding harvesting and threshing losses and that part of crop not harvested for any reason. Production therefore includes the quantities of the commodity sold in the market (marketed production) and the quantities consumed or used by the producers (auto-consumption). When the production data available refers to a production period falling into two successive calendar years and it is not possible to allocate the relative production to each of them, it is usual to refer production data to that year into which the bulk of the production falls. Crop production data are stored in tonnes (T). proprietary
geodata_2215 Hazardous Pesticides - Exports CEOS_EXTRA STAC Catalog 2007-01-01 2008-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232847283-CEOS_EXTRA.umm_json Refers to the value of the type of pesticide (put up in forms or packings for retail sale or as preparations or articles), provided to (exports) or received (imported) from the rest of the world. Differences between figures given for total exports and total imports at the world level may be due to several factors, e.g. the time lag between the dispatch of goods from exporting country and their arrival in the importing country; the use of different classification of the same product by different countries; or the fact that some countries supply data on general trade while others give data on special trade. proprietary
geodata_2216 Hazardous Pesticides - Imports CEOS_EXTRA STAC Catalog 2007-01-01 2008-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232847501-CEOS_EXTRA.umm_json Refers to the value of the type of pesticide (put up in forms or packings for retail sale or as preparations or articles), provided to (exports) or received (imported) from the rest of the world. Differences between figures given for total exports and total imports at the world level may be due to several factors, e.g. the time lag between the dispatch of goods from exporting country and their arrival in the importing country; the use of different classification of the same product by different countries; or the fact that some countries supply data on general trade while others give data on special trade. proprietary
-geodata_2217 Agricultural Area Certified Organic CEOS_EXTRA STAC Catalog 2003-01-01 2008-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232847551-CEOS_EXTRA.umm_json Land area exclusively dedicated to organic agriculture and managed by applying organic agriculture methods. It refers to the land area fully converted to organic agriculture. It is the portion of land area (including arable lands, pastures or wild areas) managed (cultivated) or wild harvested in accordance with specific organic standards or technical regulations and that has been inspected and approved by a certification body. proprietary
geodata_2217 Agricultural Area Certified Organic ALL STAC Catalog 2003-01-01 2008-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232847551-CEOS_EXTRA.umm_json Land area exclusively dedicated to organic agriculture and managed by applying organic agriculture methods. It refers to the land area fully converted to organic agriculture. It is the portion of land area (including arable lands, pastures or wild areas) managed (cultivated) or wild harvested in accordance with specific organic standards or technical regulations and that has been inspected and approved by a certification body. proprietary
+geodata_2217 Agricultural Area Certified Organic CEOS_EXTRA STAC Catalog 2003-01-01 2008-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232847551-CEOS_EXTRA.umm_json Land area exclusively dedicated to organic agriculture and managed by applying organic agriculture methods. It refers to the land area fully converted to organic agriculture. It is the portion of land area (including arable lands, pastures or wild areas) managed (cultivated) or wild harvested in accordance with specific organic standards or technical regulations and that has been inspected and approved by a certification body. proprietary
geodata_2222 Adjusted Human Water Security Threat CEOS_EXTRA STAC Catalog 1970-01-01 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232849396-CEOS_EXTRA.umm_json Rivers maintain unique biotic resources and provide critical water supplies to people. The Earth's limited supplies of fresh water and irreplaceable biodiversity are vulnerable to human mismanagement of watersheds and waterways. Multiple environmental stressors, such as agricultural runoff, pollution and invasive species, threaten rivers that serve 80 percent of the world’s population. These same stressors endanger the biodiversity of 65 percent of the world’s river habitats putting thousands of aquatic wildlife species at risk. Efforts to abate fresh water degradation through highly engineered solutions are effective at reducing the impact of threats but at a cost that can be an economic burden and often out of reach for developing nations. proprietary
geodata_2222 Adjusted Human Water Security Threat ALL STAC Catalog 1970-01-01 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232849396-CEOS_EXTRA.umm_json Rivers maintain unique biotic resources and provide critical water supplies to people. The Earth's limited supplies of fresh water and irreplaceable biodiversity are vulnerable to human mismanagement of watersheds and waterways. Multiple environmental stressors, such as agricultural runoff, pollution and invasive species, threaten rivers that serve 80 percent of the world’s population. These same stressors endanger the biodiversity of 65 percent of the world’s river habitats putting thousands of aquatic wildlife species at risk. Efforts to abate fresh water degradation through highly engineered solutions are effective at reducing the impact of threats but at a cost that can be an economic burden and often out of reach for developing nations. proprietary
geodata_2223 Global Net Primary Production (NPP) Anomaly from Multi-year Average, 2000 CEOS_EXTRA STAC Catalog 2000-01-01 2000-12-31 -180, -90, 180, -60.5033 https://cmr.earthdata.nasa.gov/search/concepts/C2232849273-CEOS_EXTRA.umm_json Terrestrial net primary production (NPP) quantifies the amount of atmospheric carbon fixed by plants and accumulated as biomass. Previous studies have shown that climate constraints were relaxing with increasing temperature and solar radiation, allowing an upward trend in NPP from 1982 through 1999. The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere. A continued decline in NPP would not only weaken the terrestrial carbon sink, but it would also intensify future competition between food demand and proposed biofuel production. proprietary
@@ -18374,8 +18375,8 @@ gone-wild-grapevines-in-forests_1.0 Gone-wild grapevines in forests may act as a
gov.noaa.ncdc:C00842_Version 1.2 Blended 6-Hourly Sea Surface Wind Vectors and Wind Stress on a Global 0.25 Degree Grid (1987-2011) NOAA_NCEI STAC Catalog 1987-07-09 2011-09-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2107093688-NOAA_NCEI.umm_json The Blended Global Sea Surface Winds products contain ocean surface wind vectors and wind stress on a global 0.25 degree grid, in multiple time resolutions of 6-hourly and monthly, with an 11-year (1995-2005) monthly climatology. Daily files from a direct average of the 6-hourly data were also produced but are not included in this archive. The period of record is July 9, 1987 to September 30, 2011 for product Version 1.2, released in July 2007. Wind speeds were generated by blending available and selected microwave and scatterometer observations using a Simple spatiotemporally weighted Interpolation (SI) method. The following satellite retrieval datasets from Remote Sensing Systems (RSS) were used for Version 1.2: SSMI Version 6, TMI Version 4, QSCAT Version 3a, and AMSRE Version 5 (updated using the SSMI rain rate). The wind directions are from the NCEP-DOE Reanalysis 2 (NRA-2). The model wind directions are interpolated onto the blended wind speed grids. The 6-hourly satellite-scaled global 0.25-degree grid wind stresses are computed as: taux_s = -[(w_s/w_m)**2]*taux_m tauy_s = -[(w_s/w_m)**2]*tauy_m where 's' indicates satellite-scaled values and 'm' indicates NRA-2 model values interpolated to the satellite grid. Files are in netCDF format and available to users via FTP and THREDDS. A near real-time (NRT) variant of the product is generated quasi-daily to satisfy the needs of real-time users. The publicly available NRT data were replaced by the delayed-mode research quality data on a monthly basis through the end of September 2011, at which time the Seawinds production was impacted by the loss of data from the AMSR-E instrument failure. Production of the delayed-mode research products ends with the loss of AMSR-E in Version 1.2; a future version will extend beyond September 2011. The NRT products are continued after September 2011; however, this archive only includes the delayed-mode research products as the NRT data have a lower maturity rating removing the basis for archiving those data. proprietary
gov.noaa.ncdc:C01381_Not Applicable AVHRR/HIRS Longwave Radiation Budget Data (RBUD) NOAA_NCEI STAC Catalog 2000-03-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2107093896-NOAA_NCEI.umm_json Radiation Budget Data - The Radiation Budget product suite is produced from the primary morning and afternoon Polar Orbiters. Product shows a measure of the longwave radiation emitted (W/m^2) by the earth-atmosphere system to space. The observations are displayed on a one degree equal area map for the day and night. The products are: GAC long wave, HIRS long wave, longwave histogram, annual mean, monthly mean, and seasonal mean. This is a NESDIS legacy product and the file naming pattern is as follows: NPR.RBSD.[SatelliteID].D[YYDDD] or NPR.RBMD.[SatelliteID].D[YYDDD] proprietary
gov.noaa.ncdc:C01560_V3 Blended Global Biomass Burning Emissions Product - Extended (GBBEPx) from Multiple Satellites NOAA_NCEI STAC Catalog 2018-01-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2107094570-NOAA_NCEI.umm_json The Blended Global Biomass Burning Emissions Product version 3 (GBBEPx V3) system produces global biomass burning emissions. The product contains daily global biomass burning emissions (PM2.5, BC, CO, CO2, OC, and SO2) blended fire observations from MODIS Quick Fire Emission Dataset (QFED), VIIRS (NPP and JPSS-1) fire emissions, and Global Biomass Burning Emission Product from Geostationary satellites (GBBEP-Geo), which are in a grid cell of 0.25 Ã 0.3125 degree and 0.1 x 0.1 degree. It also produces hourly emissions from geostationary satellites, which is at individual fire pixels. The product output also include fire detection record in a HMS format, quality flag in biomass burning emissions, spatial pattern of PM2.5 emissions, and statistic PM2.5 information at continental scale. In Version3, daily biomass burning emissions at a FV3 C384 grid in binary format and daily biomass burning emissions at a 0.1 x 0.1 degree grid that include all the emissions species are added as new output. proprietary
-gov.noaa.ncdc:C01598_Beta4 Adaptive Ecosystem Climatology Beta 4 Model and Satellite Climatology ALL STAC Catalog 1980-01-01 2012-12-31 -98, 18.091, -77.36, 30.73 https://cmr.earthdata.nasa.gov/search/concepts/C2107094643-NOAA_NCEI.umm_json The Adaptive Ecosystem Climatology (AEC) is produced by the Naval Research Laboratory (NRL). It consists of two datasets covering multiple regions of the ocean. One is a climatology derived from satellite data, the other is a climatology derived from a computer model of parts of the ocean that simulates physical and biological phenomena. The satellite climatology has data for chlorophyll concentration and sea surface temperature. The model climatology has fields for sea surface height, temperature, current, and concentrations of various types of plankton on the surface and underwater. Spatial resolution ranges from 1km to 4km depending on the product. These data are in NetCDF version 3 format with metadata attributes included. proprietary
gov.noaa.ncdc:C01598_Beta4 Adaptive Ecosystem Climatology Beta 4 Model and Satellite Climatology NOAA_NCEI STAC Catalog 1980-01-01 2012-12-31 -98, 18.091, -77.36, 30.73 https://cmr.earthdata.nasa.gov/search/concepts/C2107094643-NOAA_NCEI.umm_json The Adaptive Ecosystem Climatology (AEC) is produced by the Naval Research Laboratory (NRL). It consists of two datasets covering multiple regions of the ocean. One is a climatology derived from satellite data, the other is a climatology derived from a computer model of parts of the ocean that simulates physical and biological phenomena. The satellite climatology has data for chlorophyll concentration and sea surface temperature. The model climatology has fields for sea surface height, temperature, current, and concentrations of various types of plankton on the surface and underwater. Spatial resolution ranges from 1km to 4km depending on the product. These data are in NetCDF version 3 format with metadata attributes included. proprietary
+gov.noaa.ncdc:C01598_Beta4 Adaptive Ecosystem Climatology Beta 4 Model and Satellite Climatology ALL STAC Catalog 1980-01-01 2012-12-31 -98, 18.091, -77.36, 30.73 https://cmr.earthdata.nasa.gov/search/concepts/C2107094643-NOAA_NCEI.umm_json The Adaptive Ecosystem Climatology (AEC) is produced by the Naval Research Laboratory (NRL). It consists of two datasets covering multiple regions of the ocean. One is a climatology derived from satellite data, the other is a climatology derived from a computer model of parts of the ocean that simulates physical and biological phenomena. The satellite climatology has data for chlorophyll concentration and sea surface temperature. The model climatology has fields for sea surface height, temperature, current, and concentrations of various types of plankton on the surface and underwater. Spatial resolution ranges from 1km to 4km depending on the product. These data are in NetCDF version 3 format with metadata attributes included. proprietary
gov.noaa.ncdc:C01599_beta6 Adaptive Ecosystem Climatology Beta 6 Satellite Climatology NOAA_NCEI STAC Catalog 1980-01-01 2012-12-31 -135, 22.9276, -62.987, 53 https://cmr.earthdata.nasa.gov/search/concepts/C2107094649-NOAA_NCEI.umm_json The Adaptive Ecosystem Climatology (AEC) is produced by the Naval Research Laboratory (NRL). It consists of two datasets covering multiple regions of the ocean. One is a climatology derived from satellite data, the other is a climatology derived from a computer model of parts of the ocean that simulates physical and biological phenomena. The satellite climatology has data for chlorophyll concentration and sea surface temperature. The model climatology has fields for sea surface height, temperature, current, and concentrations of various types of plankton on the surface and underwater. Spatial resolution ranges from 1km to 4km depending on the product. These data are in NetCDF version 3 format with metadata attributes included. proprietary
gov.noaa.ncdc:C01599_beta6 Adaptive Ecosystem Climatology Beta 6 Satellite Climatology ALL STAC Catalog 1980-01-01 2012-12-31 -135, 22.9276, -62.987, 53 https://cmr.earthdata.nasa.gov/search/concepts/C2107094649-NOAA_NCEI.umm_json The Adaptive Ecosystem Climatology (AEC) is produced by the Naval Research Laboratory (NRL). It consists of two datasets covering multiple regions of the ocean. One is a climatology derived from satellite data, the other is a climatology derived from a computer model of parts of the ocean that simulates physical and biological phenomena. The satellite climatology has data for chlorophyll concentration and sea surface temperature. The model climatology has fields for sea surface height, temperature, current, and concentrations of various types of plankton on the surface and underwater. Spatial resolution ranges from 1km to 4km depending on the product. These data are in NetCDF version 3 format with metadata attributes included. proprietary
gov.noaa.ngdc.mgg.photos:12_Not Applicable April 1906 San Francisco, USA Images NOAA_NCEI STAC Catalog 1906-04-18 1906-04-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2105705777-NOAA_NCEI.umm_json The 1906 San Francisco earthquake was the largest event (magnitude 8.3) to occur in the conterminous United States in the 20th Century. Recent estimates indicate that as many as 3,000 people lost their lives in the earthquake and ensuing fire. In terms of 1906 dollars, the total property damage amounted to about $24 million from the earthquake and $350 million from the fire. The fire destroyed 28,000 buildings in a 520-block area of San Francisco. proprietary
@@ -18392,15 +18393,15 @@ gov.noaa.ngdc.mgg.photos:32_Not Applicable April 1968 Southeast of Hawaii, USA I
gov.noaa.ngdc.mgg.photos:36_Not Applicable April 1981 Westmorland, Calipatria, USA Images NOAA_NCEI STAC Catalog 1981-04-26 1981-04-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2105705807-NOAA_NCEI.umm_json Magnitude 6.3. Damage $1-$3 million. Subsidence was reported on several rural roads in the area. Liquefaction caused scores of mudpots, and oozing soil in nearby fields. One country road west of Westmorland collapsed, producing a 2-foot drop-off. In rural areas, unreinforced, concrete-lined irrigation canals were broken. proprietary
gov.noaa.ngdc.mgg.photos:4_Not Applicable April 1965 Seattle, USA Images NOAA_NCEI STAC Catalog 1965-04-29 1965-04-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2105705734-NOAA_NCEI.umm_json The magnitude 6.5 earthquake killed 7 and caused 12.5 million in property damage. proprietary
gov.noaa.ngdc.mgg.photos:52_Not Applicable April 2007 Solomon Islands, Papua New Guinea Images NOAA_NCEI STAC Catalog 2007-04-01 2007-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2105705809-NOAA_NCEI.umm_json An earthquake measuring 8.1 struck 345 kilometers northwest of the Solomon Islands' capital Honiara at 0740 local time on 2 April. (2040 GMT 1 April). The earthquake created a tsunami causing significant damage in the Solomon Islands. Large tsunami waves (reports range from 2m to 10m) are reported to have struck the islands in the Western Province area of Solomon Islands and some parts of Papua New Guinea. Affected areas include Gizo, Simbo, Ranogga, Shortlands, Munda, Noro, Vella la Vella, Kolombangarra and parts of the southern coast of Choiseul. At least 34 were killed and several dozen missing. 5,500 people are thought to have been displaced in total. The Ministry of Health and Medical Services (MHMS) estimates that up to 50,000 people may be affected out of a total population of 100,000 in Western and Choiseul provinces. proprietary
-gov.noaa.nodc:0000015_Not Applicable Alkalinity, dissolved oxygen, nutrients, pH, phosphate, salinity, silicate, and temperature collected by bottle from multiple cruises in the Southern Oceans from 1/15/1958 - 3/2/1990 (NCEI Accession 0000015) NOAA_NCEI STAC Catalog 1958-01-15 1990-03-02 6.05, -70.233333, -47.033333, -26.05 https://cmr.earthdata.nasa.gov/search/concepts/C2089372155-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0000015_Not Applicable Alkalinity, dissolved oxygen, nutrients, pH, phosphate, salinity, silicate, and temperature collected by bottle from multiple cruises in the Southern Oceans from 1/15/1958 - 3/2/1990 (NCEI Accession 0000015) ALL STAC Catalog 1958-01-15 1990-03-02 6.05, -70.233333, -47.033333, -26.05 https://cmr.earthdata.nasa.gov/search/concepts/C2089372155-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:0000015_Not Applicable Alkalinity, dissolved oxygen, nutrients, pH, phosphate, salinity, silicate, and temperature collected by bottle from multiple cruises in the Southern Oceans from 1/15/1958 - 3/2/1990 (NCEI Accession 0000015) NOAA_NCEI STAC Catalog 1958-01-15 1990-03-02 6.05, -70.233333, -47.033333, -26.05 https://cmr.earthdata.nasa.gov/search/concepts/C2089372155-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0000028_Not Applicable Benthic species - TAXA counts, identities, and wet weights collected by sediment grab from multiple cruises in Prince William Sound, Alaska, from 10/22/1985 - 8/31/1988 (NCEI Accession 0000028) NOAA_NCEI STAC Catalog 1985-10-22 1998-08-31 -146.597, 61.0802, -146.2983, 61.13 https://cmr.earthdata.nasa.gov/search/concepts/C2089372272-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:0000029_Not Applicable 1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029) ALL STAC Catalog 1990-09-26 1995-05-26 -124.041667, 0.766667, -16.25, 46.263167 https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0000029_Not Applicable 1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029) NOAA_NCEI STAC Catalog 1990-09-26 1995-05-26 -124.041667, 0.766667, -16.25, 46.263167 https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:0000029_Not Applicable 1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029) ALL STAC Catalog 1990-09-26 1995-05-26 -124.041667, 0.766667, -16.25, 46.263167 https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0000035_Not Applicable 1996 - Early 1998 CRETM/LMER Phytoplankton Data (NCEI Accession 0000035) ALL STAC Catalog 1996-07-09 1998-03-06 -124.003, 46.179833, -123.183167, 46.261667 https://cmr.earthdata.nasa.gov/search/concepts/C2089372325-NOAA_NCEI.umm_json Pump cast sampling, and associated CTD casts took place from a fixed vessel during one 28-35 day cruise per year in 1990, 1991, 1992, 1995, and 1996. In 1997 there were 2 week cruises in May, July, and October. proprietary
gov.noaa.nodc:0000035_Not Applicable 1996 - Early 1998 CRETM/LMER Phytoplankton Data (NCEI Accession 0000035) NOAA_NCEI STAC Catalog 1996-07-09 1998-03-06 -124.003, 46.179833, -123.183167, 46.261667 https://cmr.earthdata.nasa.gov/search/concepts/C2089372325-NOAA_NCEI.umm_json Pump cast sampling, and associated CTD casts took place from a fixed vessel during one 28-35 day cruise per year in 1990, 1991, 1992, 1995, and 1996. In 1997 there were 2 week cruises in May, July, and October. proprietary
-gov.noaa.nodc:0000052_Not Applicable 1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052) ALL STAC Catalog 1988-03-01 1988-06-28 -149.4083, 59.9117, -149.3583, 60.02 https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.umm_json Zooplantkon and beach tar data were collected using plankton net casts in the Gulf of Alaska from the ALPHA HELIX. Data were collected from 01 March 1988 to 28 June 1988 by University of Alaska in Fairbanks; Institute of Marine Science with support from the Gulf of Alaska - 1 (GAK-1) project. proprietary
gov.noaa.nodc:0000052_Not Applicable 1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052) NOAA_NCEI STAC Catalog 1988-03-01 1988-06-28 -149.4083, 59.9117, -149.3583, 60.02 https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.umm_json Zooplantkon and beach tar data were collected using plankton net casts in the Gulf of Alaska from the ALPHA HELIX. Data were collected from 01 March 1988 to 28 June 1988 by University of Alaska in Fairbanks; Institute of Marine Science with support from the Gulf of Alaska - 1 (GAK-1) project. proprietary
+gov.noaa.nodc:0000052_Not Applicable 1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052) ALL STAC Catalog 1988-03-01 1988-06-28 -149.4083, 59.9117, -149.3583, 60.02 https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.umm_json Zooplantkon and beach tar data were collected using plankton net casts in the Gulf of Alaska from the ALPHA HELIX. Data were collected from 01 March 1988 to 28 June 1988 by University of Alaska in Fairbanks; Institute of Marine Science with support from the Gulf of Alaska - 1 (GAK-1) project. proprietary
gov.noaa.nodc:0000064_Not Applicable Arabian Sea Biogeochemistry from 27 August 1994 to 19 December 1994 (NCEI Accession 0000064) NOAA_NCEI STAC Catalog 1994-08-27 1994-12-19 56.5529, 7.7811, 67.3194, 26.0221 https://cmr.earthdata.nasa.gov/search/concepts/C2089372546-NOAA_NCEI.umm_json Arabesque was a multidisciplinary oceanographic research project focused on the Arabian Sea and Northwest Indian Ocean during the monsoon and intermonsoon season in 1994. proprietary
gov.noaa.nodc:0000085_Not Applicable Benthic taxonomy and benthic biomass data collected by the R/V Alpha Helix in support of the ISHTAR Project in the Bering and Chukchi Seas, 1984-1990 (NCEI Accession 0000085) NOAA_NCEI STAC Catalog 1984-06-19 1990-06-21 -175.00118, 60.014, -163.75, 70 https://cmr.earthdata.nasa.gov/search/concepts/C2089372672-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0000103_Not Applicable Bering Sea Inner Front zooplankton data sets collected with CalVet net on four cruises from 6/3/1997 - 9/1/1998 (NCEI Accession 0000103) NOAA_NCEI STAC Catalog 1997-06-01 1998-09-01 -168.745, 55.0372, -159.994, 59.1733 https://cmr.earthdata.nasa.gov/search/concepts/C2089372740-NOAA_NCEI.umm_json Zooplankton and other data were collected using CalVet net in Bering sea from ALPHA HELIX. Data were collected from 01 June 1997 to 01 September 1998 by University of Alaska in Fairbanks with support from the Inner Front project. proprietary
@@ -18429,8 +18430,8 @@ gov.noaa.nodc:0000501_Not Applicable A unified, long-term, Caribbean-wide initia
gov.noaa.nodc:0000501_Not Applicable A unified, long-term, Caribbean-wide initiative to identity the factors responsible for sustaining mangrove wetland, seagrass meadow, and coral reef productivity, February 1993 - October 1998 (NCEI Accession 0000501) NOAA_NCEI STAC Catalog 1993-02-12 1998-10-15 -90.583333, 9.583333, -59.633333, 24.05 https://cmr.earthdata.nasa.gov/search/concepts/C2089375341-NOAA_NCEI.umm_json The Caribbean Coastal Marine Productivity (CARICOMP) Program is a Caribbean-wide research and monitoring network of 27 marine laboratories, parks, and reserves in 17 countries. This data set includes data collected from 42 stations at 29 sites in the Caribbean from 1993 to 1998. Line transects were used to determine the abundance of hard and soft corals, algae, sponges, urchins, and biotic material such as substrate type. proprietary
gov.noaa.nodc:0000504_Not Applicable Bacteria, plankton, and trace metal, and other data from bottle and CTD casts in the Antarctic from the NATHANIEL B. PALMER and ROGER REVELLE in support of the US Joint Global Ocean Flux Study / Antarctic Environments Southern Ocean Process Study (JGOFS /AESOPS) from 1996-10-17 to 1998-03-15 (NCEI Accession 0000504) NOAA_NCEI STAC Catalog 1996-10-17 1998-03-15 163.34, -78.05, -165.91, -52.95 https://cmr.earthdata.nasa.gov/search/concepts/C2089375350-NOAA_NCEI.umm_json Phytoplankton and other data were collected in the Antarctic from the NATHANIEL B. PALMER and ROGER REVELL from 17 October 1996 to 15 March 1998. Bottle data include enumeration and counts of bacteria, picoplankton, nanoplankton and nano microplankton. Bottle data also include concentrations of trace metals. CTD data include conductivity, temperature, and salinity profiles. Data were collected in support of the US Joint Global Ocean Flux Study / Antarctic Environments Southern Ocean Process Study (JGOFS/AESOPS). proprietary
gov.noaa.nodc:0000525_Not Applicable Chlorophyll and brevetoxin data from the ECOHAB project along the west coast of Florida from 1999-2000 (NCEI Accession 0000525) NOAA_NCEI STAC Catalog 1999-09-10 2000-09-29 -87.23565, 25.44867, -81.71588, 30.39237 https://cmr.earthdata.nasa.gov/search/concepts/C2089375484-NOAA_NCEI.umm_json Water and sediment samples were collected on annual ECOHAB Process cruises and on isolated Mote transects (10/13/99 and 10/20/99). Samples will be analyzed for brevetoxin using a competetive ELISA assay (Naar and Baden, in progress) as well as a receptor-binding assay (VanDolah et al., 1994), and have been analyzed for chlorophyll a (water only) using the Welschmeyer (1994) non-acidification technique. (To be updated when data has been analyzed.) proprietary
-gov.noaa.nodc:0000599_Not Applicable Aids to Navigation (ATONS) GIS data from the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas as of 1999-10-21 (NCEI Accession 0000599) NOAA_NCEI STAC Catalog 1999-01-01 1999-10-21 -98.320706, 17.398031, -61.876841, 32.288483 https://cmr.earthdata.nasa.gov/search/concepts/C2089376009-NOAA_NCEI.umm_json "This accession contains a GIS database of Aids to Navigation in the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas. These data were compiled on 1999-10-21. The term ""Aids to Navigation"" (ATONS or AIDS) refers to a device outside of a vessel used to assist mariners in determining their position or safe course, or to warn them of obstructions. AIDS to navigation include lighthouses, lights, buoy, sound signals, landmarks, racons, radio beacons, LORAN, and omega. These include AIDS which are installed and maintained by the Coast Guard as well as privately installed and maintained aids (permit required). This does not include unofficial AIDS (illegal) such as stakes, PVC pipes, and such placed without permission. Each USCG District Headquarters is responsible for updating their database on an ""as needed"" basis. When existing AIDS are destroyed or relocated and new AIDS are installed the database is updated. Each AID is assigned an official ""light listing number"". The light list is a document listing the current status of ATONS and it is published and distributed on a regular basis. Interim changes to the light list are published in local Notices to Mariners which are the official means which navigators are supposed to keep their charts current. In addition, the USCG broadcasts Notices to Mariners on the marine band radio as soon as changes of the status of individual AIDS are reported. The light list number and local Notices to Mariners reports are suggested ways to keep the database current on a regular or even ""real time"" basis. However, annual (or more frequent) updates of the entire dataset may be obtained from each USCG District Headquarters. Geographic Information System (GIS) software is required to display the data in this NCEI accession." proprietary
gov.noaa.nodc:0000599_Not Applicable Aids to Navigation (ATONS) GIS data from the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas as of 1999-10-21 (NCEI Accession 0000599) ALL STAC Catalog 1999-01-01 1999-10-21 -98.320706, 17.398031, -61.876841, 32.288483 https://cmr.earthdata.nasa.gov/search/concepts/C2089376009-NOAA_NCEI.umm_json "This accession contains a GIS database of Aids to Navigation in the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas. These data were compiled on 1999-10-21. The term ""Aids to Navigation"" (ATONS or AIDS) refers to a device outside of a vessel used to assist mariners in determining their position or safe course, or to warn them of obstructions. AIDS to navigation include lighthouses, lights, buoy, sound signals, landmarks, racons, radio beacons, LORAN, and omega. These include AIDS which are installed and maintained by the Coast Guard as well as privately installed and maintained aids (permit required). This does not include unofficial AIDS (illegal) such as stakes, PVC pipes, and such placed without permission. Each USCG District Headquarters is responsible for updating their database on an ""as needed"" basis. When existing AIDS are destroyed or relocated and new AIDS are installed the database is updated. Each AID is assigned an official ""light listing number"". The light list is a document listing the current status of ATONS and it is published and distributed on a regular basis. Interim changes to the light list are published in local Notices to Mariners which are the official means which navigators are supposed to keep their charts current. In addition, the USCG broadcasts Notices to Mariners on the marine band radio as soon as changes of the status of individual AIDS are reported. The light list number and local Notices to Mariners reports are suggested ways to keep the database current on a regular or even ""real time"" basis. However, annual (or more frequent) updates of the entire dataset may be obtained from each USCG District Headquarters. Geographic Information System (GIS) software is required to display the data in this NCEI accession." proprietary
+gov.noaa.nodc:0000599_Not Applicable Aids to Navigation (ATONS) GIS data from the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas as of 1999-10-21 (NCEI Accession 0000599) NOAA_NCEI STAC Catalog 1999-01-01 1999-10-21 -98.320706, 17.398031, -61.876841, 32.288483 https://cmr.earthdata.nasa.gov/search/concepts/C2089376009-NOAA_NCEI.umm_json "This accession contains a GIS database of Aids to Navigation in the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas. These data were compiled on 1999-10-21. The term ""Aids to Navigation"" (ATONS or AIDS) refers to a device outside of a vessel used to assist mariners in determining their position or safe course, or to warn them of obstructions. AIDS to navigation include lighthouses, lights, buoy, sound signals, landmarks, racons, radio beacons, LORAN, and omega. These include AIDS which are installed and maintained by the Coast Guard as well as privately installed and maintained aids (permit required). This does not include unofficial AIDS (illegal) such as stakes, PVC pipes, and such placed without permission. Each USCG District Headquarters is responsible for updating their database on an ""as needed"" basis. When existing AIDS are destroyed or relocated and new AIDS are installed the database is updated. Each AID is assigned an official ""light listing number"". The light list is a document listing the current status of ATONS and it is published and distributed on a regular basis. Interim changes to the light list are published in local Notices to Mariners which are the official means which navigators are supposed to keep their charts current. In addition, the USCG broadcasts Notices to Mariners on the marine band radio as soon as changes of the status of individual AIDS are reported. The light list number and local Notices to Mariners reports are suggested ways to keep the database current on a regular or even ""real time"" basis. However, annual (or more frequent) updates of the entire dataset may be obtained from each USCG District Headquarters. Geographic Information System (GIS) software is required to display the data in this NCEI accession." proprietary
gov.noaa.nodc:0000630_Not Applicable Baseline marine biological survey at Roi-Namur sewage outfall, United States Army Kwajalein Atoll, Republic of the Marshall Islands, 1997 (NCEI Accession 0000630) NOAA_NCEI STAC Catalog 1997-08-01 1997-08-31 167.44, 9.37, 167.46, 9.4 https://cmr.earthdata.nasa.gov/search/concepts/C2089372128-NOAA_NCEI.umm_json Roi-Namur is located at the northernmost tip of Kwajalein Atoll, approximately 64 kilometers north of the U.S. Army Kwajalein Atoll (USAKA) central command post on Kwajalein Islet. Roi-Namur has a single sewage outfall, which is located at the northwestern corner of the islet. Originally, the outfall extended from shore to a point about halfway across the reef flat where the pipe ended abruptly as an upturned, uncapped elbow. Raw sewage was pumped through the pipe in pulses approximately every 15-20 minutes. Waves and shallow currents across the reef flat carried at least some of the effluent back toward shore and the lagoon, creating a potentially unhealthy situation. In order to correct this problem, USAKA implemented a plan to extend the original outfall all the way across the reef flat and into the open ocean where the predominant current flow would carry effluent-mixed waters away from the islet. Ultimately, the extended outfall was to be connected to a new sewage treatment facility that would discharge primarily treated effluent. Because of a concern that this discharge might adversely impact the coral-reef community surrounding the end of the new outfall, a baseline marine biological survey was to be conducted prior to start-up of the new sewage treatment facility. As planned, the results of this survey would provide a baseline against which the results of future surveys could be compared in order to determine whether a balanced community of indigenous species had been maintained at the site during operation of the facility. If not, conversion to secondary treatment at the facility would need to be considered. The first resurvey was planned to occur one year after start-up of the new sewage treatment facility with subsequent resurveys planned for every five years thereafter. In August 1997, biologists from the U.S. Fish and Wildlife Service (USFWS) and the National Marine Fisheries Service (NMFS) conducted the baseline marine biological survey in the vicinity of the Roi-Namur outfall. For the National Oceanographic Data Center, interest in the report focuses on the marine element. Data tables from marine surveys of reef fishes, corals, other macroinvertebrates, and algae that exist in those habitats are provided. proprietary
gov.noaa.nodc:0000670_Not Applicable Biological assessment of marine resources for the Republic of the Maldives, Indian Ocean, August, 2001 (NCEI Accession 0000670) NOAA_NCEI STAC Catalog 2001-08-22 2001-08-29 72.716667, 2.933333, 73.566667, 5.516667 https://cmr.earthdata.nasa.gov/search/concepts/C2089372434-NOAA_NCEI.umm_json In August 2001, biologists from the U.S. Fish and Wildlife Service and the National Marine Fisheries Service were asked to conduct an assessment of the national government's capability to respond to major threats (e.g. anthropogenic and natural) to the marine habitat of the Republic of the Maldives. A marine survey was conducted at selected locations to assess impacts to the marine environment. Biologists documented reef fishes, corals, other macroinvertebrates, and algae, and provided general descriptions of the benthic community at each of four primary survey sites. proprietary
gov.noaa.nodc:0000703_Not Applicable Chemical, current meter, and other data from current meter, bottle, XBT, and CTD casts in the Gulf of Mexico as part of the Northeastern Gulf of Mexico Physical Oceanographic Program: Chemical Oceanography and Hydrography Study (NEGOM) project, 16 November 1997 to 08 August 2000 (NCEI Accession 0000703) NOAA_NCEI STAC Catalog 1997-11-16 2000-08-08 -89.94, 27.49, -82.83, 30.36 https://cmr.earthdata.nasa.gov/search/concepts/C2089372555-NOAA_NCEI.umm_json Chemical, current meter, and other data were collected using current meter, bottle, XBT, and CTD casts in the Gulf of Mexico from November 16, 1997 to August 8, 2000. Data were submitted by Texas A&M University as part of the Northeastern Gulf of Mexico Physical Oceanographic Program: Chemical Oceanography and Hydrography Study (NEGOM) project. proprietary
@@ -18438,14 +18439,14 @@ gov.noaa.nodc:0000732_Not Applicable Bacteria, carbon dioxide, and methane data
gov.noaa.nodc:0000737_Not Applicable Bacteria, carbon dioxide, and methane data from bottle casts in the Cariaco Basin on the continental shelf of Venezuela from the HERMANO GINES from 2001-04-30 to 2001-05-01 (NCEI Accession 0000737) NOAA_NCEI STAC Catalog 2001-04-30 2001-05-01 -64.66, 10.48, -64.66, 10.48 https://cmr.earthdata.nasa.gov/search/concepts/C2089372826-NOAA_NCEI.umm_json Bacteria, carbon dioxide, and methane data were collected from bottle casts from the HERMANO GINES in the Cariaco Basin on the continental shelf of Venezuela. Data were collected from 30 April 2001 to 01 May 2001. Bacteria data include rates of production of bacteria and flagellates. Abundances of remineralizers (bacteria) and regenerators (protozoa) were determined using microscopic censuses. Methane data include rates of respiration and incorporation. Data was submitted by the State University of New York, Stony Brook, as a comma- seperated value (.csv) file. proprietary
gov.noaa.nodc:0000780_Not Applicable Biological, physical, nutrients, and other data were collected from bottle casts, CTD casts, net casts, and other instruments from the A.V. HUMBOLDT and the JOHAN HJORT from the Norwegian Sea in support of the Global Ocean Ecosystems Dynamics from 1993-06-02 to 1993-06-13 (NCEI Accession 0000780) NOAA_NCEI STAC Catalog 1993-06-02 1993-06-13 -80, 60, 30, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089373165-NOAA_NCEI.umm_json Bottle, CTD, net, and other data were collected from the A.V. HUMBOLDT and the JOHAN HJORT from the Norwegian Sea. Data were collected by multiple institutions in support of the Global Ocean Ecosystems Dynamics (GLOBEC) from 02 June 1993 to 13 June 1993. Bottle data include concentration profiles of chlorophyll a,b,c. CTD data include profiles of temperature and salinity. Net data include species identities and abundance of zooplankton. proprietary
gov.noaa.nodc:0000787_Not Applicable Chlorophyll data were collected by R/V Nathaniel B. Palmer on the western Antarctic shelf in support of the GLOBEC project, 2001-04 to 2001-06 (NCEI Accession 0000787) NOAA_NCEI STAC Catalog 2001-04-04 2001-06-01 -77.76, -70.63, -67.39, -65.65 https://cmr.earthdata.nasa.gov/search/concepts/C2089373201-NOAA_NCEI.umm_json GLOBEC (Global Ocean Ecosystem Dynamics) was initiated by SCOR and the IOC of UNESCO in 1991, to understand how global change will affect the abundance, diversity and productivity of marine populations comprising a major component of oceanic ecosystems. The aim of GLOBEC is to advance our understanding of the structure and functioning of the global ocean ecosystem, its major subsystems, and its response to physical forcing so that a capability can be developed to forecast the responses of the marine ecosystem to global change. proprietary
-gov.noaa.nodc:0000794_Not Applicable A survey of selected coral and fish assemblages near the Waianae Ocean Outfall, Oahu, Hawaii, 1990-1999 (NCEI Accession 0000794) ALL STAC Catalog 1990-10-01 1999-08-31 -158.28, 21.41, -158.26, 21.43 https://cmr.earthdata.nasa.gov/search/concepts/C2089373252-NOAA_NCEI.umm_json During 1990-1999, coral growth and fish abundance were monitored at stations located at and in the vicinity of the Waianae Ocean Outfall. Comparisons of results with fish surveys showed no significant differences in the species composition or relative abundances of fish populations at Station W-2 (the sunken ship Mahi), which is located 1.2 km south of the diffuser. Fish abundance and species richness increased at Station W- 3, which is located at the diffuser, from 1990 to 1995, decreased in 1996, and increased again in 1997 through 1999. At Station WW, an inshore station located 0.8 km from shore, fish were abundant and speciose on the armor rock covering the pipeline. The fish species seen inshore are comparable to fish species seen in similar (boulder) natural biotopes around Hawaii. There were no significant differences in total mean coral cover at selected quadrats from 1994 to 1999 at Station W-2. However, there was a significant increase (approximately 8%) in total mean coral cover at this station from 1991 to 1999. At the diffuser, corals were seen growing on the diffuser pipe and on the riser discharge ports. In 1986, when the diffuser began operation at a discharge rate of 1.5 mgd (0.07 m3/s), no corals were seen at this location. At inshore station WW, corals off the pipeline were sparsely distributed but were numerous and thriving on the armor rock over the pipeline. In 1998 the inshore transect (Alpha), off the armor rock, was covered (30%) with the alga Dictyopteris plagiogramma; however, in 1999 it disappeared. This seaweed was also abundant at this location in 1995, 1996, and 1997. The water was clear at all stations surveyed (13 to 20 m horizontal visibility), and the surrounding sediments were clean and white. No significant deleterious effect due to outfall operation and discharge were seen on the biological community at the stations surveyed. The increase in fish diversity and abundance at the diffuser since 1997 may be due to natural fluctuations in abundance or to environmental conditions suitable to the fish populations living there. proprietary
gov.noaa.nodc:0000794_Not Applicable A survey of selected coral and fish assemblages near the Waianae Ocean Outfall, Oahu, Hawaii, 1990-1999 (NCEI Accession 0000794) NOAA_NCEI STAC Catalog 1990-10-01 1999-08-31 -158.28, 21.41, -158.26, 21.43 https://cmr.earthdata.nasa.gov/search/concepts/C2089373252-NOAA_NCEI.umm_json During 1990-1999, coral growth and fish abundance were monitored at stations located at and in the vicinity of the Waianae Ocean Outfall. Comparisons of results with fish surveys showed no significant differences in the species composition or relative abundances of fish populations at Station W-2 (the sunken ship Mahi), which is located 1.2 km south of the diffuser. Fish abundance and species richness increased at Station W- 3, which is located at the diffuser, from 1990 to 1995, decreased in 1996, and increased again in 1997 through 1999. At Station WW, an inshore station located 0.8 km from shore, fish were abundant and speciose on the armor rock covering the pipeline. The fish species seen inshore are comparable to fish species seen in similar (boulder) natural biotopes around Hawaii. There were no significant differences in total mean coral cover at selected quadrats from 1994 to 1999 at Station W-2. However, there was a significant increase (approximately 8%) in total mean coral cover at this station from 1991 to 1999. At the diffuser, corals were seen growing on the diffuser pipe and on the riser discharge ports. In 1986, when the diffuser began operation at a discharge rate of 1.5 mgd (0.07 m3/s), no corals were seen at this location. At inshore station WW, corals off the pipeline were sparsely distributed but were numerous and thriving on the armor rock over the pipeline. In 1998 the inshore transect (Alpha), off the armor rock, was covered (30%) with the alga Dictyopteris plagiogramma; however, in 1999 it disappeared. This seaweed was also abundant at this location in 1995, 1996, and 1997. The water was clear at all stations surveyed (13 to 20 m horizontal visibility), and the surrounding sediments were clean and white. No significant deleterious effect due to outfall operation and discharge were seen on the biological community at the stations surveyed. The increase in fish diversity and abundance at the diffuser since 1997 may be due to natural fluctuations in abundance or to environmental conditions suitable to the fish populations living there. proprietary
+gov.noaa.nodc:0000794_Not Applicable A survey of selected coral and fish assemblages near the Waianae Ocean Outfall, Oahu, Hawaii, 1990-1999 (NCEI Accession 0000794) ALL STAC Catalog 1990-10-01 1999-08-31 -158.28, 21.41, -158.26, 21.43 https://cmr.earthdata.nasa.gov/search/concepts/C2089373252-NOAA_NCEI.umm_json During 1990-1999, coral growth and fish abundance were monitored at stations located at and in the vicinity of the Waianae Ocean Outfall. Comparisons of results with fish surveys showed no significant differences in the species composition or relative abundances of fish populations at Station W-2 (the sunken ship Mahi), which is located 1.2 km south of the diffuser. Fish abundance and species richness increased at Station W- 3, which is located at the diffuser, from 1990 to 1995, decreased in 1996, and increased again in 1997 through 1999. At Station WW, an inshore station located 0.8 km from shore, fish were abundant and speciose on the armor rock covering the pipeline. The fish species seen inshore are comparable to fish species seen in similar (boulder) natural biotopes around Hawaii. There were no significant differences in total mean coral cover at selected quadrats from 1994 to 1999 at Station W-2. However, there was a significant increase (approximately 8%) in total mean coral cover at this station from 1991 to 1999. At the diffuser, corals were seen growing on the diffuser pipe and on the riser discharge ports. In 1986, when the diffuser began operation at a discharge rate of 1.5 mgd (0.07 m3/s), no corals were seen at this location. At inshore station WW, corals off the pipeline were sparsely distributed but were numerous and thriving on the armor rock over the pipeline. In 1998 the inshore transect (Alpha), off the armor rock, was covered (30%) with the alga Dictyopteris plagiogramma; however, in 1999 it disappeared. This seaweed was also abundant at this location in 1995, 1996, and 1997. The water was clear at all stations surveyed (13 to 20 m horizontal visibility), and the surrounding sediments were clean and white. No significant deleterious effect due to outfall operation and discharge were seen on the biological community at the stations surveyed. The increase in fish diversity and abundance at the diffuser since 1997 may be due to natural fluctuations in abundance or to environmental conditions suitable to the fish populations living there. proprietary
gov.noaa.nodc:0000820_Not Applicable Bacteria Biomass and Chlorophyll-a depth profiles from bottle casts off the western Antarctic Peninsula from the R/V LAURENCE M. GOULD from 23 April 2001 to 01 September 2001 (NCEI Accession 0000820) NOAA_NCEI STAC Catalog 2001-04-29 2001-09-01 -72.42, -69.88, -67.04, -66.22 https://cmr.earthdata.nasa.gov/search/concepts/C2089373349-NOAA_NCEI.umm_json Bacteria and Chlorophyll data were collected from bottle cast of the western Antarctic peninsula from the R/V Laurence M. Gould. Data were collected by the University of Nevada/Desert Research Institute (DRI) in support of the Global Ocean Ecosystems Dynamic (GLOBEC) project from 23 April 2001 to 01 September 2001. Bacteria data include profiles of bacterial abundance and biomass. Chlorophyll-a data include concentration profiles. proprietary
gov.noaa.nodc:0000829_Not Applicable Broward County Florida thermographic data collected at twelve locations along four eastward lines that cross three offshore reef Tracks during the time period July 2000 to the present using self-recording temperature gauges (NCEI Accession 0000829) NOAA_NCEI STAC Catalog 2000-07-01 2002-11-30 -80.112007, 26.020458, -80.077343, 26.159952 https://cmr.earthdata.nasa.gov/search/concepts/C2089373393-NOAA_NCEI.umm_json "Broward County Florida has responsibility for the resource management of coral reefs in marine waters adjacent to Broward County. The Department of Planning and Environmental Protection is assigned the duties of monitoring the health of the coral reefs. Environmental stresses are a limiting factor in the biomass and diversity, and maintaining these populations of coral species requires an understanding of the environmental factors. One of these factors is the water temperature. Visual surveys are conducted by divers, and the staff has implemented an environmental monitoring program with water temperature as the first measured parameter. The monitoring program is on a ""not to interfere basis"" using self-recording thermographs for data acquisition. The thermographs are placed along coral reef tracks located in three separate bands near the northern most extent of the natural range for corals. The raw data are captured from the recorder by means of a laptop computer using transfer and conversion software provided by the instrument's vendor. Upon return to the office, the raw data are transferred to separate files that are then loaded into spreadsheet files. Each spreadsheet file corresponds to a single location and only one instrument. Twelve spreadsheet files are updated every sixty days for the dynamic raw data; the static geographical information is stored in a separate spreadsheet file." proprietary
gov.noaa.nodc:0000861_Not Applicable A Hydrographic Survey of the Scotia Sea, 15 March 1999 to 22 April 1999 (NCEI Accession 0000861) ALL STAC Catalog 1999-03-15 1999-04-22 -68.260333, -67.576667, -2.296667, 10 https://cmr.earthdata.nasa.gov/search/concepts/C2089373502-NOAA_NCEI.umm_json CTD and chemical data were collected using CTD and bottle casts in the Drake Passage and Scotia Sea from the JAMES CLARK ROSS. Data were collected from 15 March 1999 to 22 April 1999. Data were collected and submitted by the University of East Anglia with support of the Antarctic Large-scale Box Analysis and the Role of the Scotia Sea (ALBATROSS) project. proprietary
gov.noaa.nodc:0000861_Not Applicable A Hydrographic Survey of the Scotia Sea, 15 March 1999 to 22 April 1999 (NCEI Accession 0000861) NOAA_NCEI STAC Catalog 1999-03-15 1999-04-22 -68.260333, -67.576667, -2.296667, 10 https://cmr.earthdata.nasa.gov/search/concepts/C2089373502-NOAA_NCEI.umm_json CTD and chemical data were collected using CTD and bottle casts in the Drake Passage and Scotia Sea from the JAMES CLARK ROSS. Data were collected from 15 March 1999 to 22 April 1999. Data were collected and submitted by the University of East Anglia with support of the Antarctic Large-scale Box Analysis and the Role of the Scotia Sea (ALBATROSS) project. proprietary
-gov.noaa.nodc:0000879_Not Applicable Abundance data acquired in support of invasive species distribution studies at ten macroalgal ecology and taxonomic assessment sites in Hawaii during 2001 (NCEI Accession 0000879) NOAA_NCEI STAC Catalog 2001-01-26 2001-05-18 -158.14, 19.27, -155.05, 21.37 https://cmr.earthdata.nasa.gov/search/concepts/C2089373608-NOAA_NCEI.umm_json Abundance data represent estimates of percent cover of species type (coral or algal) in 10 randomly placed quadrats along two 50 meter transect lines of each site. Data are available for 10 sites from Oahu to the Island of Hawaii taken in 2001 in support of the Macroalgal Ecology and Taxonomic Assessment (TEAM) Project. The species for abundance estimates include 11 corals, 5 invertebrates, 33 algals, and 2 benthic types (turf or sand). The role that marine algae play in a coral reef system is often overlooked because of lack of knowledge that they are the primary producers in the system. The coral reef ecosystem in Hawaii contains about ten times more algal species than coral species, some of them regulating space that permits coral recruitment. The primary purpose of the TEAM research program is to provide taxonomic and ecological algal expertise for the Coral Reef Monitoring and Assessment Program (CRAMP). Our group also seeks to develop, implement and assess new methodologies for quantitatively surveying benthic algal communities in the Hawaiian Islands. proprietary
gov.noaa.nodc:0000879_Not Applicable Abundance data acquired in support of invasive species distribution studies at ten macroalgal ecology and taxonomic assessment sites in Hawaii during 2001 (NCEI Accession 0000879) ALL STAC Catalog 2001-01-26 2001-05-18 -158.14, 19.27, -155.05, 21.37 https://cmr.earthdata.nasa.gov/search/concepts/C2089373608-NOAA_NCEI.umm_json Abundance data represent estimates of percent cover of species type (coral or algal) in 10 randomly placed quadrats along two 50 meter transect lines of each site. Data are available for 10 sites from Oahu to the Island of Hawaii taken in 2001 in support of the Macroalgal Ecology and Taxonomic Assessment (TEAM) Project. The species for abundance estimates include 11 corals, 5 invertebrates, 33 algals, and 2 benthic types (turf or sand). The role that marine algae play in a coral reef system is often overlooked because of lack of knowledge that they are the primary producers in the system. The coral reef ecosystem in Hawaii contains about ten times more algal species than coral species, some of them regulating space that permits coral recruitment. The primary purpose of the TEAM research program is to provide taxonomic and ecological algal expertise for the Coral Reef Monitoring and Assessment Program (CRAMP). Our group also seeks to develop, implement and assess new methodologies for quantitatively surveying benthic algal communities in the Hawaiian Islands. proprietary
+gov.noaa.nodc:0000879_Not Applicable Abundance data acquired in support of invasive species distribution studies at ten macroalgal ecology and taxonomic assessment sites in Hawaii during 2001 (NCEI Accession 0000879) NOAA_NCEI STAC Catalog 2001-01-26 2001-05-18 -158.14, 19.27, -155.05, 21.37 https://cmr.earthdata.nasa.gov/search/concepts/C2089373608-NOAA_NCEI.umm_json Abundance data represent estimates of percent cover of species type (coral or algal) in 10 randomly placed quadrats along two 50 meter transect lines of each site. Data are available for 10 sites from Oahu to the Island of Hawaii taken in 2001 in support of the Macroalgal Ecology and Taxonomic Assessment (TEAM) Project. The species for abundance estimates include 11 corals, 5 invertebrates, 33 algals, and 2 benthic types (turf or sand). The role that marine algae play in a coral reef system is often overlooked because of lack of knowledge that they are the primary producers in the system. The coral reef ecosystem in Hawaii contains about ten times more algal species than coral species, some of them regulating space that permits coral recruitment. The primary purpose of the TEAM research program is to provide taxonomic and ecological algal expertise for the Coral Reef Monitoring and Assessment Program (CRAMP). Our group also seeks to develop, implement and assess new methodologies for quantitatively surveying benthic algal communities in the Hawaiian Islands. proprietary
gov.noaa.nodc:0000918_Not Applicable Chemical data from bottle casts in the Arctic Ocean and other Sea areas by the University of Alaska, from 16 April 1948 to 17 September 2000 (NCEI Accession 0000918) NOAA_NCEI STAC Catalog 1948-04-16 2000-09-17 -71, 16, -80.123, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089373877-NOAA_NCEI.umm_json Chemical data were collected using bottle casts from multiple vessels in the Arctic Ocean and other Sea areas from 16 April 1948 to 17 September 2000. Data were submitted by the University of Alaska in Fairbanks, Alaska. Chemical data include alkalinity, nitrate, nitrite, oxygen, silicate, and phosphate. proprietary
gov.noaa.nodc:0000931_Not Applicable Aerial surveys of ringed seals (Phoca hispida) on fast and pack ice in the central Beaufort Sea of Alaska, 1985-1987 and 1996-1999 (NCEI Accession 0000931) ALL STAC Catalog 1985-05-28 1999-06-04 -156.9983, 69.6517, -141.025, 71.865 https://cmr.earthdata.nasa.gov/search/concepts/C2089373928-NOAA_NCEI.umm_json These datasets include counts of ringed seals (Phoca hispida) and other marine mammals made during aerial surveys of ringed seals on fast and pack ice of the central Alaskan Beaufort Sea during 1985-1987 and 1996-1999. The datasets includes counts of seals, by group; designation of whether seals were at holes or along cracks; ice conditions including ice deformation and ice type (fast ice or pack ice); weather conditions; time of observations, and location of observations. proprietary
gov.noaa.nodc:0000931_Not Applicable Aerial surveys of ringed seals (Phoca hispida) on fast and pack ice in the central Beaufort Sea of Alaska, 1985-1987 and 1996-1999 (NCEI Accession 0000931) NOAA_NCEI STAC Catalog 1985-05-28 1999-06-04 -156.9983, 69.6517, -141.025, 71.865 https://cmr.earthdata.nasa.gov/search/concepts/C2089373928-NOAA_NCEI.umm_json These datasets include counts of ringed seals (Phoca hispida) and other marine mammals made during aerial surveys of ringed seals on fast and pack ice of the central Alaskan Beaufort Sea during 1985-1987 and 1996-1999. The datasets includes counts of seals, by group; designation of whether seals were at holes or along cracks; ice conditions including ice deformation and ice type (fast ice or pack ice); weather conditions; time of observations, and location of observations. proprietary
@@ -18464,33 +18465,33 @@ gov.noaa.nodc:0001344_Not Applicable Chlorophyll and Plankton data from the Indi
gov.noaa.nodc:0001410_Not Applicable Bathymetric Survey of the West Florida Shelf, Gulf of Mexico 2001 (NCEI Accession 0001410) NOAA_NCEI STAC Catalog 2001-09-03 2001-10-12 -86.71, 28.04, -84.61, 30.06 https://cmr.earthdata.nasa.gov/search/concepts/C2089376038-NOAA_NCEI.umm_json A zone of deep-water reefs is thought to extend from the mid and outer shelf south of Mississippi and Alabama to at least the northwestern Florida shelf off Panama City, Florida. Reefs off Mississippi and Alabama are found in water depths of 60 to 120 m (Ludwick and Walton, 1957, Gardner et al., in press) and were the focus of a multibeam echosounder mapping survey by the U.S. Geological Survey (USGS) in 2000 (Gardner et al., 2000, in press). It is critical to determine the accurate geomorphology and type of the reefs that occur because of their importance as benthic habitats for fisheries. These data are ArcInfo GRID and XYZ ASCII format data generated from a U.S. Geological Survey multibeam sonar survey of the West Florida Shelf, Gulf of Mexico. The data include high-resolution bathymetry and calibrated acoustic backscatter. File types include arc files .dat, .nit, and .adf. Documentation is included as metadata .txt files. Because the area is so large (i.e., the file sizes are very large), the area was subdivided into North, Central, and South regions as reflected in the data subdirectories for this accession. proprietary
gov.noaa.nodc:0001419_Not Applicable Assessment of Nonindigenous Species on Coral Reefs in the Hawaiian Islands, with Emphasis on Introduced Invertebrates, November 2, 2002 - November 5, 2003 (NCEI Accession 0001419) NOAA_NCEI STAC Catalog 2002-11-02 2003-11-05 -159.65, 19.5, -155.83, 21.96 https://cmr.earthdata.nasa.gov/search/concepts/C2089376077-NOAA_NCEI.umm_json Coral reefs on the islands of Kauai, Molokai, Maui, Hawaii and Oahu were surveyed for the presence and impact of marine nonindigenous and cryptogenic species (NIS) using a rapid assessment method that standardized search effort for approximately 312 m2 at each site. A total of 41 sites were surveyed by three investigators for a total of approximately 120 hours search time on the five islands. Algae, invertebrate, and fish taxa were identified on site or returned to laboratory for identity confirmation. Only 26 NIS, comprised of three species of algae, 19 invertebrates, and four fishes were recorded from a total of 486 total taxa on the entire study, and 17 of the NIS occurred at only one or two sites. The most NIS that occurred at any site was six, and 21 of the sites had less than three. If the three species of fish that were introduced in the 1950s and known to occur throughout Hawaii are excluded, over half the sites had less than two NIS. proprietary
gov.noaa.nodc:0001624_Not Applicable Bottle and Pumpcast data collected by CTD casts from the R/V Knorr during cruises 2 through 5 of the 1988 Black Sea Oceanographic Expedition (NCEI Accession 0001624) NOAA_NCEI STAC Catalog 1988-05-14 1988-07-29 28, 41, 42, 46 https://cmr.earthdata.nasa.gov/search/concepts/C2089372426-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:0001746_Not Applicable ALINE time series (NCEI Accession 0001746) ALL STAC Catalog 1989-01-01 2001-01-01 141, 37, 150, 44 https://cmr.earthdata.nasa.gov/search/concepts/C2089372824-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0001746_Not Applicable ALINE time series (NCEI Accession 0001746) NOAA_NCEI STAC Catalog 1989-01-01 2001-01-01 141, 37, 150, 44 https://cmr.earthdata.nasa.gov/search/concepts/C2089372824-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:0001746_Not Applicable ALINE time series (NCEI Accession 0001746) ALL STAC Catalog 1989-01-01 2001-01-01 141, 37, 150, 44 https://cmr.earthdata.nasa.gov/search/concepts/C2089372824-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0001756_Not Applicable Assessment of economic benefits and costs of marine managed areas in Hawaii, 1998 - 2003 (NCEI Accession 0001756) NOAA_NCEI STAC Catalog 1998-01-01 2003-12-31 -158.9, 18.8, -154.9, 22.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089372862-NOAA_NCEI.umm_json "This dataset combines the research results from a number of papers carried out under the study ""Assessment of Economic Benefits and Costs of Marine Managed Areas in Hawaii"". The studies included a paper on the fisheries benefits of MMAs (Friedlander and Cesar, 2004), a write-up of the recreational survey at the MMA sites (Van Beukering and Cesar, 2004), a background on the institutional/regulatory framework on MMAs in Hawaii (Cesar, 2004), a paper on the economic value and cost-benefit analysis of management options for MMAs (Van Beukering and Cesar, 2004) and a paper on the international experience of sustainable financing of MMAs (Cesar and van Beukering, 2004). This dataset is basically a set of MS Word documents with mostly social-economic data embedded within tables. The habitat and fish data in this dataset are drawn from other datasets already in the NOAA archives, the NOAA Benthic Habitat Maps and the Coral Reef Assessment and Monitoring Program (CRAMP), respectively." proprietary
-gov.noaa.nodc:0001941_Not Applicable Aerial surveys of bowhead and beluga whales along with incidental sighting of other marine mammals in the Bering, Beaufort and Chukchi Seas for the Bowhead Whale Aerial Survey Project (BWASP), 1979 - 2004 (NCEI Accession 0001941) ALL STAC Catalog 1979-04-01 2004-10-18 -174.01, 57.72, -125.25, 76.14 https://cmr.earthdata.nasa.gov/search/concepts/C2089373265-NOAA_NCEI.umm_json "The Minerals Management Service (MMS), previously Bureau of Land Management, has funded fall bowhead whale aerial surveys in this area each year since 1978, using a repeatable protocol from 1982 to the present. Bowhead monitoring by MMS Environmental Studies Section, Alaska Outer Continental Shelf (OCS) Region, normally overlaps the September-October ""open-water"" season when offshore drilling and geophysical exploration are feasible and when the fall subsistence hunt for bowhead whales takes place near Kaktovik, Nuiqsut, and Barrow, Alaska. The primary survey aircraft was a de Havilland Twin Otter Series 300. The aircraft was equipped with three medium-size bubble windows that afforded complete viewing of the track-line. Geographic positions of the aircraft were logged onto a laptop computer from a Global Navigation System (1982-1991) or a Global Positioning System (1992-2000). Prior to 1992, many surveys in Block 12 (See Browse Graphic) were conducted from a Grumman Turbo Goose Model G21G. All bowhead (and beluga) whales observed were recorded, along with incidental sightings of other marine mammals. Particular emphasis was placed on regional surveys to assess large-area shifts in the migration pathway of bowhead whales and on the coordination of effort and management of data necessary to support seasonal offshore-drilling and seismic-exploration regulations. The selection of survey blocks to be flown on a given day was nonrandom, based primarily on criteria such as observed and predicted weather conditions over the study area and offshore oil-industry activities. Otherwise, the project attempted to distribute effort fairly evenly east-to-west across the entire study area. Aerial coverage favored inshore survey blocks (See Browse Graphic), since bowheads were rarely sighted north of these blocks in previous surveys (1979-1986). Surveys were flown at a target altitude of 458 m in order to maximize visibility and to minimize potential disturbance to marine mammals. Flights were normally aborted when cloud ceilings were consistently less than 305 m or the wind force was consistently above Beaufort 4. Daily flight patterns were based on sets of non-repeating transect grids computer-generated for each survey block. Transect grids were derived by dividing each survey block into sections 30 minutes of longitude across. One of the minute marks along the northern edge of each section was selected at random then connected by a straight line to a similarly selected endpoint along the southern edge of that same section. This procedure was followed for all sections of that survey block. These transect legs were then connected alternately at their northernmost or southernmost ends to produce one continuous flight grid within each survey block. Gridlines were occasionally lengthened to cover both an inshore block and the block north of it. Lines were occasionally truncated due to extended poor visibility or to avoid potential interference with subsistence whaling activities. For bowheads encountered ""on transect"", the aircraft sometimes circled for a brief (< 10 min) period to observe behavior, obtain better estimates of their numbers, and/or determine whether calves were present. Any new groups sighted when circling were recorded as ""on search""." proprietary
gov.noaa.nodc:0001941_Not Applicable Aerial surveys of bowhead and beluga whales along with incidental sighting of other marine mammals in the Bering, Beaufort and Chukchi Seas for the Bowhead Whale Aerial Survey Project (BWASP), 1979 - 2004 (NCEI Accession 0001941) NOAA_NCEI STAC Catalog 1979-04-01 2004-10-18 -174.01, 57.72, -125.25, 76.14 https://cmr.earthdata.nasa.gov/search/concepts/C2089373265-NOAA_NCEI.umm_json "The Minerals Management Service (MMS), previously Bureau of Land Management, has funded fall bowhead whale aerial surveys in this area each year since 1978, using a repeatable protocol from 1982 to the present. Bowhead monitoring by MMS Environmental Studies Section, Alaska Outer Continental Shelf (OCS) Region, normally overlaps the September-October ""open-water"" season when offshore drilling and geophysical exploration are feasible and when the fall subsistence hunt for bowhead whales takes place near Kaktovik, Nuiqsut, and Barrow, Alaska. The primary survey aircraft was a de Havilland Twin Otter Series 300. The aircraft was equipped with three medium-size bubble windows that afforded complete viewing of the track-line. Geographic positions of the aircraft were logged onto a laptop computer from a Global Navigation System (1982-1991) or a Global Positioning System (1992-2000). Prior to 1992, many surveys in Block 12 (See Browse Graphic) were conducted from a Grumman Turbo Goose Model G21G. All bowhead (and beluga) whales observed were recorded, along with incidental sightings of other marine mammals. Particular emphasis was placed on regional surveys to assess large-area shifts in the migration pathway of bowhead whales and on the coordination of effort and management of data necessary to support seasonal offshore-drilling and seismic-exploration regulations. The selection of survey blocks to be flown on a given day was nonrandom, based primarily on criteria such as observed and predicted weather conditions over the study area and offshore oil-industry activities. Otherwise, the project attempted to distribute effort fairly evenly east-to-west across the entire study area. Aerial coverage favored inshore survey blocks (See Browse Graphic), since bowheads were rarely sighted north of these blocks in previous surveys (1979-1986). Surveys were flown at a target altitude of 458 m in order to maximize visibility and to minimize potential disturbance to marine mammals. Flights were normally aborted when cloud ceilings were consistently less than 305 m or the wind force was consistently above Beaufort 4. Daily flight patterns were based on sets of non-repeating transect grids computer-generated for each survey block. Transect grids were derived by dividing each survey block into sections 30 minutes of longitude across. One of the minute marks along the northern edge of each section was selected at random then connected by a straight line to a similarly selected endpoint along the southern edge of that same section. This procedure was followed for all sections of that survey block. These transect legs were then connected alternately at their northernmost or southernmost ends to produce one continuous flight grid within each survey block. Gridlines were occasionally lengthened to cover both an inshore block and the block north of it. Lines were occasionally truncated due to extended poor visibility or to avoid potential interference with subsistence whaling activities. For bowheads encountered ""on transect"", the aircraft sometimes circled for a brief (< 10 min) period to observe behavior, obtain better estimates of their numbers, and/or determine whether calves were present. Any new groups sighted when circling were recorded as ""on search""." proprietary
-gov.noaa.nodc:0002013_Not Applicable A mesoscale hydrographic survey off Northwest Africa to examine the horizontal mixing by eddies, March - April 2003 (NCEI Accession 0002013) NOAA_NCEI STAC Catalog 2003-03-26 2003-04-16 -31.5, 6.6, -25, 11 https://cmr.earthdata.nasa.gov/search/concepts/C2089373546-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:0001941_Not Applicable Aerial surveys of bowhead and beluga whales along with incidental sighting of other marine mammals in the Bering, Beaufort and Chukchi Seas for the Bowhead Whale Aerial Survey Project (BWASP), 1979 - 2004 (NCEI Accession 0001941) ALL STAC Catalog 1979-04-01 2004-10-18 -174.01, 57.72, -125.25, 76.14 https://cmr.earthdata.nasa.gov/search/concepts/C2089373265-NOAA_NCEI.umm_json "The Minerals Management Service (MMS), previously Bureau of Land Management, has funded fall bowhead whale aerial surveys in this area each year since 1978, using a repeatable protocol from 1982 to the present. Bowhead monitoring by MMS Environmental Studies Section, Alaska Outer Continental Shelf (OCS) Region, normally overlaps the September-October ""open-water"" season when offshore drilling and geophysical exploration are feasible and when the fall subsistence hunt for bowhead whales takes place near Kaktovik, Nuiqsut, and Barrow, Alaska. The primary survey aircraft was a de Havilland Twin Otter Series 300. The aircraft was equipped with three medium-size bubble windows that afforded complete viewing of the track-line. Geographic positions of the aircraft were logged onto a laptop computer from a Global Navigation System (1982-1991) or a Global Positioning System (1992-2000). Prior to 1992, many surveys in Block 12 (See Browse Graphic) were conducted from a Grumman Turbo Goose Model G21G. All bowhead (and beluga) whales observed were recorded, along with incidental sightings of other marine mammals. Particular emphasis was placed on regional surveys to assess large-area shifts in the migration pathway of bowhead whales and on the coordination of effort and management of data necessary to support seasonal offshore-drilling and seismic-exploration regulations. The selection of survey blocks to be flown on a given day was nonrandom, based primarily on criteria such as observed and predicted weather conditions over the study area and offshore oil-industry activities. Otherwise, the project attempted to distribute effort fairly evenly east-to-west across the entire study area. Aerial coverage favored inshore survey blocks (See Browse Graphic), since bowheads were rarely sighted north of these blocks in previous surveys (1979-1986). Surveys were flown at a target altitude of 458 m in order to maximize visibility and to minimize potential disturbance to marine mammals. Flights were normally aborted when cloud ceilings were consistently less than 305 m or the wind force was consistently above Beaufort 4. Daily flight patterns were based on sets of non-repeating transect grids computer-generated for each survey block. Transect grids were derived by dividing each survey block into sections 30 minutes of longitude across. One of the minute marks along the northern edge of each section was selected at random then connected by a straight line to a similarly selected endpoint along the southern edge of that same section. This procedure was followed for all sections of that survey block. These transect legs were then connected alternately at their northernmost or southernmost ends to produce one continuous flight grid within each survey block. Gridlines were occasionally lengthened to cover both an inshore block and the block north of it. Lines were occasionally truncated due to extended poor visibility or to avoid potential interference with subsistence whaling activities. For bowheads encountered ""on transect"", the aircraft sometimes circled for a brief (< 10 min) period to observe behavior, obtain better estimates of their numbers, and/or determine whether calves were present. Any new groups sighted when circling were recorded as ""on search""." proprietary
gov.noaa.nodc:0002013_Not Applicable A mesoscale hydrographic survey off Northwest Africa to examine the horizontal mixing by eddies, March - April 2003 (NCEI Accession 0002013) ALL STAC Catalog 2003-03-26 2003-04-16 -31.5, 6.6, -25, 11 https://cmr.earthdata.nasa.gov/search/concepts/C2089373546-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:0002013_Not Applicable A mesoscale hydrographic survey off Northwest Africa to examine the horizontal mixing by eddies, March - April 2003 (NCEI Accession 0002013) NOAA_NCEI STAC Catalog 2003-03-26 2003-04-16 -31.5, 6.6, -25, 11 https://cmr.earthdata.nasa.gov/search/concepts/C2089373546-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0002170_Not Applicable 22 Real-time XBT replacements assembled by Canada Department of Fisheries and Oceans (DFO) for the Global Temperature-Salinity Profile Program (GTSPP), dates ranging from 05/26/2004 to 05/27/2004 (NCEI Accession 0002170) ALL STAC Catalog 2004-05-27 2004-05-27 9.106, 31.684, 33.058, 44.043 https://cmr.earthdata.nasa.gov/search/concepts/C2089373990-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0002170_Not Applicable 22 Real-time XBT replacements assembled by Canada Department of Fisheries and Oceans (DFO) for the Global Temperature-Salinity Profile Program (GTSPP), dates ranging from 05/26/2004 to 05/27/2004 (NCEI Accession 0002170) NOAA_NCEI STAC Catalog 2004-05-27 2004-05-27 9.106, 31.684, 33.058, 44.043 https://cmr.earthdata.nasa.gov/search/concepts/C2089373990-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:0002192_Not Applicable A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico from 1999 to 2002 (NCEI Accession 0002192) ALL STAC Catalog 1999-09-01 2002-08-25 -96.01, 23.49, -85.47, 29.38 https://cmr.earthdata.nasa.gov/search/concepts/C2089374092-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
gov.noaa.nodc:0002192_Not Applicable A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico from 1999 to 2002 (NCEI Accession 0002192) NOAA_NCEI STAC Catalog 1999-09-01 2002-08-25 -96.01, 23.49, -85.47, 29.38 https://cmr.earthdata.nasa.gov/search/concepts/C2089374092-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
+gov.noaa.nodc:0002192_Not Applicable A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico from 1999 to 2002 (NCEI Accession 0002192) ALL STAC Catalog 1999-09-01 2002-08-25 -96.01, 23.49, -85.47, 29.38 https://cmr.earthdata.nasa.gov/search/concepts/C2089374092-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
gov.noaa.nodc:0002193_Not Applicable A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002193) NOAA_NCEI STAC Catalog 1999-09-01 2002-08-01 -96, 23.47, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374098-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
gov.noaa.nodc:0002193_Not Applicable A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002193) ALL STAC Catalog 1999-09-01 2002-08-01 -96, 23.47, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374098-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
-gov.noaa.nodc:0002196_Not Applicable Acoustic doppler current meter data collected in support of the Minerals Management Service-supported Deep Water Program in the the Gulf of Mexico, 1999 - 2003 (NCEI Accession 0002196) NOAA_NCEI STAC Catalog 1999-09-01 2003-08-01 -96, 23.47, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374197-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
gov.noaa.nodc:0002196_Not Applicable Acoustic doppler current meter data collected in support of the Minerals Management Service-supported Deep Water Program in the the Gulf of Mexico, 1999 - 2003 (NCEI Accession 0002196) ALL STAC Catalog 1999-09-01 2003-08-01 -96, 23.47, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374197-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
+gov.noaa.nodc:0002196_Not Applicable Acoustic doppler current meter data collected in support of the Minerals Management Service-supported Deep Water Program in the the Gulf of Mexico, 1999 - 2003 (NCEI Accession 0002196) NOAA_NCEI STAC Catalog 1999-09-01 2003-08-01 -96, 23.47, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374197-NOAA_NCEI.umm_json "A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled ""The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology."" Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation." proprietary
gov.noaa.nodc:0002198_Not Applicable A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002198) ALL STAC Catalog 1999-09-01 2002-08-01 -96, 23.49, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374298-NOAA_NCEI.umm_json A research program has been initiated by the Minerals Management Service (Contract No.1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology. Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation. proprietary
gov.noaa.nodc:0002198_Not Applicable A survey to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002198) NOAA_NCEI STAC Catalog 1999-09-01 2002-08-01 -96, 23.49, -85.47, 29.33 https://cmr.earthdata.nasa.gov/search/concepts/C2089374298-NOAA_NCEI.umm_json A research program has been initiated by the Minerals Management Service (Contract No.1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology. Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation. proprietary
gov.noaa.nodc:0002199_Not Applicable Biological, chemical, and physical data from CTD/XCTD from five Japanese R/Vs in the North Pacific Ocean and other marginal basins from 1993 to 2003 (NCEI Accession 0002199) NOAA_NCEI STAC Catalog 1993-01-01 2003-12-31 179, 20, 130, 45 https://cmr.earthdata.nasa.gov/search/concepts/C2089374415-NOAA_NCEI.umm_json The Japan Meteorological Agency (JMA) has been carrying out oceanographic and marine meteorological observations on board research vessels, at the coastal water temperature observation stations and by ocean data buoys, for the purposes of the better understanding of dynamical processes of the oceanic general circulation affecting climate change, prevention and mitigation of natural disasters, and contributing to international cooperative activities. This Data Report contains the data obtained from the observations made by JMA in 2003 together with the explanations. The observations include the followings: 1. Oceanographic and Marine Meteorological Observations on board Research Vessels Oceanographic observations are conducted in the seas adjacent to Japan and in the western North Pacific on board five vessels: Ryofu Maru, Keifu Maru, Kofu Maru, Chofu Maru and Seifu Maru. 2. Coastal Water Temperature Observations JMA has carried out water temperature observations at the coastal stations. Historical time series of 10 day and monthly mean temperatures, daily observations and hourly observations are available in this CD-ROM. 3. Ocean Data Buoy Observations Operational ocean data buoy observations have been made to obtain marine meteorological and oceanographic observations in the seas around Japan. Correspondence relating to this Data Report may be directed to: Marine Division Climate and Marine Department Japan Meteorological Agency 1-3-4 Otemachi, Chiyoda-ku, Tokyo, 100-8122 JAPAN Facsimile: +81-3-3211-6908 E-mail: seadata@hq.kishou.go.jp proprietary
gov.noaa.nodc:0002270_Not Applicable Assessment of nonindigenous marine species in harbors and nearby coral reefs on Kauai, Molokai, Maui, and Hawaii, 2002 - 2003 (NCEI Accession 0002270) NOAA_NCEI STAC Catalog 2002-11-02 2003-06-28 -159.59, 19.73, -155.02, 21.96 https://cmr.earthdata.nasa.gov/search/concepts/C2089374772-NOAA_NCEI.umm_json Collections and observations in 2002-2003 at harbor and nearby reef sites at Nawilwili and Port Allen, Kauai; Hale O Lono and Kaunakakai, Molokai; Kahului and Maalaea, Maui; and Kawaihae and Hilo, Hawaii recorded a total of 1039 taxa of marine algae, invertebrates, and fishes, 872 of which were identified to the species level. Of these 11 were new reports for Hawaii and 112 were identified as introduced or cryptogenic species (NIS), for an overall NIS component of 10.9% of the total taxa recorded. Contrasting patterns were found between the distributions of the total identified taxa and NIS, with greater numbers of total taxa occurring at reef stations and greater numbers of NIS occurring in harbors, where they composed up to 36% of the total identified taxa. Occurrence and abundance of NIS decreased systematically from maxima in highly used commercial harbors which are isolated from oceanic circulation to relatively exposed small boat harbors to fully exposed reef sites. Only a few NIS that frequently occurred at harbor sites also occurred at reef sites. These results concur with previous studies in Hawaii and the tropical Pacific that have indicated NIS to show maximum numbers in harbors and embayments with restricted oceanic circulation and few introduced or cryptogenic species to occur on coral reefs or other ocean exposed environments. proprietary
-gov.noaa.nodc:0002295_Not Applicable A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002295) ALL STAC Catalog 1999-09-01 2002-08-20 -92.01, 23.79, -85.49, 25.49 https://cmr.earthdata.nasa.gov/search/concepts/C2089374863-NOAA_NCEI.umm_json A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology. Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation. proprietary
gov.noaa.nodc:0002295_Not Applicable A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002295) NOAA_NCEI STAC Catalog 1999-09-01 2002-08-20 -92.01, 23.79, -85.49, 25.49 https://cmr.earthdata.nasa.gov/search/concepts/C2089374863-NOAA_NCEI.umm_json A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology. Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation. proprietary
+gov.noaa.nodc:0002295_Not Applicable A survey by Texas A & M University to characterize the principal components of benthic communities over the entire northern Gulf of Mexico, 1999 - 2002 (NCEI Accession 0002295) ALL STAC Catalog 1999-09-01 2002-08-20 -92.01, 23.79, -85.49, 25.49 https://cmr.earthdata.nasa.gov/search/concepts/C2089374863-NOAA_NCEI.umm_json A research program has been initiated by the Minerals Management Service (Contract No. 1435-01-99-CT-30991) to gain better knowledge of the benthic communities of the deep Gulf of Mexico entitled The Deepwater Program: Northern Gulf of Mexico Continental Slope Habitat and Benthic Ecology. Increasing exploration and exploitation of fossil hydrocarbon resources in the deep-sea prompted the Minerals Management Service of the U.S. Department of the Interior to support an investigation of the structure and function of the assemblages of organisms that live in association with the sea floor in the deep-sea. The program, Deep Gulf of Mexico Benthos or DGoMB, is studying the northern Gulf of Mexico (GOM) continental slope from water depths of 300 meters on the upper continental slope out to greater than 3,000 meters water depth seaward of the base of the Sigsbee and Florida Escarpments. The study is focused on areas that are the most likely targets of future resource exploration and exploitation. proprietary
gov.noaa.nodc:0002316_Not Applicable Biological and other data collected from bottle casts in the NW Atlantic Ocean from HERMANO GINES from 16 January 2002 to 18 May 2004 (NCEI Accession 0002316) NOAA_NCEI STAC Catalog 2002-01-16 2004-05-18 -64.66, 10.48, -64.65, 10.48 https://cmr.earthdata.nasa.gov/search/concepts/C2089374930-NOAA_NCEI.umm_json Data collected in support of the CARIACO program, which is studying the relationship between surface primary production, physical forcing variables like the wind, and the settling flux of particulate carbon in the Cariaco Basin on the continental shelf of Venezuela. Data were collected from 16 January 2002 to 18 May 2004. proprietary
gov.noaa.nodc:0002352_Not Applicable ARGO profiling float temperature, salinity, and oxygen data measurements collected using profiling floats in the World Ocean from 1996 to 2005 (NCEI Accession 0002352) NOAA_NCEI STAC Catalog 1996-01-05 2005-08-10 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089375016-NOAA_NCEI.umm_json The U.S. National Oceanographic Data Center (NODC) operates the Global Argo Data Repository (GADR) as the long-term archive for the International Global Argo Project (for additional information about ARGO, see http://www.argo.ucsd.edu (last accessed December 2003)). Argo data archived by the USNODC on a weekly basis starting the second quarter of FY 2003, may include real-time and/or delayed mode profiles of ocean temperature and salinity, as well as related conductivity and/or pressure measurements (if any), collected by Argo profiling floats. proprietary
gov.noaa.nodc:0002449_Not Applicable Bottle data collected for chemical analysis along the coastal waters of Hawai'i as part of the Windward Community College Heeia Stream and Kaneohe Bay Water Quality Assessment Project from May 22, 2004 to March 19, 2005 (NCEI Accession 0002449) NOAA_NCEI STAC Catalog 2004-05-22 2005-03-19 -157.8164, 21.4175, -157.8078, 21.4483 https://cmr.earthdata.nasa.gov/search/concepts/C2089375205-NOAA_NCEI.umm_json Measurements of water quality parameters were taken by Windward Community College faculty and students at eight sites in the Heeia Stream and adjacent Kaneohe Bay waters from May 2004 through March 2005. Parameters include Combined Nitrogen, Photo Oxidized Nitrate, Photo Oxidized Nitrite, Total Nitrogen, and Total Phosphate. Data provided as MS Excel spreadsheets and redundant ASCII copies were made of each with same file name except for a CSV (Comma Separated Version) extension. proprietary
gov.noaa.nodc:0002602_Not Applicable Assessment of invasiveness of the Orange Keyhole Sponge, Mycale Armata, in Kaneohe Bay Oahu, Hawaii, based on surveys 2004-2005 (NCEI Accession 0002602) NOAA_NCEI STAC Catalog 2004-01-02 2005-12-31 -157.85, 21.41, -157.76, 21.51 https://cmr.earthdata.nasa.gov/search/concepts/C2089375498-NOAA_NCEI.umm_json The Orange Keyhole Sponge, Mycale armata Thiele, was unknown in Hawaii prior to 1996. First reported in Pearl Harbor, it now occurs in virtually every commercial harbor in the main Hawaiian islands, where it can be a major component of the fouling community on harbor piers and jetties. It has been reported from a few coral reef locations near harbors, but in Kaneohe Bay it has become a major component of the benthic biota in the south bay in the last 5-10 years. A study was conducted in 2004-2005 to determine Mycale armata's distribution, abundance throughout the bay, its growth rates on permanent quadrats, and whether mechanical removal would be an effective management technique for its control. Results from 190 manta board surveys on 28 reefs and paired 25 m belt transects using photo quadrats on 19 reefs indicated that the sponge had maximal coverage in the south-central part of the bay, in the vicinity of Coconut Island. proprietary
-gov.noaa.nodc:0002650_Not Applicable A survey of the marine biota of the island of Lanai, Hawaii, to determine the presence and impact of marine non-indigenous and cryptogenic species, February - March 2005 (NCEI Accession 0002650) ALL STAC Catalog 2005-02-28 2005-03-04 -157.05, 20.73, -156.88, 20.92 https://cmr.earthdata.nasa.gov/search/concepts/C2089375642-NOAA_NCEI.umm_json A baseline survey of the marine biota of the island of Lanai was conducted in May 2005. This was first comprehensive study that has been made on this island for all components of its marine nearshore community. Samples and observations were taken at seven sites around the island, and all macroalgae, macroinvertebrates and fish species collected or observed were recorded. On-site observations without collections were made at two other sites. Identified species were designated as native, nonindigenous (introduced) or cryptogenic (neither demonstrably native nor introduced) according to criteria used for previous introduced species surveys in Hawaii. A total of 294 taxa were observed or identified from collected specimens, which included 16 introduced or cryptogenic species and three new reports for the Hawaiian Islands. The 16 introduced and cryptogenic species comprised 5.4% of the total identified taxa and included seven cnidarians, one polychaete, two pericards, one decapod, one bryozoan, two ascidians and three fish. By station, the introduced/cryptogenic component ranged 3 to 7 species and 3.8% to 6.8% of the total biota. The stations included two sites at or near Kaumalapau Harbor, Lanai's principal harbor for inter-island shipping. The percent component values are similar to those that have been determined on ocean-exposed reef areas elsewhere in the Hawaiian Islands but the harbor value is well below the values in other Hawaiian harbors that are more isolated from open ocean circulation than Kaumalapau Harbor. No invasive introduced algae and only two invasive introduced invertebrates were found on the surveys. These were a single colony of the octocoral Carijoa riisei in the vicinity of Cathedrals between Manele Bay and Harbor, and a single stomatopod Gonodactylaceous falcatus at the site closest to Manele Harbor. proprietary
gov.noaa.nodc:0002650_Not Applicable A survey of the marine biota of the island of Lanai, Hawaii, to determine the presence and impact of marine non-indigenous and cryptogenic species, February - March 2005 (NCEI Accession 0002650) NOAA_NCEI STAC Catalog 2005-02-28 2005-03-04 -157.05, 20.73, -156.88, 20.92 https://cmr.earthdata.nasa.gov/search/concepts/C2089375642-NOAA_NCEI.umm_json A baseline survey of the marine biota of the island of Lanai was conducted in May 2005. This was first comprehensive study that has been made on this island for all components of its marine nearshore community. Samples and observations were taken at seven sites around the island, and all macroalgae, macroinvertebrates and fish species collected or observed were recorded. On-site observations without collections were made at two other sites. Identified species were designated as native, nonindigenous (introduced) or cryptogenic (neither demonstrably native nor introduced) according to criteria used for previous introduced species surveys in Hawaii. A total of 294 taxa were observed or identified from collected specimens, which included 16 introduced or cryptogenic species and three new reports for the Hawaiian Islands. The 16 introduced and cryptogenic species comprised 5.4% of the total identified taxa and included seven cnidarians, one polychaete, two pericards, one decapod, one bryozoan, two ascidians and three fish. By station, the introduced/cryptogenic component ranged 3 to 7 species and 3.8% to 6.8% of the total biota. The stations included two sites at or near Kaumalapau Harbor, Lanai's principal harbor for inter-island shipping. The percent component values are similar to those that have been determined on ocean-exposed reef areas elsewhere in the Hawaiian Islands but the harbor value is well below the values in other Hawaiian harbors that are more isolated from open ocean circulation than Kaumalapau Harbor. No invasive introduced algae and only two invasive introduced invertebrates were found on the surveys. These were a single colony of the octocoral Carijoa riisei in the vicinity of Cathedrals between Manele Bay and Harbor, and a single stomatopod Gonodactylaceous falcatus at the site closest to Manele Harbor. proprietary
+gov.noaa.nodc:0002650_Not Applicable A survey of the marine biota of the island of Lanai, Hawaii, to determine the presence and impact of marine non-indigenous and cryptogenic species, February - March 2005 (NCEI Accession 0002650) ALL STAC Catalog 2005-02-28 2005-03-04 -157.05, 20.73, -156.88, 20.92 https://cmr.earthdata.nasa.gov/search/concepts/C2089375642-NOAA_NCEI.umm_json A baseline survey of the marine biota of the island of Lanai was conducted in May 2005. This was first comprehensive study that has been made on this island for all components of its marine nearshore community. Samples and observations were taken at seven sites around the island, and all macroalgae, macroinvertebrates and fish species collected or observed were recorded. On-site observations without collections were made at two other sites. Identified species were designated as native, nonindigenous (introduced) or cryptogenic (neither demonstrably native nor introduced) according to criteria used for previous introduced species surveys in Hawaii. A total of 294 taxa were observed or identified from collected specimens, which included 16 introduced or cryptogenic species and three new reports for the Hawaiian Islands. The 16 introduced and cryptogenic species comprised 5.4% of the total identified taxa and included seven cnidarians, one polychaete, two pericards, one decapod, one bryozoan, two ascidians and three fish. By station, the introduced/cryptogenic component ranged 3 to 7 species and 3.8% to 6.8% of the total biota. The stations included two sites at or near Kaumalapau Harbor, Lanai's principal harbor for inter-island shipping. The percent component values are similar to those that have been determined on ocean-exposed reef areas elsewhere in the Hawaiian Islands but the harbor value is well below the values in other Hawaiian harbors that are more isolated from open ocean circulation than Kaumalapau Harbor. No invasive introduced algae and only two invasive introduced invertebrates were found on the surveys. These were a single colony of the octocoral Carijoa riisei in the vicinity of Cathedrals between Manele Bay and Harbor, and a single stomatopod Gonodactylaceous falcatus at the site closest to Manele Harbor. proprietary
gov.noaa.nodc:0002805_Not Applicable Chlorophyll data collected from the old outfall site in the south sector of Kaneohe Bay, Oahu, Hawaii, February 2001 to May 2004 (NCEI Accession 0002805) NOAA_NCEI STAC Catalog 2001-02-07 2004-05-26 -157.77, 21.41, -157.77, 21.41 https://cmr.earthdata.nasa.gov/search/concepts/C2089376053-NOAA_NCEI.umm_json Kaneohe Bay received increasing amounts of sewage from the 1950s through 1977. Most sewage was diverted from the bay in 1977 and early 1978. Data were collected beginning in September 1976 and continued until June 1979. The time series was re-established in June 1982 and continued to December 2005, when it was terminated. The sampling was at 1 m depth in the south sector of Kaneohe Bay, Oahu near the old outfall that ceased in 1977. Previous NODC Accessions 0000396 (1976-1979) and 0000422 (1982-1/2001) contained monthly averages of chlorophyll a, based on weekly to bi-weekly samples. This data set has the weekly to bi-weekly chlorophyll a, pheo, water temperature, secchi depth, and sample site depth. Additional data were taken from June 2004 - December 2005 and these will be available in a separate data set. proprietary
gov.noaa.nodc:0013170_Not Applicable Chemical and biological data collected as part of the CArbon Retention In A Colored Ocean (CARIACO) program in the Cariaco Basin off the coast of Venezuela, January 17, 2005 - January 16, 2006 (NCEI Accession 0013170) NOAA_NCEI STAC Catalog 2005-01-17 2006-01-16 -65.56, 10.45, -64.65, 10.66 https://cmr.earthdata.nasa.gov/search/concepts/C2089372614-NOAA_NCEI.umm_json Chemical and biological data were collected using bottle casts on the continental shelf of Venezuela from the HERMANO GINES from January 17, 2005 to January 16, 2006. Data were collected and submitted by Dr. Mary Scranton of Stony Brook University with support from the CArbon Retention In A Colored Ocean (CARIACO) program. proprietary
gov.noaa.nodc:0014123_Not Applicable Chemical and physical profile data collected from CTD casts from 01 January 2003 to 01 October 2005 aboard the F. G. WALTON SMITH in the Straits of Florida (NCEI Accession 0014123) NOAA_NCEI STAC Catalog 2003-01-01 2005-10-01 -81.299667, 23.249833, -79.017833, 25.627167 https://cmr.earthdata.nasa.gov/search/concepts/C2089372909-NOAA_NCEI.umm_json Not provided proprietary
@@ -18502,8 +18503,8 @@ gov.noaa.nodc:0040205_Not Applicable Carbon dioxide from surface underway survey
gov.noaa.nodc:0043167_Not Applicable Aurora 1993 XBT's temperature measurements collected using XBT from Aurora Australis in the Tasman Sea during 1993 (NCEI Accession 0043167) NOAA_NCEI STAC Catalog 1993-01-05 1993-10-08 61.52, -68.93, 159, -42.83 https://cmr.earthdata.nasa.gov/search/concepts/C2089372431-NOAA_NCEI.umm_json Temperature data received at NODC on April 14, 2008 by Tim Boyer placed on the FTP server by Ann Thresher, CSIRO (COMMONWEALTH SCIENTIFIC AND INDUSTRIAL RESEARCH ORGANIZATION) for XBT/CTD comparisons proprietary
gov.noaa.nodc:0045502_Not Applicable Carbon dioxide, temperature, salinity, and atmospheric pressure from surface underway survey in the North Pacific from January 1998 to January 2004 (NCEI Accession 0045502) NOAA_NCEI STAC Catalog 1998-01-01 2004-01-01 -100, -10, 120, 60 https://cmr.earthdata.nasa.gov/search/concepts/C2089372737-NOAA_NCEI.umm_json Sea surface pCO2, sea surface temperature, sea surface salinity, and atmospheric pressure measurements collected in the North Pacific as part of the NOAA Office of Climate Observations (OCO) and U.S. Carbon Cycle Science Programs. proprietary
gov.noaa.nodc:0045505_Not Applicable AOML VOS pCO2. temperature, salinity, and other underway measurements collected using in the Pacific and Atlantic from 2007 to 2008 (NCEI Accession 0045505) NOAA_NCEI STAC Catalog 2007-04-06 2008-01-15 -90, -40, -20, 20 https://cmr.earthdata.nasa.gov/search/concepts/C2089372759-NOAA_NCEI.umm_json AOML pCO2 underway measurements collected using in the Pacific and Atlantic from 2007 to 2008 proprietary
-gov.noaa.nodc:0046934_Not Applicable Acropora Spatial Survey Data of the Upper Florida Keys National Marine Sanctuary, 2005 - 2007 (NCEI Accession 0046934) ALL STAC Catalog 2005-01-01 2007-12-31 -81.41079, 24.54466, -80.19632, 25.29129 https://cmr.earthdata.nasa.gov/search/concepts/C2089373092-NOAA_NCEI.umm_json These data were collected by the NOAA Southeast Fisheries Science Center to document the presence or absence of Acropora spp at shallow reef sites in the Upper Florida Keys (USA). The presence or absence of acroporid corals was marked by handheld GPS during snorkel or tow surveys of shallow water (<5m) reef habitats in the Upper Florida Keys National Marine Sanctuary. The data are in GIS shape and layer files with associated attribute files, metadata files, and additional .pdf file outputs of the GIS data layers. proprietary
gov.noaa.nodc:0046934_Not Applicable Acropora Spatial Survey Data of the Upper Florida Keys National Marine Sanctuary, 2005 - 2007 (NCEI Accession 0046934) NOAA_NCEI STAC Catalog 2005-01-01 2007-12-31 -81.41079, 24.54466, -80.19632, 25.29129 https://cmr.earthdata.nasa.gov/search/concepts/C2089373092-NOAA_NCEI.umm_json These data were collected by the NOAA Southeast Fisheries Science Center to document the presence or absence of Acropora spp at shallow reef sites in the Upper Florida Keys (USA). The presence or absence of acroporid corals was marked by handheld GPS during snorkel or tow surveys of shallow water (<5m) reef habitats in the Upper Florida Keys National Marine Sanctuary. The data are in GIS shape and layer files with associated attribute files, metadata files, and additional .pdf file outputs of the GIS data layers. proprietary
+gov.noaa.nodc:0046934_Not Applicable Acropora Spatial Survey Data of the Upper Florida Keys National Marine Sanctuary, 2005 - 2007 (NCEI Accession 0046934) ALL STAC Catalog 2005-01-01 2007-12-31 -81.41079, 24.54466, -80.19632, 25.29129 https://cmr.earthdata.nasa.gov/search/concepts/C2089373092-NOAA_NCEI.umm_json These data were collected by the NOAA Southeast Fisheries Science Center to document the presence or absence of Acropora spp at shallow reef sites in the Upper Florida Keys (USA). The presence or absence of acroporid corals was marked by handheld GPS during snorkel or tow surveys of shallow water (<5m) reef habitats in the Upper Florida Keys National Marine Sanctuary. The data are in GIS shape and layer files with associated attribute files, metadata files, and additional .pdf file outputs of the GIS data layers. proprietary
gov.noaa.nodc:0049902_Not Applicable Biological dataset collected from bottle casts from the R/V LAURENCE M. GOULD and the R/V NATHANIEL B. PALMER in the Southern Drake Passage and Scotia Sea in support of National Science Foundation projects OPP 03-30443 and ANT 04-44134 from 15 February 2004 to 09 August 2006 (NCEI Accession 0049902) NOAA_NCEI STAC Catalog 2004-02-15 2006-08-09 -64.9884, -64.675, -52.8742, -54.8127 https://cmr.earthdata.nasa.gov/search/concepts/C2089373417-NOAA_NCEI.umm_json Ocean biology data were collected in Southern Drake Passage and Scotia Sea during two research cruises supported by NSF awards. These two cruises, namely LMG0402 and NBP0606, were conducted during Februay to March 2004 and July to August 2006, respectively. Dataset includes concentration of pigments in phytoplankton, particulate organic matter concentration, macronutrients, primary productivity and microbial biomass and productivity. proprietary
gov.noaa.nodc:0051848_Not Applicable Biomass measurements collected in the Pacific Ocean using a net from various platform from 1950 - 1961 (NCEI Accession 0051848) NOAA_NCEI STAC Catalog 1950-05-14 1961-07-29 -170, 0, -135, 30 https://cmr.earthdata.nasa.gov/search/concepts/C2089373644-NOAA_NCEI.umm_json Zooplankton biomass data collected from Pacific Ocean in 1950 - 1961 years received from NMFS proprietary
gov.noaa.nodc:0053277_Not Applicable Biomass measurements collected using net in the North and South Atlantic from several platforms from 1950 to 989 (NCEI Accession 0053277) NOAA_NCEI STAC Catalog 1950-01-01 1989-12-31 -86.367, -42.78, 14.175, 53.683 https://cmr.earthdata.nasa.gov/search/concepts/C2089373850-NOAA_NCEI.umm_json Zooplankton biomass data collected by Institute of Biology of the Southern Seas from the Atlantic Ocean in 1950-1989 years and received from the NMFS. proprietary
@@ -18511,8 +18512,8 @@ gov.noaa.nodc:0057319_Not Applicable Arctic Freshwater Switchyard Project: Sprin
gov.noaa.nodc:0058268_Not Applicable Beaufort Gyre hydrographic data: Temperature, salinity and transmissivity data from the Louis S St. Laurent in the Arctic Ocean, 2003 - 2008 (NCEI Accession 0058268) NOAA_NCEI STAC Catalog 2003-10-11 2008-10-20 -150, 75, -140, 78 https://cmr.earthdata.nasa.gov/search/concepts/C2089374751-NOAA_NCEI.umm_json The major goal of the observational program is to determine the variability of different components of the Beaufort Gyre fresh water (ocean and sea ice) system and to assess the partial concentrations of fresh water of different origin (rivers, Pacific Ocean, precipitation, ice/snow melt, etc). Using moorings, drifting buoys, shipboard, and remote sensing measurements we have been measuring time series of temperature, salinity, currents, geochemical tracers, sea ice draft, and sea level since August 2003, to determine freshwater content and freshwater fluxes in the Beaufort Gyre during a complete seasonal cycle and beyond. proprietary
gov.noaa.nodc:0058858_Not Applicable Abundance data for the copepod species Calanus pacificus and Metridia pacifica collected at a fixed station in Dabob Bay, Hood Canal, Puget Sound, Washington during six cruises aboard the CLIFFORD A. BARNES, October 2006 - April 2008 (NCEI Accession 0058858) NOAA_NCEI STAC Catalog 2006-10-12 2008-04-15 -122.835, 47.769, -122.835, 47.769 https://cmr.earthdata.nasa.gov/search/concepts/C2089374860-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0058858_Not Applicable Abundance data for the copepod species Calanus pacificus and Metridia pacifica collected at a fixed station in Dabob Bay, Hood Canal, Puget Sound, Washington during six cruises aboard the CLIFFORD A. BARNES, October 2006 - April 2008 (NCEI Accession 0058858) ALL STAC Catalog 2006-10-12 2008-04-15 -122.835, 47.769, -122.835, 47.769 https://cmr.earthdata.nasa.gov/search/concepts/C2089374860-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:0061208_Not Applicable Algal, coral, and other data collected by ROV and scuba diver videography from M.V. FLING and M.V. SPREE for Post-Hurricane Assessment of Sensitive Habitats of the Flower Garden Banks Vicinity project from November 13, 2005 to June 23, 2007 (NCEI Accession 0061208) NOAA_NCEI STAC Catalog 2005-11-13 2007-05-23 -93.58, 27.85, -92.45, 28.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089375074-NOAA_NCEI.umm_json The most active hurricane season on record in the Atlantic and Gulf of Mexico occurred in 2005, fueled by higher than normal sea-surface temperatures. Eleven tropical cyclones entered the Gulf of Mexico in 2005, including Hurricane Rita. Hurricane Rita was a Category 3 storm when it passed near the shelf edge banks on September 23, 2005. Several sensitive habitats within the northwestern Gulf of Mexico were close to the path of Hurricane Rita, including Sonnier, McGrail, Geyer, Bright, and East Flower Garden Banks. Hindcast hydrodynamic models estimated wave heights at 20-m or higher on these banks. This may have left some bank caps exposed, even at ~20- to 30-m depths. The implications for catastrophic damage to benthic community structure prompted the Minerals Management Service to characterize the banks in their post-hurricane state. This study, using the data in NODC Accession 0061208, characterized and compared the benthic habitats of four banks (Sonnier, McGrail, Geyer, and Bright) and recorded possible hurricane damage at these banks and the East Flower Garden Bank (EFGB). At Sonnier, McGrail, Geyer, and Bright Banks, videographic records were collected by SCUBA and ROV in April and May 2007, at four depth ranges to assess benthic cover to the lowest possible taxonomic level: 22-27 m, 30-36.5 m, 45-50 m, and 55-60 m. Video transects were qualitatively assessed for evidence of hurricane damage. To document recovery from Hurricane Rita at the existing long-term monitoring site on the EFGB, repetitive quadrats and perimeter line surveys were conducted in November 2005 and compared to data collected subsequently in June 2006. proprietary
gov.noaa.nodc:0061208_Not Applicable Algal, coral, and other data collected by ROV and scuba diver videography from M.V. FLING and M.V. SPREE for Post-Hurricane Assessment of Sensitive Habitats of the Flower Garden Banks Vicinity project from November 13, 2005 to June 23, 2007 (NCEI Accession 0061208) ALL STAC Catalog 2005-11-13 2007-05-23 -93.58, 27.85, -92.45, 28.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089375074-NOAA_NCEI.umm_json The most active hurricane season on record in the Atlantic and Gulf of Mexico occurred in 2005, fueled by higher than normal sea-surface temperatures. Eleven tropical cyclones entered the Gulf of Mexico in 2005, including Hurricane Rita. Hurricane Rita was a Category 3 storm when it passed near the shelf edge banks on September 23, 2005. Several sensitive habitats within the northwestern Gulf of Mexico were close to the path of Hurricane Rita, including Sonnier, McGrail, Geyer, Bright, and East Flower Garden Banks. Hindcast hydrodynamic models estimated wave heights at 20-m or higher on these banks. This may have left some bank caps exposed, even at ~20- to 30-m depths. The implications for catastrophic damage to benthic community structure prompted the Minerals Management Service to characterize the banks in their post-hurricane state. This study, using the data in NODC Accession 0061208, characterized and compared the benthic habitats of four banks (Sonnier, McGrail, Geyer, and Bright) and recorded possible hurricane damage at these banks and the East Flower Garden Bank (EFGB). At Sonnier, McGrail, Geyer, and Bright Banks, videographic records were collected by SCUBA and ROV in April and May 2007, at four depth ranges to assess benthic cover to the lowest possible taxonomic level: 22-27 m, 30-36.5 m, 45-50 m, and 55-60 m. Video transects were qualitatively assessed for evidence of hurricane damage. To document recovery from Hurricane Rita at the existing long-term monitoring site on the EFGB, repetitive quadrats and perimeter line surveys were conducted in November 2005 and compared to data collected subsequently in June 2006. proprietary
+gov.noaa.nodc:0061208_Not Applicable Algal, coral, and other data collected by ROV and scuba diver videography from M.V. FLING and M.V. SPREE for Post-Hurricane Assessment of Sensitive Habitats of the Flower Garden Banks Vicinity project from November 13, 2005 to June 23, 2007 (NCEI Accession 0061208) NOAA_NCEI STAC Catalog 2005-11-13 2007-05-23 -93.58, 27.85, -92.45, 28.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089375074-NOAA_NCEI.umm_json The most active hurricane season on record in the Atlantic and Gulf of Mexico occurred in 2005, fueled by higher than normal sea-surface temperatures. Eleven tropical cyclones entered the Gulf of Mexico in 2005, including Hurricane Rita. Hurricane Rita was a Category 3 storm when it passed near the shelf edge banks on September 23, 2005. Several sensitive habitats within the northwestern Gulf of Mexico were close to the path of Hurricane Rita, including Sonnier, McGrail, Geyer, Bright, and East Flower Garden Banks. Hindcast hydrodynamic models estimated wave heights at 20-m or higher on these banks. This may have left some bank caps exposed, even at ~20- to 30-m depths. The implications for catastrophic damage to benthic community structure prompted the Minerals Management Service to characterize the banks in their post-hurricane state. This study, using the data in NODC Accession 0061208, characterized and compared the benthic habitats of four banks (Sonnier, McGrail, Geyer, and Bright) and recorded possible hurricane damage at these banks and the East Flower Garden Bank (EFGB). At Sonnier, McGrail, Geyer, and Bright Banks, videographic records were collected by SCUBA and ROV in April and May 2007, at four depth ranges to assess benthic cover to the lowest possible taxonomic level: 22-27 m, 30-36.5 m, 45-50 m, and 55-60 m. Video transects were qualitatively assessed for evidence of hurricane damage. To document recovery from Hurricane Rita at the existing long-term monitoring site on the EFGB, repetitive quadrats and perimeter line surveys were conducted in November 2005 and compared to data collected subsequently in June 2006. proprietary
gov.noaa.nodc:0066319_Not Applicable Benthic data for corals, macroalgae, invertebrates, and non-living bottom types from Fagatele Bay, Pago Pago, and Fagasa, American Samoa, 2004-2008 (NCEI Accession 0066319) NOAA_NCEI STAC Catalog 2004-01-01 2008-08-01 -170.76892, -14.37023, -170.63047, -14.27847 https://cmr.earthdata.nasa.gov/search/concepts/C2089376136-NOAA_NCEI.umm_json This data set was derived from surveys in Fagatele Bay National Marine Sanctuary, Pago Pago (Rainmaker and Aua), and Fagasa (Sita Bay and Cape Larsen) conducted in 2004 and 2007-2008. Parameters include coral, algal, or invertebrate species, coral colony diameter size, and non-living bottom type. Summaries of species identification from sites above and Ofu-Olosega Islands, Ta'u Island, Aunu'u, Manu'a, and Rose Atoll, based on historic surveys back to 1917 are also given in spreadsheets. This is a working list put together by Dr. Charles Birkeland. Fish data were collected by Dr. Alison Green on the same dates and transects and are available in a separate NODC accession. proprietary
gov.noaa.nodc:0068364_Not Applicable Benthic data for corals, macroalgae, invertebrates, and non-living bottom types from Fagatele Bay National Marine Sanctuary, South Pacific Ocean, 2007-04-02 to 2008-12-31 (NCEI Accession 0068364) NOAA_NCEI STAC Catalog 2007-04-02 2008-12-31 -170.814, -14.3654, -170.562, -14.1271 https://cmr.earthdata.nasa.gov/search/concepts/C2089372324-NOAA_NCEI.umm_json Benthic transects were repeated at 12 sites around Tutuila at various depths on the reef slopes and flats. Benthic coverage categories include coral species, invertebrates, and non-living substrate type. Annual surveys took place during 2005-2009. The most detailed data are from 2008. The data were provided as spreadsheets and metadata within a PDF document, focusing on the 2008 surveys. A related data set was can be found in NCEI Accession 0066319, which was derived from surveys in Fagatele Bay National Marine Sanctuary, Pago Pago (Rainmaker and Aua), and Fagasa (Sita Bay and Cape Larsen) conducted in 2004 and 2007-2008. Parameters include coral, algal, or invertebrate species, coral colony diameter size, and non-living bottom type. Also in 0066319 are summaries of species identification from sites above and Ofu-Olosega Islands, Ta'u Island, Aunu'u, Manu'a, and Rose Atoll, based on historic surveys back to 1917 are also given in spreadsheets. This is a working list put together by Dr. Charles Birkeland. proprietary
gov.noaa.nodc:0068586_Not Applicable Chemical and physical oceanographic profile data collected from CTD casts aboard the SEWARD JOHNSON in the North Atlantic Ocean and Gulf of Mexico from 2010-07-10 to 2010-07-14 in response to the Deepwater Horizon oil spill event (NCEI Accession 0068586) NOAA_NCEI STAC Catalog 2010-07-10 2010-07-14 -83.153333, 24.251833, -79.812, 26.011833 https://cmr.earthdata.nasa.gov/search/concepts/C2089372374-NOAA_NCEI.umm_json Chemical and physical oceanographic profile data were collected aboard the SEWARD JOHNSON in the North Atlantic Ocean and Gulf of Mexico from 2010-07-10 to 2010-07-14 in response to the Deepwater Horizon oil spill event on April 20, 2010, by the Subsurface Monitoring Unit (SMU), which consists of multiple government and corporate agencies. These data include CDOM fluorescence, conductivity, dissolved oxygen, fluorescence, hydrostatic pressure, salinity, sound velocity, temperature and water density. The instruments used to collect these data were CTD, fluorometer and oxygen meter. These data have undergone quality assurance and control procedures to validate their scientific integrity at the National Coastal Data Development Center. (NODC Accession 0068586) proprietary
@@ -18662,43 +18663,43 @@ gov.noaa.nodc:0118720_Not Applicable Biological, chemical, and physical data col
gov.noaa.nodc:0124257_Not Applicable Baseline characterization of benthic and coral communities of the Flower Garden Banks, Texas from 2010-05-01 to 2012-08-31 (NCEI Accession 0124257) NOAA_NCEI STAC Catalog 2010-05-01 2012-08-31 -93.87, 27.82, -93.57, 27.99 https://cmr.earthdata.nasa.gov/search/concepts/C2089375884-NOAA_NCEI.umm_json This study utilized ROV photograph transects to quantify benthic habitat and coral communities among the five habitat types (algal nodule, coralline algal reefs, deep reefs and soft bottom) identified in the Flower Garden Banks National Marine Sanctuary (FGBNMS). ROV surveys were conducted in the mid and lower mesophotic zone of the sanctuary (17-150 m) on both the East Bank and the West Bank. The FGBNMS represents the northernmost tropical western Atlantic coral reef on the continental shelf and support the most highly developed offshore hard bank community in the region. The complexity of habitats supports a diverse assemblage of organisms including approximately 250 species of fish, 23 species of coral, and 80 species of algae in addition to large sponge communities. Understanding and monitoring these resources is critical to both sanctuary inventory and management activities. During the course of the sanctuaryÂs management plan review process, the impact of fishing was identified as a priority issue, and the concept of a research only area was suggested. The purpose of this project is to provide baseline data for all benthic habitats and coral communities. proprietary
gov.noaa.nodc:0125596_Not Applicable Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2009-03-18 to 2012-12-10 (NCEI Accession 0125596) ALL STAC Catalog 2009-03-18 2012-12-10 -51.493, -34.504, -44.498, -34.499 https://cmr.earthdata.nasa.gov/search/concepts/C2089376227-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0125596_Not Applicable Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2009-03-18 to 2012-12-10 (NCEI Accession 0125596) NOAA_NCEI STAC Catalog 2009-03-18 2012-12-10 -51.493, -34.504, -44.498, -34.499 https://cmr.earthdata.nasa.gov/search/concepts/C2089376227-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:0125597_Not Applicable Acoustic travel time, bottom pressure, and near bottom current velocities from inverted echo sounders in the Atlantic Ocean from 2004-09-27 to 2016-02-25 (NCEI Accession 0125597) NOAA_NCEI STAC Catalog 2004-09-27 2016-02-25 -76.84, 26.491, -72.004, 26.516 https://cmr.earthdata.nasa.gov/search/concepts/C2089376235-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0125597_Not Applicable Acoustic travel time, bottom pressure, and near bottom current velocities from inverted echo sounders in the Atlantic Ocean from 2004-09-27 to 2016-02-25 (NCEI Accession 0125597) ALL STAC Catalog 2004-09-27 2016-02-25 -76.84, 26.491, -72.004, 26.516 https://cmr.earthdata.nasa.gov/search/concepts/C2089376235-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:0125597_Not Applicable Acoustic travel time, bottom pressure, and near bottom current velocities from inverted echo sounders in the Atlantic Ocean from 2004-09-27 to 2016-02-25 (NCEI Accession 0125597) NOAA_NCEI STAC Catalog 2004-09-27 2016-02-25 -76.84, 26.491, -72.004, 26.516 https://cmr.earthdata.nasa.gov/search/concepts/C2089376235-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:0127525_Not Applicable Abundance and behavior of parrotfishes (Labridae, Scarinae) in the upper Florida Keys from 2013-06-19 to 2013-07-30 (NCEI Accession 0127525) NOAA_NCEI STAC Catalog 2013-06-19 2013-07-30 -80.38, 25, -80.21, 25.22 https://cmr.earthdata.nasa.gov/search/concepts/C2089376534-NOAA_NCEI.umm_json To better understand the functional roles of parrotfishes on Caribbean coral reefs we documented abundance, habitat preferences, and diets of nine species of parrotfishes (Scarus coelestinus, Scarus coeruleus, Scarus guacamaia, Scarus taeniopterus, Scarus vetula, Sparisoma aurofrenatum, Sparisoma chrysopterum, Sparisoma rubripinne, Sparisoma viride) on three high-relief spur-and-groove reefs (Molasses, Carysfort, and Elbow) offshore of Key Largo in the Florida Keys National Marine Sanctuary. On each reef, we conducted fish surveys, behavioral observations, and benthic surveys in three habitat types: high-relief spur and groove (depth 2 - 6 m), low-relief carbonate platform/hardbottom (depth 4 - 12 m), and carbonate boulder/rubble fields (depth 4 - 9 m). In addition, fish surveys were also conducted on a fourth high-relief spur-and-groove reef (French). We estimated parrotfish abundance in each of the three habitat types in order to assess the relative abundance and biomass of different species and to quantify differences in habitat selection. To estimate parrotfish density, we conducted 20 to 30 minute timed swims while towing a GPS receiver on a float on the surface to calculate the amount of area sampled. During a swim the observer would swim parallel with the habitat type being sampled and count and estimate the size to the nearest cm of all parrotfishes greater than or equal to 15 cm in length that were encountered in a 5 m wide swath. To quantify parrotfish behavior, approximately six individuals of each species were observed at each site for 20 min each. Foraging behavior was recorded by a SCUBA diver while towing a GPS receiver (Garmin GPS 72) attached to a surface float, which obtained position fixes of the focal fish at 15 s intervals. Fish were followed from a close distance (~ 2 m when possible), and food items were identified to the lowest taxonomic level possible, with macroalgae and coral usually identified to genus or species. Many bites involved scraping or excavating substrate colonized by a multi-species assemblage of filamentous âturfâ algae and crustose coralline algae (CCA). Thus, multiple species of filamentous algae, endolithic algae, and CCA could be harvested in a single bite, and it was impossible to determine the specific species of algae targeted. We also recorded the type of substrate targeted during each foraging bout, categorizing each substrate as one of the following: (1) dead coral, (2) coral pavement, (3) boulder, (4) rubble, or (5) ledge. Dead coral included both convex and concave surfaces on the vertical and horizontal planes of three dimensional coral skeletons (primarily dead Acropora palmata) that were attached to reef substrate. Coral pavement was carbonate reef with little topographic complexity (i.e., flat limestone pavement). Boulder was large remnants of dead mounding corals not clearly attached to the bottom and often partially buried in sand. Coral rubble consisted of small dead coral fragments (generally < 10 cm in any dimension) that could be moved with minimal force. Ledges consisted entirely of the undercut sides of large spurs in the high-relief spur and groove habitat. In order to quantify the relative abundance of different food types, we estimated the percent cover of algae, coral, and other sessile invertebrates on each of the five substrates commonly targeted by parrotfishes (dead coral, coral pavement, boulder, rubble, or ledge) in 0.5 m x 0.5 m photoquadrats. We photographed a total of 8 haphazardly selected quadrats dispersed throughout the study site for each substrate type at each of the three sites (N = 24 quadrats per substrate type, N = 120 quadrats total). Each photoquadrat was divided into sixteen 12 cm x 12 cm sections which were individually photographed, and percent cover was estimated from 9 stratified random points per section (N = 144 point per quadrat). proprietary
gov.noaa.nodc:0127525_Not Applicable Abundance and behavior of parrotfishes (Labridae, Scarinae) in the upper Florida Keys from 2013-06-19 to 2013-07-30 (NCEI Accession 0127525) ALL STAC Catalog 2013-06-19 2013-07-30 -80.38, 25, -80.21, 25.22 https://cmr.earthdata.nasa.gov/search/concepts/C2089376534-NOAA_NCEI.umm_json To better understand the functional roles of parrotfishes on Caribbean coral reefs we documented abundance, habitat preferences, and diets of nine species of parrotfishes (Scarus coelestinus, Scarus coeruleus, Scarus guacamaia, Scarus taeniopterus, Scarus vetula, Sparisoma aurofrenatum, Sparisoma chrysopterum, Sparisoma rubripinne, Sparisoma viride) on three high-relief spur-and-groove reefs (Molasses, Carysfort, and Elbow) offshore of Key Largo in the Florida Keys National Marine Sanctuary. On each reef, we conducted fish surveys, behavioral observations, and benthic surveys in three habitat types: high-relief spur and groove (depth 2 - 6 m), low-relief carbonate platform/hardbottom (depth 4 - 12 m), and carbonate boulder/rubble fields (depth 4 - 9 m). In addition, fish surveys were also conducted on a fourth high-relief spur-and-groove reef (French). We estimated parrotfish abundance in each of the three habitat types in order to assess the relative abundance and biomass of different species and to quantify differences in habitat selection. To estimate parrotfish density, we conducted 20 to 30 minute timed swims while towing a GPS receiver on a float on the surface to calculate the amount of area sampled. During a swim the observer would swim parallel with the habitat type being sampled and count and estimate the size to the nearest cm of all parrotfishes greater than or equal to 15 cm in length that were encountered in a 5 m wide swath. To quantify parrotfish behavior, approximately six individuals of each species were observed at each site for 20 min each. Foraging behavior was recorded by a SCUBA diver while towing a GPS receiver (Garmin GPS 72) attached to a surface float, which obtained position fixes of the focal fish at 15 s intervals. Fish were followed from a close distance (~ 2 m when possible), and food items were identified to the lowest taxonomic level possible, with macroalgae and coral usually identified to genus or species. Many bites involved scraping or excavating substrate colonized by a multi-species assemblage of filamentous âturfâ algae and crustose coralline algae (CCA). Thus, multiple species of filamentous algae, endolithic algae, and CCA could be harvested in a single bite, and it was impossible to determine the specific species of algae targeted. We also recorded the type of substrate targeted during each foraging bout, categorizing each substrate as one of the following: (1) dead coral, (2) coral pavement, (3) boulder, (4) rubble, or (5) ledge. Dead coral included both convex and concave surfaces on the vertical and horizontal planes of three dimensional coral skeletons (primarily dead Acropora palmata) that were attached to reef substrate. Coral pavement was carbonate reef with little topographic complexity (i.e., flat limestone pavement). Boulder was large remnants of dead mounding corals not clearly attached to the bottom and often partially buried in sand. Coral rubble consisted of small dead coral fragments (generally < 10 cm in any dimension) that could be moved with minimal force. Ledges consisted entirely of the undercut sides of large spurs in the high-relief spur and groove habitat. In order to quantify the relative abundance of different food types, we estimated the percent cover of algae, coral, and other sessile invertebrates on each of the five substrates commonly targeted by parrotfishes (dead coral, coral pavement, boulder, rubble, or ledge) in 0.5 m x 0.5 m photoquadrats. We photographed a total of 8 haphazardly selected quadrats dispersed throughout the study site for each substrate type at each of the three sites (N = 24 quadrats per substrate type, N = 120 quadrats total). Each photoquadrat was divided into sixteen 12 cm x 12 cm sections which were individually photographed, and percent cover was estimated from 9 stratified random points per section (N = 144 point per quadrat). proprietary
gov.noaa.nodc:0128996_Not Applicable Benthic and biological data in the New York Bight from 2010-06-01 to 2012-05-31 (NCEI Accession 0128996) NOAA_NCEI STAC Catalog 2010-06-01 2012-05-31 -75, 37, -69, 42 https://cmr.earthdata.nasa.gov/search/concepts/C2089376996-NOAA_NCEI.umm_json These data sets show the distribution of key species and habitats, such as seabirds, bathymetry, surficial sediments, deep sea corals, and oceanographic habitats. NOAAâs Biogeography Branch worked with the New York Department of State (DOS) to interpret existing ecological information and create these new data sets. New York plans to integrate this information with other ecological and human use data compiled by others (for example, The Nature Conservancy, Northeast Fisheries Science Center) and apply ecosystem-based management and plan for ocean uses. Many academic, state and federal and non-governmental organization partners contributed to this project with data, analyses and reviews. Project partners included: the University of Alaska, Biology and Wildlife Department; University of Texas, Institute for Geophysics; The Nature Conservancy, Mid-Atlantic Marine Program; the National Marine Fisheries Service (NMFS), Northeast Fisheries Science Center, and the NMFS, Deep-Sea Coral Research and Technology Program. proprietary
gov.noaa.nodc:0129395_Not Applicable Chlorophyll accessory pigments collected from NOAA Ship OSCAR ELTON SETTE in North Pacific Ocean from 2008-03-01 to 2011-04-01 (NCEI Accession 0129395) NOAA_NCEI STAC Catalog 2008-03-01 2011-04-01 -158, 26, -158, 36 https://cmr.earthdata.nasa.gov/search/concepts/C2089377189-NOAA_NCEI.umm_json These data represent the chlorophyll accessory pigments measured from discrete depth water samples collected in CTD-mounted 10 liter Niskin bottles as part of NOAA surveys in the central North Pacific Ocean north of Hawaii. Accessory pigments were measured post-survey at the University of Hawaii using HPLC methods. proprietary
gov.noaa.nodc:0130065_Not Applicable Chlorophyll A, hydrostatic pressure, and water density measurements collected from New Horizon in Gulf of California and North Pacific Ocean from 2004-07-14 to 2008-08-06 (NCEI Accession 0130065) NOAA_NCEI STAC Catalog 2004-07-14 2008-08-06 -120.5, 20.48, -106.48, 32.52 https://cmr.earthdata.nasa.gov/search/concepts/C2089377812-NOAA_NCEI.umm_json Extracted chlorophyll A, normalized to filtered volume, from suspended particulate material collected via Niskin bottle from the Gulf of California in the summers of 2004, 2005, and 2008, as well as from the Eastern Tropical North Pacific in 2008. proprietary
-gov.noaa.nodc:0130929_Not Applicable AFSC/REFM: Isolation by distance (IBD) Alaskan fish stock structure modeling (NCEI Accession 0130929) NOAA_NCEI STAC Catalog 1980-01-01 2012-01-01 170, 50, -160, 62 https://cmr.earthdata.nasa.gov/search/concepts/C2089378414-NOAA_NCEI.umm_json This model study examines several management strategies for two marine fish species subject to isolation-by-distance (IBD): Pacific cod in the Aleutian Islands (AI) and northern rockfish in the Eastern Bering Sea (EBS) and Aleutian Islands. A one-dimensional stepping stone model was used to model isolation by distance, and was intended to mimic regions where marine species are exploited along a continental shelf. The performance of spatial assessment and management methods depended on how the range was split. Splitting anywhere within the managed area led to fewer demes falling below target and threshold biomass levels and higher yield than managing the entire area as a single unit. Equilibrium yield was maximized when each deme was assessed and managed separately and under catch cascading, in which harvest quotas within a management unit are spatially allocated based upon the distribution of survey biomass. The longer-lived rockfish declined more slowly than Pacific cod, and experienced greater depletion in biomass under disproportionate fishing effort due to lower productivity. Overall, splitting a management area of the size simulated in the model improved performance measures, and the optimal management strategy grouped management units by demes with similar relative fishing effort. proprietary
gov.noaa.nodc:0130929_Not Applicable AFSC/REFM: Isolation by distance (IBD) Alaskan fish stock structure modeling (NCEI Accession 0130929) ALL STAC Catalog 1980-01-01 2012-01-01 170, 50, -160, 62 https://cmr.earthdata.nasa.gov/search/concepts/C2089378414-NOAA_NCEI.umm_json This model study examines several management strategies for two marine fish species subject to isolation-by-distance (IBD): Pacific cod in the Aleutian Islands (AI) and northern rockfish in the Eastern Bering Sea (EBS) and Aleutian Islands. A one-dimensional stepping stone model was used to model isolation by distance, and was intended to mimic regions where marine species are exploited along a continental shelf. The performance of spatial assessment and management methods depended on how the range was split. Splitting anywhere within the managed area led to fewer demes falling below target and threshold biomass levels and higher yield than managing the entire area as a single unit. Equilibrium yield was maximized when each deme was assessed and managed separately and under catch cascading, in which harvest quotas within a management unit are spatially allocated based upon the distribution of survey biomass. The longer-lived rockfish declined more slowly than Pacific cod, and experienced greater depletion in biomass under disproportionate fishing effort due to lower productivity. Overall, splitting a management area of the size simulated in the model improved performance measures, and the optimal management strategy grouped management units by demes with similar relative fishing effort. proprietary
+gov.noaa.nodc:0130929_Not Applicable AFSC/REFM: Isolation by distance (IBD) Alaskan fish stock structure modeling (NCEI Accession 0130929) NOAA_NCEI STAC Catalog 1980-01-01 2012-01-01 170, 50, -160, 62 https://cmr.earthdata.nasa.gov/search/concepts/C2089378414-NOAA_NCEI.umm_json This model study examines several management strategies for two marine fish species subject to isolation-by-distance (IBD): Pacific cod in the Aleutian Islands (AI) and northern rockfish in the Eastern Bering Sea (EBS) and Aleutian Islands. A one-dimensional stepping stone model was used to model isolation by distance, and was intended to mimic regions where marine species are exploited along a continental shelf. The performance of spatial assessment and management methods depended on how the range was split. Splitting anywhere within the managed area led to fewer demes falling below target and threshold biomass levels and higher yield than managing the entire area as a single unit. Equilibrium yield was maximized when each deme was assessed and managed separately and under catch cascading, in which harvest quotas within a management unit are spatially allocated based upon the distribution of survey biomass. The longer-lived rockfish declined more slowly than Pacific cod, and experienced greater depletion in biomass under disproportionate fishing effort due to lower productivity. Overall, splitting a management area of the size simulated in the model improved performance measures, and the optimal management strategy grouped management units by demes with similar relative fishing effort. proprietary
gov.noaa.nodc:0131425_Not Applicable Bowhead Whale Feeding Ecology Study (BOWFEST): Aerial Survey in Chukchi and Beaufort Seas conducted from 2007-08-23 to 2011-09-16 (NCEI Accession 0131425) NOAA_NCEI STAC Catalog 2007-08-23 2011-09-16 -157.33, 70.79, -151.84, 72.05 https://cmr.earthdata.nasa.gov/search/concepts/C2089378614-NOAA_NCEI.umm_json The Bowhead Whale Feeding Ecology Study (BOWFEST) was initiated in May 2007 through an Interagency Agreement between the Bureau of Ocean Energy Management (BOEM) (formerly Minerals Management Service (MMS)) and the National Marine Mammal Laboratory (NMML). This was a multi-disciplinary study involving oceanography, acoustics, tagging, stomach sampling and aerial surveys and included scientists from a wide range of institutions (Woods Hole Oceanographic Institution (WHOI), University of Rhode Island (URI), University of Alaska Fairbanks (UAF), University of Washington (UW), Oregon State University (OSU), North Slope Borough (NSB), and NMML. The data described and presented here are only from the aerial survey component of this larger study. The focus of the aerial survey was to document patterns and variability in the timing and locations of bowhead whales. Using a NOAA Twin Otter, scientists from NMML conducted aerial surveys from mid-August to mid-September during this five year study between years 2007-2011. Surveys were conducted in the BOWFEST study area (continental shelf waters between 157 degree W and 152 degree W and from the coastline to 72 degree N, with most of the effort concentrated between 157 degree W and 154 degree W and between the coastline and 71 degree 44'N). proprietary
gov.noaa.nodc:0131862_Not Applicable Cetacean line-transect survey conducted in the eastern Bering Sea shelf by Alaska Fisheries Science Center, National Marine Mammal Laboratory from NOAA Ship Miller Freeman from 1999-07-07 to 2004-06-30 (NCEI Accession 0131862) NOAA_NCEI STAC Catalog 1999-07-07 2004-06-30 -178.9167, 53.9212, -153.451, 63.0152 https://cmr.earthdata.nasa.gov/search/concepts/C2089378822-NOAA_NCEI.umm_json Visual surveys for cetaceans were conducted on the eastern Bering Sea shelf along transect lines, in association with the AFSCâs echo integration trawl surveys for walleye pollock. Surveys in 2000 and 2004 were from early June to early July, the survey in 2002 was from early June to late July, and the survey in 1999 was from early July to early August. Searches for cetaceans were conducted from the flying bridge of NOAA Ship Miller Freeman at a platform height of 12 m above the sea surface and survey speed of 18.5 22.0 km/h (10 12 kts). North south transect lines were spaced 37 km apart and defined by the historical acoustic survey for walleye pollock. Insufficient funding precluded including cetacean observers on all legs except in 2002. See Friday et al. 2012. Cetacean distribution and abundance in relation to oceanographic domains on the eastern Bering Sea shelf: 1999-2004 (http://www.sciencedirect.com/science/article/pii/S0967064512000100). proprietary
gov.noaa.nodc:0133936_Not Applicable Beluga whales aerial survey conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 1993-06-02 to 2014-06-12 (NCEI Accession 0133936) NOAA_NCEI STAC Catalog 1993-06-02 2014-06-12 -154.28, 58.82, -148.96, 61.63 https://cmr.earthdata.nasa.gov/search/concepts/C2089379076-NOAA_NCEI.umm_json The National Marine Fisheries Service (NMFS) has conducted aerial counts of Cook Inlet beluga whales (Delphinapterus leucas) from 1993 to 2014 (excluding 2013). Nearly all counts were conducted during the month of June. The routine nature of these counts and the consistency in research protocol lend themselves to inter-annual trend analyses. Beginning in 2005, an aerial survey was added during the month of August to document calving groups within the upper Inlet (north of East and West Foreland). Research protocol has been based on paired observers on the shoreward side of the aircraft and a single observer and computer operator on the offshore side independently searching for marine mammals. Data on environmental conditions, time, location, species, and inclinometer angle were collected for each sighting. The counting protocol included multiple passes near each beluga group while simultaneously collecting video footage. The counting system and observer performance has been tested through paired, independent observational effort. Aerial observer counts are used to calculate median counts for each beluga group to provide a daily index for the population prior to calculating the abundance estimate. Video has been used to count the number of animals in the group to correct for missed animals in the observer counts (perception bias). One video camera had a lens set at a wide angle to view the entire beluga group while the second video camera was zoomed to approximately 10x to magnify a subsample of individual whales in the group. The zoomed video has been used to examine color ratios of white adults relative to smaller and darker juveniles and calves and correct for those individuals missed due to their size or coloration. Aerial counts and video footage of beluga whales provide the fundamental data used to calculate the abundance of and a calving index for the Cook Inlet population. The abundance estimates are applied to trends analyses to determine the status of the stock. Three datasets are included here that contain basic survey data such as latitude, longitude and sightings, as well as the counts of beluga whale groups made by the aerial observers and the results from video analysis from data collected on surveys from 1993-2012, and 2014. proprietary
gov.noaa.nodc:0133937_Not Applicable Bowhead whale aerial abundance survey conducted by Alaska Fisheries Science Center, National Marine Mammal Laboratory from 2011-04-19 to 2011-06-11 (NCEI Accession 0133937) NOAA_NCEI STAC Catalog 2011-04-19 2011-06-11 -164.42379, 68.987009, -148.41013, 71.974838 https://cmr.earthdata.nasa.gov/search/concepts/C2089379086-NOAA_NCEI.umm_json Aerial photographic surveys for bowhead whales were conducted near Point Barrow, Alaska, from 19 April to 6 June in 2011. Approximately 4,594 photographs containing 6,801 bowhead whale images were obtained (not accounting for resightings). The 2011 field season was very successful: we flew 36 out of 49 available days and conducted 49 flights in that time; we were grounded due to weather on 13 days. The longest period of time that we were grounded due to weather (low ceilings/fog) was three days. This occurred after the migration had slowed down, during a time when few whales passed the ice perches according to the ice-based visual survey. The 2011 migration was steady with several peaks (30 April, 4-5 May, 12 May), and then the migration rate slowed down considerably after 14 May. The photographs taken in 2011 are a significant contribution to the bowhead whale photographic catalogue. They will be used to calculate a population estimate that may be used for comparison with the 2011 ice-based estimate and will provide better precision in estimates of bowhead whale life-history parameters. proprietary
gov.noaa.nodc:0137093_Not Applicable Calcification Rates of Crustose Coralline Algae derived from Calcification Accretion Units (CAUs) deployed across American Samoa and the Pacific Remote Island Areas in 2010 and recovered in 2012 (NCEI Accession 0137093) NOAA_NCEI STAC Catalog 2010-01-25 2012-05-17 -176.624, -14.5596, -160.014, 16.7477 https://cmr.earthdata.nasa.gov/search/concepts/C2089379273-NOAA_NCEI.umm_json Laboratory experiments reveal calcification rates of crustose coralline algae are strongly correlated to seawater aragonite saturation state. Predictions of reduced coral calcification rates, due to ocean acidification, suggest that coral reef communities will undergo ecological phase shifts as calcifying organisms are negatively impacted by changing seawater chemistry. The data described here result from the use of calcification accretion units, or CAUs, to assess the current effects of changes in seawater carbonate chemistry on calcification and accretion rates of calcareous and fleshy algae. This effort is a partnership between CREP and Drs. Nicole Price of Bigelow Marine Laboratory and Jen Smith of Scripps Institution of Oceanography, who have extensive knowledge of marine benthic algal community ecology. CAUs are composed of two 10 x 10 centimeter (cm) flat, square, gray PVC plates, stacked 1 cm apart, and are attached to the benthos using stainless steel threaded rods. Calcareous organisms, primarily crustose coralline algae and encrusting corals, recruit to these plates and accrete/calcify carbonate skeletons over 2-3 year deployments. Due to the simple, low-cost design and analysis, statistically robust numbers of calcification plates can easily be deployed, recovered, and processed to provide estimates of net calcification, percent cover, and vertical accretion rates. CAUs have been deployed and replaced at existing, long-term monitoring sites during Pacific RAMP cruises, in accordance with protocols developed by Price et al. 2012. There are typically five CAU sites established at each location CREP visits with five units deployed at each site. The study provides information about Pacific-wide spatial patterns of algal calcification and accretion rates and serves as a basis for detecting changes associated with changing seawater chemistry due to ocean acidification. In conjuction with benthic community composition data (separate dataset), the calcification rates will aid in determining the magnitude of how ocean acidification affects coral reefs in the natural environment. The data can be accessed online via the NOAA National Centers for Environmental Information (NCEI) Ocean Archive, accession 0137093. The reef study sites are throughout the Pacific Ocean, in areas with little or no direct local anthropogenic impacts and areas of anthropogenic impact. Pacific RAMP is an ideal platform from which to collect samples over a broad range of benthic ecosystems, oceanic regimes and gradients, to observe ecological impacts of ocean acidification on natural reef systems, outside of the laboratory. Analysis of these data will expand scientistsâ capacity for assessing coral reef resilience regarding the effects of ocean acidification outside of controlled laboratory experiments. These data can also be used in comparative analyses across natural gradients, thereby assisting efforts to determine whether key reef-building taxa can acclimatize to changing oceanographic environments. These data will have immediate, direct impacts on predictions of reef resilience in a higher CO2 world and on the design of reef management strategies. proprietary
gov.noaa.nodc:0138649_Not Applicable Bottom water temperature, salinity, pH, benthic cover, dissolved inorganic carbon and other data collected from NOAA Ship HI'IALAKAI and other in Northern Marianna Islands from 2014-05-17 to 2014-08-13 (NCEI Accession 0138649) NOAA_NCEI STAC Catalog 2014-05-17 2014-08-13 145.2074, 19.9964, 145.2316, 20.03215 https://cmr.earthdata.nasa.gov/search/concepts/C2089376259-NOAA_NCEI.umm_json These data correspond to that published in the analysis of the following manuscript: I.C. Enochs, Manzello, D.P., Donham, E.M., Kolodziej, G., Okano, R., et al. (in press) Shift from coral to macroalgae dominance on a volcanically acidified reef. Nature Climate Change. https://doi.org/10.1038/nclimate2758 proprietary
-gov.noaa.nodc:0138863_Not Applicable Acoustics short-term passive monitoring using sonobuoys in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-01 to 2015-09-28 (NCEI Accession 0138863) ALL STAC Catalog 2007-08-01 2015-09-28 -177.5925, 53.52167, -141.62497, 72.86938 https://cmr.earthdata.nasa.gov/search/concepts/C2089376269-NOAA_NCEI.umm_json The National Marine Mammal Laboratory (NMML) has conducted passive acoustic monitoring in the Bering, Chukchi, and Western Beaufort Seas to determine spatio-temporal distribution of marine mammals as well as environmental and anthropogenic noise. Species and sounds detected on sonobuoys include fin, blue, bowhead, humpback, killer, gray, minke, sperm, beluga, sei, and North Pacific right whales, walrus, ribbon and bearded seals, and seismic airguns. This short-term passive acoustic monitoring was also used to locate vocalizing species of interest for photo-identification, tagging, and behavioral studies. Recordings are available since 2007 in the Bering Sea, since 2010 in the Chukchi and Beaufort Seas, and in 2013 in the Gulf of Alaska. Both omnidirectional and DiFAR sonobuoys have been used. The vast majority of the sonobuoys were deployed opportunistically along the tracks of research cruises funded by the Bureau of Ocean Energy Management (BOEM). In one year (2009), sonobuoys were deployed opportunistically from an aerial survey plane. All sonobuoys were provided by the United States Navy (Naval Operational Logistics Support Center, Naval Surface Warfare Center, Crance Division, and the Office of the Assistant Secretary of the Navy). proprietary
gov.noaa.nodc:0138863_Not Applicable Acoustics short-term passive monitoring using sonobuoys in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-01 to 2015-09-28 (NCEI Accession 0138863) NOAA_NCEI STAC Catalog 2007-08-01 2015-09-28 -177.5925, 53.52167, -141.62497, 72.86938 https://cmr.earthdata.nasa.gov/search/concepts/C2089376269-NOAA_NCEI.umm_json The National Marine Mammal Laboratory (NMML) has conducted passive acoustic monitoring in the Bering, Chukchi, and Western Beaufort Seas to determine spatio-temporal distribution of marine mammals as well as environmental and anthropogenic noise. Species and sounds detected on sonobuoys include fin, blue, bowhead, humpback, killer, gray, minke, sperm, beluga, sei, and North Pacific right whales, walrus, ribbon and bearded seals, and seismic airguns. This short-term passive acoustic monitoring was also used to locate vocalizing species of interest for photo-identification, tagging, and behavioral studies. Recordings are available since 2007 in the Bering Sea, since 2010 in the Chukchi and Beaufort Seas, and in 2013 in the Gulf of Alaska. Both omnidirectional and DiFAR sonobuoys have been used. The vast majority of the sonobuoys were deployed opportunistically along the tracks of research cruises funded by the Bureau of Ocean Energy Management (BOEM). In one year (2009), sonobuoys were deployed opportunistically from an aerial survey plane. All sonobuoys were provided by the United States Navy (Naval Operational Logistics Support Center, Naval Surface Warfare Center, Crance Division, and the Office of the Assistant Secretary of the Navy). proprietary
+gov.noaa.nodc:0138863_Not Applicable Acoustics short-term passive monitoring using sonobuoys in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-01 to 2015-09-28 (NCEI Accession 0138863) ALL STAC Catalog 2007-08-01 2015-09-28 -177.5925, 53.52167, -141.62497, 72.86938 https://cmr.earthdata.nasa.gov/search/concepts/C2089376269-NOAA_NCEI.umm_json The National Marine Mammal Laboratory (NMML) has conducted passive acoustic monitoring in the Bering, Chukchi, and Western Beaufort Seas to determine spatio-temporal distribution of marine mammals as well as environmental and anthropogenic noise. Species and sounds detected on sonobuoys include fin, blue, bowhead, humpback, killer, gray, minke, sperm, beluga, sei, and North Pacific right whales, walrus, ribbon and bearded seals, and seismic airguns. This short-term passive acoustic monitoring was also used to locate vocalizing species of interest for photo-identification, tagging, and behavioral studies. Recordings are available since 2007 in the Bering Sea, since 2010 in the Chukchi and Beaufort Seas, and in 2013 in the Gulf of Alaska. Both omnidirectional and DiFAR sonobuoys have been used. The vast majority of the sonobuoys were deployed opportunistically along the tracks of research cruises funded by the Bureau of Ocean Energy Management (BOEM). In one year (2009), sonobuoys were deployed opportunistically from an aerial survey plane. All sonobuoys were provided by the United States Navy (Naval Operational Logistics Support Center, Naval Surface Warfare Center, Crance Division, and the Office of the Assistant Secretary of the Navy). proprietary
gov.noaa.nodc:0138984_Not Applicable Characterizing pinniped use of offshore oil and gas platforms as haulouts and foraging areas in waters off southern California from 2013-01-01 to 2015-01-31 (NCEI Accession 0138984) NOAA_NCEI STAC Catalog 2013-01-01 2015-01-31 -121, 33, -118, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2089376321-NOAA_NCEI.umm_json California sea lions (Zalophus californianus) and Pacific harbor seals (Phoca vitulina) use offshore oil and gas platforms as resting and foraging areas. Both species are protected by the Marine Mammal Protection Act (1972). The Bureau of Ocean Energy Management (BOEM) is required to collect information from platforms being used by California sea lions and harbor seals (or other pinniped species) with the goal of meeting environmental review and permitting requirements associated with the eventual decommissioning of offshore platforms. Decommissioning requirements are under the jurisdiction of BOEMs sister agency, the Bureau of Safety and Environmental Enforcement (BSEE). However, BOEM provides environmental studies and environmental review support for BSEE actions. To accomplish this goal, BOEM entered an inter-agency agreement with the National Marine Mammal Laboratories' California Current Ecosystem Program (CCEP; AFSC/NOAA) in 2012. Specifically, BOEM funded CCEP to conduct a study (from January 2012 to January 2015) to characterize and quantify California sea lion and Pacific harbor seal use of the platforms, including; abundance, seasonal use patterns, and age and sex class composition of animals on the platforms. Inter- (i.e. spatial) and intra- (i.e. temporal) platform comparisons were examined. proprietary
gov.noaa.nodc:0140481_Not Applicable Bristol Bay Beluga hearing sensitivity data collected from 2012-09-02 to 2014-09-03 (NCEI Accession 0140481) NOAA_NCEI STAC Catalog 2012-09-02 2014-09-03 -159, 58.5, -158.2, 59.7 https://cmr.earthdata.nasa.gov/search/concepts/C2089376409-NOAA_NCEI.umm_json Hearing sensitivity data was collected on beluga whales in Bristol Bay with auditory evoked potential (AEP) methods for the frequencies 4, 8, 11.2, 16, 22.5, 32, 45, 54, 80, 100, 128, 150 kHz in 7 belugas in 2012 and 9 in 2014. proprietary
-gov.noaa.nodc:0143303_Not Applicable Acoustics long-term passive monitoring using moored autonomous recorders in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-15 to 2015-04-30 (NCEI Accession 0143303) NOAA_NCEI STAC Catalog 2007-08-15 2015-04-30 171.7, 53.63, -0.78, 78.837 https://cmr.earthdata.nasa.gov/search/concepts/C2089376734-NOAA_NCEI.umm_json The National Marine Mammal Laboratory (NMML) has deployed long-term passive acoustic recorders in various locations in Alaskan waters and in the High Arctic to determine spatio-temporal distribution of marine mammals as well as environmental and anthropogenic noise. Following the timing of peak calling among the various long-term recorders may provide some insight into finer-scale movements of cetaceans throughout the Bering, Chukchi, and Beaufort Seas. Changes in ambient noise levels can also be tracked. Recordings are available since 2007 in the Bering and Beaufort Seas, since 2010 in the Chukchi, and from 2008-2012 in Fram Strait. The majority of these recorders were deployed on NMML subsurface moorings, although several have been deployed on the oceanographic moorings of other researchers. Several different types of autonomous passive acoustic recorders have been deployed, most for one year. Recording parameters varied among instrument types and have evolved among projects. The majority of these recorders and deployments were funded by the Bureau of Ocean Energy Management (BOEM); however, several were funded by a grant from the Ocean Acoustics Program (NOAA/S and T). proprietary
gov.noaa.nodc:0143303_Not Applicable Acoustics long-term passive monitoring using moored autonomous recorders in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-15 to 2015-04-30 (NCEI Accession 0143303) ALL STAC Catalog 2007-08-15 2015-04-30 171.7, 53.63, -0.78, 78.837 https://cmr.earthdata.nasa.gov/search/concepts/C2089376734-NOAA_NCEI.umm_json The National Marine Mammal Laboratory (NMML) has deployed long-term passive acoustic recorders in various locations in Alaskan waters and in the High Arctic to determine spatio-temporal distribution of marine mammals as well as environmental and anthropogenic noise. Following the timing of peak calling among the various long-term recorders may provide some insight into finer-scale movements of cetaceans throughout the Bering, Chukchi, and Beaufort Seas. Changes in ambient noise levels can also be tracked. Recordings are available since 2007 in the Bering and Beaufort Seas, since 2010 in the Chukchi, and from 2008-2012 in Fram Strait. The majority of these recorders were deployed on NMML subsurface moorings, although several have been deployed on the oceanographic moorings of other researchers. Several different types of autonomous passive acoustic recorders have been deployed, most for one year. Recording parameters varied among instrument types and have evolved among projects. The majority of these recorders and deployments were funded by the Bureau of Ocean Energy Management (BOEM); however, several were funded by a grant from the Ocean Acoustics Program (NOAA/S and T). proprietary
+gov.noaa.nodc:0143303_Not Applicable Acoustics long-term passive monitoring using moored autonomous recorders in the Bering, Chukchi, and Western Beaufort Seas conducted by Alaska Fisheries Scientific Center, National Marine Mammal Laboratory from 2007-08-15 to 2015-04-30 (NCEI Accession 0143303) NOAA_NCEI STAC Catalog 2007-08-15 2015-04-30 171.7, 53.63, -0.78, 78.837 https://cmr.earthdata.nasa.gov/search/concepts/C2089376734-NOAA_NCEI.umm_json The National Marine Mammal Laboratory (NMML) has deployed long-term passive acoustic recorders in various locations in Alaskan waters and in the High Arctic to determine spatio-temporal distribution of marine mammals as well as environmental and anthropogenic noise. Following the timing of peak calling among the various long-term recorders may provide some insight into finer-scale movements of cetaceans throughout the Bering, Chukchi, and Beaufort Seas. Changes in ambient noise levels can also be tracked. Recordings are available since 2007 in the Bering and Beaufort Seas, since 2010 in the Chukchi, and from 2008-2012 in Fram Strait. The majority of these recorders were deployed on NMML subsurface moorings, although several have been deployed on the oceanographic moorings of other researchers. Several different types of autonomous passive acoustic recorders have been deployed, most for one year. Recording parameters varied among instrument types and have evolved among projects. The majority of these recorders and deployments were funded by the Bureau of Ocean Energy Management (BOEM); however, several were funded by a grant from the Ocean Acoustics Program (NOAA/S and T). proprietary
gov.noaa.nodc:0143928_Not Applicable Benthic Habitats of the Florida Keys derived from color aerial photography collected between 1991-12 and March 1992 (NCEI Accession 0143928) NOAA_NCEI STAC Catalog 1991-12-01 1998-01-01 -83, 24.25, -80.2, 25.25 https://cmr.earthdata.nasa.gov/search/concepts/C2089376853-NOAA_NCEI.umm_json This project was a cooperative effort between the National Ocean Service and the Florida Department of Environmental Protection's Florida Marine Research Institute (now called the Fish and Wildlife Research Institute). The goal of the effort was to produce shallow-water (from 0 to approximately 30 m water depth) benthic habitat maps of the Florida Keys and adjacent waters. The maps were generated by expert visual interpretation of 1:48,000 scale color aerial photography and subsequent photogrammetric, stereo, digital compilation of interpreted habitat polygon boundaries from aerial photography. The Minimum mapping unit = 0.4 hectare (4,047 sq m; 1 acre) for all habitat. Patch reefs may be <0.5 ha. The aerial photography was acquired using a NOAA jet from December 1991 through March 1992. The photography was acquired with 60% side and 80% forward overlap to facilitate stereo compilation. Approximately 450 aerial photographs were acquired and used for the mapping project. Ground validation of interpreted habitat polygons was performed by visual verification at actual field sites prior to compilation. Aircraft Inertial Measurement Unit data were used to correct photography positioning in photogrammetric analytical plotters. The analytical solution used in the photogrammetric plotter for positioning was applied to bundles of 30-40 adjacent, overlapping aerial photographs. The stereo positioning of the photography was < 1 m. Digital data for bundles of compiled aerial photographs from the photogrammetric stereo plotter was imported into the ESRI ArcInfo GIS. The GIS was used to merge and edit the vector and attribute features of the 15 bundles to generate a mosaic benthic habitat map of the Florida Keys and adjacent areas covered by the aerial photography. Field validation of digitized habitat features visible in the aerial photography mosaics was performed to ensure correct interpretation. An assessment of the correctness of the interpreted digital map was performed by experts familiar with the the seafloor habitat found in the Florida Keys. proprietary
gov.noaa.nodc:0145165_Not Applicable California sea lion and northern fur seal censuses conducted at Channel Islands, California by Alaska Fisheries Science Center from 1969-07-31 to 2015-08-08 (NCEI Accession 0145165) NOAA_NCEI STAC Catalog 1969-07-31 2015-08-08 -120.5, 33, -119, 34.11 https://cmr.earthdata.nasa.gov/search/concepts/C2089377845-NOAA_NCEI.umm_json The National Marine Mammal Laboratories' California Current Ecosystem Program (AFSC/NOAA) initiated and maintains census programs for California sea lions (Zalophus californianus) and northern fur seals (Callorhinus ursinus) at San Miguel and San Nicolas Islands, California. The program documents annual pup births, pup mortality, and temporal patterns in adult and juvenile presence at San Miguel Island. For both species, the database contains field data on the annual number of live pups and dead pups by location. At San Miguel Island, daily counts of adults, pups, and juveniles in a sample area are also available. The data are used to describe population trends and changes in land resource use among the species. proprietary
gov.noaa.nodc:0146259_Not Applicable Capture and resight data of California sea lions in Washington State, 1989-02-15 to 2006-06-01 (NCEI Accession 0146259) NOAA_NCEI STAC Catalog 1989-02-15 2006-06-01 -132, 32, -122, 54.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089378578-NOAA_NCEI.umm_json This dataset contains data from the capture and recapture of over 1500 male California sea lions (Zalophus californianus) from Washington between 1989-2006. The data fields include capture data such as time, location, weight, length, and girth for each animal captured. The dataset also includes records of resights of each animal from records collected from observers from California to Vancouver Island, British Columbia, Canada. The dataset also contains information from opportunistic captures of Steller sea lions (Eumetopias jubatus) in the same region. proprietary
gov.noaa.nodc:0146680_Not Applicable Benthic Surveys in Vatia, American Samoa: benthic images collected during belt transect surveys from 2015-11-2 to 2015-11-12 (NCEI Accession 0146680) NOAA_NCEI STAC Catalog 2015-11-02 2015-11-12 -170.674, -14.2501, -170.667, -14.2432 https://cmr.earthdata.nasa.gov/search/concepts/C2089378606-NOAA_NCEI.umm_json Jurisdictional managers have expressed concerns that nutrients from the village of Vatia, Tutuila, American Samoa, are having an adverse effect on the coral reef ecosystem in Vatia Bay. Excess nutrient loads promote increases in algal growth that can have deleterious effects on corals, such as benthic algae outcompeting and overgrowing corals. Nitrogen and phosphorus can also directly impact corals by lowering fertilization success, and reducing both photosynthesis and calcification rates. Land-based contributions of nutrients come from a variety of sources; in Vatia the most likely sources are poor wastewater management from piggeries and septic systems. NOAA scientists conducted benthic surveys to establish a baseline against which to compare changes in the algal and coral assemblages in response to nutrient fluxes. The data described here were collected via belt transect surveys of coral demography (adult and juvenile corals) by the NOAA Coral Reef Ecosystem Program (CREP) according to protocols established by the NOAA National Coral Reef Monitoring Program (NCRMP). In 2015 data were collected at 18 stratified randomly selected sites in Vatia Bay. These data include photoquadrat benthic images. proprietary
gov.noaa.nodc:0146682_Not Applicable Benthic Surveys in Faga'alu, American Samoa: benthic images collected during belt transect surveys in 2012 and 2015 (NCEI Accession 0146682) NOAA_NCEI STAC Catalog 2012-03-28 2015-11-11 -170.681, -14.2952, -170.673, -14.287 https://cmr.earthdata.nasa.gov/search/concepts/C2089378626-NOAA_NCEI.umm_json The data described herein are part of a NOAA Coral Reef Conservation Program (CRCP) funded project aimed at establishing baseline data for coral demographics and benthic cover and composition via Rapid Ecological Assessment (REA) surveys conducted by the NOAA Coral Reef Ecosystem Program (CREP) at Faga'alu Bay, Tutuila, American Samoa between 2012 and 2015. Photoquadrat benthic images were collected in 2012 and 2015 only, via belt transect surveys of coral demography according to protocols established by CREP in 2012 and by the NOAA National Coral Reef Monitoring Program (NCRMP) in 2015. proprietary
gov.noaa.nodc:0147683_Not Applicable Bottom longline analytical data collected in Gulf of Mexico from 1995-01-01 to 2013-12-30 (NCEI Accession 0147683) NOAA_NCEI STAC Catalog 1995-01-01 2013-12-30 -97.3473, 24.3627, -81.5875, 30.3677 https://cmr.earthdata.nasa.gov/search/concepts/C2089378649-NOAA_NCEI.umm_json NOAA NMFS does not approve, recommend, or endorse any proprietary product or proprietary material mentioned in this publication. No reference shall be made to NMFS, or to this publication furnished by NMFS, in any advertising or sales promotion which would indicate or imply that NMFS approves, recommends, or endorses any proprietary product or proprietary material mentioned herein or which has as its purpose any intent to cause directly or indirectly the advertised product to be used or purchased because of this NMFS publication. NMFS is not responsible for any uses of these datasets beyond those for which they were intended, and NMFS makes no claims regarding the accuracy of any data provided by agencies or individuals outside NMFS. Acknowledgment of NOAA NMFS and SEAMAP would be appreciated in products derived or publications generated from this data. proprietary
-gov.noaa.nodc:0148759_Not Applicable AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Helheim Glacier Ice Front from 2009-08-11 to 2016-02-20 (NCEI Accession 0148759) ALL STAC Catalog 2009-08-11 2016-02-20 -38.146, 66.329, -38.146, 66.329 https://cmr.earthdata.nasa.gov/search/concepts/C2089378741-NOAA_NCEI.umm_json The Helheim Glacier was observed to retreat and speed up during the mid 2000s. One possible cause of the change in glacier behavior could be due to changes in atmosphere properties, temperature, humidity, and wind. A research program was established to monitor the atmosphere conditions near the glacier during 2009-2013. proprietary
gov.noaa.nodc:0148759_Not Applicable AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Helheim Glacier Ice Front from 2009-08-11 to 2016-02-20 (NCEI Accession 0148759) NOAA_NCEI STAC Catalog 2009-08-11 2016-02-20 -38.146, 66.329, -38.146, 66.329 https://cmr.earthdata.nasa.gov/search/concepts/C2089378741-NOAA_NCEI.umm_json The Helheim Glacier was observed to retreat and speed up during the mid 2000s. One possible cause of the change in glacier behavior could be due to changes in atmosphere properties, temperature, humidity, and wind. A research program was established to monitor the atmosphere conditions near the glacier during 2009-2013. proprietary
+gov.noaa.nodc:0148759_Not Applicable AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Helheim Glacier Ice Front from 2009-08-11 to 2016-02-20 (NCEI Accession 0148759) ALL STAC Catalog 2009-08-11 2016-02-20 -38.146, 66.329, -38.146, 66.329 https://cmr.earthdata.nasa.gov/search/concepts/C2089378741-NOAA_NCEI.umm_json The Helheim Glacier was observed to retreat and speed up during the mid 2000s. One possible cause of the change in glacier behavior could be due to changes in atmosphere properties, temperature, humidity, and wind. A research program was established to monitor the atmosphere conditions near the glacier during 2009-2013. proprietary
gov.noaa.nodc:0148760_Not Applicable AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Jakobshavn Glacier Ice Front from 2007-10-13 to 2016-02-14 (NCEI Accession 0148760) ALL STAC Catalog 2007-10-13 2016-02-14 -49.815, 69.222, -49.815, 69.222 https://cmr.earthdata.nasa.gov/search/concepts/C2089378750-NOAA_NCEI.umm_json The Jakobshavn Glacier was observed to retreat and speed up during the late 1990s and early 2000s. One possible cause of the change in glacier behavior could be due to changes in atmosphere properties, temperature, humidity, and wind. A research program was established to monitor the atmosphere conditions near the glacier during 2009-2013. proprietary
gov.noaa.nodc:0148760_Not Applicable AIR TEMPERATURE, RELATIVE HUMIDITY, and others collected from Automatic Weather Station installed on rock outcrop in Jakobshavn Glacier Ice Front from 2007-10-13 to 2016-02-14 (NCEI Accession 0148760) NOAA_NCEI STAC Catalog 2007-10-13 2016-02-14 -49.815, 69.222, -49.815, 69.222 https://cmr.earthdata.nasa.gov/search/concepts/C2089378750-NOAA_NCEI.umm_json The Jakobshavn Glacier was observed to retreat and speed up during the late 1990s and early 2000s. One possible cause of the change in glacier behavior could be due to changes in atmosphere properties, temperature, humidity, and wind. A research program was established to monitor the atmosphere conditions near the glacier during 2009-2013. proprietary
gov.noaa.nodc:0155488_Not Applicable Bottom Dissolved Oxygen Maps From SEAMAP Summer and Fall Groundfish/Shrimp Surveys from 1982 to 1998 (NCEI Accession 0155488) NOAA_NCEI STAC Catalog 1982-01-01 1998-01-01 -98, 18, -74, 37 https://cmr.earthdata.nasa.gov/search/concepts/C2089380245-NOAA_NCEI.umm_json Bottom dissolved oxygen (DO) data was extracted from environmental profiles acquired during the Southeast Fisheries Science Center Mississippi Laboratories summer groundfish trawl surveys of the Western and North-central Gulf of Mexico from 1982-1998. The data were distributed to hypoxia researchers in near real time and used to generate bottom DO maps as part of the Hypoxia Watch Project (http://www.ncddc.noaa.gov/hypoxia/). The profiles were acquired with a Sea-Bird Model SB9 profiler equipped with pressure, temperature, conductivity, fluorescence, and beam transmission sensors. The data were processed with Sea-Bird software using the standard processing protocol developed by the Mississippi Laboratories. Water temperature, beam transmission, and derived salinity, DO and DO percent saturation, and density were retained in the processed files. SAS software was used to extract the bottom DO and other relevant data (e.g., date, time, position, and station number) and format the data as comma-delimited ASCII files. proprietary
gov.noaa.nodc:0155948_Not Applicable CHLOROPHYLL A CONCENTRATION collected from NOAA Ship OSCAR ELTON SETTE in Hawaii EEZ and Palmyra EEZ from 2011-10-20 to 2011-11-17 (NCEI Accession 0155948) NOAA_NCEI STAC Catalog 2011-10-20 2011-11-17 -165.19666, 4.1355, -156.3175, 21.221 https://cmr.earthdata.nasa.gov/search/concepts/C2089376252-NOAA_NCEI.umm_json Water samples were collected from the ocean surface using a bucket and from below the surface using bottles attached to the CTD during a Pacific Islands Fisheries Science Center's Cetacean Research Program's shipboard cetacean survey (Cruise ID: SE 11-08). A minimum of three surface water samples were taken each day, primarily at 0900, 1200, and 1500 hours local ship time. Surface water samples were also collected opportunistically during some cetacean sightings. CTD samples were collected once each morning. The 250ml water samples were filtered onto GF/F filters, placed in 10ml of 90% acetone, refrigerated or frozen for 24 hours, and then analyzed for chlorophyll a concentration using the Turner Designs model 10AU field flourometer. Measurements were recorded in an Excel spreadsheet. proprietary
gov.noaa.nodc:0155964_Not Applicable CHLOROPHYLL A CONCENTRATION collected from NOAA Ship OSCAR ELTON SETTE in Hawaii EEZ and Papahanaumokuakea Marine National Monument from 2013-05-08 to 2013-06-03 (NCEI Accession 0155964) NOAA_NCEI STAC Catalog 2013-05-08 2013-06-03 -177, -14.2446, -157.92, 28.79 https://cmr.earthdata.nasa.gov/search/concepts/C2089376312-NOAA_NCEI.umm_json Water samples were collected from the ocean surface using a bucket and from below the surface using bottles attached to the CTD during a Pacific Islands Fisheries Science Center's Cetacean Research Program's shipboard cetacean survey (Cruise ID SE 13-03). A minimum of three surface water samples were taken each day, primarily at 0900, 1200, and 1500 hours local ship time. Surface water samples were also collected opportunistically during some cetacean sightings. CTD samples were collected once each morning. The 250ml water samples were filtered onto GF/F filters, placed in 10ml of 90% acetone, refrigerated or frozen for 24 hours, and then analyzed for chlorophyll a concentration using the Turner Designs model 10AU field flourometer. Measurements were recorded in an Excel spreadsheet. proprietary
gov.noaa.nodc:0155998_Not Applicable CHLOROPHYLL A CONCENTRATION collected from NOAA Ship OSCAR ELTON SETTE in Hawaii EEZ, Palmyra EEZ, and American Samoa EEZ from 2012-04-23 to 2012-05-15 (NCEI Accession 0155998) NOAA_NCEI STAC Catalog 2012-04-23 2012-05-15 -169.9633, -14.2446, -157.2218, 19.2698 https://cmr.earthdata.nasa.gov/search/concepts/C2089376410-NOAA_NCEI.umm_json Surface water samples were collected during a Pacific Islands Fisheries Science Center's Cetacean Research Program's shipboard cetacean survey (Cruise ID SE 12-03). A minimum of three surface water samples were taken each day, primarily at 0900, 1200, and 1500 hours local ship time. Samples were also collected opportunistically during some cetacean sightings. The 250ml water samples were filtered onto GF/F filters, placed in 10ml of 90% acetone, refrigerated or frozen for 24 hours, and then analyzed for chlorophyll a concentration using the Turner Designs model 10AU field flourometer. Measurements were recorded in an Excel spreadsheet. proprietary
-gov.noaa.nodc:0156424_Not Applicable Absolute Geostrophic Velocity Inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156424) NOAA_NCEI STAC Catalog 1950-01-01 1996-12-31 -180, 58, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089376812-NOAA_NCEI.umm_json The dataset (called EWG-V) comprises 3D gridded climatological fields of absolute geostrophic velocity inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean using the P-vector method. It provides a climatological velocity field that is dynamically compatible to the EWG (T, S) fields. The EWG-V velocity fields have the annual, and seasonal (winter and summer) means with the same horizontal resolution of 25 km and 90 vertical levels as the EWG temperature and salinity fields. proprietary
gov.noaa.nodc:0156424_Not Applicable Absolute Geostrophic Velocity Inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156424) ALL STAC Catalog 1950-01-01 1996-12-31 -180, 58, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089376812-NOAA_NCEI.umm_json The dataset (called EWG-V) comprises 3D gridded climatological fields of absolute geostrophic velocity inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean using the P-vector method. It provides a climatological velocity field that is dynamically compatible to the EWG (T, S) fields. The EWG-V velocity fields have the annual, and seasonal (winter and summer) means with the same horizontal resolution of 25 km and 90 vertical levels as the EWG temperature and salinity fields. proprietary
+gov.noaa.nodc:0156424_Not Applicable Absolute Geostrophic Velocity Inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156424) NOAA_NCEI STAC Catalog 1950-01-01 1996-12-31 -180, 58, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089376812-NOAA_NCEI.umm_json The dataset (called EWG-V) comprises 3D gridded climatological fields of absolute geostrophic velocity inverted from the Environmental Working Group (EWG) Joint U.S.-Russian Atlas of the Arctic Ocean using the P-vector method. It provides a climatological velocity field that is dynamically compatible to the EWG (T, S) fields. The EWG-V velocity fields have the annual, and seasonal (winter and summer) means with the same horizontal resolution of 25 km and 90 vertical levels as the EWG temperature and salinity fields. proprietary
gov.noaa.nodc:0156425_Not Applicable Absolute Geostrophic Velocity Inverted from the Polar Science Center Hydrographic Climatology (PHC3.0) of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156425) ALL STAC Catalog 1900-01-01 1998-12-31 -180, 45, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089376820-NOAA_NCEI.umm_json The dataset (called PHC-V) comprises 3D gridded climatological fields of absolute geostrophic velocity of the Arctic Ocean inverted from the Polar science center Hydrographic Climatology (PHC) temperature and salinity fields (version 3.0) using the P-vector method. It provides climatological annual, seasonal, and monthly mean velocity fields with the same horizontal resolution (1 deg in horizontal, 33 levels in vertical), and dynamical compatibility to the PHC3.0 (T, S) fields. proprietary
gov.noaa.nodc:0156425_Not Applicable Absolute Geostrophic Velocity Inverted from the Polar Science Center Hydrographic Climatology (PHC3.0) of the Arctic Ocean with the P-Vector Method (NCEI Accession 0156425) NOAA_NCEI STAC Catalog 1900-01-01 1998-12-31 -180, 45, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089376820-NOAA_NCEI.umm_json The dataset (called PHC-V) comprises 3D gridded climatological fields of absolute geostrophic velocity of the Arctic Ocean inverted from the Polar science center Hydrographic Climatology (PHC) temperature and salinity fields (version 3.0) using the P-vector method. It provides climatological annual, seasonal, and monthly mean velocity fields with the same horizontal resolution (1 deg in horizontal, 33 levels in vertical), and dynamical compatibility to the PHC3.0 (T, S) fields. proprietary
gov.noaa.nodc:0156692_Not Applicable Bioerosion Accretion Replicate (BAR) data covering in situ calcification and bioerosion rates along pH gradients at two volcanically acidified reefs in Papua New Guinea from 2013-01-18 to 2014-11-10 (NCEI Accession 0156692) NOAA_NCEI STAC Catalog 2013-01-18 2014-11-10 150.775, -9.875, 150.925, -9.725 https://cmr.earthdata.nasa.gov/search/concepts/C2089377345-NOAA_NCEI.umm_json "Bioerosion Accretion Replicate (BAR) data covering in situ calcification and bioerosion rates along pH gradients at two volcanically acidified reefs in Papua New Guinea. Methodologies, results, and analysis may be found in ""Enhanced macroboring and depressed calcification drive net dissolution at high-CO2 coral reef"" which is published in the Proceedings of the Royal Society, Series B" proprietary
@@ -18708,8 +18709,8 @@ gov.noaa.nodc:0156869_Not Applicable Captive sea turtle rearing inventory, feedi
gov.noaa.nodc:0156913_Not Applicable Carbonate Budget data of the Southeast Florida Coral Reef Initiative (SEFCRI) region from 2014-09-29 to 2014-10-17 (NCEI Accession 0156913) NOAA_NCEI STAC Catalog 2014-09-29 2014-10-17 -80.104, 25.6519, -80.077, 26.1636 https://cmr.earthdata.nasa.gov/search/concepts/C2089377484-NOAA_NCEI.umm_json This data set includes census based carbonate budget data that was collected in coral reef habitats located within the SEFCRI region. Surveys (based on Perry et al 2012) were collected over the course of several weeks at four major sites: Emerald, Oakland Ridge, Barracuda, and Pillars. Within each of these sites, six transect surveys (10m each) were conducted to quantify benthic cover, macrobioerosion, and microbioerosion. Ten parrotfish surveys were also conducted to account for parrotfish erosion rates at each site. This carbonate budget data along with other sea water chemistry data collected were used to inform the overall project looking at the sensitivity of the SEFCRI region to OA. We measured ambient seasonal variability across inshore/offshore reef habitats to predict the response of the CaCO3 budget of coral reefs in the SEFCRI region to ocean acidification. This data set includes all of the carbonate budget surveys that were collected to identify the sensitivity of the SEFCRI region to OA. proprietary
gov.noaa.nodc:0157022_Not Applicable Carbonate data collected from R/V Hildebrand in the SEFCRI region of the Florida Reef Tract from 2014-05-27 to 2015-09-02 (NCEI Accession 0157022) NOAA_NCEI STAC Catalog 2014-05-27 2015-09-02 -80.1328, 25.5906, -80.077, 26.1636 https://cmr.earthdata.nasa.gov/search/concepts/C2089377840-NOAA_NCEI.umm_json This data set includes seawater chemistry that was collected in coral reef habitats located within the SEFCRI region as well as inlets and outfalls that release nutrient rich and/or sediment laden freshwater to the coastal waters South Florida. Freshwater runoff and riverine inputs are known to be enriched in dissolved inorganic carbon, and diluted lower saline waters are known to have elevated pCO2 (e.g., Manzello et al. 2013) which is why those areas in addition to the reef sites were included in our analyses. This data along with other data collected in the field were used to inform the overall project looking at the sensitivity of the SEFCRI region to OA. We measured ambient seasonal variability across inshore/offshore reef habitats to predict the response of the CaCO3 budget of coral reefs in the SEFCRI region to ocean acidification. This data set includes all of the seawater samples that were collected and analyzed to identify the carbonate chemistry in this region. proprietary
gov.noaa.nodc:0157033_Not Applicable Atlantic Ocean Red Snapper Multi-gear CRP Project 2012 (NCEI Accession 0157033) NOAA_NCEI STAC Catalog 2012-07-25 2012-12-04 -81, 31, -76.5, 34 https://cmr.earthdata.nasa.gov/search/concepts/C2089377889-NOAA_NCEI.umm_json This data set contains information useful for red snapper stock assessment. The data set provided has count, weight, length, and location available of caught red snapper, red grouper, and other reef fishes. Catches were greatest in waters off Georgia, and declined with increasing latitude off South Carolina and North Carolina. proprietary
-gov.noaa.nodc:0157074_Not Applicable ACOUSTIC TRAVEL TIME collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) from March 1995 to March 1997 (NCEI Accession 0157074) ALL STAC Catalog 1995-03-20 1997-03-28 143.63333, -52.08133, 143.805, -47.99867 https://cmr.earthdata.nasa.gov/search/concepts/C2089378023-NOAA_NCEI.umm_json Inverted echo sounder (IES) data were collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) during March 1995 -- March 1997 conducted south of Australia. The collection, processing and calibration of the IES data are described in the report provided. These are the highest quality versions of the data after the least amount of processing. Also provided are low-passed filtered versions that have been calibrated to a common pressure level in order that the data may be used together more conveniently. The measurements were made under the support of the National Science Foundation grants OCE9204041 and OCE9912320. proprietary
gov.noaa.nodc:0157074_Not Applicable ACOUSTIC TRAVEL TIME collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) from March 1995 to March 1997 (NCEI Accession 0157074) NOAA_NCEI STAC Catalog 1995-03-20 1997-03-28 143.63333, -52.08133, 143.805, -47.99867 https://cmr.earthdata.nasa.gov/search/concepts/C2089378023-NOAA_NCEI.umm_json Inverted echo sounder (IES) data were collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) during March 1995 -- March 1997 conducted south of Australia. The collection, processing and calibration of the IES data are described in the report provided. These are the highest quality versions of the data after the least amount of processing. Also provided are low-passed filtered versions that have been calibrated to a common pressure level in order that the data may be used together more conveniently. The measurements were made under the support of the National Science Foundation grants OCE9204041 and OCE9912320. proprietary
+gov.noaa.nodc:0157074_Not Applicable ACOUSTIC TRAVEL TIME collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) from March 1995 to March 1997 (NCEI Accession 0157074) ALL STAC Catalog 1995-03-20 1997-03-28 143.63333, -52.08133, 143.805, -47.99867 https://cmr.earthdata.nasa.gov/search/concepts/C2089378023-NOAA_NCEI.umm_json Inverted echo sounder (IES) data were collected as part of the Sub-Antarctic Flux and Dynamics Experiment (SAFDE) during March 1995 -- March 1997 conducted south of Australia. The collection, processing and calibration of the IES data are described in the report provided. These are the highest quality versions of the data after the least amount of processing. Also provided are low-passed filtered versions that have been calibrated to a common pressure level in order that the data may be used together more conveniently. The measurements were made under the support of the National Science Foundation grants OCE9204041 and OCE9912320. proprietary
gov.noaa.nodc:0157087_Not Applicable Behavior of parrotfishes (Labridae, Scarinae) in St. Croix from 2015-07-06 to 2015-07-26 (NCEI Accession 0157087) NOAA_NCEI STAC Catalog 2015-07-06 2015-07-26 -64.813, 17.759, -64.608, 17.787 https://cmr.earthdata.nasa.gov/search/concepts/C2089378063-NOAA_NCEI.umm_json To better understand the functional roles of parrotfishes on coral reefs in the Caribbean this project documented the foraging behavior and diets of six species of parrotfishes (Scarus taeniopterus, Scarus vetula, Sparisoma aurofrenatum, Sparisoma chrysopterum, Sparisoma rubripinne, Sparisoma viride) at three locations (Long Reef, Cane Bay, and Buck Island) on the north shore of St. Croix, U. S. Virgin Islands. To quantify parrotfish behavior, approximately six individuals of each species were observed at each site for 20 min each. Foraging behavior was recorded by a SCUBA diver while towing a GPS receiver (Garmin GPS 72) attached to a surface float, which obtained position fixes of the focal fish at 15 s intervals. Fish were followed from a close distance (~ 2 m when possible), and food items were identified to the lowest taxonomic level possible, with macroalgae and coral usually identified to genus or species. Many bites involved scraping or excavating substrate colonized by a multi-species assemblage of filamentous âturfâ algae and crustose coralline algae (CCA). Thus, multiple species of filamentous algae, endolithic algae, and CCA could be harvested in a single bite, and it was impossible to determine the specific species of algae targeted. We also recorded the type of substrate targeted during each foraging bout, categorizing each substrate as one of the following: (1) dead coral, (2) coral pavement, (3) boulder, (4) rubble, (5) ledge, or (6) sand. In order to quantify the relative abundance of different substrates and food types, we estimated the percent cover of algae, coral, and other sessile invertebrates on each of the six substrates commonly targeted by parrotfishes (dead coral, coral pavement, boulder, rubble, ledge, and sand) in 0.5 m x 0.5 m photoquadrats. Photographs were taken at 2.5 m intervals on 30 m transects, with a total of 10 haphazardly placed transects sampled at each site. Each photoquadrat was divided into sixteen 12 cm x 12 cm sections which were individually photographed, and percent cover was estimated from 9 stratified random points per section (N = 144 point per quadrat). proprietary
gov.noaa.nodc:0157611_Not Applicable Benthic Images from Towed-Diver Surveys in the Main Hawaiian Islands to Assess the Mass Coral Bleaching Event from 2015-11-03 to 2015-11-18 (NCEI Accession 0157611) NOAA_NCEI STAC Catalog 2015-11-03 2015-11-18 -157.9472292, 19.748537, -155.829342, 21.3030689 https://cmr.earthdata.nasa.gov/search/concepts/C2089376905-NOAA_NCEI.umm_json A team from the Pacific Islands Fisheries Science Center (PIFSC), Coral Reef Ecosystem Program (CREP) deployed on a two-week research cruise in November 2015 to evaluate the impacts of the 2015 mass coral bleaching event in the Main Hawaiian Islands via towed-diver surveys. Areas surveyed included south Oahu, west Maui, Lanaâi, and west Hawaii island. Over the course of 10 survey days, the team surveyed approximately 90 km of 15-m wide transects at depths ranging from 2 to 10 m. Data provided in this dataset include benthic images that were collected during the towed-diver surveys from a camera that was mounted to the towboard. A downward-facing DSLR camera with strobes collected these photographic quadrat data by capturing an image of the benthos at 15-second intervals during the surveys. Two additional datasets were collected during the surveys and are documented separately. Towed divers recorded visual estimates of percentage of live coral that was pale and bleached, as well as presence/absence data of condition by generic composition. Oceanographic data was collected continuously throughout each survey with a suite of sensors mounted to the towboard recording conductivity, temperature, depth, flourometry (chlorophyll-a), turbidity and dissolved oxygen. proprietary
gov.noaa.nodc:0159386_Not Applicable Airborne eXpendable BathyThermographs (AXBT) data from Ocean Surveys in the Gulf of Mexico during Hurricane Lili 2002-10-02 to 2002-10-04 (NCEI Accession 0159386) NOAA_NCEI STAC Catalog 2002-10-02 2002-10-04 -88.672, 22.203, -84.062, 26.433 https://cmr.earthdata.nasa.gov/search/concepts/C2089377618-NOAA_NCEI.umm_json Airborne eXpendable BathyThermographs (AXBT) data from deployments during field operations to study Hurricane Lili. The data were used in model simulations for Uhlhorn and Shay (2013). This dataset contains water temperature and depth data for this cruise. proprietary
@@ -18717,8 +18718,8 @@ gov.noaa.nodc:0159386_Not Applicable Airborne eXpendable BathyThermographs (AXBT
gov.noaa.nodc:0159419_Not Applicable ADCP, CTD, MIDAS, and cruise track data collected from R/V Pelican in Galveston and Trinity Bay, Texas and the Gulf of Mexico from 2013-10-17 to 2013-10-20 (NCEI Accession 0159419) ALL STAC Catalog 2013-10-17 2013-10-20 -94.9828, 26.16133, -88, 29.69641 https://cmr.earthdata.nasa.gov/search/concepts/C2089377667-NOAA_NCEI.umm_json Sampling of in situ seawater, macroalgae, macrocrustaceans and associated fauna (cruise GoMRI-II, October 17-20 2013, stns 1-18, data available for all) aboard the R/V Pelican cruise id PE14-10b was targeted to repeat sampling of previously studied hard banks and adjacent deep waters west of the mouth of the Mississippi River and extending east to offshore Alabama, an area encompassing roughly 27°58'N to 29°26'N and 87°34'W to 91°01'W. Submitted metadata are ADCP, CTD, Marks and Cruise Track Data. proprietary
gov.noaa.nodc:0159419_Not Applicable ADCP, CTD, MIDAS, and cruise track data collected from R/V Pelican in Galveston and Trinity Bay, Texas and the Gulf of Mexico from 2013-10-17 to 2013-10-20 (NCEI Accession 0159419) NOAA_NCEI STAC Catalog 2013-10-17 2013-10-20 -94.9828, 26.16133, -88, 29.69641 https://cmr.earthdata.nasa.gov/search/concepts/C2089377667-NOAA_NCEI.umm_json Sampling of in situ seawater, macroalgae, macrocrustaceans and associated fauna (cruise GoMRI-II, October 17-20 2013, stns 1-18, data available for all) aboard the R/V Pelican cruise id PE14-10b was targeted to repeat sampling of previously studied hard banks and adjacent deep waters west of the mouth of the Mississippi River and extending east to offshore Alabama, an area encompassing roughly 27°58'N to 29°26'N and 87°34'W to 91°01'W. Submitted metadata are ADCP, CTD, Marks and Cruise Track Data. proprietary
gov.noaa.nodc:0159850_Not Applicable Burrowing behavior of penaeid shrimps in the Gulf of Mexico from 1984-10-01 to 1985-12-06 (NCEI Accession 0159850) NOAA_NCEI STAC Catalog 1984-10-01 1985-12-06 -94.815127, 29.275417, -94.815127, 29.275417 https://cmr.earthdata.nasa.gov/search/concepts/C2089377792-NOAA_NCEI.umm_json This data set contains hourly visual observations of burrowing behavior in penaeid shrimp. proprietary
-gov.noaa.nodc:0161311_Not Applicable A Comprehensive Inventory of Alabama Coastal Zone Wetland Habitats (Swamps, Marshes, Submersed Grassbeds) from 1980 to 1982 (NCEI Accession 0161311) ALL STAC Catalog 1979-01-01 1982-12-31 -88.431, 30.2129, -87.328, 31.0701 https://cmr.earthdata.nasa.gov/search/concepts/C2089378452-NOAA_NCEI.umm_json Digitized maps of Mobile Bay and other coastal areas of Alabama, showing habitat types and species compositions of the vegetation in three broad categories of wetland: swamps, marshes, and submersed grassbeds. All areas in the Alabama Coastal Zone of less than 10 feet elevation above sea level, up to the fork of the Tombigbee and Alabama Rivers, were included in the inventory. Habitat boundary delineations were based on aerial photographs from 1979 and 1980, with transects by boat or foot for field verification in 1980-1982. Dataset includes habitat type classifications based on species compositions, and identifications of dominant species at each location. proprietary
gov.noaa.nodc:0161311_Not Applicable A Comprehensive Inventory of Alabama Coastal Zone Wetland Habitats (Swamps, Marshes, Submersed Grassbeds) from 1980 to 1982 (NCEI Accession 0161311) NOAA_NCEI STAC Catalog 1979-01-01 1982-12-31 -88.431, 30.2129, -87.328, 31.0701 https://cmr.earthdata.nasa.gov/search/concepts/C2089378452-NOAA_NCEI.umm_json Digitized maps of Mobile Bay and other coastal areas of Alabama, showing habitat types and species compositions of the vegetation in three broad categories of wetland: swamps, marshes, and submersed grassbeds. All areas in the Alabama Coastal Zone of less than 10 feet elevation above sea level, up to the fork of the Tombigbee and Alabama Rivers, were included in the inventory. Habitat boundary delineations were based on aerial photographs from 1979 and 1980, with transects by boat or foot for field verification in 1980-1982. Dataset includes habitat type classifications based on species compositions, and identifications of dominant species at each location. proprietary
+gov.noaa.nodc:0161311_Not Applicable A Comprehensive Inventory of Alabama Coastal Zone Wetland Habitats (Swamps, Marshes, Submersed Grassbeds) from 1980 to 1982 (NCEI Accession 0161311) ALL STAC Catalog 1979-01-01 1982-12-31 -88.431, 30.2129, -87.328, 31.0701 https://cmr.earthdata.nasa.gov/search/concepts/C2089378452-NOAA_NCEI.umm_json Digitized maps of Mobile Bay and other coastal areas of Alabama, showing habitat types and species compositions of the vegetation in three broad categories of wetland: swamps, marshes, and submersed grassbeds. All areas in the Alabama Coastal Zone of less than 10 feet elevation above sea level, up to the fork of the Tombigbee and Alabama Rivers, were included in the inventory. Habitat boundary delineations were based on aerial photographs from 1979 and 1980, with transects by boat or foot for field verification in 1980-1982. Dataset includes habitat type classifications based on species compositions, and identifications of dominant species at each location. proprietary
gov.noaa.nodc:0161523_Not Applicable Biological, chemical, physical and time series data collected from station WQB04 by University of Hawai'i at Hilo and assembled by Pacific Islands Ocean Observing System (PacIOOS) in the North Pacific Ocean from 2010-10-23 to 2016-12-31 (NCEI Accession 0161523) NOAA_NCEI STAC Catalog 2010-10-23 2016-12-31 -155.082, 19.7341, -155.082, 19.7341 https://cmr.earthdata.nasa.gov/search/concepts/C2089378474-NOAA_NCEI.umm_json NCEI Accession 0161523 contains biological, chemical, physical and time series data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). University of Hawai'i at Hilo collected the data from their in-situ moored station named WQB04: PacIOOS Water Quality Buoy 04 (WQB-04): Hilo Bay, Big Island, Hawaii, in the North Pacific Ocean. PacIOOS, which assembles data from University of Hawai'i at Hilo and other sub-regional coastal and ocean observing systems of the U. S. Pacific Islands, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. Each month, NCEI adds to the accession the data collected during the previous month. The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points. WQB04 is located in Hilo Bay on the east side of the Big Island. Continuous sampling of this area provides a record of baseline conditions of the chemical and biological environment for comparison when there are pollution events such as storm runoff or a sewage spill. proprietary
gov.noaa.nodc:0162518_Not Applicable ADCP, CTD, and MIDAS data collected from Ewing and Sackett Gulf Deep Banks, Gulf of Mexico on the R/V Pelican in Gulf of Mexico from 2012-11-15 to 2012-11-17 (NCEI Accession 0162518) ALL STAC Catalog 2012-11-15 2012-11-17 -91.20748, 27.49168, -89, 29.0029 https://cmr.earthdata.nasa.gov/search/concepts/C2089380274-NOAA_NCEI.umm_json Sampling of in situ seawater, macroalgae, macrocrustaceans and associated fauna (cruise GoMRI-II, November 15-17 2012, stns 1-18, data available for all) aboard the R/V Pelican cruise id PE13-14 was targeted to repeat sampling of previously studied hard banks and adjacent deep waters west of the mouth of the Mississippi River and extending east to offshore Alabama, an area encompassing roughly 27°58'N to 29°26'N and 87°34'W to 91°01'W. Submitted metadata are ADCP, CTD, Marks and Cruise Track Data. proprietary
gov.noaa.nodc:0162518_Not Applicable ADCP, CTD, and MIDAS data collected from Ewing and Sackett Gulf Deep Banks, Gulf of Mexico on the R/V Pelican in Gulf of Mexico from 2012-11-15 to 2012-11-17 (NCEI Accession 0162518) NOAA_NCEI STAC Catalog 2012-11-15 2012-11-17 -91.20748, 27.49168, -89, 29.0029 https://cmr.earthdata.nasa.gov/search/concepts/C2089380274-NOAA_NCEI.umm_json Sampling of in situ seawater, macroalgae, macrocrustaceans and associated fauna (cruise GoMRI-II, November 15-17 2012, stns 1-18, data available for all) aboard the R/V Pelican cruise id PE13-14 was targeted to repeat sampling of previously studied hard banks and adjacent deep waters west of the mouth of the Mississippi River and extending east to offshore Alabama, an area encompassing roughly 27°58'N to 29°26'N and 87°34'W to 91°01'W. Submitted metadata are ADCP, CTD, Marks and Cruise Track Data. proprietary
@@ -18769,19 +18770,19 @@ gov.noaa.nodc:0171331_Not Applicable Biological, chemical and other data collect
gov.noaa.nodc:0171332_Not Applicable Biological, chemical and other data collected from station Indian River Lagoon - Jensen Beach (IRL-JB) by Florida Atlantic University and assembled by Southeast Coastal Ocean Observing Regional Association (SECOORA) in the Coastal Waters of Florida from 2015-10-07 to 2020-06-18 (NCEI Accession 0171332) NOAA_NCEI STAC Catalog 2015-10-07 2020-06-18 -80.20233, 27.22439, -80.20233, 27.22439 https://cmr.earthdata.nasa.gov/search/concepts/C2089377488-NOAA_NCEI.umm_json NCEI Accession 0171332 contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Florida Atlantic University collected the data from their in-situ moored station named Indian River Lagoon - Jensen Beach (IRL-JB) in the Coastal Waters of Florida. Southeast Coastal Ocean Observing Regional Association (SECOORA), which assembles data from Florida Atlantic University and other sub-regional coastal and ocean observing systems of the Southeast United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this accession when new files are available. proprietary
gov.noaa.nodc:0171345_Not Applicable Chemical, meteorological and other data collected from station Pilot's Cove, Apalachicola Bay, by Florida Department of Environmental Protection and assembled by Southeast Coastal Ocean Observing Regional Association (SECOORA) in the Coastal Waters of Florida and Gulf of Mexico from 2015-11-09 to 2020-03-09 (NCEI Accession 0171345) NOAA_NCEI STAC Catalog 2015-11-09 2020-03-09 -85.0277, 29.60139, -85.0277, 29.60139 https://cmr.earthdata.nasa.gov/search/concepts/C2089377631-NOAA_NCEI.umm_json NCEI Accession 0171345 contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Florida Department of Environmental Protection collected the data from their in-situ moored station named Pilot's Cove, Apalachicola Bay, in the Coastal Waters of Florida and Gulf of Mexico. Southeast Coastal Ocean Observing Regional Association (SECOORA), which assembles data from Florida Department of Environmental Protection and other sub-regional coastal and ocean observing systems of the Southeast United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this accession when new files are available. proprietary
gov.noaa.nodc:0171346_Not Applicable Chemical, meteorological and other data collected from station Dry Bar, Apalachicola Bay, by Florida Department of Environmental Protection and assembled by Southeast Coastal Ocean Observing Regional Association (SECOORA) in the Coastal Waters of Florida and Gulf of Mexico from 2015-12-01 to 2018-10-10 (NCEI Accession 0171346) NOAA_NCEI STAC Catalog 2015-12-01 2018-10-10 -85.05807, 29.67431, -85.05807, 29.67431 https://cmr.earthdata.nasa.gov/search/concepts/C2089377641-NOAA_NCEI.umm_json NCEI Accession 0171346 contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Florida Department of Environmental Protection collected the data from their in-situ moored station named Dry Bar, Apalachicola Bay, in the Coastal Waters of Florida and Gulf of Mexico. Southeast Coastal Ocean Observing Regional Association (SECOORA), which assembles data from Florida Department of Environmental Protection and other sub-regional coastal and ocean observing systems of the Southeast United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this accession when new files are available. proprietary
-gov.noaa.nodc:0172043_Not Applicable ADCP, CTD, and continuous data from the Multiple Instrument Data Acquisition System (MIDAS) collected in the Southeast of the Mississippi River Delta aboard the R/V Pelican from 2012-11-28 to 2012-12-19 (NCEI Accession 0172043) ALL STAC Catalog 2012-11-28 2012-12-19 -94.0863, 25.7961, -87.2228, 28.9733 https://cmr.earthdata.nasa.gov/search/concepts/C2089377986-NOAA_NCEI.umm_json This dataset contains shipboard Acoustic Doppler Current Profiles (ADCP) data from a 75khz profiler, vertical profiles of measurements made from a CTD/Rosette system and continuous data from the Multiple Instrument Data Acquisition System (MIDAS). These ancillary data gives additional information about the physical state of the ocean during the Gulf of Mexico Integrated Spill Response Consortium (GISR) G03 cruise aboard R/V Pelican held from November 28 to December 20, 2012. proprietary
gov.noaa.nodc:0172043_Not Applicable ADCP, CTD, and continuous data from the Multiple Instrument Data Acquisition System (MIDAS) collected in the Southeast of the Mississippi River Delta aboard the R/V Pelican from 2012-11-28 to 2012-12-19 (NCEI Accession 0172043) NOAA_NCEI STAC Catalog 2012-11-28 2012-12-19 -94.0863, 25.7961, -87.2228, 28.9733 https://cmr.earthdata.nasa.gov/search/concepts/C2089377986-NOAA_NCEI.umm_json This dataset contains shipboard Acoustic Doppler Current Profiles (ADCP) data from a 75khz profiler, vertical profiles of measurements made from a CTD/Rosette system and continuous data from the Multiple Instrument Data Acquisition System (MIDAS). These ancillary data gives additional information about the physical state of the ocean during the Gulf of Mexico Integrated Spill Response Consortium (GISR) G03 cruise aboard R/V Pelican held from November 28 to December 20, 2012. proprietary
-gov.noaa.nodc:0172377_Not Applicable Abundance and biomass of parrotfishes (Labridae, Scarinae) in St.Croix, U.S. Virgin Islands 2015 to 2016 (NCEI Accession 0172377) NOAA_NCEI STAC Catalog 2015-07-21 2016-08-05 -64.9199, 17.63764, -64.47889, 17.82709 https://cmr.earthdata.nasa.gov/search/concepts/C2089378141-NOAA_NCEI.umm_json We collected data on parrotfish abundance, biomass, size structure, and species composition at several sites on the N shore of St. Croix during July and August 2015 and 2016. Surveys were conducted using a method that allowed divers to rapidly survey large areas and quantify habitat assocations of different species. Researchers conducted 20-30 min timed swims towing a float with a GPS receiver, which allowed for the calculation of distance traveled during a swim and therefore the total area sampled. During the timed swim survey, the diver estimated and recorded the size to the nearest cm of all parrotfishes that were at least 10 cm in length that were encountered in a 5-m-wide swath. Because these swims often crossed multiple habitats, the diver recorded the habitat each minute. For each site, the total area of each habitat sampled was then calculated in order to determine habitat- and site-specific densities of each parrotfish species. proprietary
+gov.noaa.nodc:0172043_Not Applicable ADCP, CTD, and continuous data from the Multiple Instrument Data Acquisition System (MIDAS) collected in the Southeast of the Mississippi River Delta aboard the R/V Pelican from 2012-11-28 to 2012-12-19 (NCEI Accession 0172043) ALL STAC Catalog 2012-11-28 2012-12-19 -94.0863, 25.7961, -87.2228, 28.9733 https://cmr.earthdata.nasa.gov/search/concepts/C2089377986-NOAA_NCEI.umm_json This dataset contains shipboard Acoustic Doppler Current Profiles (ADCP) data from a 75khz profiler, vertical profiles of measurements made from a CTD/Rosette system and continuous data from the Multiple Instrument Data Acquisition System (MIDAS). These ancillary data gives additional information about the physical state of the ocean during the Gulf of Mexico Integrated Spill Response Consortium (GISR) G03 cruise aboard R/V Pelican held from November 28 to December 20, 2012. proprietary
gov.noaa.nodc:0172377_Not Applicable Abundance and biomass of parrotfishes (Labridae, Scarinae) in St.Croix, U.S. Virgin Islands 2015 to 2016 (NCEI Accession 0172377) ALL STAC Catalog 2015-07-21 2016-08-05 -64.9199, 17.63764, -64.47889, 17.82709 https://cmr.earthdata.nasa.gov/search/concepts/C2089378141-NOAA_NCEI.umm_json We collected data on parrotfish abundance, biomass, size structure, and species composition at several sites on the N shore of St. Croix during July and August 2015 and 2016. Surveys were conducted using a method that allowed divers to rapidly survey large areas and quantify habitat assocations of different species. Researchers conducted 20-30 min timed swims towing a float with a GPS receiver, which allowed for the calculation of distance traveled during a swim and therefore the total area sampled. During the timed swim survey, the diver estimated and recorded the size to the nearest cm of all parrotfishes that were at least 10 cm in length that were encountered in a 5-m-wide swath. Because these swims often crossed multiple habitats, the diver recorded the habitat each minute. For each site, the total area of each habitat sampled was then calculated in order to determine habitat- and site-specific densities of each parrotfish species. proprietary
+gov.noaa.nodc:0172377_Not Applicable Abundance and biomass of parrotfishes (Labridae, Scarinae) in St.Croix, U.S. Virgin Islands 2015 to 2016 (NCEI Accession 0172377) NOAA_NCEI STAC Catalog 2015-07-21 2016-08-05 -64.9199, 17.63764, -64.47889, 17.82709 https://cmr.earthdata.nasa.gov/search/concepts/C2089378141-NOAA_NCEI.umm_json We collected data on parrotfish abundance, biomass, size structure, and species composition at several sites on the N shore of St. Croix during July and August 2015 and 2016. Surveys were conducted using a method that allowed divers to rapidly survey large areas and quantify habitat assocations of different species. Researchers conducted 20-30 min timed swims towing a float with a GPS receiver, which allowed for the calculation of distance traveled during a swim and therefore the total area sampled. During the timed swim survey, the diver estimated and recorded the size to the nearest cm of all parrotfishes that were at least 10 cm in length that were encountered in a 5-m-wide swath. Because these swims often crossed multiple habitats, the diver recorded the habitat each minute. For each site, the total area of each habitat sampled was then calculated in order to determine habitat- and site-specific densities of each parrotfish species. proprietary
gov.noaa.nodc:0172588_Not Applicable Biological, chemical, and other data collected from station Humboldt Bay Pier by Humboldt State University and assembled by Central and Northern California Coastal Ocean Observing System (CeNCOOS) in the Northeast Pacific Ocean from 2012-12-13 to 2021-06-09 (NCEI Accession 0172588) NOAA_NCEI STAC Catalog 2012-12-13 2021-06-09 -124.19652, 40.7775, -124.19652, 40.7775 https://cmr.earthdata.nasa.gov/search/concepts/C2089378189-NOAA_NCEI.umm_json NCEI Accession 0172588 contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Humboldt State University collected the data from their in-situ moored station named Humboldt Bay Pier in the Northeast Pacific Ocean. Central and Northern California Coastal Ocean Observing System (CeNCOOS), which assembles data from Humboldt State University and other sub-regional coastal and ocean observing systems of the Central and Northern California United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this accession when new files are available. proprietary
gov.noaa.nodc:0172612_Not Applicable Biological, chemical and other data collected from station Monterey Bay Commercial Wharf by Moss Landing Marine Laboratory and assembled by Central and Northern California Coastal Ocean Observing System (CeNCOOS) in the Northeast Pacific Ocean from 2015-05-05 to 2020-01-03 (NCEI Accession 0172612) NOAA_NCEI STAC Catalog 2015-05-05 2020-01-03 -121.88935, 36.60513, -121.88935, 36.60513 https://cmr.earthdata.nasa.gov/search/concepts/C2089378278-NOAA_NCEI.umm_json NCEI Accession 0172612 contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Moss Landing Marine Laboratory collected the data from their in-situ moored station named Monterey Bay Commercial Wharf in the Northeast Pacific Ocean. Central and Northern California Coastal Ocean Observing System (CeNCOOS), which assembles data from Moss Landing Marine Laboratory and other sub-regional coastal and ocean observing systems of the Central and Northern California United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this accession when new files are available. proprietary
gov.noaa.nodc:0172613_Not Applicable Biological, chemical and other data collected from station Indian Island by Humboldt State University and assembled by Central and Northern California Coastal Ocean Observing System (CeNCOOS) in the Northeast Pacific Ocean from 2016-04-05 to 2019-10-28 (NCEI Accession 0172613) NOAA_NCEI STAC Catalog 2016-04-05 2019-10-28 -124.15754, 40.81503, -124.15754, 40.81503 https://cmr.earthdata.nasa.gov/search/concepts/C2089378289-NOAA_NCEI.umm_json NCEI Accession 0172613 contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Humboldt State University collected the data from their in-situ moored station named Indian Island in the Northeast Pacific Ocean. Central and Northern California Coastal Ocean Observing System (CeNCOOS), which assembles data from Humboldt State University and other sub-regional coastal and ocean observing systems of the Central and Northern California United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this accession when new files are available. proprietary
gov.noaa.nodc:0173246_Not Applicable Benthic Fauna and Hydrography at Four Sites in the Mobile-Tensaw River Delta, Alabama (1981-1982) (NCEI Accession 0173246) NOAA_NCEI STAC Catalog 1981-11-17 1982-09-29 -88.004, 30.411, -87.562, 31.055 https://cmr.earthdata.nasa.gov/search/concepts/C2089378543-NOAA_NCEI.umm_json Bimonthly surveys of benthic fauna were conducted at four sites in the Mobile-Tensaw River Delta from November 1981 to September 1982. Two sites were at the upper reaches of the river delta, and two were at the mouth. Fauna were enumerated and identified to lowest taxon possible. Hydrographic data were also collected, including temperature, conductivity, and dissolved oxygen. proprietary
gov.noaa.nodc:0173316_Not Applicable Carbon dioxide, hydrographic and chemical data collected from profile discrete samples during the R/V Nathaniel B. Palmer 2015 OOISO; NBP15_11, SOCCOM cruise (EXPOCODE 320620151206) in the South Pacific Ocean from 2015-12-06 to 2016-01-04 (NCEI Accession 0173316) NOAA_NCEI STAC Catalog 2015-12-06 2016-01-04 -89.72, -54.6, -80.11, -52.93 https://cmr.earthdata.nasa.gov/search/concepts/C2089378635-NOAA_NCEI.umm_json This NCEI Accession includes profile discrete measurements of CTD temperature, CTD salinity, CTD oxygen, nutrients, total alkalinity and pH on Total scale obtained during the R/V Nathaniel B. Palmer 2015 OOISO; NBP15_11, SOCCOM cruise (EXPOCODE 320620151206) in the South Pacific Ocean from 2015-12-06 to 2016-01-02. proprietary
-gov.noaa.nodc:0175745_Not Applicable Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2011-07-07 to 2016-10-29 (NCEI Accession 0175745) ALL STAC Catalog 2011-07-07 2016-10-29 -51.5, -34.503, -44.5, -34.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089380684-NOAA_NCEI.umm_json "This dataset contains round trip acoustic travel time and abmient bottom pressure from bottom-mounted instruments spaced zonally along 34.5S in the SW Atlantic east of Uruguay July 2011 to October 2016. The data were collected for the Southwest Atlantic meridional overturning circulation (""SAM"") project by the NOAA-Atlantic Oceanographic and Meteorological Laboratory. Both the processed/quality-controlled and the raw data files are available. Format is text." proprietary
gov.noaa.nodc:0175745_Not Applicable Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2011-07-07 to 2016-10-29 (NCEI Accession 0175745) NOAA_NCEI STAC Catalog 2011-07-07 2016-10-29 -51.5, -34.503, -44.5, -34.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089380684-NOAA_NCEI.umm_json "This dataset contains round trip acoustic travel time and abmient bottom pressure from bottom-mounted instruments spaced zonally along 34.5S in the SW Atlantic east of Uruguay July 2011 to October 2016. The data were collected for the Southwest Atlantic meridional overturning circulation (""SAM"") project by the NOAA-Atlantic Oceanographic and Meteorological Laboratory. Both the processed/quality-controlled and the raw data files are available. Format is text." proprietary
-gov.noaa.nodc:0175783_Not Applicable Agulhas Current transport derived from satellite altimetry observations in Indian Ocean from 1992-10-14 to 2016-12-28 (NCEI Accession 0175783) ALL STAC Catalog 1992-10-14 2016-12-28 27, -40, 30, -34 https://cmr.earthdata.nasa.gov/search/concepts/C2089380711-NOAA_NCEI.umm_json The Agulhas Current is the western boundary current closing the upper-limb of the Indian Ocean subtropical gyre, and is largely linked with the transfer of warm water from the Indian Ocean to the South Atlantic subtropical gyre. This interbasin water exchange takes place mostly through mesoscale processes that occur when the Agulhas Current retroflects south of Africa between 15°E and 25°E. Estimates of the Agulhas Current are carried out by NOAA/AOML using satellite altimetry as the main dataset, and hydrographic observations. For more information, please visit: http://www.aoml.noaa.gov/phod/indexes/index.php proprietary
+gov.noaa.nodc:0175745_Not Applicable Acoustic travel time and bottom pressure data from inverted echo sounders as part of the Southwest Atlantic Meridional Overturning Circulation project (SAM) from 2011-07-07 to 2016-10-29 (NCEI Accession 0175745) ALL STAC Catalog 2011-07-07 2016-10-29 -51.5, -34.503, -44.5, -34.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089380684-NOAA_NCEI.umm_json "This dataset contains round trip acoustic travel time and abmient bottom pressure from bottom-mounted instruments spaced zonally along 34.5S in the SW Atlantic east of Uruguay July 2011 to October 2016. The data were collected for the Southwest Atlantic meridional overturning circulation (""SAM"") project by the NOAA-Atlantic Oceanographic and Meteorological Laboratory. Both the processed/quality-controlled and the raw data files are available. Format is text." proprietary
gov.noaa.nodc:0175783_Not Applicable Agulhas Current transport derived from satellite altimetry observations in Indian Ocean from 1992-10-14 to 2016-12-28 (NCEI Accession 0175783) NOAA_NCEI STAC Catalog 1992-10-14 2016-12-28 27, -40, 30, -34 https://cmr.earthdata.nasa.gov/search/concepts/C2089380711-NOAA_NCEI.umm_json The Agulhas Current is the western boundary current closing the upper-limb of the Indian Ocean subtropical gyre, and is largely linked with the transfer of warm water from the Indian Ocean to the South Atlantic subtropical gyre. This interbasin water exchange takes place mostly through mesoscale processes that occur when the Agulhas Current retroflects south of Africa between 15°E and 25°E. Estimates of the Agulhas Current are carried out by NOAA/AOML using satellite altimetry as the main dataset, and hydrographic observations. For more information, please visit: http://www.aoml.noaa.gov/phod/indexes/index.php proprietary
+gov.noaa.nodc:0175783_Not Applicable Agulhas Current transport derived from satellite altimetry observations in Indian Ocean from 1992-10-14 to 2016-12-28 (NCEI Accession 0175783) ALL STAC Catalog 1992-10-14 2016-12-28 27, -40, 30, -34 https://cmr.earthdata.nasa.gov/search/concepts/C2089380711-NOAA_NCEI.umm_json The Agulhas Current is the western boundary current closing the upper-limb of the Indian Ocean subtropical gyre, and is largely linked with the transfer of warm water from the Indian Ocean to the South Atlantic subtropical gyre. This interbasin water exchange takes place mostly through mesoscale processes that occur when the Agulhas Current retroflects south of Africa between 15°E and 25°E. Estimates of the Agulhas Current are carried out by NOAA/AOML using satellite altimetry as the main dataset, and hydrographic observations. For more information, please visit: http://www.aoml.noaa.gov/phod/indexes/index.php proprietary
gov.noaa.nodc:0175786_Not Applicable Abundance and Distribution of Commercially Important Estuarine Dependent Species Populations within the Gulf of Mexico from 1986-04-01 to 2017-06-27 (NCEI Accession 0175786) ALL STAC Catalog 1986-04-01 2017-06-27 -89.85889, 29.8917, -87.6955, 30.68067 https://cmr.earthdata.nasa.gov/search/concepts/C2089380737-NOAA_NCEI.umm_json This dataset contains records of Gulf of Mexico (GOM) blue crab (Callinectes sapidus), white shrimp (Litopenaeus setiferus), brown shrimp (Farfantepenaeus aztecus), and fishes which can be used to quantify their population abundances and distributions. The data set contains existing data as a baseline and supplemental data from continued sampling. It contains records of early life stage blue crab, white shrimp, brown shrimp, and fishes (measurements and counts) from beach seine and trawl samples across the north GOM in the central Gulf States that were collected using standardized sampling methods. Data also include habitat assessments such as descriptions, georeferencing information, and abiotic factors (DO, salinity, temperature). proprietary
gov.noaa.nodc:0175786_Not Applicable Abundance and Distribution of Commercially Important Estuarine Dependent Species Populations within the Gulf of Mexico from 1986-04-01 to 2017-06-27 (NCEI Accession 0175786) NOAA_NCEI STAC Catalog 1986-04-01 2017-06-27 -89.85889, 29.8917, -87.6955, 30.68067 https://cmr.earthdata.nasa.gov/search/concepts/C2089380737-NOAA_NCEI.umm_json This dataset contains records of Gulf of Mexico (GOM) blue crab (Callinectes sapidus), white shrimp (Litopenaeus setiferus), brown shrimp (Farfantepenaeus aztecus), and fishes which can be used to quantify their population abundances and distributions. The data set contains existing data as a baseline and supplemental data from continued sampling. It contains records of early life stage blue crab, white shrimp, brown shrimp, and fishes (measurements and counts) from beach seine and trawl samples across the north GOM in the central Gulf States that were collected using standardized sampling methods. Data also include habitat assessments such as descriptions, georeferencing information, and abiotic factors (DO, salinity, temperature). proprietary
gov.noaa.nodc:0176496_Not Applicable Biological Baseline Studies of Mobile Bay (MESC-CAB 1980-1981): Hydrography, Sediments, Benthic Fauna, Pelagic Fauna, Phytoplankton, and Zooplankton (NCEI Accession 0176496) NOAA_NCEI STAC Catalog 1980-04-03 1981-08-26 -88.17333, 30.23833, -87.85167, 30.61333 https://cmr.earthdata.nasa.gov/search/concepts/C2089376767-NOAA_NCEI.umm_json Data from a monthly survey of Mobile Bay between April 1980 and August 1981. Extant data from the MESC Data Management System include sediment particle size distribution, discrete hydrography, identification and enumeration of benthic fauna, and identification and enumeration of water column biota. proprietary
@@ -18789,11 +18790,11 @@ gov.noaa.nodc:0185741_Not Applicable Carbonate Chemistry Dynamics on Southeast F
gov.noaa.nodc:0185742_Not Applicable Climatology for NOAA Coral Reef Watch (CRW) Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite Version 3.1 for 1985-01-01 to 2012-12-31 (NCEI Accession 0185742) NOAA_NCEI STAC Catalog 1985-01-01 2012-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089379091-NOAA_NCEI.umm_json This package contains a set of 12 monthly mean (MM) climatologies, one for each calendar month, and the maximum monthly mean (MMM) climatology. Each climatology has global coverage at 0.05-degree (5km) spatial resolution. The climatologies were derived from NOAA Coral Reef Watch's (CRW) CoralTemp Version 1.0 product and are based on the 1985-2012 time period of the CoralTemp data. They are used in deriving CRW's Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite Version 3.1. MMs are used to derive the SST Anomaly product, and the MMM is used to derive CRW's Coral Bleaching HotSpot, Degree Heating Week, and Bleaching Alert Area products. proprietary
gov.noaa.nodc:0185753_Not Applicable Abundance, biomass, and density of benthic macroinvertebrates collected from R/V Laurentian in Lake Huron, Great Lakes from 2006-09-01 to 2012-12-31 (NCEI Accession 0185753) ALL STAC Catalog 2006-09-01 2012-12-31 -84.5, 43.2, -79.8, 46.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089379102-NOAA_NCEI.umm_json Raw data from the benthic macroinvertebrate surveys conducted in Saginaw Bay in 2006-2009, and in Lake Huron, including Georgian Bay and North Channel, in 2007 and 2012. These basic benthic survey data provide number of each taxon in each replicate sample (abundance), density, and biomass. proprietary
gov.noaa.nodc:0185753_Not Applicable Abundance, biomass, and density of benthic macroinvertebrates collected from R/V Laurentian in Lake Huron, Great Lakes from 2006-09-01 to 2012-12-31 (NCEI Accession 0185753) NOAA_NCEI STAC Catalog 2006-09-01 2012-12-31 -84.5, 43.2, -79.8, 46.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089379102-NOAA_NCEI.umm_json Raw data from the benthic macroinvertebrate surveys conducted in Saginaw Bay in 2006-2009, and in Lake Huron, including Georgian Bay and North Channel, in 2007 and 2012. These basic benthic survey data provide number of each taxon in each replicate sample (abundance), density, and biomass. proprietary
-gov.noaa.nodc:0186561_Not Applicable 2003 Marine Fisheries Initiative (MARFIN) Gulf of Mexico and South Atlantic angler survey (NCEI Accession 0186561) NOAA_NCEI STAC Catalog 2003-01-01 2003-12-31 -98, 25, -80, 31 https://cmr.earthdata.nasa.gov/search/concepts/C2089380124-NOAA_NCEI.umm_json This Archival Information Package (AIP) contains information, angler experiences, and preferences for recreational fishing in the Gulf of Mexico and South Atlantic. Data were collected by the NMFS Southeast Fisheries Science Center; Miami, FL. Data are in comma separated value (CSV) format and include recreational angler information such as age, gender, income, and target fish. proprietary
gov.noaa.nodc:0186561_Not Applicable 2003 Marine Fisheries Initiative (MARFIN) Gulf of Mexico and South Atlantic angler survey (NCEI Accession 0186561) ALL STAC Catalog 2003-01-01 2003-12-31 -98, 25, -80, 31 https://cmr.earthdata.nasa.gov/search/concepts/C2089380124-NOAA_NCEI.umm_json This Archival Information Package (AIP) contains information, angler experiences, and preferences for recreational fishing in the Gulf of Mexico and South Atlantic. Data were collected by the NMFS Southeast Fisheries Science Center; Miami, FL. Data are in comma separated value (CSV) format and include recreational angler information such as age, gender, income, and target fish. proprietary
+gov.noaa.nodc:0186561_Not Applicable 2003 Marine Fisheries Initiative (MARFIN) Gulf of Mexico and South Atlantic angler survey (NCEI Accession 0186561) NOAA_NCEI STAC Catalog 2003-01-01 2003-12-31 -98, 25, -80, 31 https://cmr.earthdata.nasa.gov/search/concepts/C2089380124-NOAA_NCEI.umm_json This Archival Information Package (AIP) contains information, angler experiences, and preferences for recreational fishing in the Gulf of Mexico and South Atlantic. Data were collected by the NMFS Southeast Fisheries Science Center; Miami, FL. Data are in comma separated value (CSV) format and include recreational angler information such as age, gender, income, and target fish. proprietary
gov.noaa.nodc:0191401_Not Applicable Biogeochemical and microbiological measurements in the Cariaco Basin, a truly marine anoxic system in the southeastern Caribbean Sea, from 1995-11-13 to 2015-11-14 by the CARIACO Ocean Time Series Program (formerly known as CArbon Retention In A Colored Ocean) aboard the B/O Hermano Gines (NCEI Accession 0191401) NOAA_NCEI STAC Catalog 1995-11-13 2015-11-14 -64.66, 10.5, -64.66, 10.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089377738-NOAA_NCEI.umm_json Biogeochemical and microbiological variables were measured by Stony Brook University participants (see Author List) in the CARIACO Ocean Time-Series Program in order to study the microbial cycling of carbon, sulfur, and nitrogen occurring at depths where waters transition from oxic to anoxic to sulfidic. Samples were collected by Nikson bottles from 1995-11-13 to 2015-11-14 in the Cariaco Basin (southeastern Caribbean Sea off northeastern Venezuelan coast) aboard the B/O Hermano Gines, operated by the Fundacion La Salle, Venezuela. proprietary
-gov.noaa.nodc:0194300_Not Applicable ADCP, CTD, water and sediment chemistry, and underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24 (NCEI Accession 0194300) ALL STAC Catalog 2012-04-11 2012-04-24 -90.5895, 27.2111, -87.42629, 30.35717 https://cmr.earthdata.nasa.gov/search/concepts/C2089378330-NOAA_NCEI.umm_json This dataset contains ADCP, CTD, water and sediment chemistry, and other underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24. The CTD profiles were done at 4 locations using Sea-Bird SBE 911plus from 2012-04-11 to 2012-04-14 and include seawater conductivity, temperature, pressure, salinity, density, oxygen concentration, sound velocity, dissolved oxygen, beam attenuation, light transmission, fluorescence, surface irradiance, and depth parameters. The current velocity data was measured by a hull-mounted mounted Acoustic Doppler Current Profiler (ADCP) and other underway sensor data was measured with a Sea-Bird SBE 21 (tsg), Sea-Bird SBE 45 (tsg) and underway sensors/navigational instruments. All data records include sampling time (UTC), position (Latitude, Longitude) and water depth. In addition, the dataset also includes the water column and sediment chemistry data and the measurements include the concentration of dissolved nutrients, dissolved gases, total particulate nitrogen (TPN), total particulate carbon (TPN), particulate organic carbon (POC), and particulate inorganic carbon acquired from 8 CTD casts and 6 multiple corer drops. The objective of this cruise was to study the impact of the Deepwater Horizon (DWH) blowout on the water column and benthic communities of the Gulf of Mexico and compare these impacts to naturally occurring oil and gas seeps. These data are also available at Rolling Deck to Repository (R2R) under cruise https://doi.org/10.7284/902570. proprietary
gov.noaa.nodc:0194300_Not Applicable ADCP, CTD, water and sediment chemistry, and underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24 (NCEI Accession 0194300) NOAA_NCEI STAC Catalog 2012-04-11 2012-04-24 -90.5895, 27.2111, -87.42629, 30.35717 https://cmr.earthdata.nasa.gov/search/concepts/C2089378330-NOAA_NCEI.umm_json This dataset contains ADCP, CTD, water and sediment chemistry, and other underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24. The CTD profiles were done at 4 locations using Sea-Bird SBE 911plus from 2012-04-11 to 2012-04-14 and include seawater conductivity, temperature, pressure, salinity, density, oxygen concentration, sound velocity, dissolved oxygen, beam attenuation, light transmission, fluorescence, surface irradiance, and depth parameters. The current velocity data was measured by a hull-mounted mounted Acoustic Doppler Current Profiler (ADCP) and other underway sensor data was measured with a Sea-Bird SBE 21 (tsg), Sea-Bird SBE 45 (tsg) and underway sensors/navigational instruments. All data records include sampling time (UTC), position (Latitude, Longitude) and water depth. In addition, the dataset also includes the water column and sediment chemistry data and the measurements include the concentration of dissolved nutrients, dissolved gases, total particulate nitrogen (TPN), total particulate carbon (TPN), particulate organic carbon (POC), and particulate inorganic carbon acquired from 8 CTD casts and 6 multiple corer drops. The objective of this cruise was to study the impact of the Deepwater Horizon (DWH) blowout on the water column and benthic communities of the Gulf of Mexico and compare these impacts to naturally occurring oil and gas seeps. These data are also available at Rolling Deck to Repository (R2R) under cruise https://doi.org/10.7284/902570. proprietary
+gov.noaa.nodc:0194300_Not Applicable ADCP, CTD, water and sediment chemistry, and underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24 (NCEI Accession 0194300) ALL STAC Catalog 2012-04-11 2012-04-24 -90.5895, 27.2111, -87.42629, 30.35717 https://cmr.earthdata.nasa.gov/search/concepts/C2089378330-NOAA_NCEI.umm_json This dataset contains ADCP, CTD, water and sediment chemistry, and other underway sensor data collected aboard R/V Endeavor cruise EN505 in the Gulf of Mexico from 2012-04-11 to 2012-04-24. The CTD profiles were done at 4 locations using Sea-Bird SBE 911plus from 2012-04-11 to 2012-04-14 and include seawater conductivity, temperature, pressure, salinity, density, oxygen concentration, sound velocity, dissolved oxygen, beam attenuation, light transmission, fluorescence, surface irradiance, and depth parameters. The current velocity data was measured by a hull-mounted mounted Acoustic Doppler Current Profiler (ADCP) and other underway sensor data was measured with a Sea-Bird SBE 21 (tsg), Sea-Bird SBE 45 (tsg) and underway sensors/navigational instruments. All data records include sampling time (UTC), position (Latitude, Longitude) and water depth. In addition, the dataset also includes the water column and sediment chemistry data and the measurements include the concentration of dissolved nutrients, dissolved gases, total particulate nitrogen (TPN), total particulate carbon (TPN), particulate organic carbon (POC), and particulate inorganic carbon acquired from 8 CTD casts and 6 multiple corer drops. The objective of this cruise was to study the impact of the Deepwater Horizon (DWH) blowout on the water column and benthic communities of the Gulf of Mexico and compare these impacts to naturally occurring oil and gas seeps. These data are also available at Rolling Deck to Repository (R2R) under cruise https://doi.org/10.7284/902570. proprietary
gov.noaa.nodc:0204167_Not Applicable Cetacean digital photography and aerial observer data collected by an unmanned aerial vehicle and manned aerial vehicle in the Beaufort Sea for the Arctic Aerial Calibration Experiments (ACEs) from 2015-08-26 to 2015-09-07 (NCEI Accession 0204167) NOAA_NCEI STAC Catalog 2015-08-26 2015-09-07 -159.3, 71, -153.1, 72 https://cmr.earthdata.nasa.gov/search/concepts/C2089379246-NOAA_NCEI.umm_json This dataset includes two comma separated files containing data and metadata from three cetacean observation methods from two platforms, the manned Turbo Commander aircraft and the unmanned ScanEagle. The ACEs' imagery described here was collected and analyzed in order to conduct a 3-way comparison of data and derived statistics from the following: Observers in the manned aircraft; Digital photographs from cameras mounted to the manned aircraft; Digital photographs from cameras mounted to the Unmanned Aerial Vehicle (UAV). The Arctic Aerial Calibration Experiments (ACEs) study was designed to evaluate the ability of UAS technology (i.e., airframe, payloads, sensors, and software) to detect cetaceans, identify individuals to species, estimate group size, identify calves, and estimate density in arctic waters, relative to conventional aerial surveys conducted by human observers in fixed wing aircraft and to photographic strip transect data collected from the manned aircraft. proprietary
gov.noaa.nodc:0204646_Not Applicable Benthic cover from automated annotation of benthic images collected at coral reef sites in the Pacific Remote Island Areas and American Samoa from 2018-06-08 to 2018-08-11 (NCEI Accession 0204646) NOAA_NCEI STAC Catalog 2018-06-08 2018-08-11 -176.626077, -14.558022, -159.971695, 6.451465 https://cmr.earthdata.nasa.gov/search/concepts/C2089379357-NOAA_NCEI.umm_json "The coral reef benthic community data described here result from the automated annotation (classification) of benthic images collected during photoquadrat surveys conducted by the NOAA Pacific Islands Fisheries Science Center (PIFSC), Ecosystem Sciences Division (ESD, formerly the Coral Reef Ecosystem Division) as part of NOAA's ongoing National Coral Reef Monitoring Program (NCRMP). SCUBA divers conducted benthic photoquadrat surveys in coral reef habitats according to protocols established by ESD and NCRMP during the ESD-led NCRMP mission to the islands and atolls of the Pacific Remote Island Areas (PRIA) and American Samoa from June 8 to August 11, 2018. Still photographs were collected with a high-resolution digital camera mounted on a pole to document the benthic community composition at predetermined points along transects at stratified random sites surveyed only once as part of Rapid Ecological Assessment (REA) surveys for corals and fish (Ayotte et al. 2015; Swanson et al. 2018) and permanent sites established by ESD and resurveyed every ~3 years for climate change monitoring. Overall, 30 photoquadrat images were collected at each survey site. The benthic habitat images were quantitatively analyzed using the web-based, machine-learning, image annotation tool, CoralNet (https://coralnet.ucsd.edu; Beijbom et al. 2015; Williams et al. 2019). Ten points were randomly overlaid on each image and the machine-learning algorithm ""robot"" identified the organism or type of substrate beneath, with 300 annotations (points) generated per site. Benthic elements falling under each point were identified to functional group (Tier 1: hard coral, soft coral, sessile invertebrate, macroalgae, crustose coralline algae, and turf algae) for coral, algae, invertebrates, and other taxa following Lozada-Misa et al. (2017). These benthic data can ultimately be used to produce estimates of community composition, relative abundance (percentage of benthic cover), and frequency of occurrence." proprietary
gov.noaa.nodc:0205786_Not Applicable Assessment of heat stress exposure in the wider Caribbean coral reefs through the regional delineation of degree heating week data from 1985-01-01 to 2017-12-31 (NCEI Accession 0205786) NOAA_NCEI STAC Catalog 1985-01-01 2017-12-31 -97, 8.35, -59.2, 32.7 https://cmr.earthdata.nasa.gov/search/concepts/C2089380033-NOAA_NCEI.umm_json "This data package presents a three-decade (1985-2017) assessment of heat stress exposure in the wider Caribbean coral reefs at the ecoregional and local scales. The main heat stress indicator used was the Degree Heating Weeks (DHW) calculated from daily Sea Surface Temperature ""CoralTemp"" data from CRW-NOAA available from 1985 to the present and from the maximum monthly mean (MMM) version 3.1 at 5 km of the CRW-NOAA program. Different metrics were calculated based on daily DHW and are available in this dataset: a) the maximum value of DHW per pixel for the entire time series b) the frequency of the annual maximum values of DHW ⥠4 °C- weeks (a predictor of coral ""bleaching risk"") per pixel c) the frequency of the annual maximum values of DHW ⥠8 °C- weeks (a predictor of bleach-induced mortality or ""mortality risk"") per pixel d) the year in which the maximum of DHW occurred e) the trend of the annual maximum values of DHW per pixel. Based on the spatiotemporal annual maximum DHW, a new regionalization of heat stress was performed by cluster analysis with the K-means algorithm through the unsupervised classification, this new regionalization delimits the Caribbean in 8 Heat Stress Regions (HSR). We summarized spatiotemporal daily data to describe the temporal patterns at an ecoregional scale by calculating the descriptive statistics of the regional DHW on a given day. This dataset represents a new baseline and regionalization of heat stress in the wider Caribbean coral reefs that will enhance conservation and planning efforts underway." proprietary
@@ -18814,14 +18815,14 @@ gov.noaa.nodc:0209226_Not Applicable Acropora cervicornis outplanting scores in
gov.noaa.nodc:0209247_Not Applicable Benthic cover derived from structure from motion images collected during marine debris surveys at coral reef sites entangled with derelict fishing nets at Pearl and Hermes Atoll in the Northwestern Hawaiian Islands from 2018-09-24 to 2018-10-03 (NCEI Accession 0209247) NOAA_NCEI STAC Catalog 2018-09-24 2018-10-03 -175.8211335, 27.8274571, -175.7880926, 27.8940486 https://cmr.earthdata.nasa.gov/search/concepts/C2089378869-NOAA_NCEI.umm_json The benthic cover and fishing-net related data described in this dataset are derived from the GIS analysis of benthic orthophotos. The source imagery was collected using a Structure from Motion (SfM) approach during in-water marine debris swim surveys conducted by snorkelers in search of derelict fishing nets. Surveys were conducted by the NOAA Fisheries, Ecosystem Sciences Division (ESD) from September 24 to October 3, 2018 at Pearl and Hermes Atoll during an ESD-led marine debris mission to the Northwestern Hawaiian Islands (NWHI) aboard NOAA Ship Oscar Elton Sette. The lagoon at Pearl and Hermes was surveyed equally across the spatial gradient, from locations where derelict fishing nets are common to locations where derelict fishing nets have never been observed. During the 2018 mission, only a subset of marine debris surveys resulted in a SfM survey. Fishing nets were located during swim surveys and selected for SfM if the net was interacting with coral or hard substrate, the depth of the net was within ~1â4 m of the surface, and the area of the net fit within the 9 sq. meter SFM survey plot. During a SFM survey, a permanent 3 x 3 m plot was established around the center of the fishing net, and the net was photographed using a back and forth swim pattern (âbeforeâ photos) for later processing using a SfM approach. The net was then removed, the volume of net removed was estimated and recorded, and the same area was photographed again in the same way (âafterâ photos). A nearby (>50 m distant) paired control site was also photographed using the same method (âcontrolâ photos). The photographs were processed using Agisoft Metashape software to generate orthomosaic images that were analyzed in ArcGIS for benthic cover using a random point approach. The number of points at net-impacted sites were constrained to the net coverage area and were scaled to the net area to ensure an equal point density among replicate net-impact sites. The same number of points were randomly assigned to the 3 Ã 3 m paired control site. Each point was classified into one of seven benthic categories: turf algae, macroalgae, sand, bare substrate, Porites compressa, sponge, or crustose coralline algae (CCA). The annotated points for each site were converted to percent cover for each benthic category. Fishing net size (sq m) and degree of fouling were also calculated from the orthophotos. Analyses were conducted to compare the benthic composition of net sites to control sites and to determine if fouling or net size contributed to these differences. proprietary
gov.noaa.nodc:0209357_Not Applicable A Toolbox for secondary quality control on ocean chemistry and hydrographic data (NCEI Accession 0209357) ALL STAC Catalog 2000-01-01 2020-03-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089379328-NOAA_NCEI.umm_json This NCEA Accession contains MatLab files for a Toolbox for secondary quality control (2nd QC) on ocean chemistry and hydrographic data. High quality, reference measurements of chemical and physical properties of seawater are of great importance for a wide research community, including the need to validate models and attempts to quantify spatial and temporal variability. Whereas data precision has been improved by technological advances, the data accuracy has improved mainly by the use of certified reference materials (CRMs). However, since CRMs are not available for all variables, and use of CRMs does not guarantee bias-free data, we here present a recently developed Matlab toolbox for performing so-called secondary quality control on oceanographic data by the use of crossover analysis. This method and how it has been implemented in this toolbox is described in detail. This toolbox is developed mainly for use by sea-going scientists as a tool for quickly assessing possible bias in the measurements that can, hopefully, be remedied during the expedition, but also for possible post-cruise adjustment of data to be consistent with previous measurements in the region. proprietary
gov.noaa.nodc:0209357_Not Applicable A Toolbox for secondary quality control on ocean chemistry and hydrographic data (NCEI Accession 0209357) NOAA_NCEI STAC Catalog 2000-01-01 2020-03-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2089379328-NOAA_NCEI.umm_json This NCEA Accession contains MatLab files for a Toolbox for secondary quality control (2nd QC) on ocean chemistry and hydrographic data. High quality, reference measurements of chemical and physical properties of seawater are of great importance for a wide research community, including the need to validate models and attempts to quantify spatial and temporal variability. Whereas data precision has been improved by technological advances, the data accuracy has improved mainly by the use of certified reference materials (CRMs). However, since CRMs are not available for all variables, and use of CRMs does not guarantee bias-free data, we here present a recently developed Matlab toolbox for performing so-called secondary quality control on oceanographic data by the use of crossover analysis. This method and how it has been implemented in this toolbox is described in detail. This toolbox is developed mainly for use by sea-going scientists as a tool for quickly assessing possible bias in the measurements that can, hopefully, be remedied during the expedition, but also for possible post-cruise adjustment of data to be consistent with previous measurements in the region. proprietary
-gov.noaa.nodc:0210577_Not Applicable Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from 2014-07-15 to 2018-11-11 (NCEI Accession 0210577) NOAA_NCEI STAC Catalog 2014-07-15 2018-11-11 -162, 11, -50, 43 https://cmr.earthdata.nasa.gov/search/concepts/C2089380393-NOAA_NCEI.umm_json Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from the World Ocean. ALAMO profiling floats measure temperature, salinity, and pressure and were developed to be air deployed in previously difficult locations, including tropical cyclones and around sea ice. Data files in NetCDF. proprietary
gov.noaa.nodc:0210577_Not Applicable Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from 2014-07-15 to 2018-11-11 (NCEI Accession 0210577) ALL STAC Catalog 2014-07-15 2018-11-11 -162, 11, -50, 43 https://cmr.earthdata.nasa.gov/search/concepts/C2089380393-NOAA_NCEI.umm_json Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from the World Ocean. ALAMO profiling floats measure temperature, salinity, and pressure and were developed to be air deployed in previously difficult locations, including tropical cyclones and around sea ice. Data files in NetCDF. proprietary
+gov.noaa.nodc:0210577_Not Applicable Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from 2014-07-15 to 2018-11-11 (NCEI Accession 0210577) NOAA_NCEI STAC Catalog 2014-07-15 2018-11-11 -162, 11, -50, 43 https://cmr.earthdata.nasa.gov/search/concepts/C2089380393-NOAA_NCEI.umm_json Air-Launched Autonomous Micro Observer (ALAMO) profiling float data from the World Ocean. ALAMO profiling floats measure temperature, salinity, and pressure and were developed to be air deployed in previously difficult locations, including tropical cyclones and around sea ice. Data files in NetCDF. proprietary
gov.noaa.nodc:0210808_Not Applicable Assessment of coral reef fish and benthic communities in the West Hawaii Habitat Focus Area from 2015-10-13 to 2015-10-23 (NCEI Accession 0210808) NOAA_NCEI STAC Catalog 2015-10-13 2015-10-23 -156.048008, 19.568405, -155.828939, 20.059629 https://cmr.earthdata.nasa.gov/search/concepts/C2089380539-NOAA_NCEI.umm_json This archive package contains data on species composition, density, size, and abundance for coral reef fish as well as coral counts, benthic cover, and macroalga cover in the West Hawaii Habitat Focus Area along the Kona coast of the island of Hawaii. Data provided in this collection were gathered as part of the NOAA Habitat Blueprint initiative with support from the Coral Reef Conservation Program. Data were collected primarily by The Nature Conservancy Hawaii. Data were collected in 2015 using the Belt Transect method. This is the first year in a series of monitoring efforts which have taken place in subsequent years to evaluate the resilience of coral reefs in the Focus Area. This dataset serves as a baseline as it was collected during the 2015 coral bleaching event. The dataset accompanies the NOAA technical report Maynard et al. 2016. proprietary
gov.noaa.nodc:0213517_Not Applicable Black Sea High Resolution SST L4 Analysis 0.0625 deg Resolution for 2019-09-18 (NCEI Accession 0213517) NOAA_NCEI STAC Catalog 2019-09-18 2019-09-18 26.375, 38.75, 42.375, 48.8125 https://cmr.earthdata.nasa.gov/search/concepts/C2089376602-NOAA_NCEI.umm_json CNR MED Sea Surface Temperature provides daily gap-free maps (L4) at 0.0625 deg. x 0.0625 deg. horizontal resolution over the Black Sea. The data are obtained from infra-red measurements collected by satellite radiometers and statistical interpolation. It is the CMEMS sea surface temperature nominal operational product for the Black sea. proprietary
gov.noaa.nodc:0218215_Not Applicable Circulation, temperature, and water surface elevation from Finite Volume Community Ocean Model (FVCOM) simulations of Lake Superior, Great Lakes region from 2010-01-01 to 2012-12-31 to study the 2010 coastal upwelling event (NCEI Accession 0218215) NOAA_NCEI STAC Catalog 2010-01-01 2012-12-31 -92.08, 46.44, -84.38, 48.79 https://cmr.earthdata.nasa.gov/search/concepts/C2089376983-NOAA_NCEI.umm_json "This dataset contains a three-dimensional (3-D), coupled ice-ocean Finite Volume Community Ocean Model (FVCOM) hydrodynamic simulations of circulation, temperature, and water surface elevation of Lake Superior for the years 2010-2012. The model was validated with temperature observations at National Oceanic and Atmospheric Administration (NOAA) buoys and mooring data from 2010. The upwelling event observed in satellite imagery and at a mooring station was reproduced by the model, in August 2010 along the northwestern coast. FVCOM version 3.1.6 was used for these simulations including custom modifications for wind-wave mixing (Hu and Wang, 2010) and centered-difference time integration. Ice simulations used the unstructured-grid, community ice code (UG-CICE) that was included with FVCOM version 3.1.6 (Chen et al. 2011; Gao et al. 2011). North American Regional Reanalysis (NARR) 32 km data (Mesinger et al. 2006) was used as atmospheric boundary conditions which included heat flux components (i.e., ""heating_on=T"" in the namelist). To convert the NARR forcings to the FVCOM unstructured grid, the interpolation scheme built in to FVCOM (WRF2FVCOM) was used. Details for these simulations can be found in the namelist file ""narr_0913_run.nml"" included in this data archive." proprietary
gov.noaa.nodc:0220639_Not Applicable Barium isotopes collected from world-wide oceans from 1970 to 2006 and analyzed at WHOI (NCEI Accession 0220639) NOAA_NCEI STAC Catalog 1970-01-01 2006-01-01 -178.073, -76.449, 174.4, 48 https://cmr.earthdata.nasa.gov/search/concepts/C2089377693-NOAA_NCEI.umm_json Barium isotope data from marine barites deposited throughout the world wide oceans. Samples include cold seep, hydrothermal and pelagic barites. Samples were collected from 1970 to 2006, and analyses were conducted in the NIRVANA lab at WHOI between 2016 and 2019. Data are in spreadsheet format. proprietary
-gov.noaa.nodc:0221188_Not Applicable 3-dimensional current velocity and other parameters taken by ADCP from the offshore supply ship Gerry Bordelon in Gulf of Mexico on 2017-09-24 (NCEI Accession 0221188) NOAA_NCEI STAC Catalog 2017-09-24 2017-09-24 -88.974, 28.932, -88.965, 28.944 https://cmr.earthdata.nasa.gov/search/concepts/C2089377874-NOAA_NCEI.umm_json The data consist of four ADCP surveys in the Mississippi Canyon Block 20 region of the Gulf of Mexico. ADCP2_D20170924_SW and ADCP3_D20170924_SW were run to the southwest of ADCP2_D20170929_NE and ADCP3_D20170929_NE. ADCP2 surveys were run from 01:20 to 01:36 UTC on September, 24 2017. ADCP3 surveys were run from 04:84 - 09:21 UTC on September, 24 2017. Sea state was up during ADCP3 surveys. Data are in NetCDF. proprietary
gov.noaa.nodc:0221188_Not Applicable 3-dimensional current velocity and other parameters taken by ADCP from the offshore supply ship Gerry Bordelon in Gulf of Mexico on 2017-09-24 (NCEI Accession 0221188) ALL STAC Catalog 2017-09-24 2017-09-24 -88.974, 28.932, -88.965, 28.944 https://cmr.earthdata.nasa.gov/search/concepts/C2089377874-NOAA_NCEI.umm_json The data consist of four ADCP surveys in the Mississippi Canyon Block 20 region of the Gulf of Mexico. ADCP2_D20170924_SW and ADCP3_D20170924_SW were run to the southwest of ADCP2_D20170929_NE and ADCP3_D20170929_NE. ADCP2 surveys were run from 01:20 to 01:36 UTC on September, 24 2017. ADCP3 surveys were run from 04:84 - 09:21 UTC on September, 24 2017. Sea state was up during ADCP3 surveys. Data are in NetCDF. proprietary
+gov.noaa.nodc:0221188_Not Applicable 3-dimensional current velocity and other parameters taken by ADCP from the offshore supply ship Gerry Bordelon in Gulf of Mexico on 2017-09-24 (NCEI Accession 0221188) NOAA_NCEI STAC Catalog 2017-09-24 2017-09-24 -88.974, 28.932, -88.965, 28.944 https://cmr.earthdata.nasa.gov/search/concepts/C2089377874-NOAA_NCEI.umm_json The data consist of four ADCP surveys in the Mississippi Canyon Block 20 region of the Gulf of Mexico. ADCP2_D20170924_SW and ADCP3_D20170924_SW were run to the southwest of ADCP2_D20170929_NE and ADCP3_D20170929_NE. ADCP2 surveys were run from 01:20 to 01:36 UTC on September, 24 2017. ADCP3 surveys were run from 04:84 - 09:21 UTC on September, 24 2017. Sea state was up during ADCP3 surveys. Data are in NetCDF. proprietary
gov.noaa.nodc:0225446_Not Applicable Assessment of coral reef benthic communities and reef fish survey data from locations in the Commonwealth of Northern Marianas Islands from 2014-10-01 to 2018-09-30 (NCEI Accession 0225446) NOAA_NCEI STAC Catalog 2014-10-01 2018-09-30 145.131154, 14.1136578, 145.8147431, 16.7162927 https://cmr.earthdata.nasa.gov/search/concepts/C2089379287-NOAA_NCEI.umm_json Overview Currently, the LTMMP has 52 long-term monitoring sites across Saipan, Tinian, and Rota that are surveyed on a rotating biennial basis. Three main habitat types are covered: Fore reef, reef flat (lagoon), and seagrass beds (lagoon). Most sites have been selected based on their association with management concerns (runoff, sewage outfalls, urban development, etc.) and/or management actions (watershed restorations efforts, marine protected areas, etc.) and include impacted sites and relatively non-impacted reference sites. In general, monitoring surveys are conducted using standard and proven ecological field survey methods. All surveys are conducted along 3-5, 50 m transect lines laid out along the depth contour (~9m depth) on the fore reef, or along consistent habitat in the lagoon (back reef and seagrass). While benthic cover analysis provides the foundation of the CNMI monitoring program, the current protocol uses several survey types per site to provide ecological depth beyond percent cover. Fore Reef Photos are taken every meter along each transect line using a 0.25m2 quadrat frame, for a total of 250 photos at each site. In the office, the computer program CPCe is used to place five random points on each photo and the biota or substrate type under each point is identified. Organisms are identified to the genus level. This analysis provides benthic percent cover and community diversity. Twelve, 3 minute, 5 m radius stationary point counts (SPC) are conducted at each site to evaluate fish assemblages. Each SPC is systematically positioned throughout the length of a site (250 m). The species and size (fork length) of all food fishes within the 5 meter radius are recorded. This provides relative diversity, abundances, species compositions, size class distribution, and biomass of the fish community. Sixteen 0.25m2 quadrats are haphazardly tossed along the length of the site and every coral colony within the quadrats is identified to the species level and measured. This method provides relative diversity, abundances, species composition, and size class of the coral community. Within these same quadrats, all algae species present are identified to the species level to provide a measure of algae community composition and species richness. Finally, non-coral macro-invertebrates including sea cucumbers, urchins, crown-of-thorns starfish, giant clams, among others, are identified and counted within 1 m of each side of the transect lines (i.e. 5, 2mx50m belt transects). This provides invertebrate abundances, species composition, and diversity. Saipan Lagoon Saipan Lagoon habitats that are monitored include Halodule uninervis beds, staghorn Acropora thickets, and mixed coral back reefs. At lagoon sites, benthic cover is quantified using a 0.25 m2 string quadrat with six intersections, placed every meter along the transect line. The biota or substrate under each intersection is recorded to the genus level, in situ. Additionally, 10, 1 m2 quads are haphazardly placed across the length of the site (250 m) and all seagrass, algae, coral, and macro-invertebrates are identified to the species level and recorded. This method captures the relative diversity, abundance, and species compositions of lagoon communities. Finally, non-coral macro-invertebrate abundances and diversity are quantified as described above for reef slope sites. proprietary
gov.noaa.nodc:0225545_Not Applicable Bulk density and pore water, sediment texture and composition data from sediment cores collected aboard R/V Weatherbird II cruises WB-0812 and WB-0813 in the northern Gulf of Mexico from 2012-08-14 to 2013-08-21 (NCEI Accession 0225545) NOAA_NCEI STAC Catalog 2012-08-14 2013-08-21 -88.86673, 28.97363, -86.33833, 29.73833 https://cmr.earthdata.nasa.gov/search/concepts/C2089379450-NOAA_NCEI.umm_json This dataset contains the bulk density and pore water, sediment texture and composition data from sediment cores collected aboard R/V Weatherbird II cruises WB-0812 and WB-0813 in the northern Gulf of Mexico (nGoM) from 2012-08-14 to 2013-08-21. These data were generated for selected core sub-samples at 2mm sampling intervals for âsurficial unitâ and 5mm sampling resolution intervals to the base of cores. For the bulk density and pore water data, sediment cores were collected on board the R/V Weatherbird II cruise WB-0812 in the nGoM from 2012-08-14 to 2012-08-16. It reports measurement of sediment sample wet weight (g), dry weight (g) and percent pore water. Bulk density is the dry weight per sampling volume expressed as g/cm3. Whereas, sediment texture and composition data were collected aboard R/V Weatherbird II cruise WB-0813 in the nGoM from 2013-08-20 to 2013-08-21. Sediment texture values were expressed as percent gravel, sand, silt, and clay. Percent of mud can be calculated by combining percent silt and clay. Sediment composition was expressed as percent total organic matter (TOM) measured by loss on ignition (LOI), percent carbonate content measured by acid leaching, and the percent insoluble residue (IR), which was likely dominated by terrigenous clastic (land-derived) sediment sources. proprietary
gov.noaa.nodc:0225979_Not Applicable Biological, chemical, physical and time series data collected from station WQBAW by University of Hawai'i at Hilo and University of Hawai'i at MÄnoa and assembled by Pacific Islands Ocean Observing System (PacIOOS) in the North Pacific Ocean from 2008-06-06 to 2016-12-06 (NCEI Accession 0225979) NOAA_NCEI STAC Catalog 2008-06-06 2016-12-06 -157.848, 21.2799, -157.848, 21.2799 https://cmr.earthdata.nasa.gov/search/concepts/C2089379551-NOAA_NCEI.umm_json NCEI Accession 0225979 contains biological, chemical, physical and time series data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). University of Hawai'i at Hilo and University of Hawai'i at MÄnoa collected the data from their in-situ moored station named WQBAW: PacIOOS Water Quality Buoy AW (WQB-AW): Ala Wai, Oahu, Hawaii, in the North Pacific Ocean. PacIOOS, which assembles data from University of Hawai'i at Hilo and University of Hawai'i at MÄnoa and other sub-regional coastal and ocean observing systems of the U. S. Pacific Islands, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. Each month, NCEI adds to the accession the data collected during the previous month. The water quality buoys are part of the Pacific Islands Ocean Observing System (PacIOOS) and are designed to measure a variety of ocean parameters at fixed points. WQB-AW is located at the exit of the Ala Wai Canal, near Magic Island. Continuous sampling of this outflow area provides a record of baseline conditions of the chemical and biological environment for comparison when there are pollution events such as storm runoff or a sewage spill. proprietary
@@ -18839,10 +18840,10 @@ gov.noaa.nodc:6800230_Not Applicable Cloud amount/frequency, NITRATE and other d
gov.noaa.nodc:6900225_Not Applicable Cloud amount/frequency, NITRATE and other data from GOA from 1968-09-19 to 1968-11-17 (NCEI Accession 6900225) NOAA_NCEI STAC Catalog 1968-09-19 1968-11-17 9, -17, 13.5, -4.8 https://cmr.earthdata.nasa.gov/search/concepts/C2089382177-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:6901098_Not Applicable Cloud amount/frequency, NITRATE and other data from PANULIRUS and PANULIRUS II from 1966-10-18 to 1969-11-06 (NCEI Accession 6901098) NOAA_NCEI STAC Catalog 1966-10-18 1969-11-06 -64.5, 32.1, -64.5, 32.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089381131-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7000052_Not Applicable BAROMETRIC PRESSURE and Other Data from ALPHA HELIX From Prince William Sound (Gulf of Alaska) from 1986-12-15 to 1986-12-18 (NCEI Accession 7000052) NOAA_NCEI STAC Catalog 1986-12-15 1986-12-18 -150, 59, -149, 60.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089381217-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:7000422_Not Applicable AIR PRESSURE and Other Data from GOSNOLD From NW Atlantic (limit-40 W) from 1969-10-28 to 1969-10-29 (NCEI Accession 7000422) ALL STAC Catalog 1969-10-28 1969-10-29 -72, 39, -71, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2089383028-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7000422_Not Applicable AIR PRESSURE and Other Data from GOSNOLD From NW Atlantic (limit-40 W) from 1969-10-28 to 1969-10-29 (NCEI Accession 7000422) NOAA_NCEI STAC Catalog 1969-10-28 1969-10-29 -72, 39, -71, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2089383028-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:7000981_Not Applicable A summary of seawater chemistry analysis of stations in North Atlantic Ocean from 1970-06-20 to 1970-07-03 (NCEI Accession 7000981) ALL STAC Catalog 1970-06-01 1970-07-01 -29.33, 50.01, -14.2, 55.56 https://cmr.earthdata.nasa.gov/search/concepts/C2089381614-NOAA_NCEI.umm_json Seawater chemistry data were collected using bottle from the USNS KANE in the North Atlantic Ocean. Data were collected from 20 July 1970 to 03 July 1970. The seawater chemistry data includes reactive phosphate, reactive silicate, and nitrate. proprietary
+gov.noaa.nodc:7000422_Not Applicable AIR PRESSURE and Other Data from GOSNOLD From NW Atlantic (limit-40 W) from 1969-10-28 to 1969-10-29 (NCEI Accession 7000422) ALL STAC Catalog 1969-10-28 1969-10-29 -72, 39, -71, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2089383028-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7000981_Not Applicable A summary of seawater chemistry analysis of stations in North Atlantic Ocean from 1970-06-20 to 1970-07-03 (NCEI Accession 7000981) NOAA_NCEI STAC Catalog 1970-06-01 1970-07-01 -29.33, 50.01, -14.2, 55.56 https://cmr.earthdata.nasa.gov/search/concepts/C2089381614-NOAA_NCEI.umm_json Seawater chemistry data were collected using bottle from the USNS KANE in the North Atlantic Ocean. Data were collected from 20 July 1970 to 03 July 1970. The seawater chemistry data includes reactive phosphate, reactive silicate, and nitrate. proprietary
+gov.noaa.nodc:7000981_Not Applicable A summary of seawater chemistry analysis of stations in North Atlantic Ocean from 1970-06-20 to 1970-07-03 (NCEI Accession 7000981) ALL STAC Catalog 1970-06-01 1970-07-01 -29.33, 50.01, -14.2, 55.56 https://cmr.earthdata.nasa.gov/search/concepts/C2089381614-NOAA_NCEI.umm_json Seawater chemistry data were collected using bottle from the USNS KANE in the North Atlantic Ocean. Data were collected from 20 July 1970 to 03 July 1970. The seawater chemistry data includes reactive phosphate, reactive silicate, and nitrate. proprietary
gov.noaa.nodc:7001081_Not Applicable Characteristics of Sediments in the James River Estuary, Virginia, 1968 (NCEI Accession 7001081) NOAA_NCEI STAC Catalog 1966-04-01 1967-08-30 -77, 36.7, -76.15, 37.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089382141-NOAA_NCEI.umm_json This report presents data on the physical and chemical characteristics of bottom sediments in the James River estuary, Virgina. The data were generated as part of a comprehensive study of sedimentation in which the initial objective was to broadly define the distribution of sediment properties. proprietary
gov.noaa.nodc:7100000_Not Applicable Cloud amount/frequency, NITRATE and other data from NOAA Ship DISCOVERER, JAMES COOK and other platforms from 1964-08-24 to 1971-11-17 (NCEI Accession 7100000) NOAA_NCEI STAC Catalog 1964-08-24 1971-11-17 -155.5, -66.7, 175.2, 50.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089383124-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7100048_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM and Other Platforms From NE Pacific (limit-180) from 1969-08-01 to 1969-08-31 (NCEI Accession 7100048) NOAA_NCEI STAC Catalog 1969-08-01 1969-08-31 -85, 7, -75, 12 https://cmr.earthdata.nasa.gov/search/concepts/C2089383261-NOAA_NCEI.umm_json Not provided proprietary
@@ -18851,8 +18852,8 @@ gov.noaa.nodc:7100165_Not Applicable Chemical, physical, and other data collecte
gov.noaa.nodc:7100603_Not Applicable Chemical, physical, and other data collected using bottle, BT, current meter, MBT, meteorological sensors, and secchi disk casts in the North Pacific Ocean as part of the California Cooperative Fisheries Investigation (CALCOFI) project, from 1968-01-01 to 1968-12-04 (NCEI Accession 7100603) NOAA_NCEI STAC Catalog 1968-01-01 1968-12-04 -122.9, 36.6, -121.9, 37 https://cmr.earthdata.nasa.gov/search/concepts/C2089381029-NOAA_NCEI.umm_json Chemical, physical, and other data were collected using bottle, BT, current meter, MBT, meteorological sensors, and secchi disk casts from January 1, 1968 to December 4, 1968. Data were submitted by Stanford University; Hopkins Marine Station as part of the California Cooperative Fisheries Investigation (CALCOFI) project. Data were processed by NODC to the NODC standard F004 water physics and chemistry format. Full F004 Format descriptions are available from the NODC homepage at www.nodc.noaa.gov/. The F004 format contains data from measurements and analysis of physical and chemical characteristics of the water column. Chemical parameters that may be recorded are salinity, pH and concentration of oxygen, ammonia, nitrate, phosphate, chlorophyll and suspended solids. Physical parameters that may be recorded include temperature, density (sigma-t), transmissivity and current velocity (east-west and north-south components). Cruise and station information may include environmental conditions of the study site at the time of observation. Data are very sparse prior to 1951. proprietary
gov.noaa.nodc:7200096_Not Applicable Cloud amount/frequency, NITRATE and other data from EASTWARD from 1968-02-23 to 1971-11-16 (NCEI Accession 7200096) NOAA_NCEI STAC Catalog 1968-02-23 1971-11-16 -86.4, 11, -61.1, 37.1 https://cmr.earthdata.nasa.gov/search/concepts/C2089383889-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7200319_Not Applicable Cloud amount/frequency, NITRATE and other data from BELLOWS from 1972-02-02 to 1972-02-10 (NCEI Accession 7200319) NOAA_NCEI STAC Catalog 1972-02-02 1972-02-10 -85.4, 27.2, -82.8, 29.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089384562-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:7200320_Not Applicable AIR PRESSURE and Other Data from UNKNOWN PLATFORMS and Other Platforms from 1955-03-01 to 1970-08-13 (NCEI Accession 7200320) NOAA_NCEI STAC Catalog 1955-03-01 1970-08-13 -71.9, 29.4, 8.8, 65.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089384570-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7200320_Not Applicable AIR PRESSURE and Other Data from UNKNOWN PLATFORMS and Other Platforms from 1955-03-01 to 1970-08-13 (NCEI Accession 7200320) ALL STAC Catalog 1955-03-01 1970-08-13 -71.9, 29.4, 8.8, 65.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089384570-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:7200320_Not Applicable AIR PRESSURE and Other Data from UNKNOWN PLATFORMS and Other Platforms from 1955-03-01 to 1970-08-13 (NCEI Accession 7200320) NOAA_NCEI STAC Catalog 1955-03-01 1970-08-13 -71.9, 29.4, 8.8, 65.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089384570-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7200698_Not Applicable Cloud amount/frequency, NITRATE and other data from EASTWARD from 1971-12-31 to 1972-05-06 (NCEI Accession 7200698) NOAA_NCEI STAC Catalog 1971-12-31 1972-05-06 -81.3, 17, -66.5, 37.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089381211-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7201127_Not Applicable Cloud amount/frequency, NITRATE and other data from EASTWARD from 1972-06-25 to 1972-06-27 (NCEI Accession 7201127) NOAA_NCEI STAC Catalog 1972-06-25 1972-06-27 -76.7, 34, -75.8, 34.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089381653-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7201380_Not Applicable Cloud amount/frequency, NITRATE and other data from EASTWARD from 1971-07-19 to 1972-11-04 (NCEI Accession 7201380) NOAA_NCEI STAC Catalog 1971-07-19 1972-11-04 -80.7, 30.4, -72.7, 38.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089382013-NOAA_NCEI.umm_json Not provided proprietary
@@ -18877,8 +18878,8 @@ gov.noaa.nodc:7600769_Not Applicable Cloud amount/frequency, NITRATE and other d
gov.noaa.nodc:7601177_Not Applicable Cloud amount/frequency, NITRATE and other data from MURRE II in the NE Pacific from 1975-06-20 to 1976-03-29 (NCEI Accession 7601177) NOAA_NCEI STAC Catalog 1975-06-20 1976-03-29 -135.7, 58, -134.2, 58.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089384847-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7601212_Not Applicable BENTHIC SPECIES and Other Data from KANA KEOKI From Gulf of Mexico from 1974-10-26 to 1974-12-21 (NCEI Accession 7601212) NOAA_NCEI STAC Catalog 1974-10-26 1974-12-21 -100, 17, -81, 31.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089384895-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7601237_Not Applicable Chemical and physical data from thermistor, fluorometer, and bottle casts in the Patuxent River from 1972-10-15 to 1972-10-19 (NCEI Accession 7601237) NOAA_NCEI STAC Catalog 1972-10-15 1972-10-19 -76.7, 38, -76.7, 42 https://cmr.earthdata.nasa.gov/search/concepts/C2089384911-NOAA_NCEI.umm_json "The Patuxent River estuary was investigated over a 25-hour tidal cycle from October 17-18, 1972, during the Patuxent River Cooperative Study (conducted by the University of Maryland). These data were collected as part of a joint investigation by the University of Maryland's Center for Environmental and Estuarine Studies (Chesapeake Biological Lab) and the Institute for Fluid Dynamics and Applied Mathematics (College Park, Maryland). The resulting chemical, physical, and biological data were assembled into a format that could be utilized by investigators, collectively titled the Patuxent River Data Bank. The Patuxent River Data Bank was submitted to NODC on a 9-track, 1600 BPI tape in EBCDIC and contains headers and one data file. Heat concentration (in kilocalories/liter) and instantaneous flux magnitude (in megacalories/square meter/second) were recorded over the tidal cycle. Other data associated with this study are filed under NODC Reference #'s L01574 and L01576; all data are in the Level-A directory under L01574.001. Data associated with marine chemistry include: Dissolved organic carbon (milligrams/liter), Particulate carbon (milligrams/liter), salts (grams/liter), Dissolved oxygen (milligrams/liter), and total particulates (milligrams/liter). Instantaneous flux magnitudes for carbon were measured in grams/liter; for salts, in kilograms/liter; for oxygen, in milligrams/liter; and for total particulates, milligrams/liter. Parameters associated with primary productivity (L505) include: Nitrate +Nitrite conc., Ammonia Nitrogen conc., Total Kjeldahl Nitrogen, Organic Phosphate conc., Total Hydrolyzable Phosphate, Active Chlorophyll-a, and Total Chlorophyll. Nutrients were measured in milligrams/liter; chlorophyll concentrations were measured in micrograms/liter. Instantaneous flux magnitudes were measured in milligrams/square meter/second. Additional data collected during this investigation are filed under NODC Reference #'s L01575 and one tape of Patuxent River Estuary Hydro data ""OLD STUFF""" proprietary
-gov.noaa.nodc:7601613_Not Applicable AIR PRESSURE and Other Data from TIDE STATIONS From North American Coastline-North and Others from 1972-01-01 to 1974-06-30 (NCEI Accession 7601613) ALL STAC Catalog 1972-01-01 1974-06-30 -77, 37, -76, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2089384776-NOAA_NCEI.umm_json This entry contains tidal information for Chesapeake Bay. Data was submitted by Saul Berkman, NOS Tides Branch, Oceanographic Division. These data are in NODC format. These data were collected roughly 37-39 degrees N, 75 degrees W (stations were in Baltimore, Bayport VA, Cambridge MD, Cheathem Annex VA, Chesapeake City, MD, Gaskins Point, VA, Hampton Roads, VA, Kiptopeke Beach VA, Lower Marlboro, MD, Old Pt Comfort VA, Portsmouth VA, Solomons MD, Taylor Island MD, Washington DC, and Windmill Point VA. The data are in half-hourly units and includes latitude, longitude, date, time, and tidal height. The documentation describes the record format. Tide heights are referred to North American Datum (NAD) 1929. proprietary
gov.noaa.nodc:7601613_Not Applicable AIR PRESSURE and Other Data from TIDE STATIONS From North American Coastline-North and Others from 1972-01-01 to 1974-06-30 (NCEI Accession 7601613) NOAA_NCEI STAC Catalog 1972-01-01 1974-06-30 -77, 37, -76, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2089384776-NOAA_NCEI.umm_json This entry contains tidal information for Chesapeake Bay. Data was submitted by Saul Berkman, NOS Tides Branch, Oceanographic Division. These data are in NODC format. These data were collected roughly 37-39 degrees N, 75 degrees W (stations were in Baltimore, Bayport VA, Cambridge MD, Cheathem Annex VA, Chesapeake City, MD, Gaskins Point, VA, Hampton Roads, VA, Kiptopeke Beach VA, Lower Marlboro, MD, Old Pt Comfort VA, Portsmouth VA, Solomons MD, Taylor Island MD, Washington DC, and Windmill Point VA. The data are in half-hourly units and includes latitude, longitude, date, time, and tidal height. The documentation describes the record format. Tide heights are referred to North American Datum (NAD) 1929. proprietary
+gov.noaa.nodc:7601613_Not Applicable AIR PRESSURE and Other Data from TIDE STATIONS From North American Coastline-North and Others from 1972-01-01 to 1974-06-30 (NCEI Accession 7601613) ALL STAC Catalog 1972-01-01 1974-06-30 -77, 37, -76, 39 https://cmr.earthdata.nasa.gov/search/concepts/C2089384776-NOAA_NCEI.umm_json This entry contains tidal information for Chesapeake Bay. Data was submitted by Saul Berkman, NOS Tides Branch, Oceanographic Division. These data are in NODC format. These data were collected roughly 37-39 degrees N, 75 degrees W (stations were in Baltimore, Bayport VA, Cambridge MD, Cheathem Annex VA, Chesapeake City, MD, Gaskins Point, VA, Hampton Roads, VA, Kiptopeke Beach VA, Lower Marlboro, MD, Old Pt Comfort VA, Portsmouth VA, Solomons MD, Taylor Island MD, Washington DC, and Windmill Point VA. The data are in half-hourly units and includes latitude, longitude, date, time, and tidal height. The documentation describes the record format. Tide heights are referred to North American Datum (NAD) 1929. proprietary
gov.noaa.nodc:7601642_Not Applicable Bacteria, taxonomic code, and other data collected from G.W. PIERCE in North Atlantic Ocean from sediment sampler; 1976-02-20 to 1976-03-23 (NCEI Accession 7601642) NOAA_NCEI STAC Catalog 1976-02-20 1976-03-23 -75.3, 37.1, -71.9, 39.9 https://cmr.earthdata.nasa.gov/search/concepts/C2089384806-NOAA_NCEI.umm_json Bacteria, taxonomic code, and other data were collected using sediment sampler and other instruments in the North Atlantic Ocean from G.W. PIERCE. Data were collected from 20 February 1976 to 23 March 1976 by Virginia Institute of Marine Science in Gloucester Point with support from the Ocean Continental Shelf - Mid Atlantic (OCS-Mid Atlantic) project. proprietary
gov.noaa.nodc:7601772_Not Applicable Cloud amount/frequency, NITRATE and other data from NOAA Ship OREGON II in the NW Atlantic from 1976-02-20 to 1976-02-25 (NCEI Accession 7601772) NOAA_NCEI STAC Catalog 1976-02-20 1976-02-25 -74.4, 36.8, -72.6, 38.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089384997-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:7617993_Not Applicable Cloud amount/frequency, NITRATE and other data from CAPRICORNE from 1974-07-25 to 1974-08-10 (NCEI Accession 7617993) NOAA_NCEI STAC Catalog 1974-07-25 1974-08-10 -10.3, -2.2, -3.9, 4.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089385626-NOAA_NCEI.umm_json Not provided proprietary
@@ -19162,8 +19163,8 @@ gov.noaa.nodc:9500149_Not Applicable ALACE subsurface drifter data in South Paci
gov.noaa.nodc:9500152_Not Applicable BAROMETRIC PRESSURE and Other Data from AURORA AUSTRALIS and Other Platforms from 1991-01-06 to 1992-03-06 (NCEI Accession 9500152) NOAA_NCEI STAC Catalog 1991-01-06 1992-03-06 67.5, -69.5, 135.4, -50.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089386699-NOAA_NCEI.umm_json The Conductivity, Temperature and Depth (CTD) and other data were collected from Ship AURORA AUSTRALIS. The data was collected over a period spanning from January 6, 1991 and March 6, 1992. Data from 343 casts containing 185,102 records was submitted via File Transfer Protocol by Ms. Edwina Tanner, Antarctic Cooperative Research Centre, University of Tasmania, Australia. proprietary
gov.noaa.nodc:9500160_Not Applicable BAROMETRIC PRESSURE and Other Data from ALPHA HELIX From Chukchi Sea from 1995-08-24 to 1995-09-01 (NCEI Accession 9500160) NOAA_NCEI STAC Catalog 1995-08-24 1995-09-01 163.988167, 66.665667, -168.998, 71.312667 https://cmr.earthdata.nasa.gov/search/concepts/C2089386823-NOAA_NCEI.umm_json The Conductivity, Temperature and Depth (CTD) and other data were collected from 73 stations in Chukchi Sea and East Siberian Sea area. The station numbers are 1-6, 8-30, 32-74, 76. Data was collected from Ship ALPHA HELIX cruise HX189. The data was collected BY Dr. J. Grebmeier of the University of Tennessee over a period spanning from August 24, 1995 to September 1, 1995. This project was funded by Office of Naval Research under grant no: NAVY N00014-94-1-1042Grebmeier. Data in NODC file format F022 was submitted by Dr. Chirk Chu, Institute of Marine Science, University of Alaska, Fairbanks. proprietary
gov.noaa.nodc:9600001_Not Applicable BAROMETRIC PRESSURE and Other Data from ALPHA HELIX From Chukchi Sea from 1995-09-10 to 1995-10-08 (NCEI Accession 9600001) NOAA_NCEI STAC Catalog 1995-09-10 1995-10-08 160, 52, -156, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2089386837-NOAA_NCEI.umm_json The Conductivity, Temperature and Depth (CTD) and other data were collected in Chukchi Sea as part of Office of Naval Research project. Data was collected from Ship ALPHA HELIX cruise HX-190. The data was collected over a period spanning from September 11, 1995 to October 8, 1995. Data was collected from 209 CTD stations by Institute of Marine Science, University of Alaska, Fairbanks, AK and was submitted by Dr Thomas Weingartner via File transfer Protocol in F022 file format of NODC. proprietary
-gov.noaa.nodc:9600025_Not Applicable AIR PRESSURE and Other Data from SHI YAN 3 From Antarctic and Others from 1992-11-09 to 1993-02-24 (NCEI Accession 9600025) ALL STAC Catalog 1992-11-09 1993-02-24 158, -2, 158, -2 https://cmr.earthdata.nasa.gov/search/concepts/C2089386973-NOAA_NCEI.umm_json The accession contains Surface Wave data and Sea Surface Temperature (SST) data collected as part of Tropical Ocean Global Atmosphere (TOGA) and Coupled Ocean-Atmosphere Response Experiment (COARE) International Project by a remote measuring buoy. The data was collected in Southern Oceans (> 60 degrees South), TOGA Area - Pacific (30 N to 30 S) from ship SHI YAN 3 between November 9, 1992 and February 24, 1993. Data was submitted by Chen Junchang of South China Sea Institute of Oceanology, Chinese Academy of Sciences. The data was made available by TOGA COARE International Project Office (TCIPO) via FTP. During the TOGA COARE Intensive Observing Period (IOP), the PRC R/V Shiyan #3 was stationed at 2 14'S, 158E for the three legs of data collection. Good format description accompanies the data. proprietary
gov.noaa.nodc:9600025_Not Applicable AIR PRESSURE and Other Data from SHI YAN 3 From Antarctic and Others from 1992-11-09 to 1993-02-24 (NCEI Accession 9600025) NOAA_NCEI STAC Catalog 1992-11-09 1993-02-24 158, -2, 158, -2 https://cmr.earthdata.nasa.gov/search/concepts/C2089386973-NOAA_NCEI.umm_json The accession contains Surface Wave data and Sea Surface Temperature (SST) data collected as part of Tropical Ocean Global Atmosphere (TOGA) and Coupled Ocean-Atmosphere Response Experiment (COARE) International Project by a remote measuring buoy. The data was collected in Southern Oceans (> 60 degrees South), TOGA Area - Pacific (30 N to 30 S) from ship SHI YAN 3 between November 9, 1992 and February 24, 1993. Data was submitted by Chen Junchang of South China Sea Institute of Oceanology, Chinese Academy of Sciences. The data was made available by TOGA COARE International Project Office (TCIPO) via FTP. During the TOGA COARE Intensive Observing Period (IOP), the PRC R/V Shiyan #3 was stationed at 2 14'S, 158E for the three legs of data collection. Good format description accompanies the data. proprietary
+gov.noaa.nodc:9600025_Not Applicable AIR PRESSURE and Other Data from SHI YAN 3 From Antarctic and Others from 1992-11-09 to 1993-02-24 (NCEI Accession 9600025) ALL STAC Catalog 1992-11-09 1993-02-24 158, -2, 158, -2 https://cmr.earthdata.nasa.gov/search/concepts/C2089386973-NOAA_NCEI.umm_json The accession contains Surface Wave data and Sea Surface Temperature (SST) data collected as part of Tropical Ocean Global Atmosphere (TOGA) and Coupled Ocean-Atmosphere Response Experiment (COARE) International Project by a remote measuring buoy. The data was collected in Southern Oceans (> 60 degrees South), TOGA Area - Pacific (30 N to 30 S) from ship SHI YAN 3 between November 9, 1992 and February 24, 1993. Data was submitted by Chen Junchang of South China Sea Institute of Oceanology, Chinese Academy of Sciences. The data was made available by TOGA COARE International Project Office (TCIPO) via FTP. During the TOGA COARE Intensive Observing Period (IOP), the PRC R/V Shiyan #3 was stationed at 2 14'S, 158E for the three legs of data collection. Good format description accompanies the data. proprietary
gov.noaa.nodc:9600039_Not Applicable Bacterial production, primary production, phytoplankton, zooplankton, biological analysis of fish, and massive fish length data from the EVRIKA and other platforms in the Antarctic from 23 February 1980 to 09 December 1988 (NCEI Accession 9600039) NOAA_NCEI STAC Catalog 1980-02-23 1988-12-09 -62.76, -63.98, -31.83, -50 https://cmr.earthdata.nasa.gov/search/concepts/C2089387013-NOAA_NCEI.umm_json Bacterial production, primary production, phytoplankton, zooplankton, biological analysis of fish, and massive fish length data were collected from the EVRIKA and other platforms in the Antarctic. Data were collected by the Atlantic Research Institute of Fishing Economy and Ocean from 23 February 1980 to 09 December 1988. proprietary
gov.noaa.nodc:9600065_Not Applicable BAROMETRIC PRESSURE and Other Data from THOMAS G. THOMPSON and Other Platforms From TOGA Area - Pacific (30 N to 30 S) from 1992-10-13 to 1992-12-13 (NCEI Accession 9600065) NOAA_NCEI STAC Catalog 1992-10-13 1992-12-13 -149.389635, -17.193678, -134.31313, 12.067383 https://cmr.earthdata.nasa.gov/search/concepts/C2089387122-NOAA_NCEI.umm_json The data in this accession was collected as part of Joint Global Ocean Flux Study/Equatorial Pacific Basin Study (JGOFS/EQPAC) in TOGA Area - Pacific (30 N to 30 S) using Ship THOMAS G. THOMPSON. CTD Data were collected by University of Washington, Seattle, WA between October 13, 1992 and December 13, 1992. Five Files of CTD data were submitted by Dr. Wilford Gardner. Good documentation accompanies this data. proprietary
gov.noaa.nodc:9600140_Not Applicable BAROMETRIC PRESSURE and Other Data from NOAA Ship ALBATROSS IV and Other Platforms From NW Atlantic (limit-40 W) from 1995-02-11 to 1995-07-20 (NCEI Accession 9600140) NOAA_NCEI STAC Catalog 1995-02-11 1995-07-20 -69.237, 40.413, -65.647, 42.335 https://cmr.earthdata.nasa.gov/search/concepts/C2089387550-NOAA_NCEI.umm_json Hydrochemical, hydrophysical, and other data were collected from the ENDEAVOR and NOAA Ship ALBATROSS IV from February 11, 1995 to July 20, 1995. Data were submitted by Dr. David Mountain from the US DOC; NOAA; NATIONAL MARINE FISHERIES SERVICE - WOODS HOLE. These data were collected using meteorological sensors, secchi disks, transmissometers, bottle casts, and CTD casts in the Northwest Atlantic Ocean. proprietary
@@ -19196,18 +19197,18 @@ gov.noaa.nodc:9800123_Not Applicable AIR PRESSURE and Other Data from FIXED PLAT
gov.noaa.nodc:9800129_Not Applicable Chemical, zooplankton, and phytoplankton data from CTD and other instruments in the Mississippi River and Gulf of Mexico as part of the Nutrient Enhanced Coastal Ocean Productivity (NECOP) project, from 1985-07-15 to 1993-05-12 (NCEI Accession 9800129) NOAA_NCEI STAC Catalog 1985-07-15 1993-05-12 -90.28, 28.52, -89.41, 29.7 https://cmr.earthdata.nasa.gov/search/concepts/C2089386593-NOAA_NCEI.umm_json Chemical, zooplankton, and phytoplankton data were collected using bottle, CTD, fluorometer, oxygen meter, GPS, plankton trap, and sediment sampler from NOAA Ship MALCOLM BALDRIGE and NOAA Ship RESEARCHER. Data were collected from the Mississippi River and Gulf of Mexico from July 15, 1985 to May 12, 1993. Data were submitted by Dr. Nancy Rabalais from the Louisiana Universities Marine Consortium as part of the Nutrient Enhanced Coastal Ocean Productivity (NECOP) project. proprietary
gov.noaa.nodc:9800160_Not Applicable Chemical data collected from THOMAS G. THOMPSON using CTD and bottle casts in Arabian Sea from 1995-03-07 to 1995-08-15 (NCEI Accession 9800160) NOAA_NCEI STAC Catalog 1995-03-07 1995-08-15 57, 9, 68, 22 https://cmr.earthdata.nasa.gov/search/concepts/C2089386883-NOAA_NCEI.umm_json Chemical data were collected using CTD and bottle casts in the Arabian Sea from THOMAS G. THOMPSON. Data were collected from 07 March 1995 to 15 August 1995 by Lamont-Doherty Earth Observatory with support from the U.S. Joint Global Ocean Flux Study / Arabian Sea Process Studies (JOGFS/Arabian Sea) project. proprietary
gov.noaa.nodc:9800161_Not Applicable Chemical data collected from THOMAS G. THOMPSON using CTD and bottle casts in Arabian Sea from 1995-01-08 to 1995-11-26 (NCEI Accession 9800161) NOAA_NCEI STAC Catalog 1995-01-08 1995-11-26 56, 9, 68, 23 https://cmr.earthdata.nasa.gov/search/concepts/C2089386911-NOAA_NCEI.umm_json Chemical data were collected using CTD and bottle casts in the Arabian Sea from THOMAS G. THOMPSON. Data were collected from 08 January 1995 to 26 November 1995 by Harvard University with support from the U.S. Joint Global Ocean Flux Study / Arabian Sea Process Studies (JOGFS/Arabian Sea) project. proprietary
-gov.noaa.nodc:9800197_Not Applicable Algal species and other data collected using photographs in the southern coast of the island of Ofu from 1992-09-08 to 1992-09-11 (NCEI Accession 9800197) NOAA_NCEI STAC Catalog 1992-09-08 1992-09-11 -169.7, -14.2, -169.7, -14.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089387161-NOAA_NCEI.umm_json The US Congress has authorized the Department of the Interior to enter into a lease agreement with the Governor of American Samoa to establish the National Park of American Samoa. This park would include a nearshore reef along the southern coast of the island of Ofu. This fringing reef on Ofu provides a natural lagoon habitat which is uncommon in American Samoa. This area supports a local subsistence fishery and provides excellent opportunities for diving and snorkeling. A survey of the nearshore reefs in the area of the proposed national park at Ofu was conducted between 7-12 September, 1992. The goals of the survey were to: 1) collect baseline data on the current status of the reefs and reef resources in the area, 2) to establish long-term monitoring stations to enable documentation of the health of the reef communities through time, and 3) to contribute information to a comprehensive coastal resource survey of Tutuila and the Manua Islands. The overall purpose of the work was to design and implement the biotic component of a reef monitoring program for the areas within and adjacent to the proposed national park site. proprietary
gov.noaa.nodc:9800197_Not Applicable Algal species and other data collected using photographs in the southern coast of the island of Ofu from 1992-09-08 to 1992-09-11 (NCEI Accession 9800197) ALL STAC Catalog 1992-09-08 1992-09-11 -169.7, -14.2, -169.7, -14.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089387161-NOAA_NCEI.umm_json The US Congress has authorized the Department of the Interior to enter into a lease agreement with the Governor of American Samoa to establish the National Park of American Samoa. This park would include a nearshore reef along the southern coast of the island of Ofu. This fringing reef on Ofu provides a natural lagoon habitat which is uncommon in American Samoa. This area supports a local subsistence fishery and provides excellent opportunities for diving and snorkeling. A survey of the nearshore reefs in the area of the proposed national park at Ofu was conducted between 7-12 September, 1992. The goals of the survey were to: 1) collect baseline data on the current status of the reefs and reef resources in the area, 2) to establish long-term monitoring stations to enable documentation of the health of the reef communities through time, and 3) to contribute information to a comprehensive coastal resource survey of Tutuila and the Manua Islands. The overall purpose of the work was to design and implement the biotic component of a reef monitoring program for the areas within and adjacent to the proposed national park site. proprietary
+gov.noaa.nodc:9800197_Not Applicable Algal species and other data collected using photographs in the southern coast of the island of Ofu from 1992-09-08 to 1992-09-11 (NCEI Accession 9800197) NOAA_NCEI STAC Catalog 1992-09-08 1992-09-11 -169.7, -14.2, -169.7, -14.2 https://cmr.earthdata.nasa.gov/search/concepts/C2089387161-NOAA_NCEI.umm_json The US Congress has authorized the Department of the Interior to enter into a lease agreement with the Governor of American Samoa to establish the National Park of American Samoa. This park would include a nearshore reef along the southern coast of the island of Ofu. This fringing reef on Ofu provides a natural lagoon habitat which is uncommon in American Samoa. This area supports a local subsistence fishery and provides excellent opportunities for diving and snorkeling. A survey of the nearshore reefs in the area of the proposed national park at Ofu was conducted between 7-12 September, 1992. The goals of the survey were to: 1) collect baseline data on the current status of the reefs and reef resources in the area, 2) to establish long-term monitoring stations to enable documentation of the health of the reef communities through time, and 3) to contribute information to a comprehensive coastal resource survey of Tutuila and the Manua Islands. The overall purpose of the work was to design and implement the biotic component of a reef monitoring program for the areas within and adjacent to the proposed national park site. proprietary
gov.noaa.nodc:9800199_Not Applicable BACTERIA - BACTERIAL DENSITY and Other Data from HERMANO GINES from 1996-07-09 to 1997-07-09 (NCEI Accession 9800199) NOAA_NCEI STAC Catalog 1996-07-09 1997-07-09 -64.7, 10.5, -64.7, 10.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089387176-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900010_Not Applicable CAS (CHEMICAL ABSTRACTS SOCIETY) PARAMETER CODES and Other Data from THOMAS G. THOMPSON From Arabian Sea from 1995-03-18 to 1997-08-13 (NCEI Accession 9900010) NOAA_NCEI STAC Catalog 1995-03-18 1997-08-13 56.5, 10, 68.8, 24.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089387251-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900014_Not Applicable CAS (CHEMICAL ABSTRACTS SOCIETY) PARAMETER CODES and Other Data from THOMAS G. THOMPSON From Arabian Sea from 1995-01-09 to 1995-09-12 (NCEI Accession 9900014) NOAA_NCEI STAC Catalog 1995-01-09 1995-09-12 57.3, 10, 68.8, 22.5 https://cmr.earthdata.nasa.gov/search/concepts/C2089387273-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900015_Not Applicable CARBON DIOXIDE - PARTIAL PRESSURE (pCO2) - SEA and Other Data from NOAA Ship DISCOVERER and Other Platforms from 1987-05-19 to 1994-01-07 (NCEI Accession 9900015) NOAA_NCEI STAC Catalog 1987-05-19 1994-01-07 -179.9, -70.3, 179.9, 54.9 https://cmr.earthdata.nasa.gov/search/concepts/C2089387289-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:9900022_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM and Other Platforms from 1998-08-01 to 1998-12-31 (NCEI Accession 9900022) NOAA_NCEI STAC Catalog 1998-08-01 1998-12-31 -124.1, 44.6, -124, 44.8 https://cmr.earthdata.nasa.gov/search/concepts/C2089387361-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900022_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM and Other Platforms from 1998-08-01 to 1998-12-31 (NCEI Accession 9900022) ALL STAC Catalog 1998-08-01 1998-12-31 -124.1, 44.6, -124, 44.8 https://cmr.earthdata.nasa.gov/search/concepts/C2089387361-NOAA_NCEI.umm_json Not provided proprietary
-gov.noaa.nodc:9900054_Not Applicable Algal species and other data collected using photographs in the South Pacific Ocean from 1992-01-02 to 1992-12-31 (NCEI Accession 9900054) NOAA_NCEI STAC Catalog 1992-01-02 1992-12-31 -170.8, -14.4, -170.6, -14.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089387610-NOAA_NCEI.umm_json Data from a 1992 survey of the American Samoa coral reef ecosystem was received from Dr. Barry Smith of the University of Guam. The digital files replace a paper report submitted to NODC in Fall 1998. This study was part of the American Samoa Coastal Resources Inventory (ASCRI), partly funded by Sea Grant. His component of the study focuses on a systematic inventory of conspicuous marine macro-invertebrates observations. proprietary
+gov.noaa.nodc:9900022_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM and Other Platforms from 1998-08-01 to 1998-12-31 (NCEI Accession 9900022) NOAA_NCEI STAC Catalog 1998-08-01 1998-12-31 -124.1, 44.6, -124, 44.8 https://cmr.earthdata.nasa.gov/search/concepts/C2089387361-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900054_Not Applicable Algal species and other data collected using photographs in the South Pacific Ocean from 1992-01-02 to 1992-12-31 (NCEI Accession 9900054) ALL STAC Catalog 1992-01-02 1992-12-31 -170.8, -14.4, -170.6, -14.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089387610-NOAA_NCEI.umm_json Data from a 1992 survey of the American Samoa coral reef ecosystem was received from Dr. Barry Smith of the University of Guam. The digital files replace a paper report submitted to NODC in Fall 1998. This study was part of the American Samoa Coastal Resources Inventory (ASCRI), partly funded by Sea Grant. His component of the study focuses on a systematic inventory of conspicuous marine macro-invertebrates observations. proprietary
-gov.noaa.nodc:9900094_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-01-01 to 1999-04-29 (NCEI Accession 9900094) ALL STAC Catalog 1999-01-01 1999-04-29 -124, 44.6, -124, 44.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089387865-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:9900054_Not Applicable Algal species and other data collected using photographs in the South Pacific Ocean from 1992-01-02 to 1992-12-31 (NCEI Accession 9900054) NOAA_NCEI STAC Catalog 1992-01-02 1992-12-31 -170.8, -14.4, -170.6, -14.3 https://cmr.earthdata.nasa.gov/search/concepts/C2089387610-NOAA_NCEI.umm_json Data from a 1992 survey of the American Samoa coral reef ecosystem was received from Dr. Barry Smith of the University of Guam. The digital files replace a paper report submitted to NODC in Fall 1998. This study was part of the American Samoa Coastal Resources Inventory (ASCRI), partly funded by Sea Grant. His component of the study focuses on a systematic inventory of conspicuous marine macro-invertebrates observations. proprietary
gov.noaa.nodc:9900094_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-01-01 to 1999-04-29 (NCEI Accession 9900094) NOAA_NCEI STAC Catalog 1999-01-01 1999-04-29 -124, 44.6, -124, 44.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089387865-NOAA_NCEI.umm_json Not provided proprietary
+gov.noaa.nodc:9900094_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-01-01 to 1999-04-29 (NCEI Accession 9900094) ALL STAC Catalog 1999-01-01 1999-04-29 -124, 44.6, -124, 44.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089387865-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900119_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-05-01 to 1999-06-30 (NCEI Accession 9900119) ALL STAC Catalog 1999-05-01 1999-06-30 -124, 44.6, -124, 44.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089388259-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900119_Not Applicable AIR PRESSURE and Other Data from FIXED PLATFORM from 1999-05-01 to 1999-06-30 (NCEI Accession 9900119) NOAA_NCEI STAC Catalog 1999-05-01 1999-06-30 -124, 44.6, -124, 44.6 https://cmr.earthdata.nasa.gov/search/concepts/C2089388259-NOAA_NCEI.umm_json Not provided proprietary
gov.noaa.nodc:9900158_Not Applicable CAS (CHEMICAL ABSTRACTS SOCIETY) PARAMETER CODES and Other Data from OCEANUS and Other Platforms from 1993-03-12 to 1993-03-23 (NCEI Accession 9900158) NOAA_NCEI STAC Catalog 1993-03-12 1993-03-23 -67.2, 31.7, -64.1, 36.8 https://cmr.earthdata.nasa.gov/search/concepts/C2089388472-NOAA_NCEI.umm_json Not provided proprietary
@@ -19646,8 +19647,8 @@ heard_bathy_gis_1 Heard and McDonald Islands - Bathymetric data created for 1:1
heard_coast_gis_1 Heard Island Coast GIS Dataset AU_AADC STAC Catalog 1997-04-04 1997-04-04 73.24, -53.21, 73.9, -52.95 https://cmr.earthdata.nasa.gov/search/concepts/C1214313514-AU_AADC.umm_json A coastline of Heard Island and McDonald Islands, created in the AMBIS (Australian Maritime Boundaries Information System) by Geoscience Australia (previously AUSLIG). proprietary
heard_dem_radarsat02_1 Heard Island RADARSAT (2002) Digital Elevation Model (DEM) AU_AADC STAC Catalog 2002-01-24 2002-03-13 73.18306, -53.27694, 73.97306, -52.80806 https://cmr.earthdata.nasa.gov/search/concepts/C1214308612-AU_AADC.umm_json "This dataset is a Digital Elevation Model (DEM) of Heard Island derived by interferometric processing from RADARSAT images acquired on 17 February 2002 and 13 March 2002. The DEM was created by a contractor for the Australian Antarctic Data Centre. The cell size is 10 metres. Processing stages included: 1 Detection of a coastline from a RADARSAT image of Heard Island acquired 24 January 2002 and rectified using ground control points provided by a second contractor. 2 Generation of the interferometric SAR (InSAR) DEM using the RADARSAT images acquired on 17 February 2002 and 13 March 2002. 3 Co-registration of the InSAR DEM with a DEM derived from stereoscopic RADARSAT images acquired in March and April of 1997 and described by the metadata record 'Heard Island RADARSAT (1997) DEM'. 4 Merging of the InSAR DEM with the 1997 stereoscopic DEM and the coastline detected in stage 1. The following are available for download from the Related URLs below: 1 The final DEM in ArcInfo interchange or ArcInfo ascii formats. 2 The rectified RADARSAT image of Heard Island acquired 24 January 2002. Rectified using ground control points and subsequently used in processing of the DEM. 3 Contours generated from the DEM and the island polygon (coastline) extracted from the rectified RADARSAT image acquired 24 January 2002. 4 A detailed deport describing the generation of the DEM. 5 A report by Dr Arko Lucieer Centre for Spatial Information Science School of Geography and Environmental Studies University of Tasmania Private Bag 76 Hobart 7001 Tasmania, Australia outlining some errors and artefacts in the DEM. Dr Lucieer produced this report while working for the Australian Antarctic Division. On 3 July 2003 Henk Brolsma (Mapping Officer, Australian Antarctic Division) wrote the following email to the contractor who created the DEM. ""What I'm really interested in are the 20 metre contours for the areas with high coherency. These are the areas where most of the field work takes place and where we have a need for contours with an accuracy better than 50 metres and my reason for using INSAR in the first instance. So can you send me: 1. The 20 metre contours for the areas with high coherency? 2. The zone or line where the INSAR and Stereo Imagery were integrated? This would be very useful for the metadata."" He did not receive a reply to that email and that was the reason why he was reluctant to make the DEM public. Since he won't now get a reply and the DEM is probably better than the 1997 DEM, he considers the 2002 DEM should now be published." proprietary
heard_dem_radarsat97_1 Heard Island RADARSAT (1997) Digital Elevation Model (DEM) AU_AADC STAC Catalog 1997-10-24 1997-10-24 73.238, -53.2, 73.89, -52.957 https://cmr.earthdata.nasa.gov/search/concepts/C1214313515-AU_AADC.umm_json A Digital Elevation Model (DEM) of Heard island, with a 50 metre grid interval, and held in UTM Zone 43(WGS-84) coordinates. Heights are referenced to mean sea level. 50 metre contours (including a coastline) were derived. Elevation range 0 - less than 2800m. proprietary
-heard_dem_terrasar_1 A Digital Elevation Model of Heard Island derived from TerraSAR satellite imagery ALL STAC Catalog 2009-10-31 2009-11-14 73.185, -53.266, 74.02, -52.931 https://cmr.earthdata.nasa.gov/search/concepts/C1214313516-AU_AADC.umm_json This dataset is a Digital Elevation Model (DEM) of Heard Island derived from TerraSAR_X imagery using radargrammetric methods. At least one pair of ascending images and one pair of descending images were used at each location. The TerraSAR_X stereo pairs were acquired between 31 October 2009 and 14 November 2009. The DEM was created by a contractor for the Australian Antarctic Data Centre. It is in geotiff format stored in a UTM zone 43 projection, horizontal datum WGS84. The cell size is 10 metres. Included with the DEM are some auxiliary files and documentation. This includes: 1 an xml file with metadata; 2 a shapefile detailing the images used for each part of the DEM; 3 a geotiff showing the correlation between the images used at each point in the DEM; 4 a spreadsheet with an accuracy assessment of the DEM using ground control points provided by the Australian Antarctic Data Centre. proprietary
heard_dem_terrasar_1 A Digital Elevation Model of Heard Island derived from TerraSAR satellite imagery AU_AADC STAC Catalog 2009-10-31 2009-11-14 73.185, -53.266, 74.02, -52.931 https://cmr.earthdata.nasa.gov/search/concepts/C1214313516-AU_AADC.umm_json This dataset is a Digital Elevation Model (DEM) of Heard Island derived from TerraSAR_X imagery using radargrammetric methods. At least one pair of ascending images and one pair of descending images were used at each location. The TerraSAR_X stereo pairs were acquired between 31 October 2009 and 14 November 2009. The DEM was created by a contractor for the Australian Antarctic Data Centre. It is in geotiff format stored in a UTM zone 43 projection, horizontal datum WGS84. The cell size is 10 metres. Included with the DEM are some auxiliary files and documentation. This includes: 1 an xml file with metadata; 2 a shapefile detailing the images used for each part of the DEM; 3 a geotiff showing the correlation between the images used at each point in the DEM; 4 a spreadsheet with an accuracy assessment of the DEM using ground control points provided by the Australian Antarctic Data Centre. proprietary
+heard_dem_terrasar_1 A Digital Elevation Model of Heard Island derived from TerraSAR satellite imagery ALL STAC Catalog 2009-10-31 2009-11-14 73.185, -53.266, 74.02, -52.931 https://cmr.earthdata.nasa.gov/search/concepts/C1214313516-AU_AADC.umm_json This dataset is a Digital Elevation Model (DEM) of Heard Island derived from TerraSAR_X imagery using radargrammetric methods. At least one pair of ascending images and one pair of descending images were used at each location. The TerraSAR_X stereo pairs were acquired between 31 October 2009 and 14 November 2009. The DEM was created by a contractor for the Australian Antarctic Data Centre. It is in geotiff format stored in a UTM zone 43 projection, horizontal datum WGS84. The cell size is 10 metres. Included with the DEM are some auxiliary files and documentation. This includes: 1 an xml file with metadata; 2 a shapefile detailing the images used for each part of the DEM; 3 a geotiff showing the correlation between the images used at each point in the DEM; 4 a spreadsheet with an accuracy assessment of the DEM using ground control points provided by the Australian Antarctic Data Centre. proprietary
heard_glacier_gis_1 Heard Island - Glacier extents mapped from satellite imagery and aerial photography. AU_AADC STAC Catalog 1987-01-01 1997-12-31 73.24, -53.21, 73.9, -52.95 https://cmr.earthdata.nasa.gov/search/concepts/C1214308621-AU_AADC.umm_json Abstract from: 'An inventory of present glaciers on Heard Island and their historical variation' by Andrew Ruddell. Heard Island is a large ice-covered volcanic cone situated in the south Indian Ocean. Its location enables unique climatic information to be obtained from a very remote and predominantly maritime region. Past studies show that while some glaciers have undergone major recession since the late 1940s, others, such as large non-calving glaciers, have shown little change in extent. The island is usually cloud covered and this has hampered aerial and ground based surveys. Using SPOT satellite imagery acquired in 1988 and supplemented by aerial photography in 1987 and a digital elevation model derived from 1997 Radarsat imagery, an inventory of glacier extent is provided and this indicates that there are a total of 29 glaciated basins (41 termini), with an area of 257 km2 and an estimated volume of 14.2 km3. The satellite imagery is used to rectify earlier estimates of glacier extent based on aerial photography in 1947 and 1980. Between 1947 and 1988 the glaciated area had decreased by 11% and volume by 12%. Approximately half of this occurred during the 1980s. A variety of historical records have been compiled and these provide evidence of glacier behaviour since the mid-1800s when they were at their greatest extent during the recorded period. The elevation range of a glacier is a good indication of glacier hypsometry and its sensitivity to mass balance and climate variations. Glaciers such as the Gotley are of large elevation range and high mass turnover. Such glaciers show little sensitivity to climate variations as they lose much of their ice through calving into the sea rather than surface melt. Glaciers of low elevation range such as those on the Laurens Peninsula are especially sensitive to climate change. Glaciers of this type indicate that while minor decadal fluctuations have occurred in the period from at least 1902 to the 1950s, the recession of many glaciers during the past 50 years has been unprecedented. The glacier variations correlate with observed temperature records. Observations of occasional volcanic eruptions since the 1880s indicate that most activity is related to lava flows from Mawson Peak and fumerole activity on its upper southwestern slope. This activity appears to have had little effect on the Gotley and Lied glaciers. proprietary
heard_ice_gis_1 Heard Island Ice Coverage GIS Dataset AU_AADC STAC Catalog 1991-04-07 1991-09-09 73.24, -53.21, 73.9, -52.95 https://cmr.earthdata.nasa.gov/search/concepts/C1214308622-AU_AADC.umm_json Heard Island, ice layer. This is a polygon dataset stored in the Geographical Information System (GIS). The ice layer shows ice/snow as depicted on the Heard Island satellite image map, published in 1991. The amount of ice/snow is as captured on the SPOT image 9 Jan 1988. proprietary
heard_is_sat_1 Heard Island and McDonald Islands Satellite Image Map 1:50000 AU_AADC STAC Catalog 1991-12-01 1991-12-31 73.24, -53.21, 73.9, -52.95 https://cmr.earthdata.nasa.gov/search/concepts/C1214308616-AU_AADC.umm_json Satellite image map of Heard Island and McDonald Islands, Antarctica. This map was produced for the Australian Antarctic Division by AUSLIG (now Geoscience Australia) Commercial, in Australia, in 1991. The map is at a scale of 1:50000, and was produced from multispectral space imagery SPOT 1 and SPOT 2 scenes, with some areas of photography. It is projected on a Transverse Mercator projection, and shows glaciers/ice shelves, stations/bases, refuges/depots, and gives some historical text information. The map has both geographical and UTM co-ordinates. proprietary
@@ -19733,8 +19734,8 @@ inishell-2-0-4_2.0.4 Inishell-2.0.4 ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5
inpe_CPTEC_GLOBAl_FORECAST Global Meteorological Model Analysis and Forecast Images (INPE/CPTEC) CEOS_EXTRA STAC Catalog 1970-01-01 -120, -60, 0, 30 https://cmr.earthdata.nasa.gov/search/concepts/C2227456094-CEOS_EXTRA.umm_json "CPTEC offers global model analysis and forecast images for twelve meteorological parameters. Forecast time steps range from the initial analysis each day out to six days. The user may choose forecasts from the most recent forecast run back to the previous 36 hours. Parameters Forecasted: Mean Sea Level Pressure Temperature at 1000 hPa Relative Humidity at 925 hPa, 850 hPa Vertical p_Velocity at 850 hPa, 500 hPa, 200 hPa Velocity Potential at 925 hPa, 200 hPa Stream Function at 925 hPa, 200 hPa 500/1000 hPa Thickness Advection of Temperature at 925 hPa, 850 hPa, 500 hPa Advection of Vorticity at 925 hPa, 850 hPa, 500 hPa Convergence of Humidity Flux at 925 hPa, 850 hPa Streamlines and Wind Speed at 925 hPa, 850 hPa, 200 hPa Total Precipitation Last 24 Hours All forecast images can be obtained via World Wide Web from the CPTEC Home Page. Link to: ""http://www.cptec.inpe.br/""" proprietary
input-data-for-break-point-detection-of-swiss-snow-depth-time-series_1.0 Input data for break point detection of Swiss snow depth time series ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815138-ENVIDAT.umm_json Data set consists of monthly mean values for snow depth and days with snow on the ground intended for the use of break detection with ACMANT, Climatol and HOMER. List and coordinates of stations used as well as metadata and break detection results from all three methods is included. ## Columns Monthly means for each hydrological year: Nov, Dec, Jan, Feb, Mar, Apr with May to Oct set to zero proprietary
input-data-for-impact-assessment-of-homogenised-snow-series_1.0 Input data for impact assessment of homogenised snow series ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226082287-ENVIDAT.umm_json # Input data for the following research article: Impact assessment of homogenised snow depth series on trends The data consists of separate output files from the following homogenisation methods: * Climatol * HOMER * interpQM The variable is seasonal mean snow depth (HSavg) plot.data is an additional data frame containing trends of HSavg (station, method, value, pvalue, altitude) proprietary
-insects_subsaharanAfrica A Checklist of the Insects of Subsaharan Africa ALL STAC Catalog 2000-01-01 13.68, -35.9, 33.98, -21.27 https://cmr.earthdata.nasa.gov/search/concepts/C1214611706-SCIOPS.umm_json "One of the most basic needs for inventorying, exploiting and monitoring the changes in the insect diversity of Africa is a complete list of species which are already know to occur in Africa. Surprisingly, such a basic list does not exist, despite some 250 years of formal scientific description of life on earth. The International Centre of Insect Physiology and Ecology (ICIPE), along with the National Museum of Natural History, is therefore sponsoring the production of the list, which will provide a reliable platform of 'standard' names for species on which many other projects depend. This list, or authority file, will greatly enhance communication both among scientists and between scientists and users of scientific data. The African list will also be a major contribution toward the proposed list of world species (e.g. the Global Biodiversity Information Facility (GBIF) and Species 2000 initiative of DIVERSITAS). A demonstration database is provided for the species of the orders Odonata (dragonflies and damselflies), Ephemeroptera (mayflies), Plecoptera (stoneflies), Megaloptera (alderflies), Hemiptera-Heteroptera (true bugs), Homoptera (cicadas, leafhoppers, planthoppers, scales, and others), and Trichoptera (caddisflies). Invitation to collaboration: Compilation of the checklist is being coordinated by Nearctica (formerly Entomological Information Specialists), because of their experience with Nomina Insecta Nearctica. We are attempting to collaborate with known specialists as contributors and reviewers, but we welcome additional suggestions of collaborators. Inquires can be directed to Scott Miller (miller.scott@nmnh.si.edu). Information was obtained from ""http://entomology.si.edu/""." proprietary
insects_subsaharanAfrica A Checklist of the Insects of Subsaharan Africa SCIOPS STAC Catalog 2000-01-01 13.68, -35.9, 33.98, -21.27 https://cmr.earthdata.nasa.gov/search/concepts/C1214611706-SCIOPS.umm_json "One of the most basic needs for inventorying, exploiting and monitoring the changes in the insect diversity of Africa is a complete list of species which are already know to occur in Africa. Surprisingly, such a basic list does not exist, despite some 250 years of formal scientific description of life on earth. The International Centre of Insect Physiology and Ecology (ICIPE), along with the National Museum of Natural History, is therefore sponsoring the production of the list, which will provide a reliable platform of 'standard' names for species on which many other projects depend. This list, or authority file, will greatly enhance communication both among scientists and between scientists and users of scientific data. The African list will also be a major contribution toward the proposed list of world species (e.g. the Global Biodiversity Information Facility (GBIF) and Species 2000 initiative of DIVERSITAS). A demonstration database is provided for the species of the orders Odonata (dragonflies and damselflies), Ephemeroptera (mayflies), Plecoptera (stoneflies), Megaloptera (alderflies), Hemiptera-Heteroptera (true bugs), Homoptera (cicadas, leafhoppers, planthoppers, scales, and others), and Trichoptera (caddisflies). Invitation to collaboration: Compilation of the checklist is being coordinated by Nearctica (formerly Entomological Information Specialists), because of their experience with Nomina Insecta Nearctica. We are attempting to collaborate with known specialists as contributors and reviewers, but we welcome additional suggestions of collaborators. Inquires can be directed to Scott Miller (miller.scott@nmnh.si.edu). Information was obtained from ""http://entomology.si.edu/""." proprietary
+insects_subsaharanAfrica A Checklist of the Insects of Subsaharan Africa ALL STAC Catalog 2000-01-01 13.68, -35.9, 33.98, -21.27 https://cmr.earthdata.nasa.gov/search/concepts/C1214611706-SCIOPS.umm_json "One of the most basic needs for inventorying, exploiting and monitoring the changes in the insect diversity of Africa is a complete list of species which are already know to occur in Africa. Surprisingly, such a basic list does not exist, despite some 250 years of formal scientific description of life on earth. The International Centre of Insect Physiology and Ecology (ICIPE), along with the National Museum of Natural History, is therefore sponsoring the production of the list, which will provide a reliable platform of 'standard' names for species on which many other projects depend. This list, or authority file, will greatly enhance communication both among scientists and between scientists and users of scientific data. The African list will also be a major contribution toward the proposed list of world species (e.g. the Global Biodiversity Information Facility (GBIF) and Species 2000 initiative of DIVERSITAS). A demonstration database is provided for the species of the orders Odonata (dragonflies and damselflies), Ephemeroptera (mayflies), Plecoptera (stoneflies), Megaloptera (alderflies), Hemiptera-Heteroptera (true bugs), Homoptera (cicadas, leafhoppers, planthoppers, scales, and others), and Trichoptera (caddisflies). Invitation to collaboration: Compilation of the checklist is being coordinated by Nearctica (formerly Entomological Information Specialists), because of their experience with Nomina Insecta Nearctica. We are attempting to collaborate with known specialists as contributors and reviewers, but we welcome additional suggestions of collaborators. Inquires can be directed to Scott Miller (miller.scott@nmnh.si.edu). Information was obtained from ""http://entomology.si.edu/""." proprietary
instm_trawl National Institute of Marine Sciences and Technologies - Trawling Surveys CEOS_EXTRA STAC Catalog 1983-04-16 2006-11-03 5.14, 17.1, 13.37, 38.1 https://cmr.earthdata.nasa.gov/search/concepts/C2232477692-CEOS_EXTRA.umm_json The National Institute of Marine Sciences and Technologies (INSTM) fo Tunisia has four laboratories. Regular trawl surveys are done by the Laboratory of Marine Living Resources to assess the exploitable resource stocks. This dataset consists of 7664 records of 90 families. proprietary
intercomparison-of-photogrammetric-platforms_1.0 Photogrammetric snow depth maps from satellite-, airplane-, UAS and terrestrial platforms from the Davos region (Switzerland) ENVIDAT STAC Catalog 2020-01-01 2020-01-01 9.7544861, 46.6485877, 10.0428772, 46.844319 https://cmr.earthdata.nasa.gov/search/concepts/C2789815195-ENVIDAT.umm_json "This data set contains the produced snow depth maps as well as the reference data set (manual and snow pole measurements) from our paper ""Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping"". __Abstract.__ Snow depth has traditionally been estimated based on point measurements collected either manually or at automated weather stations. Point measurements, though, do not represent the high spatial variability of snow depths present in alpine terrain. Photogrammetric mapping techniques have progressed in recent years and are capable of accurately mapping snow depth in a spatially continuous manner, over larger areas, and at various spatial resolutions. However, the strengths and weaknesses associated with specific platforms and photogrammetric techniques, as well as the accuracy of the photogrammetric performance on snow surfaces have not yet been sufficiently investigated. Therefore, industry-standard photogrammetric platforms, including high-resolution satellites (Pléiades), airplane (Ultracam Eagle M3), Unmanned Aerial System (eBee+ with S.O.D.A. camera) and terrestrial (single lens reflex camera, Canon EOS 750D), were tested for snow depth mapping in the alpine Dischma valley (Switzerland) in spring 2018. Imagery was acquired with airborne and space-borne platforms over the entire valley, while Unmanned Aerial Systems (UAS) and terrestrial photogrammetric imagery was acquired over a subset of the valley. For independent validation of the photogrammetric products, snow depth was measured by probing, as well as using remote observations of fixed snow poles. When comparing snow depth maps with manual and snow pole measurements the root mean square error (RMSE) values and the normalized median deviation (NMAD) values were 0.52 m and 0.47 m respectively for the satellite snow depth map, 0.17 m and 0.17 m for the airplane snow depth map, 0.16 m and 0.11 m for the UAS snow depth map. The area covered by the terrestrial snow depth map only intersected with 4 manual measurements and did not generate statistically relevant measurements. When using the UAS snow depth map as a reference surface, the RMSE and NMAD values were 0.44 m and 0.38 m for the satellite snow depth map, 0.12 m and 0.11 m for the airplane snow depth map, 0.21 and 0.19 m for the terrestrial snow depth map. When compared to the airplane dataset over a large part of the Dischma valley (40 km2), the snow depth map from the satellite yielded a RMSE value of 0.92 m and a NMAD value of 0.65 m. This study provides comparative measurements between photogrammetric platforms to evaluate their specific advantages and disadvantages for operational, spatially continuous snow depth mapping in alpine terrain over both small and large geographic areas." proprietary
interview-guide-and-transcripts_1.0 Interview guide and transcripts (CONCUR Aim 2 on Governance) ENVIDAT STAC Catalog 2021-01-01 2021-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815227-ENVIDAT.umm_json This dataset is composed of an interview guide used to conduct 43 in-depth, qualitative, and in-person interviews with planning experts, academics and practitioners, in 14 European urban regions and the corresponding interview transcripts (verbatim). These interviews were conducted in the selected urban regions between March and September 2016. They were first digitally recorded and later thoroughly transcribed. proprietary
@@ -19845,8 +19846,8 @@ larval-food-composition-of-four-wild-bee-species-in-five-european-cities_1.0 Lar
latent-reserves-in-the-swiss-nfi_1.0 'Latent reserves' within the Swiss NFI ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.umm_json "The files refer to the data used in Portier et al. ""‘Latent reserves’: a hidden treasure in National Forest Inventories"" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement." proprietary
latent-reserves-in-the-swiss-nfi_1.0 'Latent reserves' within the Swiss NFI ALL STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.umm_json "The files refer to the data used in Portier et al. ""‘Latent reserves’: a hidden treasure in National Forest Inventories"" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement." proprietary
law_dome_1977_1 Law Dome Field Logs And Strain Grid Results, 1977 AU_AADC STAC Catalog 1977-03-16 1977-12-14 110, -70, 114, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214311164-AU_AADC.umm_json In 1977 several traverses were carried out over the Law Dome area, primarily to drill new ice cores on the dome. The 1974 drill site (near Cape Folger) was redrilled to add instrumentation for inclination, while additional holes at BHQ (418m) and the dome summit (475m, 2x 30m) were also drilled. In addition to the drilling work, two strain grids were laid out on the ice surface, and the grid laid out in 1974 was remeasured. Notes on the traverse and drilling (but few results) are contained in this record, along with the results of the strain grid surveys. Records for this work have been archived at the Australian Antarctic Division. Logbook(s): Glaciology Log of 1977 Field Work proprietary
-law_dome_700yr_ion_chem_2 700 Years of Ice Core Major Ion Chemistry Data from Law Dome, Antarctica ALL STAC Catalog 1988-01-01 2000-03-06 112.8, -66.76, 112.86, -66.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214313592-AU_AADC.umm_json A compilation of 700 years of Law Dome major ion chemistry data, recorded from 3 ice cores; DSS97, DSS99, DSS main. This work was completed as part of ASAC project 757 (ASAC_757). Species which have been the subject of publication and could be made available after consultation: Species, Period (AD), Resolution, Comments SO4, 1301-1995, Fine (full) NO3, 1888-1995, Fine (full), full 700 year annuals used by Mayewski solar-polar paper in preparation (Ca,K,Mg,Na,NO3,SO4,Cl), 1301-1995, Annual MSA, 1841-1995, Annual Na, 1301-1995, Fine (full) Na, 1301-1995, Annual non-sea-salt SO4 (nss SO4), 1301-1995, Annual, Uses a calculated SO4 fractionation % to correct the seawater ratio (due to fractionation at the source). Corrected ratio 0.087 (using uEq/L). There are still 'negative' values and some zero's - this data has not been 'cleaned'. If you need to use this, please contact Mark Curran for help. An updated copy of this dataset was submitted to the Australian Antarctic Data Centre in early July of 2012. proprietary
law_dome_700yr_ion_chem_2 700 Years of Ice Core Major Ion Chemistry Data from Law Dome, Antarctica AU_AADC STAC Catalog 1988-01-01 2000-03-06 112.8, -66.76, 112.86, -66.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214313592-AU_AADC.umm_json A compilation of 700 years of Law Dome major ion chemistry data, recorded from 3 ice cores; DSS97, DSS99, DSS main. This work was completed as part of ASAC project 757 (ASAC_757). Species which have been the subject of publication and could be made available after consultation: Species, Period (AD), Resolution, Comments SO4, 1301-1995, Fine (full) NO3, 1888-1995, Fine (full), full 700 year annuals used by Mayewski solar-polar paper in preparation (Ca,K,Mg,Na,NO3,SO4,Cl), 1301-1995, Annual MSA, 1841-1995, Annual Na, 1301-1995, Fine (full) Na, 1301-1995, Annual non-sea-salt SO4 (nss SO4), 1301-1995, Annual, Uses a calculated SO4 fractionation % to correct the seawater ratio (due to fractionation at the source). Corrected ratio 0.087 (using uEq/L). There are still 'negative' values and some zero's - this data has not been 'cleaned'. If you need to use this, please contact Mark Curran for help. An updated copy of this dataset was submitted to the Australian Antarctic Data Centre in early July of 2012. proprietary
+law_dome_700yr_ion_chem_2 700 Years of Ice Core Major Ion Chemistry Data from Law Dome, Antarctica ALL STAC Catalog 1988-01-01 2000-03-06 112.8, -66.76, 112.86, -66.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214313592-AU_AADC.umm_json A compilation of 700 years of Law Dome major ion chemistry data, recorded from 3 ice cores; DSS97, DSS99, DSS main. This work was completed as part of ASAC project 757 (ASAC_757). Species which have been the subject of publication and could be made available after consultation: Species, Period (AD), Resolution, Comments SO4, 1301-1995, Fine (full) NO3, 1888-1995, Fine (full), full 700 year annuals used by Mayewski solar-polar paper in preparation (Ca,K,Mg,Na,NO3,SO4,Cl), 1301-1995, Annual MSA, 1841-1995, Annual Na, 1301-1995, Fine (full) Na, 1301-1995, Annual non-sea-salt SO4 (nss SO4), 1301-1995, Annual, Uses a calculated SO4 fractionation % to correct the seawater ratio (due to fractionation at the source). Corrected ratio 0.087 (using uEq/L). There are still 'negative' values and some zero's - this data has not been 'cleaned'. If you need to use this, please contact Mark Curran for help. An updated copy of this dataset was submitted to the Australian Antarctic Data Centre in early July of 2012. proprietary
law_dome_700yr_na_1 700 Year Record of Winter Sodium Concentrations (May June July averages) from Law Dome ALL STAC Catalog 1301-01-01 1995-12-31 112.806946, -66.76972, 112.806946, -66.76972 https://cmr.earthdata.nasa.gov/search/concepts/C1214311149-AU_AADC.umm_json This file is a 700 year record of winter sodium concentrations (May June July averages) from Law Dome. This was calculated by dividing each annual cycle into 12 even time bins (nominally months) and taking the average concentrations for bins 5, 6 and 7 (nominally May, june and July). More detail can be found in the publication listed below. For further information regarding this data set please contact Mark Curran at the address below. proprietary
law_dome_700yr_na_1 700 Year Record of Winter Sodium Concentrations (May June July averages) from Law Dome AU_AADC STAC Catalog 1301-01-01 1995-12-31 112.806946, -66.76972, 112.806946, -66.76972 https://cmr.earthdata.nasa.gov/search/concepts/C1214311149-AU_AADC.umm_json This file is a 700 year record of winter sodium concentrations (May June July averages) from Law Dome. This was calculated by dividing each annual cycle into 12 even time bins (nominally months) and taking the average concentrations for bins 5, 6 and 7 (nominally May, june and July). More detail can be found in the publication listed below. For further information regarding this data set please contact Mark Curran at the address below. proprietary
law_dome_gravity_1964_1968_1 Gravity Measurements on Law Dome, 1964-1968 AU_AADC STAC Catalog 1964-01-01 1968-12-31 110, -68, 115, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214311151-AU_AADC.umm_json A compilation of gravity measurements taken on Law Dome from 1964-1968. The hard copy of this document has been archived in the Australian Antarctic Division Records Store. proprietary
@@ -19857,8 +19858,8 @@ law_dome_met_obs_1981_1 Meteorological Observations, Winter Traverses, Law Dome
law_dome_wilkes_land_1984_1 Law Dome/Wilkes Land Traverse Data 1984 AU_AADC STAC Catalog 1984-01-01 1984-12-31 108, -74, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214311153-AU_AADC.umm_json Raw logs for snow accumulation, snow density, gravity and snow pit stratigraphy recorded during 1984 traverse season on Law Dome/Wilkes Land. Copies of these documents have been archived in the records store of the Australian Antarctic Division. proprietary
lawdome_1968_season_1 Field and traverse data, Law Dome, 1968 AU_AADC STAC Catalog 1968-01-01 1968-12-31 110, -68, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214313593-AU_AADC.umm_json Notes and data observations from field work out of Casey in the 1968 season. Includes data on gravity, accumulation, strain grid measurements, ice core density measurements, levelling, met obs, and echo sounding results. proprietary
lawdome_1970_1 Glaciology and geophysical survey of Law Dome, 1970 AU_AADC STAC Catalog 1970-01-01 1970-12-31 110, -68, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1291724265-AU_AADC.umm_json Log books (2) from the 1970 traverses on Law Dome, recording barometric pressure, air temperature, magnetic fields and gravity. Physical copies of these documents have been stored in the Australian Antarctic Division records store. proprietary
-lawdome_1979_field_data_1 Accumulation, Air Temperature, Barometric Pressure and Magnetic Readings from Law Dome and Wilkes Land, 1979 ALL STAC Catalog 1979-01-01 1979-12-31 110, -68, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214311166-AU_AADC.umm_json A collection of observations made during the Autumn-Spring 1979 traverses on Law Dome and Wilkes Land. Measurements include accumulation, air temperature, barometric pressure, and magnetic field strength. The data is recorded in four log books and a set of loose pages. Physical copies of these documents have been stored in the Australian Antarctic Division records store. proprietary
lawdome_1979_field_data_1 Accumulation, Air Temperature, Barometric Pressure and Magnetic Readings from Law Dome and Wilkes Land, 1979 AU_AADC STAC Catalog 1979-01-01 1979-12-31 110, -68, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214311166-AU_AADC.umm_json A collection of observations made during the Autumn-Spring 1979 traverses on Law Dome and Wilkes Land. Measurements include accumulation, air temperature, barometric pressure, and magnetic field strength. The data is recorded in four log books and a set of loose pages. Physical copies of these documents have been stored in the Australian Antarctic Division records store. proprietary
+lawdome_1979_field_data_1 Accumulation, Air Temperature, Barometric Pressure and Magnetic Readings from Law Dome and Wilkes Land, 1979 ALL STAC Catalog 1979-01-01 1979-12-31 110, -68, 115, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214311166-AU_AADC.umm_json A collection of observations made during the Autumn-Spring 1979 traverses on Law Dome and Wilkes Land. Measurements include accumulation, air temperature, barometric pressure, and magnetic field strength. The data is recorded in four log books and a set of loose pages. Physical copies of these documents have been stored in the Australian Antarctic Division records store. proprietary
lawdome_1981_traverse_1 Law Dome and Wilkes Land Traverse Logbooks, 1981 AU_AADC STAC Catalog 1981-01-01 1981-12-31 110, -70, 115, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214311154-AU_AADC.umm_json Log books for the traverse work carried out on Law Dome and Wilkes Land in 1981. Information recorded includes snow cane accumulation readings, barometric pressure, gravity, temperature, wind, and some oxygen isotope results. Copies of these documents have been archived in the records store of the Australian Antarctic Division. proprietary
lawdome_borehole_temp_1987_1 Ice Core Borehole Temperatures, Law Dome 1987 AU_AADC STAC Catalog 1987-01-01 1987-12-31 110.52246, -66.58461, 111.5332, -66.05511 https://cmr.earthdata.nasa.gov/search/concepts/C1214311167-AU_AADC.umm_json A compilation of temperature measurements taken from ice core boreholes on Law Dome in the 1987 season. Includes detailed notes on measuring methodology, and papers on the interpretation of results from the specific equipment used to record the temperatures, as well as calibration work done. A text file of blended borehole temperature readings for the Law Dome DSS (Dome Summit South) site is available for download. A copy of the referenced publication is available to AAD staff. van Ommen, T. D., V. I. Morgan, T. H. Jacka, S. Woon and A. Elcheikh (1999) Near-surface temperatures in the Dome Summit South (Law Dome, East Antarctica) borehole Annals of Glaciology, 29. 141-144. Physical copies of these documents have been stored in the Australian Antarctic Division records store. proprietary
lawdome_gravity_1973_74_1 Law Dome Gravity Readings, 1973-1974 AU_AADC STAC Catalog 1973-01-10 1974-02-22 110, -68, 115, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214313573-AU_AADC.umm_json Gravity readings on Law Dome for the International Global Aerosol Programme (IGAP) during the 1973/1974 season. The Casey 1973 wintering team included physicists Lyle H Supp (Arizona, USA) and Ian Lawrence McIntosh, who were possibly involved in the collection of these data. The Casey 1974 wintering team included the physicist Gregory Ross Howarth, who may also have been involved. Two geodesists from the US, DL Schneider and HL Edwards were also present, and may also have been involved. These documents are only available in hard copy, and have been archived by the Australian Antarctic Division. proprietary
@@ -19981,8 +19982,8 @@ macquarie_aws_1 Automatic Weather Station Data from Macquarie Island AU_AADC STA
macquarie_heli_zone_1 Macquarie Island Helicopter Exclusion Zone AU_AADC STAC Catalog 2005-01-01 2005-01-24 158.75, -54.8, 158.97, -54.46 https://cmr.earthdata.nasa.gov/search/concepts/C1214313628-AU_AADC.umm_json The Macquarie Island Helicopter Exclusion Zone was created in January 2005 in consultation with Peter Cusick, Parks and Wildlife Service, Tasmania. The zone was created by buffering the coastline by 1 km on the seaward side of the island, generally following the escarpment on the interior of the island and buffering the refuges by 200 m to create an approximately 400 m wide corridor to the refuges. Access corridors were also created at the station. The Australian Antarctic Data Centre's topographic data representing coastline, escarpment and refuges was used. In March 2007 the zone was modifed in consultation with Terry Reid, Parks and Wildlife Service, Tasmania. The corridors to the refuges were extended through to the escarpment. The Helicopter Exclusion Zone is shown in a map of the island (see link below). proprietary
macquarie_quickbird_mapping_1 Macquarie Island mapping from Quickbird satellite imagery. AU_AADC STAC Catalog 2003-02-25 2003-06-20 158.85, -54.56, 158.94, -54.49 https://cmr.earthdata.nasa.gov/search/concepts/C1214313631-AU_AADC.umm_json Features of a northwest part of Macquarie Island mapped from mosaiced pan sharpened Quickbird satellite imagery derived from Quickbird satellite imagery captured on 25 February 2003. The mapped features are coastline, walking tracks and the edge of vegetation. proprietary
macquarie_sma_gis_1 Macquarie Island Special Management Areas AU_AADC STAC Catalog 2003-11-01 2003-11-30 158.77, -54.78, 158.95, -54.49 https://cmr.earthdata.nasa.gov/search/concepts/C1214313610-AU_AADC.umm_json Macquarie Island Nature Reserve Special Management Areas were originally defined for 2003/04 and have since been updated. Special Management areas are declared from year to year to protect vulnerable species, vegetation communities or sites extremely vulnerable to human disturbance. Related URLs provide: 1 the download of a shapefile with the boundaries of the Special Management Areas; and 2 a link to the website of Parks and Wildlife Service, Tasmania with information about the Special Management Areas. proprietary
-macquarie_taspaws_grid_1 A grid system used by the Parks and Wildlife Service, Tasmania, for Macquarie Island, 1974 to June 2001 AU_AADC STAC Catalog 1974-01-01 2001-06-02 158.7322, -54.8011, 158.9781, -54.4714 https://cmr.earthdata.nasa.gov/search/concepts/C1214313536-AU_AADC.umm_json "This metadata record describes a grid system for Macquarie Island formerly used by the Parks and Wildlife Service, Tasmania. The grid was first adopted by Irynej Skira in 1974 and was based on the 1:50000 scale map of the island published by Australia's Division of National Mapping in 1971. Data was continually recorded on this system up to June 2001 when the Universal Transverse Mercator (UTM) grid was adopted. The dataset available for download from this metadata record includes a map with the grid system and a document compiled by Geoff Copson with details about converting from the Parks and Wildlife grid to the UTM grid. Geoff states in the document ""The 1971 map was particularly inaccurate in the centre two quarters of the island. The grid for the Parks and Wildlife Service system was hand drawn and fairly variable. Conversion values are averaged out on coastal points around the island.""" proprietary
macquarie_taspaws_grid_1 A grid system used by the Parks and Wildlife Service, Tasmania, for Macquarie Island, 1974 to June 2001 ALL STAC Catalog 1974-01-01 2001-06-02 158.7322, -54.8011, 158.9781, -54.4714 https://cmr.earthdata.nasa.gov/search/concepts/C1214313536-AU_AADC.umm_json "This metadata record describes a grid system for Macquarie Island formerly used by the Parks and Wildlife Service, Tasmania. The grid was first adopted by Irynej Skira in 1974 and was based on the 1:50000 scale map of the island published by Australia's Division of National Mapping in 1971. Data was continually recorded on this system up to June 2001 when the Universal Transverse Mercator (UTM) grid was adopted. The dataset available for download from this metadata record includes a map with the grid system and a document compiled by Geoff Copson with details about converting from the Parks and Wildlife grid to the UTM grid. Geoff states in the document ""The 1971 map was particularly inaccurate in the centre two quarters of the island. The grid for the Parks and Wildlife Service system was hand drawn and fairly variable. Conversion values are averaged out on coastal points around the island.""" proprietary
+macquarie_taspaws_grid_1 A grid system used by the Parks and Wildlife Service, Tasmania, for Macquarie Island, 1974 to June 2001 AU_AADC STAC Catalog 1974-01-01 2001-06-02 158.7322, -54.8011, 158.9781, -54.4714 https://cmr.earthdata.nasa.gov/search/concepts/C1214313536-AU_AADC.umm_json "This metadata record describes a grid system for Macquarie Island formerly used by the Parks and Wildlife Service, Tasmania. The grid was first adopted by Irynej Skira in 1974 and was based on the 1:50000 scale map of the island published by Australia's Division of National Mapping in 1971. Data was continually recorded on this system up to June 2001 when the Universal Transverse Mercator (UTM) grid was adopted. The dataset available for download from this metadata record includes a map with the grid system and a document compiled by Geoff Copson with details about converting from the Parks and Wildlife grid to the UTM grid. Geoff states in the document ""The 1971 map was particularly inaccurate in the centre two quarters of the island. The grid for the Parks and Wildlife Service system was hand drawn and fairly variable. Conversion values are averaged out on coastal points around the island.""" proprietary
macquarie_tracks_1 Macquarie Island walking tracks AU_AADC STAC Catalog 1997-09-01 2012-06-30 158.77, -54.78, 158.95, -54.48 https://cmr.earthdata.nasa.gov/search/concepts/C1214311191-AU_AADC.umm_json This GIS dataset represents walking tracks on Macquarie Island and was compiled by the Australian Antarctic Data Centre from surveys and other sources. This data is displayed in a pair of A3 1:50000 maps of Macquarie Island (see a Related URL). proprietary
madagascar_diatoms MADAGASCAR National Oceanographic Data Centre - Diatoms CEOS_EXTRA STAC Catalog 2003-10-01 2004-10-31 43.61, -23.38, 43.68, -23.35 https://cmr.earthdata.nasa.gov/search/concepts/C2232477687-CEOS_EXTRA.umm_json The Madagascar National Oceanographic Data Centre is attached to the University of Toliara. Some of the research achievements of the Oceanographic Data Centre are: a project for the protection of coastal reefs in south-western Madagascar; a marine biodiversity assessment in the same coastal area; a socio-economic investigation of traditional fishing practices; and bio-ecological surveys to facilitate the development of a sustainable marine park in the Masoala area far away on Madagascar’s northeast coast. This dataset of diatoms has been collected at three stations in Toliara Bay, and it currently consists of 2754 records of 19 families. proprietary
madagascar_dinoflagelles MADAGASCAR National Oceanographic Data Centre - Dinoflagellates CEOS_EXTRA STAC Catalog 2002-12-01 2003-12-31 43.61, -23.38, 43.68, -23.35 https://cmr.earthdata.nasa.gov/search/concepts/C2232477667-CEOS_EXTRA.umm_json The Madagascar National Oceanographic Data Centre is attached to the University of Toliara. Some of the research achievements of the Oceanographic Data Centre are: a project for the protection of coastal reefs in south-western Madagascar; a marine biodiversity assessment in the same coastal area; a socio-economic investigation of traditional fishing practices; and bio-ecological surveys to facilitate the development of a sustainable marine park in the Masoala area far away on Madagascar’s northeast coast. This dataset of dinoflagellates has been collected at three stations in Toliara Bay, and it currently consists of 1297 records of 15 families. proprietary
@@ -20013,17 +20014,17 @@ mawson_gravity_1989_1 Gravity Measurements At/Near Mawson, 1989 AU_AADC STAC Cat
mawson_north_sat_1 Mawson Escarpment North Satellite Image Map 1:100000 AU_AADC STAC Catalog 1995-12-01 1995-12-31 66, -73, 69, -72 https://cmr.earthdata.nasa.gov/search/concepts/C1214313618-AU_AADC.umm_json Satellite image map of the northern end of the Mawson Escarpment, Antarctica. This map was produced for the Australian Antarctic Division by AUSLIG (now Geoscience Australia) Commercial, in Australia, in 1995. The map is at a scale of 1:100000, and was produced from Landsat TM scenes (WRS 128-111, 127-112). It is projected on a Transverse Mercator projection, and shows glaciers/ice shelves and gives some historical text information. The map has both geographical and UTM co-ordinates. proprietary
mawson_south_sat_1 Mawson Escarpment South Satellite Image Map 1:100000 AU_AADC STAC Catalog 1995-12-01 1995-12-31 66.12, -73.7083, 69.1883, -73.065 https://cmr.earthdata.nasa.gov/search/concepts/C1214313637-AU_AADC.umm_json Satellite image map of Mawson Escarpment south, Antarctica. This map was produced for the Australian Antarctic Division by AUSLIG (Now Geoscience Australia) Commercial, in Australia, in 1995. The map is at a scale of 1:100000, and was produced from Landsat TM scenes (WRS 128-111, 128-112, 124-112). It is projected on a Transverse Mercator projection, and shows glaciers/ice shelves and gives some historical text information. The map has both geographical and UTM co-ordinates. proprietary
mawsonbathy_gis_1 Bathymetry of Approaches to Mawson Station AU_AADC STAC Catalog 1987-02-03 1992-03-04 62, -68, 63, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214313619-AU_AADC.umm_json Bathymetric contours and height range polygons of approaches to Mawson Station, derived from RAN Fair sheet, Aurora Australis and GEBCO soundings. proprietary
-mbs_wilhelm_msa_hooh_1 15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS) ALL STAC Catalog 1984-01-01 1998-12-31 86.082, -69.13, 86.084, -69.12 https://cmr.earthdata.nasa.gov/search/concepts/C1214313640-AU_AADC.umm_json This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757). proprietary
mbs_wilhelm_msa_hooh_1 15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS) AU_AADC STAC Catalog 1984-01-01 1998-12-31 86.082, -69.13, 86.084, -69.12 https://cmr.earthdata.nasa.gov/search/concepts/C1214313640-AU_AADC.umm_json This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757). proprietary
-mcdonald_dem_may2012_1 A Digital Elevation Model of McDonald Island derived from GeoEye-1 stereo imagery captured 19 May 2012 AU_AADC STAC Catalog 2012-05-19 2012-05-19 72.533, -53.067, 72.74, -53.003 https://cmr.earthdata.nasa.gov/search/concepts/C1214311211-AU_AADC.umm_json This dataset consists of: 1 GeoEye-1 stereo imagery of an area of approximately 100 square kilometres including McDonald Island, captured 19 May 2012 2 A Digital Elevation Model (DEM) derived from the GeoEye-1 stereo imagery; and 3 Image products derived from the most vertical dataset of the stereo imagery and orthorectified using the DEM. 4 Contours generated from the DEM. The DEM was produced at a 1 metre pixel size and is available in ESRI grid, ESRI ascii and BIL formats. The DEM and image products are stored in a Universal Transverse Mercator zone 43 south projection, based on the WGS84 datum. The image products are geotiffs as follows. McDonald_Island_BGRN.tif: GeoEye-1 4-band multispectral (vis blue, green, red and Near Infrared), 2 metre resolution. McDonald_Island_PAN.tif: GeoEye-1 panchromatic, 0.5 metre resolution. McDonald_Island_PS_BGRN.tif: GeoEye-1 pansharpened, 4-band multispectral (vis blue, green, red and Near Infrared), 0.5 metre resolution. McDonald_Island_RGB.tif: GeoEye-1 pansharpened, natural colour enhancement, 0.5 metre resolution. proprietary
+mbs_wilhelm_msa_hooh_1 15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS) ALL STAC Catalog 1984-01-01 1998-12-31 86.082, -69.13, 86.084, -69.12 https://cmr.earthdata.nasa.gov/search/concepts/C1214313640-AU_AADC.umm_json This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757). proprietary
mcdonald_dem_may2012_1 A Digital Elevation Model of McDonald Island derived from GeoEye-1 stereo imagery captured 19 May 2012 ALL STAC Catalog 2012-05-19 2012-05-19 72.533, -53.067, 72.74, -53.003 https://cmr.earthdata.nasa.gov/search/concepts/C1214311211-AU_AADC.umm_json This dataset consists of: 1 GeoEye-1 stereo imagery of an area of approximately 100 square kilometres including McDonald Island, captured 19 May 2012 2 A Digital Elevation Model (DEM) derived from the GeoEye-1 stereo imagery; and 3 Image products derived from the most vertical dataset of the stereo imagery and orthorectified using the DEM. 4 Contours generated from the DEM. The DEM was produced at a 1 metre pixel size and is available in ESRI grid, ESRI ascii and BIL formats. The DEM and image products are stored in a Universal Transverse Mercator zone 43 south projection, based on the WGS84 datum. The image products are geotiffs as follows. McDonald_Island_BGRN.tif: GeoEye-1 4-band multispectral (vis blue, green, red and Near Infrared), 2 metre resolution. McDonald_Island_PAN.tif: GeoEye-1 panchromatic, 0.5 metre resolution. McDonald_Island_PS_BGRN.tif: GeoEye-1 pansharpened, 4-band multispectral (vis blue, green, red and Near Infrared), 0.5 metre resolution. McDonald_Island_RGB.tif: GeoEye-1 pansharpened, natural colour enhancement, 0.5 metre resolution. proprietary
+mcdonald_dem_may2012_1 A Digital Elevation Model of McDonald Island derived from GeoEye-1 stereo imagery captured 19 May 2012 AU_AADC STAC Catalog 2012-05-19 2012-05-19 72.533, -53.067, 72.74, -53.003 https://cmr.earthdata.nasa.gov/search/concepts/C1214311211-AU_AADC.umm_json This dataset consists of: 1 GeoEye-1 stereo imagery of an area of approximately 100 square kilometres including McDonald Island, captured 19 May 2012 2 A Digital Elevation Model (DEM) derived from the GeoEye-1 stereo imagery; and 3 Image products derived from the most vertical dataset of the stereo imagery and orthorectified using the DEM. 4 Contours generated from the DEM. The DEM was produced at a 1 metre pixel size and is available in ESRI grid, ESRI ascii and BIL formats. The DEM and image products are stored in a Universal Transverse Mercator zone 43 south projection, based on the WGS84 datum. The image products are geotiffs as follows. McDonald_Island_BGRN.tif: GeoEye-1 4-band multispectral (vis blue, green, red and Near Infrared), 2 metre resolution. McDonald_Island_PAN.tif: GeoEye-1 panchromatic, 0.5 metre resolution. McDonald_Island_PS_BGRN.tif: GeoEye-1 pansharpened, 4-band multispectral (vis blue, green, red and Near Infrared), 0.5 metre resolution. McDonald_Island_RGB.tif: GeoEye-1 pansharpened, natural colour enhancement, 0.5 metre resolution. proprietary
mcm_seals Marine and Coastal Management (MCM) - Seal Surveys CEOS_EXTRA STAC Catalog 1974-04-08 2001-06-01 11.68, -34.98, 26.11, -17.47 https://cmr.earthdata.nasa.gov/search/concepts/C2232477678-CEOS_EXTRA.umm_json Marine and Coastal Management (MCM) is one of four branches of the Department of Environmental Affairs and Tourism. It is the regulatory authority responsible for managing all marine and coastal activities. The seal data set is a collection of seals shot at-sea cruises, and has been collected from cruises around the South African Coast, and currently contains 2440 records of 1 family (Otariidae). proprietary
mean-insect-occupancy-1970-2020_1.0 Mean insect occupancy 1970–2020 ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226082591-ENVIDAT.umm_json This dataset contains all data, on which the following publication below is based. **Paper Citation**: Neff, F., Korner-Nievergelt, F., Rey, E., Albrecht, M., Bollmann, K., Cahenzli, F., Chittaro, Y., Gossner, M. M., Martínez-Núñez, C., Meier, E. S., Monnerat, C., Moretti, M., Roth, T., Herzog, F., Knop, E. 2022. Different roles of concurring climate and regional land-use changes in past 40 years' insect trends. Nature Communications, DOI: [10.1038/s41467-022-35223-3](https://doi.org/10.1038/s41467-022-35223-3) Please cite this paper together with the citation for the datafile. Please also refer to this publication for details on the methods. ## Summary Mean annual occupancy estimates for 390 insect species (215 butterflies [Papilionoidea, incl. Zygaenidae moths], 103 grasshoppers [Orthoptera], 72 dragonflies [Odonata]) for nine bioclimatic zones in Switzerland. Covers the years 1970-2020 (for butterflies) and 1980-2020 (for grasshoppers and dragonflies). Mean occupancy denotes the average number of 1 km x 1 km squares in a zone occupied by the focal species. Occupancy estimates stem from occupancy-detection models run with species records data hosted and curated by [info fauna](http://www.infofauna.ch). Data on the level of single MCMC iterations of model fitting are included (4000 sampling iterations). The nine bioclimatic zones were defined based on biogeographic regions and two elevation classes (square above or below 1000 m. asl) proprietary
-medical_bibliography_1 A bibliography of polar medicine related articles ALL STAC Catalog 1947-01-01 2007-06-06 60, -90, 160, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214311212-AU_AADC.umm_json This bibliography contains a list of publications in medical sciences from Australian National Antarctic Research Expeditions (ANARE) and the Australian Antarctic Program (AAP) from 1947-2007. The bibliography also contains publications related to Australian involvement in the International Biomedical Expedition to the Antarctic (IBEA), 1980-1981. Currently (as at 2007-06-06) the bibliography stands at 285 references, but is updated annually. The publications are divided into the following areas: Clinical medicine Clinical medicine - case reports Telemedicine Dentistry Diving Epidemiology Polar human research - general Physiology Immunology Photobiology Microbiology Psychology and behavioural studies Nutrition Theses Popular articles Miscellaneous IBEA Posters The fields in this dataset are: Author Title Journal Year proprietary
medical_bibliography_1 A bibliography of polar medicine related articles AU_AADC STAC Catalog 1947-01-01 2007-06-06 60, -90, 160, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214311212-AU_AADC.umm_json This bibliography contains a list of publications in medical sciences from Australian National Antarctic Research Expeditions (ANARE) and the Australian Antarctic Program (AAP) from 1947-2007. The bibliography also contains publications related to Australian involvement in the International Biomedical Expedition to the Antarctic (IBEA), 1980-1981. Currently (as at 2007-06-06) the bibliography stands at 285 references, but is updated annually. The publications are divided into the following areas: Clinical medicine Clinical medicine - case reports Telemedicine Dentistry Diving Epidemiology Polar human research - general Physiology Immunology Photobiology Microbiology Psychology and behavioural studies Nutrition Theses Popular articles Miscellaneous IBEA Posters The fields in this dataset are: Author Title Journal Year proprietary
+medical_bibliography_1 A bibliography of polar medicine related articles ALL STAC Catalog 1947-01-01 2007-06-06 60, -90, 160, -42 https://cmr.earthdata.nasa.gov/search/concepts/C1214311212-AU_AADC.umm_json This bibliography contains a list of publications in medical sciences from Australian National Antarctic Research Expeditions (ANARE) and the Australian Antarctic Program (AAP) from 1947-2007. The bibliography also contains publications related to Australian involvement in the International Biomedical Expedition to the Antarctic (IBEA), 1980-1981. Currently (as at 2007-06-06) the bibliography stands at 285 references, but is updated annually. The publications are divided into the following areas: Clinical medicine Clinical medicine - case reports Telemedicine Dentistry Diving Epidemiology Polar human research - general Physiology Immunology Photobiology Microbiology Psychology and behavioural studies Nutrition Theses Popular articles Miscellaneous IBEA Posters The fields in this dataset are: Author Title Journal Year proprietary
mega-plots_1.0 Towards comparable species richness estimates across plot-based inventories - data ENVIDAT STAC Catalog 2022-01-01 2022-01-01 -14.0625, 33.1375512, 42.1875, 72.1818036 https://cmr.earthdata.nasa.gov/search/concepts/C2789816317-ENVIDAT.umm_json "The data file refers to the data used in Portier et al. ""Plot size matters: towards comparable species richness estimates across plot-based inventories"" (2022) *Ecology and Evolution*. This paper describes a methodoligical framework developed to allow meaningful species richness comparisons across plot-based inventories using different plot sizes. To this end, National Forest Inventory data from Switzerland, Slovakia, Norway and Spain were used. NFI plots were aggregated into mega-plots of larger sizes to build rarefaction curves. The data stored here correspond to the mega-plot level data used in the analyses, including for each country the size of the mega-plots in square meters (A), the corresponding species richness (SR) as well as all enrionmental heterogeneity measures described in the corresponding paper. Mega-plots of country-specific downscaled datasets are also provided. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). Contact details for data requests from all NFIs can be found in the ENFIN website (http://enfin.info/)." proprietary
-mendocino_mathison_peak_nff_sr Airborne laser swath mapping (ALSM) data of the San Andreas fault SCIOPS STAC Catalog 2003-02-05 2003-02-11 -123.81387, 39.31092, -123.720085, 39.333496 https://cmr.earthdata.nasa.gov/search/concepts/C1214614580-SCIOPS.umm_json "This airborne laser swath mapping (ALSM) data of the San Andreas fault zone in northern California was acquired by TerraPoint, LLC under contract to the National Aeronautics and Space Administration in collaboration with the United States Geological Survey. The data were acquired by means of LIght Detection And Ranging (LIDAR) using a discrete-return, scanning laser altimeter capable of acquiring up to 4 returns per laser pulse. The data were acquired with a nominal density of 1 laser pulses per square meter achieved with 58% overlap of adjacent data swaths (all areas were mapped at least twice and the data combined to produce final products). The data set consists of 3 parts: (1) the LIDAR point cloud providing the location and elevation of each laser return, along with associated acquisition and classification parameters, (2) a highest-surface digital elevation model (DEM) produced at a 6 foot grid spacing, where each grid cell elevation corresponds to the highest laser return within the cell (cells lacking returns are undefined, usually associated with water or low reflectance surfaces such as fresh asphalt), and (3) a ""bald Earth"" DEM, with vegetation cover and buildings removed, produced at a 6 foot grid spacing by sampling a triangular irregular network (TIN). The TIN was constructed from those returns classified as being from the ground or water based on spatial filtering of the point cloud. Comparison to GPS-established ground control in flat, vegetation-free areas indicates that the DEM vertical accuracy is 17 cm (RMSE for 85 points). Bald Earth elevations under vegetation and for water bodies are less accurate where laser returns from the ground or water are sparse. The highest surface and bald Earth DEMs are distributed as georeferenced geotiff elevation and shaded relief images. The grid cell values in the elevation images are orthometric elevations in international feet referenced to North American Vertical Datum 1988 (NAVD-88) stored as signed floating point values with undefined grid cells set to -99. The shaded relief images are byte values from 0 (shaded) to 255 (illuminated) computed using ENVI 4.0 shaded relief modeling with an illumination azimuth of 225 degrees, illumination elevation of 60 degrees, and a 3x3 kernel size. The images are mosaics based on USGS 7.5 minute quadrangle boundaries. Each mosaic is an east-west strip covering the northern or southern half of adjacent quadrangles. File names include the quadrangle names, a northern (N) or southern (S) half designation, a bald Earth (BE) or highest-surface (FF) designation, and an elevation image (elev) or shaded relief image (SR) designation. FF refers to full-feature indicating vegetation and buildings have not been removed.These data were developed in order to study the geomorphic expression of natural hazards in support of the National Aeronautics and Space Administration (NASA) Solid Earth and Natural Hazards (SENH) Program, the United States Geological Survey (USGS), and the Geology component of the Earthscope Plate Boundary Observatory. Spatial Data Organization Information - Direct Spatial Reference: Raster Raster Object Type: Pixel Row Count: 1285 Column Count: 4398 Vertical Count: 1 Spatial Reference Information - Horizontal Coordinate System Definition - Planar - Map Projection Name: Lambert Conformal Conic Standard Parallel: 38.333333 Standard Parallel: 39.833333 Longitude of Central Meridian: -122.000000 Latitude of Projection Origin: 37.666667 False Easting: 6561666.666667 False Northing: 1640416.666667 Planar Coordinate Encoding Method: row and column Coordinate Representation: Abscissa Resolution: 6.000000 Ordinate Resolution: 6.000000 Distance and Bearing Representation: Planar Distance Units: survey feet Geodetic Model: Horizontal Datum Name: North American Datum of 1983 Ellipsoid Name: Geodetic Reference System 80 Semi-major Axis: 6378137.000000 Denominator of Flattening Ratio: 298.257222" proprietary
mendocino_mathison_peak_nff_sr Airborne laser swath mapping (ALSM) data of the San Andreas fault ALL STAC Catalog 2003-02-05 2003-02-11 -123.81387, 39.31092, -123.720085, 39.333496 https://cmr.earthdata.nasa.gov/search/concepts/C1214614580-SCIOPS.umm_json "This airborne laser swath mapping (ALSM) data of the San Andreas fault zone in northern California was acquired by TerraPoint, LLC under contract to the National Aeronautics and Space Administration in collaboration with the United States Geological Survey. The data were acquired by means of LIght Detection And Ranging (LIDAR) using a discrete-return, scanning laser altimeter capable of acquiring up to 4 returns per laser pulse. The data were acquired with a nominal density of 1 laser pulses per square meter achieved with 58% overlap of adjacent data swaths (all areas were mapped at least twice and the data combined to produce final products). The data set consists of 3 parts: (1) the LIDAR point cloud providing the location and elevation of each laser return, along with associated acquisition and classification parameters, (2) a highest-surface digital elevation model (DEM) produced at a 6 foot grid spacing, where each grid cell elevation corresponds to the highest laser return within the cell (cells lacking returns are undefined, usually associated with water or low reflectance surfaces such as fresh asphalt), and (3) a ""bald Earth"" DEM, with vegetation cover and buildings removed, produced at a 6 foot grid spacing by sampling a triangular irregular network (TIN). The TIN was constructed from those returns classified as being from the ground or water based on spatial filtering of the point cloud. Comparison to GPS-established ground control in flat, vegetation-free areas indicates that the DEM vertical accuracy is 17 cm (RMSE for 85 points). Bald Earth elevations under vegetation and for water bodies are less accurate where laser returns from the ground or water are sparse. The highest surface and bald Earth DEMs are distributed as georeferenced geotiff elevation and shaded relief images. The grid cell values in the elevation images are orthometric elevations in international feet referenced to North American Vertical Datum 1988 (NAVD-88) stored as signed floating point values with undefined grid cells set to -99. The shaded relief images are byte values from 0 (shaded) to 255 (illuminated) computed using ENVI 4.0 shaded relief modeling with an illumination azimuth of 225 degrees, illumination elevation of 60 degrees, and a 3x3 kernel size. The images are mosaics based on USGS 7.5 minute quadrangle boundaries. Each mosaic is an east-west strip covering the northern or southern half of adjacent quadrangles. File names include the quadrangle names, a northern (N) or southern (S) half designation, a bald Earth (BE) or highest-surface (FF) designation, and an elevation image (elev) or shaded relief image (SR) designation. FF refers to full-feature indicating vegetation and buildings have not been removed.These data were developed in order to study the geomorphic expression of natural hazards in support of the National Aeronautics and Space Administration (NASA) Solid Earth and Natural Hazards (SENH) Program, the United States Geological Survey (USGS), and the Geology component of the Earthscope Plate Boundary Observatory. Spatial Data Organization Information - Direct Spatial Reference: Raster Raster Object Type: Pixel Row Count: 1285 Column Count: 4398 Vertical Count: 1 Spatial Reference Information - Horizontal Coordinate System Definition - Planar - Map Projection Name: Lambert Conformal Conic Standard Parallel: 38.333333 Standard Parallel: 39.833333 Longitude of Central Meridian: -122.000000 Latitude of Projection Origin: 37.666667 False Easting: 6561666.666667 False Northing: 1640416.666667 Planar Coordinate Encoding Method: row and column Coordinate Representation: Abscissa Resolution: 6.000000 Ordinate Resolution: 6.000000 Distance and Bearing Representation: Planar Distance Units: survey feet Geodetic Model: Horizontal Datum Name: North American Datum of 1983 Ellipsoid Name: Geodetic Reference System 80 Semi-major Axis: 6378137.000000 Denominator of Flattening Ratio: 298.257222" proprietary
+mendocino_mathison_peak_nff_sr Airborne laser swath mapping (ALSM) data of the San Andreas fault SCIOPS STAC Catalog 2003-02-05 2003-02-11 -123.81387, 39.31092, -123.720085, 39.333496 https://cmr.earthdata.nasa.gov/search/concepts/C1214614580-SCIOPS.umm_json "This airborne laser swath mapping (ALSM) data of the San Andreas fault zone in northern California was acquired by TerraPoint, LLC under contract to the National Aeronautics and Space Administration in collaboration with the United States Geological Survey. The data were acquired by means of LIght Detection And Ranging (LIDAR) using a discrete-return, scanning laser altimeter capable of acquiring up to 4 returns per laser pulse. The data were acquired with a nominal density of 1 laser pulses per square meter achieved with 58% overlap of adjacent data swaths (all areas were mapped at least twice and the data combined to produce final products). The data set consists of 3 parts: (1) the LIDAR point cloud providing the location and elevation of each laser return, along with associated acquisition and classification parameters, (2) a highest-surface digital elevation model (DEM) produced at a 6 foot grid spacing, where each grid cell elevation corresponds to the highest laser return within the cell (cells lacking returns are undefined, usually associated with water or low reflectance surfaces such as fresh asphalt), and (3) a ""bald Earth"" DEM, with vegetation cover and buildings removed, produced at a 6 foot grid spacing by sampling a triangular irregular network (TIN). The TIN was constructed from those returns classified as being from the ground or water based on spatial filtering of the point cloud. Comparison to GPS-established ground control in flat, vegetation-free areas indicates that the DEM vertical accuracy is 17 cm (RMSE for 85 points). Bald Earth elevations under vegetation and for water bodies are less accurate where laser returns from the ground or water are sparse. The highest surface and bald Earth DEMs are distributed as georeferenced geotiff elevation and shaded relief images. The grid cell values in the elevation images are orthometric elevations in international feet referenced to North American Vertical Datum 1988 (NAVD-88) stored as signed floating point values with undefined grid cells set to -99. The shaded relief images are byte values from 0 (shaded) to 255 (illuminated) computed using ENVI 4.0 shaded relief modeling with an illumination azimuth of 225 degrees, illumination elevation of 60 degrees, and a 3x3 kernel size. The images are mosaics based on USGS 7.5 minute quadrangle boundaries. Each mosaic is an east-west strip covering the northern or southern half of adjacent quadrangles. File names include the quadrangle names, a northern (N) or southern (S) half designation, a bald Earth (BE) or highest-surface (FF) designation, and an elevation image (elev) or shaded relief image (SR) designation. FF refers to full-feature indicating vegetation and buildings have not been removed.These data were developed in order to study the geomorphic expression of natural hazards in support of the National Aeronautics and Space Administration (NASA) Solid Earth and Natural Hazards (SENH) Program, the United States Geological Survey (USGS), and the Geology component of the Earthscope Plate Boundary Observatory. Spatial Data Organization Information - Direct Spatial Reference: Raster Raster Object Type: Pixel Row Count: 1285 Column Count: 4398 Vertical Count: 1 Spatial Reference Information - Horizontal Coordinate System Definition - Planar - Map Projection Name: Lambert Conformal Conic Standard Parallel: 38.333333 Standard Parallel: 39.833333 Longitude of Central Meridian: -122.000000 Latitude of Projection Origin: 37.666667 False Easting: 6561666.666667 False Northing: 1640416.666667 Planar Coordinate Encoding Method: row and column Coordinate Representation: Abscissa Resolution: 6.000000 Ordinate Resolution: 6.000000 Distance and Bearing Representation: Planar Distance Units: survey feet Geodetic Model: Horizontal Datum Name: North American Datum of 1983 Ellipsoid Name: Geodetic Reference System 80 Semi-major Axis: 6378137.000000 Denominator of Flattening Ratio: 298.257222" proprietary
met-obs-jmr-stations-1976_1 Meteorological Observations Made At JMR Stations 1976-1977 AU_AADC STAC Catalog 1976-01-01 1977-12-31 124.5, -78.5, 93, -67 https://cmr.earthdata.nasa.gov/search/concepts/C1214313660-AU_AADC.umm_json During the Mirny-Dome C traverse in 1976/77, time was spent at a number of cane sites taking JMR measurements, to determine the precise location. During this time, basic meteorological observations of air temperature and pressure were made and recorded. These documents have been archived in the records store at the Australian Antarctic Division. proprietary
met_profile_SA_729_1 SAFARI 2000 Upper Air Meteorological Profiles, South Africa, Dry Season 2000 ORNL_CLOUD STAC Catalog 2000-08-01 2000-09-30 -10, -41, 31, -24 https://cmr.earthdata.nasa.gov/search/concepts/C2789021046-ORNL_CLOUD.umm_json The University of Wyoming has a series of balloonborne radiosonde measurements from all around the world, from the surface to 30 km. This data set contains upper air meteorological profiles from 594 radiosonde launches deployed from sites in South Africa. These sonde launches were made to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaign of 2000.Vaisala RS80 sondes were launched from nine sites in South Africa between August 1, 2000 and September 30, 2000. The launch sites were Pietersburg (changed to Polokwane after 2000), Pretoria (Irene), Bethlehem, Springbok, De Aar, Durban, Cape Town, Port Elizabeth, and Gough Island. The parameters measured by the radiosonde instruments include: pressure, air temperature, relative humidity, wind speed, and wind direction. proprietary
met_profile_skukuza_728_1 SAFARI 2000 Upper Air Meteorological Profiles, Skukuza, Dry Seasons 1999-2000 ORNL_CLOUD STAC Catalog 1999-08-14 2000-09-23 31.59, -24.97, 31.59, -24.97 https://cmr.earthdata.nasa.gov/search/concepts/C2789020292-ORNL_CLOUD.umm_json Vaisala RS80 sondes were deployed from Skukuza Airport, South Africa, to collect atmospheric sounding profiles of temperature and moisture data from the surface to 30 km. These sonde launches were coordinated to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaigns of 1999 and 2000. The radiosondes were launched from Skukuza Airport between August 14-September 3, 1999, and between August 24-September 23, 2000. The radiosonde instrument package RS80 measured the following meteorological parameters: pressure in hecto-Pascals (P), ambient temperature in degrees Celsius (T), and relative humidity in percentage (RH). A hydrostatic equation was applied to the recorded data, after error-checking, to calculate the output parameters: height above sea level in meters, dew point temperature in degrees Celsius, and q (g/kg) which is specific humidity in grams per kilogram. proprietary
@@ -20164,11 +20165,11 @@ number_of_woody_species_from_40_cm_height-144_1.0 Number of woody species (from
number_of_woody_species_gt_12_cm_dbh-41_1.0 Number of woody species (>= 12 cm DBH) ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789816627-ENVIDAT.umm_json Number of tree and shrub species starting at 12 cm dbh (diameter at breast height) within the 200 m2 sample plot. __Citation:__ > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_ proprietary
number_of_young_forest_plants_by_damage-209_1.0 Number of young forest plants by damage ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789816738-ENVIDAT.umm_json Number of regeneration trees starting at 10 cm height up to 11.9 cm dbh with a particular type of damage or with no damage. The attribute is recorded by targeting the next regeneration tree in the centre of the subplot during NFI’s regeneration survey. A regeneration tree may have more than one type of damage, which means it may contribute to the total number of regeneration trees for several different types of damage. __Citation:__ > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_ proprietary
nutrient-addition-stillberg_1.0 Nutrient addition experiment at the Alpine treeline site Stillberg, Switzerland ENVIDAT STAC Catalog 2023-01-01 2023-01-01 9.867544, 46.7716544, 9.867544, 46.7716544 https://cmr.earthdata.nasa.gov/search/concepts/C3226082769-ENVIDAT.umm_json # Background information The availability of nitrogen (N) and phosphorus (P) is considered to be a major factor limiting growth and productivity in terrestrial ecosystems globally. This project aimed to determine whether the growth stimulation documented in previous short‐term fertilisation trials persisted in a longer‐term study (12 years) in the treeline ecotone, and whether possible negative effects of nutrient addition offset the benefits of any growth stimulation. Over the course of the 12 study years, NPK fertiliser corresponding to 15 or 30 kg N ha−1 a−1 was added annually to plots containing 30‐year‐old *Larix decidua* or 32‐year-old *Pinus uncinata* individuals with an understorey of mainly ericaceous dwarf shrubs. To quantify growth, annual shoot increments of trees and dwarf shrubs as well as radial growth increments of trees were measured. Nutrient concentrations in the soil were also measured and the foliar nutritional status of trees and dwarf shrubs was assessed. # Experimental design Over an elevation gradient of 140 m across the treeline afforestation site Stillberg, 22 locations were chosen that covered the whole range of microenvironmental conditions (*see* Nutrient addition experimental design.png). Half of the blocks included European larch (*L. decidua*) and the other half included mountain pine (*P. uncinata*). Within each block, three plantation quadrats were randomly selected as experimental plots and each plot was assigned to a control (no fertilisation) or to one of two fertiliser dose treatments (15 kg and 30 kg N ha−1 a−1). Treatments were assigned randomly but confined so that the location of fertilised plots within a block was not directly above control plots to avoid nutrient input from drainage. For details about the experiment, *see* Möhl et al (2019). # Data description The available datasets contain climate variables (2004-2016), nutrient isotope measurements (2010 & 2016), shrub growth measurements (2004-2016), soil parameter measurements and annual ring and shoot measurements (2004-2016). All data can be found here: proprietary
-nwrc_amphibianslowermiss A Multi-scale Habitat Evaluation of Amphibians in the Lower Mississippi River Alluvial Valley CEOS_EXTRA STAC Catalog 1999-09-05 1999-12-05 -91.95, 31.15, -91.25, 32.4333 https://cmr.earthdata.nasa.gov/search/concepts/C2231550400-CEOS_EXTRA.umm_json Bottomland hardwood forests are floodplain forests distributed along rivers and streams throughout the central and southern United States. The largest bottomland hardwood ecosystem in North America occurred within the Lower Mississippi River Alluvial Valley (LMAV). By the 1980.s, an estimated 80% of the former 10 million ha of bottomland hardwood forest in the LMAV were cleared for flood control efforts, agriculture, and development. Forests are continuing to be cleared today at an alarming rate, and the forests that remain are highly degraded and fragmented. In addition, these forests are subjected to extreme hydrological alterations. Over the past few decades, extensive efforts have begun to reforest marginal agricultural lands within the LMAV. Restoration efforts are limited by the lack of information concerning the habitat needs of bottomland wildlife species. Amphibians are one group of species for which little is known about their population status or habitat requirements in the LMAV. Information concerning the population status of amphibians in the LMAV is especially important since amphibians appear to be declining worldwide. Amphibians may also be important indicators of environmental health because of their sensitivity to land management practices and water quality. Understanding the habitat requirements of amphibians can be a step toward enhancing wildlife populations within the LMAV by providing valuable information for improving land management practices and wetland restoration techniques. To provide an inventory of amphibians at Tensas River and Lake Ophelia National Wildlife Refuges. In addition, to determine amphibian distribution patterns in the LMAV as they relate to landscape habitat features. Research results will be used to develop reports and manuscripts, and to assist land managers in management decisions to benefit amphibian populations. Information was obtained from Janene Lichtenberg for this metadata. proprietary
nwrc_amphibianslowermiss A Multi-scale Habitat Evaluation of Amphibians in the Lower Mississippi River Alluvial Valley ALL STAC Catalog 1999-09-05 1999-12-05 -91.95, 31.15, -91.25, 32.4333 https://cmr.earthdata.nasa.gov/search/concepts/C2231550400-CEOS_EXTRA.umm_json Bottomland hardwood forests are floodplain forests distributed along rivers and streams throughout the central and southern United States. The largest bottomland hardwood ecosystem in North America occurred within the Lower Mississippi River Alluvial Valley (LMAV). By the 1980.s, an estimated 80% of the former 10 million ha of bottomland hardwood forest in the LMAV were cleared for flood control efforts, agriculture, and development. Forests are continuing to be cleared today at an alarming rate, and the forests that remain are highly degraded and fragmented. In addition, these forests are subjected to extreme hydrological alterations. Over the past few decades, extensive efforts have begun to reforest marginal agricultural lands within the LMAV. Restoration efforts are limited by the lack of information concerning the habitat needs of bottomland wildlife species. Amphibians are one group of species for which little is known about their population status or habitat requirements in the LMAV. Information concerning the population status of amphibians in the LMAV is especially important since amphibians appear to be declining worldwide. Amphibians may also be important indicators of environmental health because of their sensitivity to land management practices and water quality. Understanding the habitat requirements of amphibians can be a step toward enhancing wildlife populations within the LMAV by providing valuable information for improving land management practices and wetland restoration techniques. To provide an inventory of amphibians at Tensas River and Lake Ophelia National Wildlife Refuges. In addition, to determine amphibian distribution patterns in the LMAV as they relate to landscape habitat features. Research results will be used to develop reports and manuscripts, and to assist land managers in management decisions to benefit amphibian populations. Information was obtained from Janene Lichtenberg for this metadata. proprietary
+nwrc_amphibianslowermiss A Multi-scale Habitat Evaluation of Amphibians in the Lower Mississippi River Alluvial Valley CEOS_EXTRA STAC Catalog 1999-09-05 1999-12-05 -91.95, 31.15, -91.25, 32.4333 https://cmr.earthdata.nasa.gov/search/concepts/C2231550400-CEOS_EXTRA.umm_json Bottomland hardwood forests are floodplain forests distributed along rivers and streams throughout the central and southern United States. The largest bottomland hardwood ecosystem in North America occurred within the Lower Mississippi River Alluvial Valley (LMAV). By the 1980.s, an estimated 80% of the former 10 million ha of bottomland hardwood forest in the LMAV were cleared for flood control efforts, agriculture, and development. Forests are continuing to be cleared today at an alarming rate, and the forests that remain are highly degraded and fragmented. In addition, these forests are subjected to extreme hydrological alterations. Over the past few decades, extensive efforts have begun to reforest marginal agricultural lands within the LMAV. Restoration efforts are limited by the lack of information concerning the habitat needs of bottomland wildlife species. Amphibians are one group of species for which little is known about their population status or habitat requirements in the LMAV. Information concerning the population status of amphibians in the LMAV is especially important since amphibians appear to be declining worldwide. Amphibians may also be important indicators of environmental health because of their sensitivity to land management practices and water quality. Understanding the habitat requirements of amphibians can be a step toward enhancing wildlife populations within the LMAV by providing valuable information for improving land management practices and wetland restoration techniques. To provide an inventory of amphibians at Tensas River and Lake Ophelia National Wildlife Refuges. In addition, to determine amphibian distribution patterns in the LMAV as they relate to landscape habitat features. Research results will be used to develop reports and manuscripts, and to assist land managers in management decisions to benefit amphibian populations. Information was obtained from Janene Lichtenberg for this metadata. proprietary
nymesoimpacts_1 New York State Mesonet IMPACTS GHRC_DAAC STAC Catalog 2020-01-03 2023-03-02 -79.6375, 40.594, -72.1909, 44.9057 https://cmr.earthdata.nasa.gov/search/concepts/C1995873777-GHRC_DAAC.umm_json The New York State Mesonet IMPACTS dataset is browse-only. It consists of temperature, wind, wind direction, mean sea level pressure, precipitation, and snow depth measurements, as well as profiler Doppler LiDAR and Microwave Radiometer (MWR) measurements from the New York State Mesonet network during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign, a three-year sequence of winter season deployments conducted to study snowstorms over the U.S. Atlantic coast. IMPACTS aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to advance prediction capabilities significantly. The Mesonet network consists of ground weather stations, LiDAR profilers, and microwave radiometer (MWR) profilers. These browse files are available from January 3, 2020, through March 2, 2023, in PNG format. proprietary
-obrienbay_bathy_dem_1 A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands AU_AADC STAC Catalog 1997-03-31 1997-03-31 110.516, -66.297, 110.54, -66.293 https://cmr.earthdata.nasa.gov/search/concepts/C1214311199-AU_AADC.umm_json A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands. proprietary
obrienbay_bathy_dem_1 A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands ALL STAC Catalog 1997-03-31 1997-03-31 110.516, -66.297, 110.54, -66.293 https://cmr.earthdata.nasa.gov/search/concepts/C1214311199-AU_AADC.umm_json A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands. proprietary
+obrienbay_bathy_dem_1 A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands AU_AADC STAC Catalog 1997-03-31 1997-03-31 110.516, -66.297, 110.54, -66.293 https://cmr.earthdata.nasa.gov/search/concepts/C1214311199-AU_AADC.umm_json A bathymetric Digital Elevation Model (DEM) of O'Brien Bay, Windmill Islands. proprietary
observational-data-switzerland-2016-2021_1.0 Observational data: avalanche observations, danger signs and stability test results, Switzerland (2016/2017 to 2020/2021 ) ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815389-ENVIDAT.umm_json This is the freely available part of the data used in the publication by Techel et al. (2022): _On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger_ - danger signs - human triggered avalanches - rutschblock test results (still to be added) - extended column test results (still to be added) proprietary
observed-and-simulated-snow-profile-data-from-switzerland_1.0 Observed and simulated snow profile data ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C3226082908-ENVIDAT.umm_json This data set includes information on all observed and simulated snow profiles that were used to train and validate the random forest model described in Mayer et al. (2022). The RF model was trained to assess snow instability from simulated snow stratigraphy. The data set contains observed snow profiles from the region of Davos (DAV subset, 512 profiles) and from all over Switzerland (SWISS subset, 230 profiles). For each observed snow profile, there is a corresponding simulated profile which was obtained using meteorological input data for the numerical snow cover model SNOWPACK. The information on the observed snow profile contains a Rutschblock test result including the depth of the failure interface. As part of the study described in Mayer et al. (2022), each observed snow profile was manually compared to its simulated counterpart and the simulated layer corresponding to the Rutschblock failure layer was identified. The data are provided in the following form: one file each per observed and simulated snow profile (2x512 files DAV, 2x230 files SWISS), two files (1 file DAV, 1 file SWISS) containing the observed information on snow instability, the allocation between observed and simulated failure layer, and all features extracted from the simulated weak layers that were used to develop the RF model. proprietary
observer-driven-pseudoturnover-in-vegetation-surveys_1.0 Observer-driven pseudoturnover in vegetation surveys ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815537-ENVIDAT.umm_json "This dataset was used to analyze the inter-observer error (i.e. pseudoturnover) in vegetation surveys for the publication Boch S, Küchler H, Küchler M, Bedolla A, Ecker KT, Graf UH, Moser T, Holderegger R, Bergamini A (2022) Observer-driven pseudoturnover in vegetation monitoring is context dependent but does not affect ecological inference. Applied Vegetation Science. In the framework of the project ""Monitoring the effectiveness of habitat conservation in Switzerland"", we double-surveyed a total of 224 plots that were marked once in the field and then sampled by two observers independently on the same day. Both observers conducted full vegetation surveys, recording all vascular plant species, their cover, and additional plot information. We then calculated mean ecological indicator values and pseudoturnover. The excel file contains two sheets: 1) Raw species lists of the 224 plots conducted by two different observers. Woody species are distinguished in three layers: H (herb layer; woody species <0.5 m in height), S (shrub layer; woody species 0.5–3 m in height) and T (tree layer; woody species >3 m in height). ""cf."" indicates uncertain identification, ""aggr."" indicates that the plant was identified only to the aggregate level. Cover was estimated for each species using a modified Braun-Blanquet scale (r ≙ <0.1%, + ≙ 0.1% to <1%, 1 ≙ 1% to <5%, 2 ≙ 5% to <25%, 3 ≙ 25% to <50%, 4 ≙ 50% to <75%, 5 ≙ 75% to <100%). 2) File used for the linear mixed effects model." proprietary
@@ -20184,8 +20185,8 @@ orbview_3 Orbview-3 USGS_LTA STAC Catalog 2003-01-01 2007-12-31 -180, -90, 180,
oriental-beech-spectral-and-trait-data_1.0 Oriental and European beech spectral, traits and genetics data ENVIDAT STAC Catalog 2023-01-01 2023-01-01 7.35, 48.65, 7.35, 48.65 https://cmr.earthdata.nasa.gov/search/concepts/C3226082588-ENVIDAT.umm_json The dataset includes leaf spectroscopy, leaf traits and genetic data for oriental and european beech trees at two mature forest sites (Allenwiller in France and Wäldi in Switzerland) sampled in summer 2021 and 2022 for top and bottom of canopy leaves. proprietary
ornl_lai_point_971_1 ISLSCP II Leaf Area Index (LAI) from Field Measurements, 1932-2000 ORNL_CLOUD STAC Catalog 1932-01-01 2000-12-31 -156.67, -54.5, 172.75, 71.3 https://cmr.earthdata.nasa.gov/search/concepts/C2784892799-ORNL_CLOUD.umm_json Leaf Area Index (LAI) data from the scientific literature, covering the period from 1932-2000, have been compiled at the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) to support model development and validation for products from the MODerate Resolution Imaging Spectroradiometer (MODIS) instrument. There is one data file which consists of a spreadsheet table, together with a bibliography of more than 300 original-source references. Although the majority of measurements are from natural or semi-natural ecosystems, some LAI values have been included from crops (limited to a sub-set representing different crops at different stages of development under a range of treatments). Like Net Primary Productivity (NPP), Leaf Area Index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange. Modeling and validation of coarse scale satellite measurements both require field measurements to constrain LAI values for different biomes (typical minimum, maximum values, phenology, etc.). Maximum values for point measurements are unlikely to be approached or exceeded by area-weighted LAI, which is what satellites and true spatial models are estimating. proprietary
otdlip_1 OPTICAL TRANSIENT DETECTOR (OTD) LIGHTNING V1 GHRC_DAAC STAC Catalog 1995-04-13 2000-03-23 -180, -70, 180, 70 https://cmr.earthdata.nasa.gov/search/concepts/C1979889849-GHRC_DAAC.umm_json The Optical Transient Detector (OTD) records optical measurements of global lightning events in the daytime and nighttime. The data includes individual point (lightning) data, satellite metadata, and several derived products. The OTD was launched on 3 April 1995 aboard the Microlab-1 satellite into a near polar orbit with an inclination of 70 degrees with respect to the equator, at an altitude of 740 km. proprietary
-oxygen-isotopes-plateau-1984_1 7 year oxygen isotope results from samples taken on Antarctic Plateau traverse, 1984 ALL STAC Catalog 1978-01-01 1984-12-31 100, -75, 130, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214313700-AU_AADC.umm_json A total of nine stations were sampled for oxygen isotopes during the 1984 spring traverse to the Antarctic Plateau. The aim of this program was to take a number of samples from a core or a pit, at stations of known accumulation over a particular period, to see how far inland the annual cycles could accurately be traced. The samples were not taken at ice movement stations, but at canes each 2km along the line, to avoid sampling the accumulation, and thus isotope disturbance resulting from parking the vans beside the IMS poles in 1978 and 1979. The accumulation for the cane at each sampled station was calculated for the six years since 1978, and the total multiplied by 7/6 to give the sampling depth required to cover 7 years. Seventy samples were taken at each station, i.e. approximately 10 per year. At most stations a PICO drill was used to obtain a core, and the samples cut with a stainless steel knife on the stainless sink in the living van. At the southern end of the line where the accumulation is much lower, the samples were taken from the wall of a pit, as the small length of core for each sample did not provide enough melt. The snow was sampled in the pits by sliding a flat sheet of galvanized iron into the snow at each interval starting at the top, and scraping the snow above this into a melt jar. Isotopic contamination of samples from both these methods should be negligible. All samples were melted in plastic jars, and then transferred into 5Oml plastic bottles. A total of 630 samples from 9 stations were returned to Australia for oxygen isotope analysis, carried out in Melbourne by Ted Vishart, Dick Marriot, and Gao Xiangqun. The station/cane labels for the sample sites were: A028 V140/4 (near GC30) V230/4 (near GC37) V270/1 (near GC38) V300/1 (near GC39) V350/1 (near GC40) V400/1 (near GC41) V450/1 (near GC42) V630/1 (near GC47) The columns in the spreadsheet are: Sequence Number Core depth (metres) Oxygen isotope value (the number is a ratio of O18 per ml of O16, expressed as a percentage (but as parts per 1000 instead of 100)) proprietary
oxygen-isotopes-plateau-1984_1 7 year oxygen isotope results from samples taken on Antarctic Plateau traverse, 1984 AU_AADC STAC Catalog 1978-01-01 1984-12-31 100, -75, 130, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214313700-AU_AADC.umm_json A total of nine stations were sampled for oxygen isotopes during the 1984 spring traverse to the Antarctic Plateau. The aim of this program was to take a number of samples from a core or a pit, at stations of known accumulation over a particular period, to see how far inland the annual cycles could accurately be traced. The samples were not taken at ice movement stations, but at canes each 2km along the line, to avoid sampling the accumulation, and thus isotope disturbance resulting from parking the vans beside the IMS poles in 1978 and 1979. The accumulation for the cane at each sampled station was calculated for the six years since 1978, and the total multiplied by 7/6 to give the sampling depth required to cover 7 years. Seventy samples were taken at each station, i.e. approximately 10 per year. At most stations a PICO drill was used to obtain a core, and the samples cut with a stainless steel knife on the stainless sink in the living van. At the southern end of the line where the accumulation is much lower, the samples were taken from the wall of a pit, as the small length of core for each sample did not provide enough melt. The snow was sampled in the pits by sliding a flat sheet of galvanized iron into the snow at each interval starting at the top, and scraping the snow above this into a melt jar. Isotopic contamination of samples from both these methods should be negligible. All samples were melted in plastic jars, and then transferred into 5Oml plastic bottles. A total of 630 samples from 9 stations were returned to Australia for oxygen isotope analysis, carried out in Melbourne by Ted Vishart, Dick Marriot, and Gao Xiangqun. The station/cane labels for the sample sites were: A028 V140/4 (near GC30) V230/4 (near GC37) V270/1 (near GC38) V300/1 (near GC39) V350/1 (near GC40) V400/1 (near GC41) V450/1 (near GC42) V630/1 (near GC47) The columns in the spreadsheet are: Sequence Number Core depth (metres) Oxygen isotope value (the number is a ratio of O18 per ml of O16, expressed as a percentage (but as parts per 1000 instead of 100)) proprietary
+oxygen-isotopes-plateau-1984_1 7 year oxygen isotope results from samples taken on Antarctic Plateau traverse, 1984 ALL STAC Catalog 1978-01-01 1984-12-31 100, -75, 130, -65 https://cmr.earthdata.nasa.gov/search/concepts/C1214313700-AU_AADC.umm_json A total of nine stations were sampled for oxygen isotopes during the 1984 spring traverse to the Antarctic Plateau. The aim of this program was to take a number of samples from a core or a pit, at stations of known accumulation over a particular period, to see how far inland the annual cycles could accurately be traced. The samples were not taken at ice movement stations, but at canes each 2km along the line, to avoid sampling the accumulation, and thus isotope disturbance resulting from parking the vans beside the IMS poles in 1978 and 1979. The accumulation for the cane at each sampled station was calculated for the six years since 1978, and the total multiplied by 7/6 to give the sampling depth required to cover 7 years. Seventy samples were taken at each station, i.e. approximately 10 per year. At most stations a PICO drill was used to obtain a core, and the samples cut with a stainless steel knife on the stainless sink in the living van. At the southern end of the line where the accumulation is much lower, the samples were taken from the wall of a pit, as the small length of core for each sample did not provide enough melt. The snow was sampled in the pits by sliding a flat sheet of galvanized iron into the snow at each interval starting at the top, and scraping the snow above this into a melt jar. Isotopic contamination of samples from both these methods should be negligible. All samples were melted in plastic jars, and then transferred into 5Oml plastic bottles. A total of 630 samples from 9 stations were returned to Australia for oxygen isotope analysis, carried out in Melbourne by Ted Vishart, Dick Marriot, and Gao Xiangqun. The station/cane labels for the sample sites were: A028 V140/4 (near GC30) V230/4 (near GC37) V270/1 (near GC38) V300/1 (near GC39) V350/1 (near GC40) V400/1 (near GC41) V450/1 (near GC42) V630/1 (near GC47) The columns in the spreadsheet are: Sequence Number Core depth (metres) Oxygen isotope value (the number is a ratio of O18 per ml of O16, expressed as a percentage (but as parts per 1000 instead of 100)) proprietary
p3metnavimpacts_1 P-3 Meteorological and Navigation Data IMPACTS GHRC_DAAC STAC Catalog 2020-01-12 2023-02-28 -95.243, 33.261, -64.987, 48.237 https://cmr.earthdata.nasa.gov/search/concepts/C1995868137-GHRC_DAAC.umm_json The P-3 Meteorological and Navigation Data IMPACTS dataset is a subset of airborne measurements that include GPS positioning and trajectory data, aircraft orientation, and atmospheric state measurements of temperature, pressure, water vapor, and horizontal winds. These measurements were taken from the NASA P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Funded by NASA’s Earth Venture program, IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to advance prediction capabilities significantly. Data are available in ASCII-ict format from January 12, 2020, through February 28, 2023. proprietary
p_pet_500m_1.0 Average precipitation and PET over Switzerland at 500m resolution ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815390-ENVIDAT.umm_json "Long-term (1980-2011) average annual precipitation (pcp_ch_longterm_yr_avg.tif) and potential evapotranspiration (pet_ch_longterm_yr_avg.tif) at 500m resolution. Units are mm per year. Files are GeoTIFF rasters, and can be read in R using the command raster(""pcp_ch_longterm_yr_avg.tif), after installing packages ""raster"" and ""rgdal""." proprietary
panpfcov_283_1 BOREAS Prince Albert National Park Forest Cover Data in Vector Format ORNL_CLOUD STAC Catalog 1978-01-01 1994-12-31 -106.8, 53.56, -105.99, 54.33 https://cmr.earthdata.nasa.gov/search/concepts/C2846961321-ORNL_CLOUD.umm_json Detailed canopy, understory, and ground cover, height, density, and condition information for PANP in the western part of the BOREAS SSA in vector form. proprietary
@@ -20306,8 +20307,8 @@ rlc_landcover_far_east_690_1 RLC AVHRR-Derived Land Cover, Former Soviet Union,
rlc_vector_data_698_1 RLC Selected Infrastructure Data for the Former Soviet Union, 1993 ORNL_CLOUD STAC Catalog 1993-01-01 1993-12-31 25, 23.21, 180, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2810672079-ORNL_CLOUD.umm_json This data set consists of roads, drainage, railroads, utilities, and population center information in readily usable vector format for the land area of the Former Soviet Union. The purpose of this dataset was to create a completely intact vector layer which could be readily used to aid in mapping efforts for the area of the FSU. These five vector data layers were assembled from the Digital Chart of the World (DCW), 1993. Individual record attributes were stored for population centers only. Vector maps for the FSU are in ArcView shapefile format. proprietary
rlc_vegetation_1990_700_1 RLC Vegetative Cover of the Former Soviet Union, 1990 ORNL_CLOUD STAC Catalog 1973-01-01 1973-12-31 19.82, 35.17, 170, 75 https://cmr.earthdata.nasa.gov/search/concepts/C2810672200-ORNL_CLOUD.umm_json This dataset is a 1:4 million scale vegetation map for the land area of the Former Soviet Union. Three hundred seventy-three cover classes are distinguished, of which nearly 145 are forest cover-related classes. Stone and Schlesinger (1993) digitized the map Vegetation of the Soviet Union, 1990 (Institute of Geography, 1990). proprietary
rlc_world_forest_map_697_1 RLC Generalized Forest Map of the Former Soviet Union, 1-km ORNL_CLOUD STAC Catalog 1998-01-01 1998-12-31 25, 23.21, 180, 71 https://cmr.earthdata.nasa.gov/search/concepts/C2810671823-ORNL_CLOUD.umm_json This data set is the Former Soviet Union (FSU) portion of the Generalized World Forest Map (WCMC, 1998), a 1-kilometer resolution generalized forest cover map for the land area of the Former Soviet Union. There are five forest classes in the original global generalized map. Only two of those classes were distinguished in the geographical portion comprising the FSU. proprietary
-robinson_adelie_colonies_1 Adelie penguin colonies in the Robinson Group, Antarctica: surveys conducted during 2005/06 and 2006/07 ALL STAC Catalog 2005-09-30 2007-03-31 63.233334, -67.51667, 63.85, -67.36667 https://cmr.earthdata.nasa.gov/search/concepts/C1214311232-AU_AADC.umm_json GPS surveys of Adelie Penguin colonies in the Robinson Group, Antarctica were carried out by field biologists from the Australian Antarctic Division during the 2005/06 and 2006/07 seasons. In 2005/06 point data were collected representing the presence or absence of colonies on the islands. The data were collected by Matt Low and Lisa Meyer. In 2006/07 polygon data were collected representing the colonies on the islands. The data were collected by Matt Low and Rhonda Pike. The biologists were working on a project led by Dr Colin Southwell of the Australian Antarctic Division. proprietary
robinson_adelie_colonies_1 Adelie penguin colonies in the Robinson Group, Antarctica: surveys conducted during 2005/06 and 2006/07 AU_AADC STAC Catalog 2005-09-30 2007-03-31 63.233334, -67.51667, 63.85, -67.36667 https://cmr.earthdata.nasa.gov/search/concepts/C1214311232-AU_AADC.umm_json GPS surveys of Adelie Penguin colonies in the Robinson Group, Antarctica were carried out by field biologists from the Australian Antarctic Division during the 2005/06 and 2006/07 seasons. In 2005/06 point data were collected representing the presence or absence of colonies on the islands. The data were collected by Matt Low and Lisa Meyer. In 2006/07 polygon data were collected representing the colonies on the islands. The data were collected by Matt Low and Rhonda Pike. The biologists were working on a project led by Dr Colin Southwell of the Australian Antarctic Division. proprietary
+robinson_adelie_colonies_1 Adelie penguin colonies in the Robinson Group, Antarctica: surveys conducted during 2005/06 and 2006/07 ALL STAC Catalog 2005-09-30 2007-03-31 63.233334, -67.51667, 63.85, -67.36667 https://cmr.earthdata.nasa.gov/search/concepts/C1214311232-AU_AADC.umm_json GPS surveys of Adelie Penguin colonies in the Robinson Group, Antarctica were carried out by field biologists from the Australian Antarctic Division during the 2005/06 and 2006/07 seasons. In 2005/06 point data were collected representing the presence or absence of colonies on the islands. The data were collected by Matt Low and Lisa Meyer. In 2006/07 polygon data were collected representing the colonies on the islands. The data were collected by Matt Low and Rhonda Pike. The biologists were working on a project led by Dr Colin Southwell of the Australian Antarctic Division. proprietary
rock_samples_1 Compilation of Rock Samples collected by ANARE AU_AADC STAC Catalog 1954-02-01 1999-11-22 60, -75, 160, -35 https://cmr.earthdata.nasa.gov/search/concepts/C1214313719-AU_AADC.umm_json Rocks from Australian Antarctic Division library This collection turns out to be rather interesting with some of heritage significance. Box 1 is basically odds and ends but includes a bag of coal from the Prince Charles Mountains worthy of display. Boxes 2 and 3 probably all are Phil Law collections. Unfortunately, locality information generally is lacking, but there are some interesting rocks. Box 1. A.Loose samples Two pale grey, rounded specimens, one with round depression. Very light weight (low density). Probably diatomite or radiolarite. Source? Dark grey with some red colours. Fragment of rounded river pebble that has been broken. Very tough, either quartzite or volcanic rock. Source? Scallop (Pecten meridionalis), left valve Tasmania Pink and yellow chert, varnished. One part of outside looks as if it has been fossil wood. Could be recrystallised chert from fossil wood locality. Source? Could be Tasmanian. Two small, dark, angular specimens, quite coarse grained with obvious crystal faces that flash. Specimens are of quartz and galena (PbS). Source? Could be west coast Tasmania such as Zeehan. Three elongate specimens, pale yellow/off white. They fit together to produce original specimen about 20 cm long. These are quite common around coastal Australia where rain soaks through sand, dissolves CaCO3 from surface shell material and redeposits it on the way down, perhaps along the roots of a plant. Goes by various names such as 'fossil roots' (which is wrong), travertine Large lump of black glass. Probably furnace slag but could conceivably be volcanic glass (probably too high density for that). Vesicles (gas bubbles quite common). B. Sample bag A calico bag of Permian coal from the Prince Charles Mountains. Bag is labelled to Assistant Director Science but probably was given to Evlyn Barrett as there is a note inside it suggesting that it is a present. Some specimens are good and could be used for display. Box 2. A note in the box (from me to Knowles Kerry) notes that these rocks were collected by Phil Law. While some cards are there, they are not related to the rocks. Most would appear to be Antarctic. Sample with cellotape, labelled Cape North. Fragment of vein quartz. Pumice. Grey, very light weight. Floats. Product of March 1962 submarine eruption at Protector Shoal in South Sandwich Islands. Rafts of this pumice circulated around Southern Hemisphere for years, slowly disappearing as the material became dispersed, washed onto beaches (small fragments still common on Australian beaches and some on Heard Island) and as fragments rubbed together, ground small chips off and these sank. This sample has some flow structure in it from the original eruption and due to elongation of gas bubbles as it flowed and cooled. It may well be from Heard Island. &It is identical in composition to material collected by Dr Jon Stephenson in 1963 from 'flotsam north of Heard Island' collected during his period on the latter expedition (Stephenson 1964) and identified as having been derived from vast rafts of pumice released in the South Atlantic Ocean during the eruption in the South Sandwich Islands area in 1962 (Gass et al.. 1963). This is probably the same material referred to by Dr Phil Law, who commented (personal communication, 19 August 1993) that he had seen rafts of pumice near Heard Island in January 1963.& (quote from Quilty and Wheller in preparation for Heard Island symposium of 1998). Flat dark grey fragment about 1 cm thick. Otherwise triangular with sharp corners. Rock is phyllite, rather low grade metamorphic rock, originally a shale in which clay has changed to muscovite to generate the good cleavage. Source? Would like to know because I have identical material as a glacial erratic from Kerguelen Plateau. 'Granite' Two fragments - angular, one rounded - of grey granite. Good samples. They are not quite the same material. Angular specimen is probably strictly granodiorite (the difference is important only to geologists). It contains quartz (very pale grey, glassy), two white feldspars (plagioclase-Na-CaAlsSi3O8 - and orthoclase - KalSi3O8) which make up the bulk of the rock in roughly equal proportions and come in two grain sizes - coarse (about 1 cm) and finer (about 2 mm). Dark minerals are biotite (black mica) and hornblende (complex Fe/Mg silicate). Rounded specimen is more uniform in grain and probably has the same pale minerals but they are not so easy to identify. Dark mineral hornblende. Biotite not seen. There also is a brown mineral, sometimes rhomboid in cross section. This probably is sphene. Source of samples? Rauer Island Rocks. (Probably Phil Law's own labelling) Replaced in old plastic bag and in turn in a new thin one. Two glassy (vitreous) grey samples. Monominerallic. Vein quartz. Two flat specimens with marked orientation of very uniform grained constituent minerals. Both high grade metamorphic rocks - amphibolite gneiss. Mineralogy - quartz, amphibole (probably hornblende), plagioclase feldspar. In one the quartz is white and in the other, more yellowish. Rounded specimen with two rock types in it with clear boundary. Pale rock is quartzite and other is amphibolite, probably part of same sequence as other amphibolites. Other rock has great variation in grain size but is otherwise part of the same sequence. Darker part is amphibolite, coarser than in samples described above and with yellowish quartz and orthoclase. This rock seems to be the source of the sand grains as it is more friable than others. Garnet rich sample - Bag 1 One rounded sample contains a significant content of garnet in white 'matrix'. The pale material is quartz/orthoclase and there is a fine grained, high lustre black mineral that could be magnetite (Fe3 O4). Source??? Probably a Law sample. Three specimens in small bag - Bag 2 All are characterised by having quartz veins 1-1.5 cm thick, cutting across the sample and bounded by a layer 1-2 mm thick of a black mineral (amphibole, probably hornblende). Other constituents of the rock are yellowish quartz, traces of garnet and biotite. I couldn't identify any feldspar but would expect it. The rocks, although not labelled with a locality, are very similar to some of those described as from the Rauer Islands but there are some in the Vestfold Hills that are very similar. Metabasalt? - Bag 4 - two samples These look rather like the basalt dykes that are so characteristic of the Vestfold Hills but are they? And who collected them? They probably are Phil Law collections. The dykes were intruded in a series of about 9 episodes from about 2.2 billion to 1.1 billion years. They have been altered since intrusion and while bulk composition changed little, the mineralogy did. They are now very tough rocks that break with highly angular, brittle fractures. Box 3 Judging by the brown sample bag, I suspect these are also Phil Law collections but where from? Brown calico bag - 5 specimens Large specimen is amphibolite gneiss consisting of layers that are amphibole and biotite rich. Also has traces of garnet. Locality? Two pale specimens. Both contain prominent garnet in quartz-feldspar matrix, orthoclase dominating. Metamorphic. Locality? Two small specimens. One is coarser than the other and has obvious garnet with hornblende, biotite, quartz and feldspar. The other is mainly hornblende/quartz but is a surface specimen, somewhat weathered. Brown paper bag (now in plastic bag - 5) Small sample (two almost black specimens). These are different from anything noted above. While the black biotite is the dominant source of the colour, there is also some quartz and I suspect feldspar. There also is quite a deal of very fine acicular mineral. It could be one of several but sillimanite (one of several minerals with the formula Al2SIO3) is a possibility. Largest, dark sample. Amphibolite gneiss. Well banded. Pale bands of quartz-feldspar-muscovite (white mica). Dark bands of hornblende-biotite. Source??? Dominantly pale sample with dark patch. Pale part is quartz-feldspar and the dark is hornblende plus minor acicular mineral (sillimanite?). Thin sample, 6 x 5 cm, 4 mm thick. Details not clear. Too fine grained but probably mainly quartz-feldspar with minor dark mineral (hornblende?). Plastic bag 6. Large flat specimen and one chip off the large block. Low grade metamorphic rock, originally fine sandstone. Source? Plastic bag 7 Rock mainly of coarse K-feldspar and quartz with minor plagioclase. Rock includes layers of brown mica (phlogopite?). Metamorphic. Source? Plastic bag 8. 8A. 3 specimens (2 are counterparts). See also 'Brown paper bag' sample above. Biotite-quartz-sillimanite. 8B. 2 specimens. Beautiful banded gneiss. Bands are pale, dominantly quartz and dark, dominantly biotite with some hornblende. 8C. 2 specimens. Quartz-biotite schist with trace of acicular mineral (sillimanite?) and pyrite. Two remaining specimens. One is of quartz/feldspar(?)/biotite/hornblende-sillimanite? Is feldspar correctly identified? Sieve texture. Other is subrounded boulder, greenish (chlorite?). Patrick G. Quilty AM 22 November 1999 proprietary
rockfall-gallery-testing-parde-2016_1.0 Rockfall gallery testing Parde 2016 ENVIDAT STAC Catalog 2018-01-01 2018-01-01 8.698082, 46.6532196, 8.698082, 46.6532196 https://cmr.earthdata.nasa.gov/search/concepts/C2789816316-ENVIDAT.umm_json "Five full-scale field tests were conducted with concrete blocks weighting between 800 and 3200 kg being dropped onto the roof of a gallery structure made from reinforced concrete. The impacts were recorded using high-speed video and acceleration measurements at the falling blocks. The dataset contains the raw data as well as the analyses of the block trajectories, i.e. kinetics and dynamics. Setup of the measurements and the analyses conducted are published in Volkwein, A. ""Durchführung und Auswertung von Steinschlagversuchen auf eine Stahlbetongalerie"", WSL-Berichte, Heft 68, 2018." proprietary
root-traits_1.0 Root-traits ENVIDAT STAC Catalog 2019-01-01 2019-01-01 7.6130533, 46.3023351, 7.6130533, 46.3023351 https://cmr.earthdata.nasa.gov/search/concepts/C2789816345-ENVIDAT.umm_json Fine-root traits of Scots pine in response to enhanced soil water availability deriving from long-term irrigation in the Pfynwald Data_Fig.1.xlsx Fine-root biomass of the topsoil (0-10 cm) in the dry and irrigated treatment of the Scots pine forest of the years 2003 to 2016 recorded by soil coring Data_Tab1+2_2005.xlsx Fine-root traits from roots of ingrowth cores from 2005 after two years of growth in the dry and irrigated treatment of the Scots pine forest Data_Tab1+2_2016.xlsx Fine-root traits from roots of ingrowth cores from 2016 after two years of growth, and from roots of the soil-coring sampling from 2016 in the dry and irrigated treatment of the Scots pine forest proprietary
@@ -20414,28 +20415,28 @@ sbuparsimpacts_1 SBU Parsivel IMPACTS GHRC_DAAC STAC Catalog 2020-01-01 2023-03-
sbuplimpacts_1 SBU Pluvio Precipitation Gauge IMPACTS GHRC_DAAC STAC Catalog 2020-01-07 2023-03-02 -73.138, 40.8556, -72.8714, 40.90712 https://cmr.earthdata.nasa.gov/search/concepts/C1995869760-GHRC_DAAC.umm_json The SBU Pluvio Precipitation Gauge IMPACTS dataset consists of precipitation intensity and precipitation accumulation collected using the OTT Pluvio2 weighing rain gauge during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. NASA’s Earth Venture program funded IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. Data files in this dataset are available in ASCII-CSV format from January 7, 2020, through March 2, 2023. proprietary
sbuskylerimpacts_1 SBU X-band Phased Array Radar (SKYLER) IMPACTS GHRC_DAAC STAC Catalog 2022-01-17 2023-02-28 -77.4867, 40.1501, -71.266, 43.695 https://cmr.earthdata.nasa.gov/search/concepts/C2704110186-GHRC_DAAC.umm_json The SBU X-band Phased Array Radar (SKYLER) IMPACTS dataset consists of polarimetric radar data collected by the Stony Brook University (SBU) X-band Phased Array Radar (SKYLER) during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S. Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. SKYLER provided detailed observations of cloud and precipitation microphysics, specifically ice and snow processes. These data include reflectivity, mean velocity, spectrum width, linear depolarization ratio, differential reflectivity, differential phase, specific differential phase, co-polarized correlation coefficient, and signal-to-noise ratio. The dataset files are available from January 17, 2022, through February 28, 2023, in netCDF-4 format. proprietary
sbusndimpacts_1 SBU Mobile Soundings IMPACTS GHRC_DAAC STAC Catalog 2020-01-18 2023-02-28 -76.980629, 40.4841385, -70.8692093, 43.7849808 https://cmr.earthdata.nasa.gov/search/concepts/C1995869776-GHRC_DAAC.umm_json The SBU Mobile Sounding IMPACTS dataset consists of mobile sounding profiles collected during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Funded by NASA’s Earth Venture program, IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. Mobile-sounding profiles were obtained about every three hours during snow events by Stony Brook University (SBU). The sounding measures temperature, humidity, height, and horizontal wind direction and speed in the atmosphere. Atmospheric pressure is calculated from GPS height. Data files are available from January 18, 2020, through February 28, 2023 in netCDF-3 format. proprietary
-scarmarbin_1647 Admiralty Bay Benthos Diversity Data Base (ABBED). Tanaidacea. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155436-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1647 Admiralty Bay Benthos Diversity Data Base (ABBED). Tanaidacea. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155436-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
-scarmarbin_1648 Admiralty Bay Benthos Diversity Data Base (ABBED). Cumacea. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155484-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
+scarmarbin_1647 Admiralty Bay Benthos Diversity Data Base (ABBED). Tanaidacea. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155436-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1648 Admiralty Bay Benthos Diversity Data Base (ABBED). Cumacea. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155484-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
+scarmarbin_1648 Admiralty Bay Benthos Diversity Data Base (ABBED). Cumacea. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155484-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1649 Admiralty Bay Benthos Diversity Data Base (ABBED). Pycnogonida. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155485-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1649 Admiralty Bay Benthos Diversity Data Base (ABBED). Pycnogonida. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155485-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1651 Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 ALL STAC Catalog 1979-01-01 1986-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155486-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1651 Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 SCIOPS STAC Catalog 1979-01-01 1986-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155486-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
-scarmarbin_1716 Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 - scarmarbin_1716 SCIOPS STAC Catalog 1979-12-27 1980-02-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1221420764-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1716 Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 - scarmarbin_1716 ALL STAC Catalog 1979-12-27 1980-02-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1221420764-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
+scarmarbin_1716 Admiralty Bay Benthos Diversity Data Base (ABBED). Polychaeta. 1979-80 - scarmarbin_1716 SCIOPS STAC Catalog 1979-12-27 1980-02-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1221420764-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1772 Admiralty Bay Benthos Diversity Data Base (ABBED). Ophiuroidea. SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155493-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1772 Admiralty Bay Benthos Diversity Data Base (ABBED). Ophiuroidea. ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155493-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1806 Admiralty Bay Benthos Diversity Data Base (ABBED). Amphipoda (1997). ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155503-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1806 Admiralty Bay Benthos Diversity Data Base (ABBED). Amphipoda (1997). SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155503-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
-scarmarbin_1807 Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1994). ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155504-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1807 Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1994). SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155504-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
+scarmarbin_1807 Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1994). ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155504-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1808 Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1997). SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155505-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
scarmarbin_1808 Admiralty Bay Benthos Diversity Data Base (ABBED). Gastropoda (1997). ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155505-SCIOPS.umm_json Information system on benthic organisms of Admiralty Bay (King George Island, South Shetland Islands, Antarctic). proprietary
-scarmarbin_987 A Biotic Database of Indo-Pacific Marine Mollusks (Southern Ocean Collection) ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155566-SCIOPS.umm_json The primary objective of this project is to provide a database of the estimated 25,000 named species of mollusks in the Indo-Pacific region, with summary data on their distribution and ecology. Another objective is to combine Indo-Pacific data with existing databases for Western Atlantic and Europe marine mollusk species and for higher taxa of mollusks to form the basis of a global database of Mollusca. This database will provide a uniform framework for linking specimen records from museum collections and data from fisheries to show spatial and temporal patterns of occurrence and abundance. This datasource provides primary access to the Indo-Pacific Mollusc Dataset using the obis schema. Data in the Indo-Paciffic Mollusc database use names from the Indo-Pacific Mollusc project together with point records from the Academy of Natural Sciences and the Australian Museum. Specimens referenced in this data set may be in the collections of either the Australian Museum or the Academy of Natural Sciences, but may have current identifications in those collections that are junior synonymys (or other junior names) of names in current use in the Indo-Pacific Mollusc database. proprietary
scarmarbin_987 A Biotic Database of Indo-Pacific Marine Mollusks (Southern Ocean Collection) SCIOPS STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155566-SCIOPS.umm_json The primary objective of this project is to provide a database of the estimated 25,000 named species of mollusks in the Indo-Pacific region, with summary data on their distribution and ecology. Another objective is to combine Indo-Pacific data with existing databases for Western Atlantic and Europe marine mollusk species and for higher taxa of mollusks to form the basis of a global database of Mollusca. This database will provide a uniform framework for linking specimen records from museum collections and data from fisheries to show spatial and temporal patterns of occurrence and abundance. This datasource provides primary access to the Indo-Pacific Mollusc Dataset using the obis schema. Data in the Indo-Paciffic Mollusc database use names from the Indo-Pacific Mollusc project together with point records from the Academy of Natural Sciences and the Australian Museum. Specimens referenced in this data set may be in the collections of either the Australian Museum or the Academy of Natural Sciences, but may have current identifications in those collections that are junior synonymys (or other junior names) of names in current use in the Indo-Pacific Mollusc database. proprietary
-scarmarbin_ABBED Admiralty Bay Benthos Biodiversity Database [SCAR-MarBIN] ALL STAC Catalog 1906-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155568-SCIOPS.umm_json Admiralty Bay is one of the best studied sites in the maritime Antarctic. The first benthos data has been recorded in 1906 and knowledge is constantly gained by the research activities of permanent stations, Arctowski (Poland, since 1977), and Ferraz (Brazil, since 1984). Admiralty Bay is a protected area within the Antarctic Treaty System, an Antarctic Specially Managed Area (ASMA). It was also a reference site under the EASIZ programme, and has been or is currently investigated by several nations : Poland, Brazil, United States, Peru, Ecuador, Germany, The Netherlands, Belgium. ABBED (Admiralty Bay Benthos Biodiversity Database) is a Belgian-Polish initiative, which aims at compiling and linking existing information on Admiralty Bay benthos biodiversity and ecology. This information will be digitized into a database and linked to wider Antarctic marine biodiversity initiatives, such as SCAR-MarBIN, which will disseminate the information through a web portal. Being highly diverse in its content, formats and data providers, ABBED will constitute an extremely interesting case-study for SCAR-MarBIN, allowing to test strategic options which were retained for the development of the network. Moreover, the quality and quantity of data which will be made available to the community will reinforce the status of Admiralty Bay as a true reference point for Antarctic biodiversity research. The project aims at developing an interactive database on the biodiversity of benthic communities of Admiralty Bay, King George Island, for scientific, monitoring, management and conservation purposes. It is intended to be a springboard for promoting future research in this region, by centralizing the relevant information for i.e. scientific programme design. proprietary
+scarmarbin_987 A Biotic Database of Indo-Pacific Marine Mollusks (Southern Ocean Collection) ALL STAC Catalog 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155566-SCIOPS.umm_json The primary objective of this project is to provide a database of the estimated 25,000 named species of mollusks in the Indo-Pacific region, with summary data on their distribution and ecology. Another objective is to combine Indo-Pacific data with existing databases for Western Atlantic and Europe marine mollusk species and for higher taxa of mollusks to form the basis of a global database of Mollusca. This database will provide a uniform framework for linking specimen records from museum collections and data from fisheries to show spatial and temporal patterns of occurrence and abundance. This datasource provides primary access to the Indo-Pacific Mollusc Dataset using the obis schema. Data in the Indo-Paciffic Mollusc database use names from the Indo-Pacific Mollusc project together with point records from the Academy of Natural Sciences and the Australian Museum. Specimens referenced in this data set may be in the collections of either the Australian Museum or the Academy of Natural Sciences, but may have current identifications in those collections that are junior synonymys (or other junior names) of names in current use in the Indo-Pacific Mollusc database. proprietary
scarmarbin_ABBED Admiralty Bay Benthos Biodiversity Database [SCAR-MarBIN] SCIOPS STAC Catalog 1906-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155568-SCIOPS.umm_json Admiralty Bay is one of the best studied sites in the maritime Antarctic. The first benthos data has been recorded in 1906 and knowledge is constantly gained by the research activities of permanent stations, Arctowski (Poland, since 1977), and Ferraz (Brazil, since 1984). Admiralty Bay is a protected area within the Antarctic Treaty System, an Antarctic Specially Managed Area (ASMA). It was also a reference site under the EASIZ programme, and has been or is currently investigated by several nations : Poland, Brazil, United States, Peru, Ecuador, Germany, The Netherlands, Belgium. ABBED (Admiralty Bay Benthos Biodiversity Database) is a Belgian-Polish initiative, which aims at compiling and linking existing information on Admiralty Bay benthos biodiversity and ecology. This information will be digitized into a database and linked to wider Antarctic marine biodiversity initiatives, such as SCAR-MarBIN, which will disseminate the information through a web portal. Being highly diverse in its content, formats and data providers, ABBED will constitute an extremely interesting case-study for SCAR-MarBIN, allowing to test strategic options which were retained for the development of the network. Moreover, the quality and quantity of data which will be made available to the community will reinforce the status of Admiralty Bay as a true reference point for Antarctic biodiversity research. The project aims at developing an interactive database on the biodiversity of benthic communities of Admiralty Bay, King George Island, for scientific, monitoring, management and conservation purposes. It is intended to be a springboard for promoting future research in this region, by centralizing the relevant information for i.e. scientific programme design. proprietary
+scarmarbin_ABBED Admiralty Bay Benthos Biodiversity Database [SCAR-MarBIN] ALL STAC Catalog 1906-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214155568-SCIOPS.umm_json Admiralty Bay is one of the best studied sites in the maritime Antarctic. The first benthos data has been recorded in 1906 and knowledge is constantly gained by the research activities of permanent stations, Arctowski (Poland, since 1977), and Ferraz (Brazil, since 1984). Admiralty Bay is a protected area within the Antarctic Treaty System, an Antarctic Specially Managed Area (ASMA). It was also a reference site under the EASIZ programme, and has been or is currently investigated by several nations : Poland, Brazil, United States, Peru, Ecuador, Germany, The Netherlands, Belgium. ABBED (Admiralty Bay Benthos Biodiversity Database) is a Belgian-Polish initiative, which aims at compiling and linking existing information on Admiralty Bay benthos biodiversity and ecology. This information will be digitized into a database and linked to wider Antarctic marine biodiversity initiatives, such as SCAR-MarBIN, which will disseminate the information through a web portal. Being highly diverse in its content, formats and data providers, ABBED will constitute an extremely interesting case-study for SCAR-MarBIN, allowing to test strategic options which were retained for the development of the network. Moreover, the quality and quantity of data which will be made available to the community will reinforce the status of Admiralty Bay as a true reference point for Antarctic biodiversity research. The project aims at developing an interactive database on the biodiversity of benthic communities of Admiralty Bay, King George Island, for scientific, monitoring, management and conservation purposes. It is intended to be a springboard for promoting future research in this region, by centralizing the relevant information for i.e. scientific programme design. proprietary
schweizerisches-landesforstinventar-2009-2017_1.0 Schweizerisches Landesforstinventar. Ergebnisse der vierten Erhebung 2009–2017 ENVIDAT STAC Catalog 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789817193-ENVIDAT.umm_json Swiss National Forest Inventory. Results of the fourth survey 2009–2017. The collection of data for the fourth National Forest Inventory (NFI) was carried out from 2009 to 2017, on average eight years after the third survey. The findings about state and development of Swiss forests are described and explained in detail. The report is structured according to the European criteria and indicators for sustainable forest management, namely: forest resources, health and vitality, wood production, biological diversity, protection forest and social economy. Finally, conclusions about sustainability are drawn based on the NFI findings. Keywords: forest area, growing stock, increment, yield, forest structure, forest condition, timber production, biodiversity, protection forest, recreation, sustainability, results National Forest Inventory, Switzerland Schweizerisches Landesforstinventar. Ergebnisse der vierten Erhebung 2009–2017. In den Jahren 2009 bis 2017 fanden die Erhebungen zum vierten Schweizerischen Landesforstinventar (LFI) statt, im Durchschnitt acht Jahre nach der dritten Erhebung. Die Resultate über den Zustand und die Entwicklung des Schweizer Waldes werden umfassend dargestellt und erläutert. Der Bericht ist thematisch strukturiert nach den europäischen Kriterien und Indikatoren zur nachhaltigen Bewirtschaftung des Waldes: Waldressourcen, Gesundheit und Vitalität, Holzproduktion, biologische Vielfalt, Schutzwald und Sozioökonomie. Eine Bilanz zur Nachhaltigkeit, basierend auf LFI-Ergebnissen, schliesst die Publikation ab. Keywords: Waldfläche, Holzvorrat, Zuwachs, Nutzung, Waldaufbau, Waldzustand, Holzproduktion, Biodiversität, Schutzwald, Erholung, Nachhaltigkeit, Ergebnisse Landesforstinventar, Schweiz Content license: All rights reserved. Copyright © 2020 by WSL, Birmensdorf. proprietary
scolytidae_1.0 Scolytidae ENVIDAT STAC Catalog 2019-01-01 2019-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789817304-ENVIDAT.umm_json Scolytidae data from all historic up to the recent projects (29.10.2019) of WSL, collected with various methods in forests of different types. Data are provided on request to contact person against bilateral agreement. proprietary
scrxsondecpexaw_1 St. Croix Radiosondes CPEX-AW V1 GHRC_DAAC STAC Catalog 2021-08-19 2021-09-14 -65.2209, 17.4441, -64.6749, 18.0047 https://cmr.earthdata.nasa.gov/search/concepts/C2418992215-GHRC_DAAC.umm_json The St. Croix Radiosondes CPEX-AW dataset consists of atmospheric pressure, atmospheric temperature, relative humidity, wind speed, and wind direction measurements. These measurements were taken from the DFM-09 Radiosonde instrument during the Convective Processes Experiment – Aerosols & Winds (CPEX-AW) field campaign. CPEX-AW was a joint effort between the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) with the primary goal of conducting a post-launch calibration and validation activities of the Atmospheric Dynamics Mission-Aeolus (ADM-AEOLUS) Earth observation wind Lidar satellite in St. Croix, U.S. Virgin Islands. Data are available from August 19, 2021 through September 14, 2021 in netCDF and ASCII formats, with associated browse imagery in PNG format. proprietary
@@ -20470,8 +20471,8 @@ sentinel-3-olci-l1-bundle-1_NA Sentinel-3/OLCI - Level-1B Full Resolution INPE S
shadoz_ozonesonde_726_1 SAFARI 2000 SHADOZ Ozonesonde Data, Zambia and Regional Sites, Dry Season 2000 ORNL_CLOUD STAC Catalog 2000-08-01 2000-11-30 55.48, -7.98, 55.48, -7.98 https://cmr.earthdata.nasa.gov/search/concepts/C2789016629-ORNL_CLOUD.umm_json Ozonesonde launches were made by the Southern Hemisphere ADditional OZonesondes (SHADOZ) group as part of the SAFARI 2000 Dry Season Campaign in September 2000 (Thompson et al., 2002). Ozonesondes are balloon-borne instruments measuring profile ozone, as well as temperature and pressure from an attached radiosonde, up to 35 km in height (around 5 hPa in pressure coordinates) capturing the troposphere and lower stratospheric portion of the atmosphere. During the campaign, ozonesondes were launched daily during the height of the burning season and in a region of active biomass burning activity. proprietary
shirley_dem_1 A digital elevation model (DEM) and orthophoto of Shirley Island, Windmill Islands, Antarctica ALL STAC Catalog 2005-01-01 2007-05-01 110.473, -66.287, 110.509, -66.277 https://cmr.earthdata.nasa.gov/search/concepts/C1214311290-AU_AADC.umm_json This dataset includes: (i) a 2 metre resolution digital elevation model (DEM) of Shirley Island, Windmill Islands, Antarctica; (ii) reliability data for the DEM; (iii) contours interpolated from the DEM; and (iv) an orthophoto created using the DEM. The data are stored in the UTM zone 49 map projection. The horizontal datum is WGS84. The data were created by Robert Anders, Centre for Spatial Information Science, University of Tasmania, Australia to support the postgraduate research of Phillipa Bricher into the nesting sites of Adelie Penguins. See a related URL below for a map showing Shirley island. proprietary
shirley_dem_1 A digital elevation model (DEM) and orthophoto of Shirley Island, Windmill Islands, Antarctica AU_AADC STAC Catalog 2005-01-01 2007-05-01 110.473, -66.287, 110.509, -66.277 https://cmr.earthdata.nasa.gov/search/concepts/C1214311290-AU_AADC.umm_json This dataset includes: (i) a 2 metre resolution digital elevation model (DEM) of Shirley Island, Windmill Islands, Antarctica; (ii) reliability data for the DEM; (iii) contours interpolated from the DEM; and (iv) an orthophoto created using the DEM. The data are stored in the UTM zone 49 map projection. The horizontal datum is WGS84. The data were created by Robert Anders, Centre for Spatial Information Science, University of Tasmania, Australia to support the postgraduate research of Phillipa Bricher into the nesting sites of Adelie Penguins. See a related URL below for a map showing Shirley island. proprietary
-simrad_SO Acoustic responses to water column features, Antarctic, Aug-Sept 2002, GLOBEC. SCIOPS STAC Catalog 2002-08-03 2002-09-15 -75.5, -68.75, -69.5, -65.75 https://cmr.earthdata.nasa.gov/search/concepts/C1214155475-SCIOPS.umm_json Using the hull mounted Simrad EK500 Scientific Sounder System, acoustic returns from 38, 120, and 200 kHz transducers were recorded continuously along ship's track from Aug 3 - Sept 15, 2002. Of interest, was the acoustic returns from zooplankton patches and density structures, and the signel correlations with known plankton tows and CTD casts. The survey area included the continental margin to the west of the Antarctic Peninsula extending from the northern tip of Adelaide Island to the southern portion of Alexander Island, Crystal Sound, and Marguerite Bay. These data have been reduced to daily files and are supported by software for manipulative purposes. Ship name/cruise ID/dates of cruise RVIB Nathaniel B. Palmer / NBP0204 / Jul 31-Sep 18 2002 proprietary
simrad_SO Acoustic responses to water column features, Antarctic, Aug-Sept 2002, GLOBEC. ALL STAC Catalog 2002-08-03 2002-09-15 -75.5, -68.75, -69.5, -65.75 https://cmr.earthdata.nasa.gov/search/concepts/C1214155475-SCIOPS.umm_json Using the hull mounted Simrad EK500 Scientific Sounder System, acoustic returns from 38, 120, and 200 kHz transducers were recorded continuously along ship's track from Aug 3 - Sept 15, 2002. Of interest, was the acoustic returns from zooplankton patches and density structures, and the signel correlations with known plankton tows and CTD casts. The survey area included the continental margin to the west of the Antarctic Peninsula extending from the northern tip of Adelaide Island to the southern portion of Alexander Island, Crystal Sound, and Marguerite Bay. These data have been reduced to daily files and are supported by software for manipulative purposes. Ship name/cruise ID/dates of cruise RVIB Nathaniel B. Palmer / NBP0204 / Jul 31-Sep 18 2002 proprietary
+simrad_SO Acoustic responses to water column features, Antarctic, Aug-Sept 2002, GLOBEC. SCIOPS STAC Catalog 2002-08-03 2002-09-15 -75.5, -68.75, -69.5, -65.75 https://cmr.earthdata.nasa.gov/search/concepts/C1214155475-SCIOPS.umm_json Using the hull mounted Simrad EK500 Scientific Sounder System, acoustic returns from 38, 120, and 200 kHz transducers were recorded continuously along ship's track from Aug 3 - Sept 15, 2002. Of interest, was the acoustic returns from zooplankton patches and density structures, and the signel correlations with known plankton tows and CTD casts. The survey area included the continental margin to the west of the Antarctic Peninsula extending from the northern tip of Adelaide Island to the southern portion of Alexander Island, Crystal Sound, and Marguerite Bay. These data have been reduced to daily files and are supported by software for manipulative purposes. Ship name/cruise ID/dates of cruise RVIB Nathaniel B. Palmer / NBP0204 / Jul 31-Sep 18 2002 proprietary
simulated-avalanche-problem-types-at-weissfluhjoch-1999-2017_1.0 Simulated avalanche problem types and seismic avalanche activity around Weissfluhjoch ENVIDAT STAC Catalog 2021-01-01 2021-01-01 9.80934, 46.82962, 9.80934, 46.82962 https://cmr.earthdata.nasa.gov/search/concepts/C2789817408-ENVIDAT.umm_json Avalanche problem types were derived from snow cover simulations with the models Crocus and SNOWPACK at the Weissfluhjoch study plot, Davos, CH. The data include annual frequencies of avalanche problem types for the seasons 1999-2017 and daily presence of avalanche problem types for the period 01.01.2016 - 30.04.2016. Avalanche activity was derived from two seismic sensor arrays deployed no further than 15 km from Weissfluhjoch, Davos, CH. The data cover the period 01.01.2016 - 30.04.2016. proprietary
simulated-future-discharge-and-climatological-variables_1.0 Simulated future discharge and climatological variables for medium-sized catchments in Switzerland ENVIDAT STAC Catalog 2019-01-01 2019-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789817564-ENVIDAT.umm_json "Daily discharge and the related hydro-meteorological variables precipitation, snowmelt, and soil moisture are provided for current (1981-2017) and for future climate conditions (1981-2100) for 307 medium-sized catchments in Switzerland. The catchments have a median catchment area of 117 km². The 307 catchments together form a set representative of the climatological conditions and runoff characteristics in Switzerland. The four variables were simulated at a daily resolution using the hydrological model PREVAH. PREVAH is a conceptual process-based model that was run in this study in its fully distributed version on a 500 m grid (Viviroli et al. 2009a). For the calibration, runoff time series from 140 mesoscale catchments covering the different runoff regimes were used. The model calibration was conducted over the period 1993-1997. Verification was performed on the period 1983-2005 using (i) volumetric deviation (Viviroli et al. 2007) and (ii) benchmark efficiency (Schäfli et al 2007) as objective functions. The calibration and validation procedures are described in detail in Köplin et al. (2010). The parameters for each model grid cell were derived by regionalizing the parameters obtained for the 140 catchments with a procedure based on ordinary kriging (Viviroli et al. 2009b, Köplin et al. 2010). The calibrated and validated model was then driven with transient meteorological data (precipitation, temperature, radiation, and wind) representing both reference (1981-2017) and future climate conditions (2018-2099). The data were derived from the CH2018 climate scenarios (NCCS 2018) provided by the Swiss National Centre for Climate Services (NCCS). They were obtained from climate experiments produced with different climate modeling chains, consisting of a global and a regional circulation model each, within EUROCORDEX for three representative concentration pathways (RCP) emission scenarios. Downscaled output of ten climate model chains derived by quantile mapping were considered. The focus was on the chains of the EUR-11 domain with a horizontal resolution of 0.11 degrees (roughly 12.5 km). The climate model chains (GCM, RCM, RCP, and grid resolution) used are listed below: - ICHEC-EC-EARTH DMI-HIRHAM5 2.6 EUR-11 - ICHEC-EC-EARTH DMI-HIRHAM5 4.5 EUR-11 - ICHEC-EC-EARTH DMI-HIRHAM5 8.5 EUR-11 - ICHEC-EC-EARTH SMHI-RCA4 2.6 EUR-11 - ICHEC-EC-EARTH SMHI-RCA4 4.5 EUR-11 - ICHEC-EC-EARTH SMHI-RCA4 8.5 EUR-11 - MOHC-HadGEM2-ES SMHI-RCA4 4.5 EUR-11 - MOHC-HadGEM2-ES SMHI-RCA4 8.5 EUR-11 - MPI-M-MPI-ESM-LR SMHI-RCA4 4.5 EUR-11 - MPI-M-MPI-ESM-LR SMHI-RCA4 8.5 EUR-11 __*References*__: - Köplin, N., D. Viviroli, B. Schädler, and R. Weingartner (2010), _How does climate change affect mesoscale catchments in Switzerland? - A framework for a comprehensive assessment_, Advances in Geosciences, 27, 111-119, doi:10.5194/adgeo-27-111-2010. - National Centre for Climate Services (2018), CH2018 - _Climate Scenarios for Switzerland_, Tech. rep., NCCS, Zurich. - Schäfli, B., and H. V. Gupta (2007), _Do Nash values have value?_, Hydrological Processes, 21, 2075-2080, doi:10.1002/hyp.6825. - Viviroli, D., J. Gurtz, and M. Zappa (2007), _The hydrological modelling system PREVAH. Part II - Physical model description_, Geographica Bernensia, 40, 1-89. - Viviroli, D., M. Zappa, J. Gurtz, and R. Weingartner (2009a), _An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools_, Environmental Modelling & Software, 24, 1209-1222, doi:10.1016/j.envsoft.2009.04.001. - Viviroli, D., H. Mittelbach, J. Gurtz, and R. Weingartner (2009b), _Continuous simulation for flood estimation in ungauged mesoscale catchments of Switzerland-Part II: Parameter regionalisation and flood estimation results_, Journal of Hydrology, 377 (1), 208-225, doi:10.1016/j.jhydrol.2009.08.022." proprietary
simulating-chamois-populations_1.0 Simulating population divergence of Northern chamois in the Alps based on habitat dynamics ENVIDAT STAC Catalog 2022-01-01 2022-01-01 4.8, 43.5, 16.3, 48.3 https://cmr.earthdata.nasa.gov/search/concepts/C2789817711-ENVIDAT.umm_json # General description Genomic data, habitat suitability raster files and scripts to run gen3sis to simulate cumulative divergence over time as approximation for genetic differentiation. Scripts for basic analysis of the simulations (e.g., create distance matrix from sampling locations) are provided, too. See original publication (doi link will be provided after publication) for details. The study area are the European Alps. All data is uploaded as zipped file. Unzip them after the download and put all data in one folder. See linked publications for correct citation of the data used, use of the data without correct citation is not allowed. __Corresponding author__: Flurin Leugger, email: flurin.leugger@gmail.com # Description of the data (content of the different zip folders) ## Abiotic data ### Glaciers Folders with raster stacks with glaciated areas at 0.05° resolution in WGS84 projection from Seguinot et al. (2018). Seguinot, J., Ivy-Ochs, S., Jouvet, G., Huss, M., Funk, M., & Preusser, F. (2018). Modelling last glacial cycle ice dynamics in the Alps. _The Cryosphere, 12(10)_, 3265–3285. https://doi.org/10.5194/tc-12-3265-2018 ### Rivers * __river_raster_elevation_class.tif__: raster file (.tif) at 0.05° resolution and WGS84 projection with large rivers (scenario 2 from publication). The rivers (each cell) is classified according to the elevation of the cell. Natural Earth. (2018). Rivers + lake centerlines version 4.1.0. Retrieved January 22, 2020, from https://www.naturalearthdata.com/downloads/50m-physical-vectors/50m-rivers-lake-centerlines * __river_raster_strahler_class_5km.tif__: raster file at 0.05° resolution and WGS84 projection with medium rivers. The rivers are classified according to their Strahler order. Food and Agriculture Organization of the United Nations. (2014). Rivers in Europe (Derived from HydroSHEDS). Retrieved January 29, 2020, from http://www.fao.org/geonetwork/srv/fr/google.kml?uuid=e0243940-e5d9-487c-8102-45180cf1a99f&layers=AQUAMAPS:37253_rivers_europe ## Fossil records * __chamois_fossil_combined_public.xlsx__: list with fossil records until 20,000 years BP from Central Europe, see linked references for citation. ## Chamois occurrences * __chamois_occurrence.csv__: Chamois presences from all sources used for the publication (see Suppl. mat. Table S1 for detailed information and correct citations of the data) aggregated at 0.05° resolution (~5km). ## Gen3sis * __config__: folders with all configuration files used to run the simulations for the publication (different dispersal divergence parameters). * __scripts__: scripts (and helper functions) to run the gen3sis simulations including scripts for the beginning of the subsequent analysis. ## Genetic * __populations.snps.light.vcf__: vcf file of the sampled Northern chamois _(Rupicapra rupicapra)_ . The genomic data encompasses 20k SNPs (from ddRAD sequencing). * __Sequencing_final_without_slovakia.txt__: sampling locations of Northern chamois _(Rupicapra rupicapra)_ ## HSM * __habitat_suitability_hindcasting__: Aggregated habitat suitability raster files (stacks, .grd files) at 0.05° resolution and WGS84 projection from 20,000 years BP until today in 100 year time steps. There are separate folders for each environmental variable scenario used (different terrain slope variables) an the different occurrence/pseudo-absence sampling strategy used. * __ODMAP_LeuggerEtAl__2021-10-25.csv__: ODMAP protocol proprietary
@@ -20899,8 +20900,8 @@ usgs_nawqa_acf_surfacewater Apalachicola-Chatahoochee-Flint River Basin Surface
usgs_nawqa_acfriver_groundwater Apalachicola-Chatahoochee Flint River Basin Ground Water Data CEOS_EXTRA STAC Catalog 1992-08-01 1995-09-01 -86, 30, -81, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2231550128-CEOS_EXTRA.umm_json Surface- and ground-water quality data were collected in the Apalachicola-Chattahoochee-Flint (ACF) River basin from August 1992 to September 1995 as part of the USGS National Water Quality Assessment (NAWQA) program described below. The ACF River basin drains about 19,800 square miles in western Georgia, eastern Alabama, and the Florida panhandle into the Apalachicola Bay, which discharges into the Gulf of Mexico. Data collected as part of this study focused on five major land uses: poultry production in the headwaters of the Chattahoochee River, urban and suburban areas of Metropolitan Atlanta and Columbus, silviculture in the piedmont and fall line hills, and row crop agriculture in the upper coastal plain (clastic hydrogeologic setting) and the lower coastal plain (karst hydrogeologic setting). This description is for the ground-water data. Data for the ground-water component of the ACF River basin study were collected as part of three studies: Study Unit Survey, Land Use Studies (Urban and Agriculture) and Agricultural flow system study. The data are grouped by study component and site type (wells, springs, drains, and pore water) and are subdivided into sets of data consisting of related constituents. A complete list of constituent names and MRL's are available. The user can view and retrieve these ground-water data sets: Field measurements, Nutrients, Organic carbon, Turbidity, Major Ions, Pesticides, Trace elements (collected as part of the Study Unit Survey and Urban Landuse only), Volatile organic compounds, Radionuclides and Stable isotopes. Ground-water quality data were collected at 161 sites within the ACF River basin. These sites included a combination of monitoring and domestic wells, springs and seeps, and subsurface drains. The data are concentrated in the Metropolitan Atlanta (urban land use) area and in the coastal plain (agricultural land use). These data and associated locator maps are accessible on the World Wide Web at the ACF NAWQA home page. Data are presented in manageable tables that are grouped based on land use, site type, and project component. The user can view maps and data tables on the computer screen, or downloaded data tables as tab delimited (RDB) files. Data collected as part of the ACF River basin study are presented by project component: surface-water, ground-water, special studies, streamflow, ancillary, and quality assurance data. The water-quality data are presented by major headings, including water-column, bed-sediment and tissue, and biological. The data are further subdivided into data sets consisting of related constituents. Data tables can be viewed on the users computer screen or retrieved to a users computer as a tab delimited Relational Data Base (RDB) file. To reduce the size of the pesticide, volatile organic compound, bed sediment and tissue, and trace element tables, only those compounds found equal to, or above the minimum reporting limit (MRL) for one or more sites within a group, are shown. The remaining compounds were not detected. A complete list of constituent names and MRL's are available. The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) is designed to describe the status and trends in the quality of the Nation's ground- and surface-water resources and to provide a sound understanding of the natural and human factors that affect the quality of these resources (Leahy and others, 1990). Because much of the public concern over water quality stems from a desire to protect both human health and aquatic life, the NAWQA Program will, in addition to measuring physical and chemical indicators of water-quality, assess the status of aquatic life through surveys of fish, invertebrates, and benthic algae, and habitat conditions (National Research Council, 1990). As an integrated assessment of water quality incorporating physical, chemical, and biological components, the NAWQA Program is ecological in approach. proprietary
usgs_nps_agatefossilbeds Agate Fossil Beds National Monument, Field Plots Data Base for Vegetation Mapping CEOS_EXTRA STAC Catalog 1995-07-10 1995-08-15 -103.8, 42.40833, -103.7, 42.44167 https://cmr.earthdata.nasa.gov/search/concepts/C2231549635-CEOS_EXTRA.umm_json "Vegetation field plots at Agate Fossil Beds NM were visited, described, and documented in a digital database. The database consists of 2 parts - (1) Physical Descriptive Data, and (2) Species Listings. The purpose of the field plots was to provide National Parks with the necessary tools to effectively manage their natural resources. Plot data is collected and analyzed to develop a classification (using the Standardized National Vegetation Classification System) and description of vegetation types in preparation for photointerpretation and mapping of the monument's vegetation types. The field plotting took place in the Agate Fossil Beds National Monument and a 400 meter buffer. Field sampling was done using releve plots. The descriptive plot data were collected for 39 sites whose vegetation represents a full spectrum of alliance types present within Agate Fossil Beds National Monument and its immediate surroundings. Physical description - Attributes collected for each site include: a plot number, a unique plot identification code, community name, field name, state, park name, quad name, map projection, datum, GPS file name, raw UTM coordinates, differentially corrected UTM coordinates, plot survey date, name(s) of surveyors, length, width, photo type, elevation, slope, aspect, topographic position, landform, surface geology, Cowardin System category, hydrology, surface material description, soil texture, soil drainage, leaf phenology, leaf type, and physiognomy. Species - Individual species described at each of 39 plots is listed, one line per species, with the following information: Plot Identification Code, Numeric Species Code, Species Name, Species Cover (0=trace, 1=< 1%, 2=1-5%, 3=5-25%, 4=25-50%, 5=50-75%, 6=75-100%), Plantcode, and Strata Code (T1=emergent, T2=canopy, T3=sub-canopy, S1=tall shrub, S2=short shrub, H=herbaceous, N=non-vascular, V=vinae/liana, E=epiphyte). Information for this metadata was taken from ""http://biology.usgs.gov/npsveg/agfo/metaagfofield.html""." proprietary
usgs_nps_agatefossilbeds Agate Fossil Beds National Monument, Field Plots Data Base for Vegetation Mapping ALL STAC Catalog 1995-07-10 1995-08-15 -103.8, 42.40833, -103.7, 42.44167 https://cmr.earthdata.nasa.gov/search/concepts/C2231549635-CEOS_EXTRA.umm_json "Vegetation field plots at Agate Fossil Beds NM were visited, described, and documented in a digital database. The database consists of 2 parts - (1) Physical Descriptive Data, and (2) Species Listings. The purpose of the field plots was to provide National Parks with the necessary tools to effectively manage their natural resources. Plot data is collected and analyzed to develop a classification (using the Standardized National Vegetation Classification System) and description of vegetation types in preparation for photointerpretation and mapping of the monument's vegetation types. The field plotting took place in the Agate Fossil Beds National Monument and a 400 meter buffer. Field sampling was done using releve plots. The descriptive plot data were collected for 39 sites whose vegetation represents a full spectrum of alliance types present within Agate Fossil Beds National Monument and its immediate surroundings. Physical description - Attributes collected for each site include: a plot number, a unique plot identification code, community name, field name, state, park name, quad name, map projection, datum, GPS file name, raw UTM coordinates, differentially corrected UTM coordinates, plot survey date, name(s) of surveyors, length, width, photo type, elevation, slope, aspect, topographic position, landform, surface geology, Cowardin System category, hydrology, surface material description, soil texture, soil drainage, leaf phenology, leaf type, and physiognomy. Species - Individual species described at each of 39 plots is listed, one line per species, with the following information: Plot Identification Code, Numeric Species Code, Species Name, Species Cover (0=trace, 1=< 1%, 2=1-5%, 3=5-25%, 4=25-50%, 5=50-75%, 6=75-100%), Plantcode, and Strata Code (T1=emergent, T2=canopy, T3=sub-canopy, S1=tall shrub, S2=short shrub, H=herbaceous, N=non-vascular, V=vinae/liana, E=epiphyte). Information for this metadata was taken from ""http://biology.usgs.gov/npsveg/agfo/metaagfofield.html""." proprietary
-usgs_nps_agatefossilbedsspatial Agate Fossil Beds National Monument Spatial Vegetation Data: Cover Type/Association Level of the National Vegetation Classification System CEOS_EXTRA STAC Catalog 1995-07-29 1995-07-29 -103.8, 42.40833, -103.7, 42.44167 https://cmr.earthdata.nasa.gov/search/concepts/C2231550884-CEOS_EXTRA.umm_json "The National Park Service (NPS), in conjunction with the Biological Resources Division (BRD) of the U.S. Geological Survey (USGS), has implemented a program to ""develop a uniform hierarchical vegetation methodology"" at a national level. The program will also create a geographic information system (GIS) database for the parks under its management. The purpose of the data is to document the state of vegetation within the NPS service area during the 1990's, thereby providing a baseline study for further analysis at the Regional or Service-wide level. The vegetation units of this map were determined through stereoscopic interpretation of aerial photographs supported by field sampling and ecological analysis. The vegetation boundaries were identified on the photographs by means of the photographic signatures and collateral information on slope, hydrology, geography, and vegetation in accordance with the Standardized National Vegetation Classification System (October 1995). The mapped vegetation reflects conditions that existed during the specific year and season that the aerial photographs were taken (July, 1995). There is an inherent margin of error in the use of aerial photography for vegetation delineation and classification. The purpose of this spatial data is to provide the National Park Service the necessary tools to manage the natural resources within this park system. Several parks, representing different regions, environmental conditions, and vegetation types, were chosen by BRD to be part of the prototype phase of the program. The initial goal of the prototype phase is to ""develop, test, refine, and finalize the standards and protocols"" to be used during the production phase of the project. This includes the development of a standardized vegetation classification system for each park and the establishment of photointerpretation, field, and accuracy assessment procedures. Agate Fossil Beds National Monument was designated as one of the prototype parks. The monument is located in the high Great Plains. It contains prairie, hill, and riverine environments, with vegetation types that include prairie grassland, riverine woodland, and wetlands. The vegetation units were photointerpreted from stereo-paired, natural color photography. Agate Fossil Beds National Monument was created by the National Park Service on June 5, 1965. The park occupies 4.5 square miles of land straddling the Niobrara River in the middle of the Nebraska Panhandle. The park is noted for its history, prehistoric fossils, and scenic quality. Historically, the park was a part of the Agate Springs Ranch, owned by Captain James H. Cook. The park has a collection of ranching and Native American artifacts and memorabilia as a result of its donation from the Ranch. Paleontologically, the park contains a number of Miocene fossil quarries that were excavated through the late 19th century and early 20th century. From a scenic aspect, the park has views of rolling hills, bluffs, and the Niobrara River floodplain. Ranching is also an active part of the landscape. The park is located in the grassy rolling hills of Western Nebraska. The park landscape consists of the east-west trending cap-rocked northern and southern hills, with the treeless Niobrara River floodplain running down the middle of the valley. The city of Harrison is located 23 miles to the north, Mitchell is 34 miles to the south. State Highway 29 runs north-south through the western part of the park. The Vegetation mapping was conducted in Agate Fossil Beds National Moument, Nebraska with a 400 meter buffer. A total of 39 plots were obtained from July 10 through August 15, 1995. These plots were used by TNC to describe the vegetation associations found within the park. These descriptions are in the companion report by TNC. Map Validation A field trip was conducted in August of 1997 to assess the initial mapping effort and to refine map class. Information for this metadata was taken from ""http://biology.usgs.gov/npsveg/agfo/metaagfospatial.html"" and converted to the NASA Directory Interchange Format. Another site to obtain the data is located at Online_Resource: ""ftp://ftp.cbi.usgs.gov/pub/vegmapping/agfo/agfo.exe""." proprietary
usgs_nps_agatefossilbedsspatial Agate Fossil Beds National Monument Spatial Vegetation Data: Cover Type/Association Level of the National Vegetation Classification System ALL STAC Catalog 1995-07-29 1995-07-29 -103.8, 42.40833, -103.7, 42.44167 https://cmr.earthdata.nasa.gov/search/concepts/C2231550884-CEOS_EXTRA.umm_json "The National Park Service (NPS), in conjunction with the Biological Resources Division (BRD) of the U.S. Geological Survey (USGS), has implemented a program to ""develop a uniform hierarchical vegetation methodology"" at a national level. The program will also create a geographic information system (GIS) database for the parks under its management. The purpose of the data is to document the state of vegetation within the NPS service area during the 1990's, thereby providing a baseline study for further analysis at the Regional or Service-wide level. The vegetation units of this map were determined through stereoscopic interpretation of aerial photographs supported by field sampling and ecological analysis. The vegetation boundaries were identified on the photographs by means of the photographic signatures and collateral information on slope, hydrology, geography, and vegetation in accordance with the Standardized National Vegetation Classification System (October 1995). The mapped vegetation reflects conditions that existed during the specific year and season that the aerial photographs were taken (July, 1995). There is an inherent margin of error in the use of aerial photography for vegetation delineation and classification. The purpose of this spatial data is to provide the National Park Service the necessary tools to manage the natural resources within this park system. Several parks, representing different regions, environmental conditions, and vegetation types, were chosen by BRD to be part of the prototype phase of the program. The initial goal of the prototype phase is to ""develop, test, refine, and finalize the standards and protocols"" to be used during the production phase of the project. This includes the development of a standardized vegetation classification system for each park and the establishment of photointerpretation, field, and accuracy assessment procedures. Agate Fossil Beds National Monument was designated as one of the prototype parks. The monument is located in the high Great Plains. It contains prairie, hill, and riverine environments, with vegetation types that include prairie grassland, riverine woodland, and wetlands. The vegetation units were photointerpreted from stereo-paired, natural color photography. Agate Fossil Beds National Monument was created by the National Park Service on June 5, 1965. The park occupies 4.5 square miles of land straddling the Niobrara River in the middle of the Nebraska Panhandle. The park is noted for its history, prehistoric fossils, and scenic quality. Historically, the park was a part of the Agate Springs Ranch, owned by Captain James H. Cook. The park has a collection of ranching and Native American artifacts and memorabilia as a result of its donation from the Ranch. Paleontologically, the park contains a number of Miocene fossil quarries that were excavated through the late 19th century and early 20th century. From a scenic aspect, the park has views of rolling hills, bluffs, and the Niobrara River floodplain. Ranching is also an active part of the landscape. The park is located in the grassy rolling hills of Western Nebraska. The park landscape consists of the east-west trending cap-rocked northern and southern hills, with the treeless Niobrara River floodplain running down the middle of the valley. The city of Harrison is located 23 miles to the north, Mitchell is 34 miles to the south. State Highway 29 runs north-south through the western part of the park. The Vegetation mapping was conducted in Agate Fossil Beds National Moument, Nebraska with a 400 meter buffer. A total of 39 plots were obtained from July 10 through August 15, 1995. These plots were used by TNC to describe the vegetation associations found within the park. These descriptions are in the companion report by TNC. Map Validation A field trip was conducted in August of 1997 to assess the initial mapping effort and to refine map class. Information for this metadata was taken from ""http://biology.usgs.gov/npsveg/agfo/metaagfospatial.html"" and converted to the NASA Directory Interchange Format. Another site to obtain the data is located at Online_Resource: ""ftp://ftp.cbi.usgs.gov/pub/vegmapping/agfo/agfo.exe""." proprietary
+usgs_nps_agatefossilbedsspatial Agate Fossil Beds National Monument Spatial Vegetation Data: Cover Type/Association Level of the National Vegetation Classification System CEOS_EXTRA STAC Catalog 1995-07-29 1995-07-29 -103.8, 42.40833, -103.7, 42.44167 https://cmr.earthdata.nasa.gov/search/concepts/C2231550884-CEOS_EXTRA.umm_json "The National Park Service (NPS), in conjunction with the Biological Resources Division (BRD) of the U.S. Geological Survey (USGS), has implemented a program to ""develop a uniform hierarchical vegetation methodology"" at a national level. The program will also create a geographic information system (GIS) database for the parks under its management. The purpose of the data is to document the state of vegetation within the NPS service area during the 1990's, thereby providing a baseline study for further analysis at the Regional or Service-wide level. The vegetation units of this map were determined through stereoscopic interpretation of aerial photographs supported by field sampling and ecological analysis. The vegetation boundaries were identified on the photographs by means of the photographic signatures and collateral information on slope, hydrology, geography, and vegetation in accordance with the Standardized National Vegetation Classification System (October 1995). The mapped vegetation reflects conditions that existed during the specific year and season that the aerial photographs were taken (July, 1995). There is an inherent margin of error in the use of aerial photography for vegetation delineation and classification. The purpose of this spatial data is to provide the National Park Service the necessary tools to manage the natural resources within this park system. Several parks, representing different regions, environmental conditions, and vegetation types, were chosen by BRD to be part of the prototype phase of the program. The initial goal of the prototype phase is to ""develop, test, refine, and finalize the standards and protocols"" to be used during the production phase of the project. This includes the development of a standardized vegetation classification system for each park and the establishment of photointerpretation, field, and accuracy assessment procedures. Agate Fossil Beds National Monument was designated as one of the prototype parks. The monument is located in the high Great Plains. It contains prairie, hill, and riverine environments, with vegetation types that include prairie grassland, riverine woodland, and wetlands. The vegetation units were photointerpreted from stereo-paired, natural color photography. Agate Fossil Beds National Monument was created by the National Park Service on June 5, 1965. The park occupies 4.5 square miles of land straddling the Niobrara River in the middle of the Nebraska Panhandle. The park is noted for its history, prehistoric fossils, and scenic quality. Historically, the park was a part of the Agate Springs Ranch, owned by Captain James H. Cook. The park has a collection of ranching and Native American artifacts and memorabilia as a result of its donation from the Ranch. Paleontologically, the park contains a number of Miocene fossil quarries that were excavated through the late 19th century and early 20th century. From a scenic aspect, the park has views of rolling hills, bluffs, and the Niobrara River floodplain. Ranching is also an active part of the landscape. The park is located in the grassy rolling hills of Western Nebraska. The park landscape consists of the east-west trending cap-rocked northern and southern hills, with the treeless Niobrara River floodplain running down the middle of the valley. The city of Harrison is located 23 miles to the north, Mitchell is 34 miles to the south. State Highway 29 runs north-south through the western part of the park. The Vegetation mapping was conducted in Agate Fossil Beds National Moument, Nebraska with a 400 meter buffer. A total of 39 plots were obtained from July 10 through August 15, 1995. These plots were used by TNC to describe the vegetation associations found within the park. These descriptions are in the companion report by TNC. Map Validation A field trip was conducted in August of 1997 to assess the initial mapping effort and to refine map class. Information for this metadata was taken from ""http://biology.usgs.gov/npsveg/agfo/metaagfospatial.html"" and converted to the NASA Directory Interchange Format. Another site to obtain the data is located at Online_Resource: ""ftp://ftp.cbi.usgs.gov/pub/vegmapping/agfo/agfo.exe""." proprietary
usgs_nps_congareeswamp Congaree Swamp National Monument Field Plots Data Base for Vegetation Mapping CEOS_EXTRA STAC Catalog 1996-06-01 1996-09-01 -80.85, 33.75, -80.67083, 33.84167 https://cmr.earthdata.nasa.gov/search/concepts/C2231552960-CEOS_EXTRA.umm_json "Vegetation field plots at Congaree Swamp National Monument were visited, described, and documented in a digital database. The database consists of 2 parts - (1) Physical Descriptive Data, and (2) Species Listings. The vegetation plots were used to describe the vegetation in and around Congaree Swamp National Monument and to assist in developing a final mapping classification system. On June 30, 1983, Congaree Swamp National Monument became an International Biosphere Reserve. Congaree is noted for containing one of the last significant stands of old growth bottomland hardwood forest, over 11,000 acres in all. The Monument contains over 90 species of trees, 16 of which hold state records for size. Included in this list of records is a national record sweet gum with a basal circumference of nearly 20 feet. Congaree Swamp National Monument is located approximately 15 miles southeast of Columbia, the state capitol of South Carolina. Old Bluff Highway (old Highway 48) lies just north of the Monument boundary. The eastern boundary is located just northwest of the confluence of the Congaree and Wateree Rivers. The Monument extends west to where Cedar Creek and Myers Creek join. The methods used for the sampling and analysis of vegetation data and the development of the classification generally followed the standards Doutline in the Field Methods for Vegetation Mapping document ""http://biology.usgs.gov/npsveg/fieldmethods/index.html"" produced for the USGS-NPS Vegetation Mapping project. This process began with the development of a provisional list of twenty-five vegetation types from teh International Classification of Ecological Communities (ICEC) that were thought to have a high likelihood of being in the park based on an initial field visit on 13-14 June, 1996. One hundred twenty-eight plots were sampled by two two-person field teams in July, August, and September of 1996. In a devation from the methodology outlined in the Field Methods document, initial sample points were selected in order to have plots in each of the aerial photograph signature types. The gradsect approach was rejected because there appeared to be no potential for stratifying sampling of the park based on slope, aspect, elevation, soil or other natural features due to a lack of available information. Furthermore, because of isolation from roads and trails of many portions of the park, it was deemed not feasible to use a transect to establish plot locations. After sampling, plots were tentatively assigned to the ICEC at the alliance level and our goal was to have at least five plots in each of the twenty-five provisional vegetation types. TIme limitations precluded the ability of the field teams to install ten plots in each of the expected vegetation types as recommended in the Field Methods document. The information for the metadata came from ""http://biology.usgs.gov/npsveg/cosw/metacoswfield.html""" proprietary
usgs_nps_congareeswampspatial Congaree Swamp National Monument Spatial Vegetation Data; Cover Type/Association Level of the National Vegetation Classification System CEOS_EXTRA STAC Catalog 1996-04-27 1996-04-27 -80.85, 33.75, -80.67083, 33.84167 https://cmr.earthdata.nasa.gov/search/concepts/C2231550252-CEOS_EXTRA.umm_json "The National Park Service (NPS), in conjunction with the Biological Resources Division (BRD) of the U.S. Geological Survey (USGS), has implemented a program to ""develop a uniform hierarchical vegetation methodology"" at a national level. The program will also create a geographic information system (GIS) database for the parks under its management. The purpose of the data is to document the state of vegetation within the NPS service area during the 1990's, thereby providing a baseline study for further analysis at the Regional or Service-wide level. The vegetation units of this map were determined through stereoscopic interpretation of aerial photographs supported by field sampling and ecological analysis. The vegetation boundaries were identified on the photographs by means of the photographic signatures and collateral information on slope, hydrology, geography, and vegetation in accordance with the Standardized National Vegetation Classification System (October 1995). The mapped vegetation reflects conditions that existed during the specific year and season that the aerial photographs were taken (April, 1996). There is an inherent margin of error in the use of aerial photography for vegetation delineation and classification. The purpose of this spatial data is to provide the National Park Service the necessary tools to manage the natural resources within this park system. Several parks, representing different regions, environmental conditions, and vegetation types, were chosen by BRD to be part of the prototype phase of the program. The initial goal of the prototype phase is to ""develop, test, refine, and finalize the standards and protocols"" to be used during the production phase of the project. This includes the development of a standardized vegetation classification system for each park and the establishment of photointerpretation, field, and accuracy assessment procedures. Congaree Swamp National Monument was designated as one of the prototype parks. Congaree Swamp National Monument, established in 1976, was designated as one of the prototypes within the National Park System. The park contains approximately 22,200 acres (34 square miles). Congaree Swamp National Monument is located approximately 15 miles southeast of Columbia, the state capitol of South Carolina. The Congaree River, draining over 8,000 square miles of Piedmont land to the northwest, forms the southern border. On June 30, 1983, Congaree Swamp National Monument became an International Biosphere Reserve. Congaree is noted for containing one of the last significant stands of old growth bottomland hardwood forest, over 11,000 acres in all. The Monument contains over 90 species of trees, 16 of which hold state records for size. Included in this list of records is a national record sweet gum with a basal circumference of nearly 20 feet. Congaree Swamp National Monument is located approximately 15 miles southeast of Columbia, the state capitol of South Carolina. Old Bluff Highway (old Highway 48) lies just north of the Monument boundary. The eastern boundary is located just northwest of the confluence of the Congaree and Wateree Rivers. The Monument extends west to where Cedar Creek and Myers Creek join. The normal process in vegetation mapping is to conduct an initial field reconnaissance, map the vegetation units through photointerpretation, and then conduct a field verification. The field reconnaissance visit serves two major functions. First, the photointerpreter keys the signature on the aerial photos to the vegetation on the ground at each signature site. Second, the photointerpreter becomes familiar with the flora, vegetation communities and local ecology that occur in the study area. Park and/or TNC field biologists that are familiar with the local vegetation and ecology of the park are present to help the photointerpreter understand these elements and their relationship with the geography of the park. Upon completion of the field reconnaissance, photo interpreters delineate vegetation units on mylar that overlay the 9x9 aerial photos. This effort is conducted in accordance with the TNC vegetation classification and criteria for defining each community or alliance. The initial mapping is then followed by a field verification session, whose purpose is to verify that the vegetation units were mapped correctly. Any PI related questions are also addressed during the visit. The vegetation mapping at Congaree Swamp National Monument in general followed the normal mapping procedure as described in the above paragraph with two major exceptions: 1) Preliminary delineations for most of the park, including a set of Focused Transect overlays that were labeled with an initial PI signature commenced prior to the field reconnaissance visit. 2) A TNC classification did not exist at the time the initial delineations began. TNC ecologist and AIS photo interpreters worked together to develop an interim signature key which addressed what was known at the time. At that time, no comprehensive study containing plot data was available to create an interim classification. From the onset of the Vegetation Inventory and Mapping Program, a standardized program-wide mapping criteria has been used. The mapping criteria contains a set of documented working decision rules used to facilitate the maintenance of accuracy and consistency of the photointerpretation. This criteria assists the user in understanding the characteristics, definition and context for each vegetation community. The mapping criteria for Congaree Swamp National Monument was composed of four parts: The standardized program-wide general mapping criteria A park specific mapping criteria A working photo signature key The TNC classification, key and descriptions The following sections detail the mapping criteria used during the photointerpretation of Congaree Swamp. General Mapping Criteria The mapping criteria at Congaree Swamp are a modified version from previously mapped parks. The criteria differs primarily in that the height and density variables were not mapped at Congaree Swamp. Instead, two additional variables were addressed: pre-hurricane Hugo community types and areas of pine that have been logged since the time of the 1976 aerial photography. These two categories will be addressed in the Park Specific Mapping Criteria section of this report. Since forest densities within the Monument are nearly always greater than 60%, it served little or no purpose in addressing this element as a separate attribute in the database. In addition it was also determined that height categories are extremely difficult to map in the Monument due to variability of the tree emergent layer, and lack of any significant reference points that help in determining canopy heights. Alliance / Community Associations The assignment of alliance and community association to the vegetation is based on criteria formulated by the field effort and classification development. In the case of Congaree Swamp National Monument, TNC provided AIS with a tentative community classification in April 1998. A final vegetation classification, key, and descriptions of each alliance and community, was provided in October 1998. In addition, TNC provided AIS with detailed plot data showing how the communities were developed in the Monument. The information for the metadata came from ""http://biology.usgs.gov/npsveg/cosw/metacoswspatial.html"" and was converted to the NASA Directory Interchange Format." proprietary
usgs_nps_d_microbialcontam Microbial Contamination of Water Resources in the Chatahoochee River National Recreation Area, Georgia CEOS_EXTRA STAC Catalog 1999-03-01 2000-04-01 -86, 30, -81, 35 https://cmr.earthdata.nasa.gov/search/concepts/C2231549590-CEOS_EXTRA.umm_json The study area is the watershed for the Chattahoochee River from Buford Dam to just downstream of the mouth of Peachtree Creek. This study area includes the entire Chattahoochee River National Recreation Area, much of Metropolitan Atlanta, and extends downstream of two major wastewater treatment plant outfalls for the City of Atlanta and Cobb County. The 2-year study is for fiscal years 1999 and 2000. There are six months of microbial sampling in each fiscal year spanning from April 1, 1999 through March 30, 2000. This study measures fecal-indicator bacteria (fecal coliform, E. coli, and enterococci) every five days from April 1, 1999 to September 30, 1999 and every 8 days from October 1, 1999 to March 30, 2000 at three main stem Chattahoochee River sites. The five-day and eight-day sampling intervals will ensure mid week and weekend flow conditions are sampled. Indicator bacteria samples will also be collected during one 26-hour period to look at diel fluctuations. Another indicator bacteria (Clostridium perfringens), F-specific coliphages, somatic coliphages, and chemical sewage tracers will be measured as part of several synoptic surveys at 3 fixed sites and 9 synoptic sites. The 2-year project investigates the existence, severity, and extent of microbial contamination in the Chattahoochee River and 8 major tributaries within the Chattahoochee River National Recreation Area (CRNRA). High levels of fecal-indicator bacteria are the principal basis for impairment of streams in the CRNRA. Three data-collection activities include: 1.Fixed interval: Sample fecal-indicator bacteria and predictor variables (stream stage, stream flow, turbidity, and field water-quality parameters) every 5 days from April 1 to September 30, 1999 and every 8 days from October 1, 1999 to March 30, 2000 at 3 Chattahoochee River sites. (view map) 2.Synoptic surveys: Sample fecal-indicator bacteria, Clostridium perfringens, viruses, predictor variables, and chemical sewage tracers at 4 Chattahoochee River sites and 8 tributary sites during critical seasons and hydrologic conditions. 3.Diel samples: Sample fecal-indicator bacteria and predictor variables every 2 hours for one 26-hour period (August 4-5, 1999) at the Chattahoochee River at Atlanta, which is downstream of the CRNRA. Four proposed main stem sampling sites in downstream order on the Chattahoochee River include: 1.Chattahoochee River at Settles Bridge Road near Suwanee 2.Chattahoochee River at Johnsons Ferry Road near Atlanta 3.Chattahoochee River at Atlanta (Paces Ferry Road; downstream from Palisades Unit) 4.Chattahoochee River at State Highway 280, near Atlanta (Synoptic site only; downstream from all of the CRNRA, much of Metropolitan Atlanta, and 2 major wastewater treatment outfalls for the City of Atlanta and Cobb County; will provide microbial data for a Chattahoochee River site directly affected by point sources of wastewater effluent) Eight proposed tributary sampling sites within the CRNRA watershed in downstream order include: 1.James Creek near Cumming (James Burgess Road) 2.Suwanee Creek near Suwanee (at US Route 23, Buford Hwy) 3.Johns Creek near Warsaw (Buice Road) 4.Crooked Creek near Norcross (Spalding Road) 5.Big Creek near Roswell (below Water Works intake) 6.Willeo Creek near Roswell (State Route 120) 7.Sope Creek near Marietta (Lower Roswell Road) 8.Rottenwood Creek near Smyrna (Interstate Parkway North) In general, fecal-indicator bacteria are used to assess the public-health acceptability of water. The concentration of indicator bacteria is a measure of water safety for body-contact recreation or for consumption (Myers and Sylvester, 1997). Indicator bacteria do not typically cause diseases (pathogenic), but they indicate the possible presence of pathogenic organisms. Escherichia coli (E. coli) and enterococci are currently the preferred fecal indicators for recreational freshwaters because they are superior to fecal coliforms and fecal streptococci as predictors of swimming-associated gastroenteritis (Cabelli, 1977; Dufour, 1984); however fecal coliforms are still used by many states including Georgia to monitor recreational waters. Most historical indicator bacteria data for surface water within the CRNRA are fecal coliform counts collected once a month on a mid-weekday during normal working hours. This study proposes to measure fecal coliform using the membrane filter technique (preferred over the broth technique used by Georgia EPD),E. coli, and enterococci every five days during the recreation season at three main stem sites. The five-day cycle will ensure mid week and weekend flow conditions are sampled. All samples will be collected using USGS protocols for bacteria and equal width interval (EWI) sampling. Clostridium perfringens (C. perfringens) is another indicator bacteria that is present in large numbers in human and animal wastes, and its spores are more resistant to disinfection and environmental stresses than are most other bacteria. It is also a sensitive indicator of microorganisms that enter streams from point sources (Sorenson and others, 1989). It must be analyzed under anaerobic conditions in a laboratory and is best attempted by a biologist or highly trained technician. This study proposes to measure C. perfringens at 4 main stem and 8 tributary sites as part of synoptic surveys during critical seasons and hydrologic conditions. Because monitoring of enteric viruses is recognized as being difficult,time consuming, and expensive, some researchers advocate the use of coliphage for routine viral monitoring. Coliphages are bacteriophages that infect and replicate in coliform bacteria. Although somatic and Fecal-Specific coliphages are not consistently found in feces, they are found in high numbers in sewage and are thought to be reliable indicators of the sewage contamination of waters (International Association on Water Pollution Research and Control, 1991). Coliphage is also recognized to be representative of the survival transport of viruses in the environment. However, to date, they have not been found to correlate with the presence of pathogenic viruses. This study proposes to measure enteric viruses at 4 main stem and 8 tributary sites as part of synoptic surveys during critical seasons and hydrologic conditions. proprietary
@@ -20918,11 +20919,11 @@ usgs_npwrc_acutetoxicity_Version 06JUL2000 Acute Toxicity of Fire-Control Chemic
usgs_npwrc_alpha_Version 16MAY2000 Alpha Status, Dominance, and Division of Labor in Wolf Packs. CEOS_EXTRA STAC Catalog 1986-01-01 1998-12-31 -145.27, 37.3, -48.11, 87.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231552683-CEOS_EXTRA.umm_json "The prevailing view of a wolf (Canis lupus) pack is that of a group of individuals ever vying for dominance but held in check by the ""alpha"" pair, the alpha male and the alpha female. Most research on the social dynamics of wolf packs, however, has been conducted on non-natural assortments of captive wolves. Here I describe the wolf-pack social order as it occurs in nature, discuss the alpha concept and social dominance and submission, and present data on the precise relationships among members in free-living packs based on a literature review and 13 summers of observations of wolves on Ellesmere Island, Northwest Territories, Canada. I conclude that the typical wolf pack is a family, with the adult parents guiding the activities of the group in a division-of-labor system in which the female predominates primarily in such activities as pup care and defense and the male primarily during foraging and food-provisioning and the travels associated with them." proprietary
usgs_npwrc_canvasbacks_Version 13NOV2001 Influence of Age and Selected Environmental Factors on Reproductive Performance of Canvasbacks CEOS_EXTRA STAC Catalog 1974-01-01 1980-01-01 -102.5, 48, -95, 60 https://cmr.earthdata.nasa.gov/search/concepts/C2231549601-CEOS_EXTRA.umm_json Age, productivity, and other factors affecting breeding performance of canvasbacks (Aythya valisineria) are poorly understood. Consequently, we tested whether reproductive performance of female canvasbacks varied with age and selected environmental factors in southwestern Manitoba from 1974 to 1980. Neither clutch size, nest parasitism, nest success, nor the number of ducklings/brood varied with age. Return rates, nest initiation dates, renesting, and hen success were age-related. Return rates averaged 21% for second-year (SY) and 69% for after-second-year (ASY) females (58% for third-year and 79% for after-third-year females). Additionally, water conditions and spring temperatures influenced chronology of arrival, timing of nesting, and reproductive success. Nest initiation by birds of all ages was affected by minimum April temperatures. Clutch size was higher in nests initiated earlier. Interspecific nest parasitism did not affect clutch size, nest success, hen success, or hatching success. Nest success was lower in dry years (17%) than in moderately wet (54%) or wet (60%) years. Nests per female were highest during wet years. No nests of SY females were found in dry years. In years of moderate to good wetland conditions, females of all ages nested. Predation was the primary factor influencing nest success. Hen success averaged 58% over all years. The number of ducklings surviving 20 days averaged 4.7/brood. Because SY females have lower return rates and hen success than ASY females, especially during drier years, management to increase canvasback populations might best be directed to increasing first year recruitment (no. of females returning to breed) and to increasing overall breeding success by reducing predation and enhancing local habitat conditions during nesting. proprietary
usgs_npwrc_ducks_Version 07JAN98 Assessing Breeding Populations of Ducks by Ground Counts. CEOS_EXTRA STAC Catalog 1952-01-01 1959-12-31 -145.27, 37.3, -48.11, 87.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231554819-CEOS_EXTRA.umm_json Waterfowl inventories taken during the breeding season are recognized as a basic technique in assessing the number of ducks per unit area. That waterfowl censusing is still an inexact technology leading to divergent interpretations of results is also recognized. The inexactness stems from a wide spectrum of factors that include weather, breeding phenology, asynchronous nesting periods, vegetative growth, species present and their daily activity, previous field experience of personnel, plus others (Stewart et al., 1958; Diem and Lu, 1960; Crissey, 1963a). In spite of the possible errors, accurate estimates are necessary to our understanding of production rates of all North American breeding waterfowl. Statistically adequate censuses of breeding pairs and accurate predictions of young produced per pair still remain as two of the primary statistics in determining yearly recruitment rate of species breeding in particular units of pond habitats. Without precise breeding pair and production data, the problems involved in describing the reproductive potential of any species and its environmental or density-dependent limiting factors cannot be adequately resolved. The purposes of this paper are to (1) describe methods used to estimate yearly breeding pair abundance on two study areas, one in Manitoba and the other in Saskatchewan; (2) assess the relative consistency, precision, and accuracy of pair counts as related to the breeding biology of duck species; and (3) recommend census methods that can more closely approximate absolute populations breeding in parkland and grassland habitats. proprietary
-usgs_npwrc_graywolves_Version 30APR2001 Accuracy and Precision of Estimating Age of Gray Wolves by Tooth Wear ALL STAC Catalog 1970-01-01 -168, 43.5, -75, 55 https://cmr.earthdata.nasa.gov/search/concepts/C2231553641-CEOS_EXTRA.umm_json We evaluated the accuracy and precision of tooth wear for aging gray wolves (Canis lupus) from Alaska, Minnesota, and Ontario based on 47 known-age or known-minimum-age skulls. Estimates of age using tooth wear and a commercial cementum annuli-aging service were useful for wolves up to 14 years old. The precision of estimates from cementum annuli was greater than estimates from tooth wear, but tooth wear estimates are more applicable in the field. We tended to overestimate age by 1-2 years and occasionally by 3 or 4 years. The commercial service aged young wolves with cementum annuli to within year of actual age, but under estimated ages of wolves 9 years old by 1-3 years. No differences were detected in tooth wear patterns for wild wolves from Alaska, Minnesota, and Ontario, nor between captive and wild wolves. Tooth wear was not appropriate for aging wolves with an underbite that prevented normal wear or severely broken and missing teeth. proprietary
usgs_npwrc_graywolves_Version 30APR2001 Accuracy and Precision of Estimating Age of Gray Wolves by Tooth Wear CEOS_EXTRA STAC Catalog 1970-01-01 -168, 43.5, -75, 55 https://cmr.earthdata.nasa.gov/search/concepts/C2231553641-CEOS_EXTRA.umm_json We evaluated the accuracy and precision of tooth wear for aging gray wolves (Canis lupus) from Alaska, Minnesota, and Ontario based on 47 known-age or known-minimum-age skulls. Estimates of age using tooth wear and a commercial cementum annuli-aging service were useful for wolves up to 14 years old. The precision of estimates from cementum annuli was greater than estimates from tooth wear, but tooth wear estimates are more applicable in the field. We tended to overestimate age by 1-2 years and occasionally by 3 or 4 years. The commercial service aged young wolves with cementum annuli to within year of actual age, but under estimated ages of wolves 9 years old by 1-3 years. No differences were detected in tooth wear patterns for wild wolves from Alaska, Minnesota, and Ontario, nor between captive and wild wolves. Tooth wear was not appropriate for aging wolves with an underbite that prevented normal wear or severely broken and missing teeth. proprietary
+usgs_npwrc_graywolves_Version 30APR2001 Accuracy and Precision of Estimating Age of Gray Wolves by Tooth Wear ALL STAC Catalog 1970-01-01 -168, 43.5, -75, 55 https://cmr.earthdata.nasa.gov/search/concepts/C2231553641-CEOS_EXTRA.umm_json We evaluated the accuracy and precision of tooth wear for aging gray wolves (Canis lupus) from Alaska, Minnesota, and Ontario based on 47 known-age or known-minimum-age skulls. Estimates of age using tooth wear and a commercial cementum annuli-aging service were useful for wolves up to 14 years old. The precision of estimates from cementum annuli was greater than estimates from tooth wear, but tooth wear estimates are more applicable in the field. We tended to overestimate age by 1-2 years and occasionally by 3 or 4 years. The commercial service aged young wolves with cementum annuli to within year of actual age, but under estimated ages of wolves 9 years old by 1-3 years. No differences were detected in tooth wear patterns for wild wolves from Alaska, Minnesota, and Ontario, nor between captive and wild wolves. Tooth wear was not appropriate for aging wolves with an underbite that prevented normal wear or severely broken and missing teeth. proprietary
usgs_npwrc_incidentalmarinecatc_Version 11APR2001 Incidental Catch of Marine Birds in the North Pacific High Seas Driftnet Fisheries in 1990. CEOS_EXTRA STAC Catalog 1990-01-01 1990-01-01 -140, 20, 140, 50 https://cmr.earthdata.nasa.gov/search/concepts/C2231553439-CEOS_EXTRA.umm_json "The incidental take of marine birds was estimated for the following North Pacific driftnet fisheries in 1990: Japanese squid, Japanese large-mesh, Korean squid, and Taiwanese squid and large-mesh combined. The take was estimated by assuming that the data represented a random sample from an unstratified population of all driftnet fisheries in the North Pacific. Estimates for 13 species or species groups are presented, along with some discussion of inadequacies of the design. About 416,000 marine birds were estimated to be taken incidentally during the 1990 season; 80 % of these were in the Japanese squid fishery. Sooty Shearwaters, Short-tailed Shearwaters, and Laysan Albatrosses were the most common species in the bycatch. Regression models were also developed to explore the relations between bycatch rate of three groups Black-footed Albatross, Laysan Albatross, and ""dark"" shearwatersand various explanatory variables, such as latitude, longitude, month, vessel, sea surface temperature, and net soak time (length of time nets were in the water). This was done for only the Japanese squid fishery, for which the most complete information was available. For modeling purposes, fishing operations for each vessel were grouped into 5-degree blocks of latitude and longitude. Results of model building indicated that vessel had a significant influence on bycatch rates of all three groups. This finding emphasizes the importance of the sample of vessels being representative of the entire fleet. In addition, bycatch rates of all three groups varied spatially and temporally. Bycatch rates for Laysan Albatrosses tended to decline during the fishing season, whereas those for Black-footed Albatrosses and dark shearwaters tended to increase as the season progressed. Bycatch rates were positively related to net soak time for Laysan Albatrosses and dark shearwaters. Bycatch rates of dark shearwaters were lower for higher sea surface temperatures." proprietary
-usgs_npwrc_manitobaspiders_Version 16JUL97 A Checklist of Manitoba Spiders (Araneae) with Notes on Geographic Relationships CEOS_EXTRA STAC Catalog 1970-01-01 -145.27, 37.3, -48.11, 87.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231553142-CEOS_EXTRA.umm_json An annotated list of spider species is compiled from museum collections and several personal collections. This list includes 483 species in 20 families; 139 species are new provincial records. The spider fauna of Manitoba is compared with that of British Columbia, Quebec, and Newfoundland. Manitoba's spider fauna is composed of northern elements (arctic or subarctic species), boreal elements (holarctic or nearctic), and eastern elements (mainly species of the eastern deciduous forest), and a few that are regarded as introductions from abroad. Forty-three species reach the limits of their ranges here. This relatively small province (6.5% of the total land mass of Canada) contains 59% of the Canadian spider families and 37% of the Canadian species. proprietary
usgs_npwrc_manitobaspiders_Version 16JUL97 A Checklist of Manitoba Spiders (Araneae) with Notes on Geographic Relationships ALL STAC Catalog 1970-01-01 -145.27, 37.3, -48.11, 87.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231553142-CEOS_EXTRA.umm_json An annotated list of spider species is compiled from museum collections and several personal collections. This list includes 483 species in 20 families; 139 species are new provincial records. The spider fauna of Manitoba is compared with that of British Columbia, Quebec, and Newfoundland. Manitoba's spider fauna is composed of northern elements (arctic or subarctic species), boreal elements (holarctic or nearctic), and eastern elements (mainly species of the eastern deciduous forest), and a few that are regarded as introductions from abroad. Forty-three species reach the limits of their ranges here. This relatively small province (6.5% of the total land mass of Canada) contains 59% of the Canadian spider families and 37% of the Canadian species. proprietary
+usgs_npwrc_manitobaspiders_Version 16JUL97 A Checklist of Manitoba Spiders (Araneae) with Notes on Geographic Relationships CEOS_EXTRA STAC Catalog 1970-01-01 -145.27, 37.3, -48.11, 87.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231553142-CEOS_EXTRA.umm_json An annotated list of spider species is compiled from museum collections and several personal collections. This list includes 483 species in 20 families; 139 species are new provincial records. The spider fauna of Manitoba is compared with that of British Columbia, Quebec, and Newfoundland. Manitoba's spider fauna is composed of northern elements (arctic or subarctic species), boreal elements (holarctic or nearctic), and eastern elements (mainly species of the eastern deciduous forest), and a few that are regarded as introductions from abroad. Forty-three species reach the limits of their ranges here. This relatively small province (6.5% of the total land mass of Canada) contains 59% of the Canadian spider families and 37% of the Canadian species. proprietary
usgs_npwrc_muskoxen_Version 31MAY2000 Lack of Reproduction in Muskoxen and Arctic Hares Caused by Early Winter CEOS_EXTRA STAC Catalog 1998-07-01 1998-07-11 -86.1, 79.5, -85.9, 80.5 https://cmr.earthdata.nasa.gov/search/concepts/C2231549051-CEOS_EXTRA.umm_json A lack of young muskoxen (Ovibos moschatus) and arctic hares (Lepus arcticus) in the Eureka area of Ellesmere Island, Northwest Territories (now Nunavut), Canada, was observed during summer 1998, in contrast to most other years since 1986. Evidence of malnourished muskoxen was also found. Early winter weather and a consequent 50% reduction of the 1997 summer replenishment period appeared to be the most likely cause, giving rise to a new hypothesis about conditions that might cause adverse demographic effects in arctic herbivores. The study area included a 150 km2 region of the Fosheim Peninsula in a 180o arc north of Eureka, Ellesmere Island, Nunavut, Canada (all within about 9 km of 80oN, 86oW). The area, extending from Eureka Sound to Remus Creek and from Slidre Fiord to Eastwind Lake, included shoreline, hills, lowlands, creek bottoms, and the west side of Blacktop Ridge. An associate, Layne Adams, and I spent 1-11 July 1998 in this area on all-terrain vehicles, following a pair of wolves Canis lupus (Mech, 1994). Adams and I also surveyed the surrounding area with binoculars for prey animals, in much the same manner that my assistants and I have practiced for one to six weeks each summer in the same area since 1986 (Mech, 1995, 1997). Because both muskoxen and arctic hares were common residents of the area during most years and were not the focus of our studies, no standardized counts were made. However, general field notes were sufficient to document that during most summers both species and their young were present. proprietary
usgs_npwrc_nestingsuccess_Version 26MAR2001 Importance of Individual Species of Predators on Nesting Success of Ducks in the Canadian Prairie Pothole Region CEOS_EXTRA STAC Catalog 1970-01-01 -145.27, 37.3, -48.11, 87.61 https://cmr.earthdata.nasa.gov/search/concepts/C2231551032-CEOS_EXTRA.umm_json We followed 3094 upland nests of several species of ducks. Clutches in most nests were lost to predation. We related daily nest predation rates to indices of activity of eight egg-eating predators, precipitation during the nesting season, and measures of wetland conditions. Activity indices of red fox (Vulpes vulpes), striped skunk (Mephitis mephitis), and raccoon (Procyon lotor) activity were positively correlated, as were activity indices of coyote (Canis latrans), Franklin's ground squirrel (Spermophilus franklinii), and black-billed magpie (Pica pica). Indices of fox and coyote activity were strongly negatively correlated (r = early-season nests were lower in areas and years in which larger fractions of seasonal wetlands contained water. For late-season nests, a similar relationship held involving semipermanent wetlands. We suspect that the wetland measures, which reflect precipitation during some previous period, also indicate vegetation growth and the abundance of buffer prey, factors that may influence nest predation rates. proprietary
usgs_npwrc_purpleloostrife_Version 04JUN99 Avian Use of Purple Loosestrife Dominated Habitat Relative to Other Vegetation Types in a Lake Huron Wetland Complex CEOS_EXTRA STAC Catalog 1994-01-01 1995-12-31 -84.2, 43.3, -82.5, 44.1 https://cmr.earthdata.nasa.gov/search/concepts/C2231555362-CEOS_EXTRA.umm_json Purple loosestrife (Lythrum salicaria), a native of Eurasia, is an introduced perennial plant in North American wetlands that displaces other wetland plants. Although not well studied, purple loosestrife is widely believed to have little value as habitat for birds. To examine the value of purple loosestrife as avian breeding habitat, we conducted early, mid-, and late season bird surveys during two years (1994 and 1995) at 258 18-m (0.1 ha) fixed-radius plots in coastal wetlands of Saginaw Bay, Lake Huron. We found that loosestrife-dominated habitats had higher avian densities, but lower avian diversities than other vegetation types. The six most commonly observed bird species in all habitats combined were Sedge Wren (Cistothorus platensis), Marsh Wren (C. palustris), Yellow Warbler (Dendroica petechia), Common Yellowthroat (Geothylpis trichas), Swamp Sparrow (Melospiza georgiana), and Red-winged Blackbird (Agelaius phoeniceus). Swamp Sparrow densities were highest and Marsh Wren densities were lowest in loosestrife dominated habitats. We observed ten breeding species in loosestrife dominated habitats. We conclude that avian use of loosestrife warrants further quantitative investigation because avian use may be higher than is commonly believed. Received 27 May 1998, accepted 26 Aug. 1998. proprietary
@@ -20933,8 +20934,8 @@ usgsbrdfcsc_d_seagrass Mapping and Characterizing Seagrass Areas Important to Ma
usgsbrdfcsc_d_vieques Mapping and Characterization of Nearshore Benthic Habitats around Vieques Island, Puerto Rico CEOS_EXTRA STAC Catalog 1995-09-01 -65.75, 18.15, -65.5, 18.3 https://cmr.earthdata.nasa.gov/search/concepts/C2231553026-CEOS_EXTRA.umm_json "The Vieques Island Mapping Project was initiated in September 1995 as a cooperative effort between NSRR and the Sirenia Project (Military Interdepartmental Purchase Request no. NOO38995MP00012). Caribbean Fisheries Consultants, Inc. was contracted by the Sirenia Project to help produce the desired information in conjunction with Sirenia Project biologists. Products include maps delineating Vieques' benthic habitat and coastal wetlands, an electronic georeferenced habitat map (UTM coordinate system) in a format compatible with ARC/INFO (Environmental Systems Research Institute, Inc.) and a report describing methods used, the classification scheme, and the relationship of these habitats to manatee use of Vieques Island. These map products complement the Navy's Vieques Land Use Management Plan by identifying marine resources targeted for protection in the plan. Objectives include producing maps of the coastal seagrass beds and other bottom habitat (including coral reefs) surrounding the island of Vieques and characterizing the species composition and density of seagrasses in areas frequented by manatees near Vieques. Ground truthing by boat around Vieques Island was conducted from May 14 to May 19 1996 and from October 4 through October 9 1996. The ground truthing was conducted to verify the interpretation of benthic habitat visible in the images, verify accuracy of the shoreline limits, and refine the habitat classification scheme used for the Vieques maps. Three hundred and thirty-two ground truth stations were established around Vieques Island, located on the aerial image overlays, and digitized. These sites are plotted as a layer on the habitat map. The listing of ground truth sites includes site identifier, latitude and longitude, community classification, depteh, dominant community elements, less dominant elements, and other pertinent information. Latitude and longitude were obtained for each station in the field using a Garmin 45 GPS unit. Water depth for each station was determined from a Hummingbird LCR - 400 Video Fathometer with transom mounted transducer. Underwater Hi-8 video and 35 mm photography were used to document observations at selected sites. The habitat classification scheme used is similar to that used by Kruer and others in southern Forida seagrass beds and other benthic habitats in the Florida Keys National Marine Sanctuary and Biscayne National Park. This scheme, also used for benthic habitat mapping at NSRR in 1994/1995 (Kruer 1995), was refined for the Vieques Island mapping project by adding the category ""sand bottom with rock"". Also, mangroves were mapped in interior areas. The information for this metadata was partially taken from the report - Mapping and characterization of Nearshore Benthic Habitats around Vieques Island, Puerto Rico." proprietary
usgsbrdnpwrc_d_birds_checklists_Version 12MAY03 Birds Checklists of the United States CEOS_EXTRA STAC Catalog 1996-01-01 -125, 25, -67, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231550188-CEOS_EXTRA.umm_json This resource is known as Bird Checklists of the United States. Bird Checklists of the United States. For years, people and groups have developed listings or checklists of birds that occur in a particular region. Information on the distribution or seasonal occurrence of birds in an area, however, can change over time. Bird checklists often are outdated in only a few years after printing, but budget and time constraints prohibit regular updates. The Internet provides new opportunities for the compilation and dissemination of current information on bird distribution. Here we offer bird checklists developed by others that indicate the seasonal occurrence of birds in state, federal, and private management areas, nature preserves, and other areas of special interest in the United States. Bird checklists exist for Great Plains States: Colorado, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, New Mexico, North Dakota, Oklahoma, South Dakota, Texas, Wyoming; East of Great Plains states: Alabama, Arkansas, Connecticut, Delaware, Florida, Georgia, Illinois, Indiana, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Tennessee, Vermont, Virginia, West Virginia, Wisconsin; and West of Great Plains: Arizona, California, Idaho, Nevada, Oregon, Utah, Washington. It is hoped that these checklists will serve several purposes. First, we hope the checklists will help bird enthusiasts decide where to visit. A visit to these unique areas can be a rewarding experience for both the amateur and expert birdwatcher. Second, we hope that these checklists will provide potential visitors with a guide to birds that might occur in a region during a particular season. The checklists were kept simple to facilitate printing so they can be easily carried into the field. And third, we hope that these checklists will stimulate and encourage visitors to these areas to help improve the accuracy and completeness of the checklists. The information in some checklists already has been updated; these checklists contain more current information than the printed versions. Sightings of birds and other wildlife are an important part of monitoring wildlife use. Visitors are encouraged to share their observations of rare, aberrant, or occasional birds with the staff at these areas. With each checklist, we have included an address for visitors to send information on rare birds so that checklists can be updated. To assist in establishing standards in observation and reporting, we also provide a Record Documentation Form to document supporting details of rare bird observations. The efforts and dedication of the many birders, birding groups, biologists, and resource managers who developed these checklists are acknowledged. The information for this metadata was partially taken from the Northern Prairie Wildlife Research Center website at http://www.npwrc.usgs.gov/resource/birds/chekbird/index.htm proprietary
usgsbrdnpwrc_d_ndfleas_Version 16JUL97 Fleas of North Dakota CEOS_EXTRA STAC Catalog 1970-01-01 -104, 46, -96.5, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231553614-CEOS_EXTRA.umm_json The dataset contains distribution maps for the following species of fleas: Aetheca wagneri, Amaradix euphorbi, Amphipsylla sibirica pollionis, Callistopsyllus terinus campestris, Cediopsylla inaequalis inaequalis, Ceratophyllus (Ceratophyllus) idius, Corrodopsylla curvata curvata, Chaetopsylla lotoris, Ctenocephalides canis, Epitedia faceta, Epitedia wenmanni, Euhoplopsyllus glacialis affinis, Eumolpianus eumolpi eumolpi, Foxella ignota albertensis, Hystrichopsylla dippiei dippiei, Megabothris (Megabothris) asio megacolpus, Megabothris (Amegabothris) lucifer, Meringis jamesoni, Myodopsylla insignis, Nearctopsylla genalis hygini, Neopsylla inopina, Nosopsyllus fasciatus, Oropsylla (Oropsylla) arctomys, Opisodasys (Opisodasys) pseudarctomys, Orchopeas caedens, Orchopeas howardi, Peromyscopsylla hamifer, Pleochaetis exilis, Pules irritans, Rhadinopsylla (Actenophthalmus) fraterna, Thrassis bacchi bacchi. The information for this metadata was partially taken from the Northern Prairie Wildlife Research Center website at http://www.npwrc.usgs.gov/resource/insects/ndfleas/ proprietary
-usgsbrdnpwrcb00000013_Version 30SEP2002 A Bibliography of Fisheries Biology in North and South Dakota CEOS_EXTRA STAC Catalog 1970-01-01 -104, 43, -96, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231550006-CEOS_EXTRA.umm_json This bibliography lists as many fisheries biology and related references as possible from North Dakota and South Dakota waters for use by fishery biologists. Selected references from contiguous states sharing river basins with the Dakotas are included. Studies in the Missouri River downstream from Gavins Point Dam are also included. In addition to published fishery and related aquatic studies, attempts were made to list all dissertations and Masters theses in these fields. proprietary
usgsbrdnpwrcb00000013_Version 30SEP2002 A Bibliography of Fisheries Biology in North and South Dakota ALL STAC Catalog 1970-01-01 -104, 43, -96, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231550006-CEOS_EXTRA.umm_json This bibliography lists as many fisheries biology and related references as possible from North Dakota and South Dakota waters for use by fishery biologists. Selected references from contiguous states sharing river basins with the Dakotas are included. Studies in the Missouri River downstream from Gavins Point Dam are also included. In addition to published fishery and related aquatic studies, attempts were made to list all dissertations and Masters theses in these fields. proprietary
+usgsbrdnpwrcb00000013_Version 30SEP2002 A Bibliography of Fisheries Biology in North and South Dakota CEOS_EXTRA STAC Catalog 1970-01-01 -104, 43, -96, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231550006-CEOS_EXTRA.umm_json This bibliography lists as many fisheries biology and related references as possible from North Dakota and South Dakota waters for use by fishery biologists. Selected references from contiguous states sharing river basins with the Dakotas are included. Studies in the Missouri River downstream from Gavins Point Dam are also included. In addition to published fishery and related aquatic studies, attempts were made to list all dissertations and Masters theses in these fields. proprietary
usgsbrdnpwrcb00000016_Version 16JUL97 American Wildcelery (Vallisneria americana) Ecological Considerations for Restoration CEOS_EXTRA STAC Catalog 1970-01-01 -125, 25, -67, 50 https://cmr.earthdata.nasa.gov/search/concepts/C2231548602-CEOS_EXTRA.umm_json The success of vegetation management programs for waterfowl is dependent on knowing the physical and physiological requirements of the target species. Lakes and riverine impoundments that contain an abundance of the American wildcelery plant (Vallisneria americana) have traditionally been favored by canvasback ducks (Aythya valisineria) and other waterfowl species as feeding areas during migration. Information on the ecology of V. americana is summarized to serve as a guide for potential wetland restoration projects. Because of the geographic diversity and wetland conditions in which V. americana is found, we have avoided making hard-and-fast conclusions about the requirements of the plant. Rather, we present as much general information as possible and provide the sources of more specific information. Vallisneria americana is a submersed aquatic plant that has management potential. Techniques are described for transplanting winter buds from one location to another. Management programs that employ these techniques should define objectives clearly and evaluate the water regime carefully before initiating a major effort. proprietary
usgsbrdnpwrcd00000002_Version 02MAR98 Ecological Effects of Fire Retardant Chemicals and Fire Suppressant Foams CEOS_EXTRA STAC Catalog 1993-01-01 1998-01-01 -98, 47, -98, 47 https://cmr.earthdata.nasa.gov/search/concepts/C2231550534-CEOS_EXTRA.umm_json Laboratory studies with algae, aquatic invertebrates, and fish. Short-term toxicity tests showed that both fire-retardant and foam-suppressant chemicals were very toxic to aquatic organisms including algae, aquatic invertebrates, and fish. Foam-suppressant are more toxic than fire-retardant chemicals. The primary toxicant in fire-retardants is the ammonia component, whereas the nitrite and nitrate components do not seem to contribute much to the toxicity of the formulations. In foam suppressants the primary toxicant is the surfactant component. The most sensitive life-stage for fish is the swim-up stage. Accidental spills of fire-fighting chemicals in streams could cause substantial fish kills depending on the stream size and flow rate. For example, the retardant Fire-Trol GTS-R is prepared for field use by mixing 1.66 pounds per gallon of water to produce 1.1 gallons of slurry, which is equivalent to 198,930 mg/liter. Comparing the concentration of FT GTS-R field mixture to the acute toxicity values for the most sensitive life stage for rainbow trout gives a ratio of 853 in soft water and 1474 in hard water. Applying a safety factor of 100 to this ratio suggests a dilution of 85, 300 in soft water and 147,400 in hard water is needed to lower the chemical concentration in a receiving water to limit adverse effects, i.e., fish kill, in a stream. For rainbow trout, other dilution factors would be 52,100 for Fire-Trol LCG-R, 85,600 for Phos-Chek D75-F, 71,400 for Phos-Chek WD-881, and 50,000 for Silv-ex. Fire-fighting chemicals are very toxic in aquatic environments and fire control managers need to consider protection of aquatic resources, especially if endangered species are present. proprietary
usgsbrdnpwrcd00000012_Version 31JUL97 Changes in Breeding Bird Populations in North Dakota: 1967 to 1992-93. CEOS_EXTRA STAC Catalog 1967-01-01 1993-01-01 -104, 46, -97, 49 https://cmr.earthdata.nasa.gov/search/concepts/C2231551668-CEOS_EXTRA.umm_json Breeding bird populations in North Dakota were compared using surveys conducted in 1967 and 1992-93. In decreasing order, the five most frequently occurring species were Horned Lark (Eremophia alpestris), Brown-headed Cowbird (Molothrus ater), Western Meadowlark (Sturnella neglecta), Red-winged Blackbird (Agelaius phoeniceus), and Eastern Kingbird (Tyrannus tyrannus). The five most abundant species - Horned Lark, Chestnut-collared Longspur (Calcarius ornatus), Red-winged Blackbird, Western Meadowlark, and Brown-headed Cowbird - accounted for 31-41% of the estimated statewide breeding bird population in the three years. Although species composition remained relatively similar among years, between-year patterns in abundance and frequency varied considerably among species. Data from this survey and the North American Breeding Bird Survey indicated that species exhibiting significant declines were primarily grassland- and wetland-breeding birds, whereas species exhibiting significant increases primarily were those associated with human structures and woody vegetation. Population declines and increases for species with similar habitat associations paralleled breeding habitat changes, providing evidence that factors on the breeding grounds are having a detectable effect on breeding birds in the northern Great Plains. proprietary
@@ -20977,8 +20978,8 @@ volume_of_bole_wood_hg_2010-211_1.0 Volume of bole wood (HG 2010) ENVIDAT STAC C
volume_of_dead_wood-24_1.0 Volume of dead wood ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789818001-ENVIDAT.umm_json "Volume of stemwood with bark of all dead trees and shrubs (standing and lying) starting at 12 cm dbh. Unlike this theme , the ""Amount of deadwood according to the method of NFI3"" includes all lying deadwood starting at 7 cm in diameter. __Citation:__ > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_" proprietary
volume_of_dead_wood_nfi1-249_1.0 Volume of dead wood NFI1 ENVIDAT STAC Catalog 2018-01-01 2018-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789818053-ENVIDAT.umm_json Volume of stemwood with bark of all dead trees and shrubs (standing and lying) starting at 12 cm dbh recorded according to the NFI1 method. In NFI1 only those dead trees were recorded whose wood could still be exploited. In addition, lying green trees were classified in NFI1 as deadwood. __Citation:__ > _Abegg, M.; Brändli, U.-B.; Cioldi, F.; Fischer, C.; Herold-Bonardi, A.; Huber M.; Keller, M.; Meile, R.; Rösler, E.; Speich, S.; Traub, B.; Vidondo, B. (2014). Fourth national forest inventory - result tables and maps on the Internet for the NFI 2009-2013 (NFI4b). [Published online 06.11.2014] Available from World Wide Web http://www.lfi.ch/resultate/ Birmensdorf, Swiss Federal Research Institute WSL. [doi:10.21258/1057112](https://doi.org/10.21258/1057112)_ proprietary
voyages_2 List of voyages and station parties between 1947 and 1989 in which Australians participated, including winter and some summer personnel AU_AADC STAC Catalog 1947-01-01 1989-12-31 62.86, -68.581, 158.977, -52.95 https://cmr.earthdata.nasa.gov/search/concepts/C1214311442-AU_AADC.umm_json This document contains detailed descriptions of Antarctic and subantarctic voyages undertaken by Australians or in which Australians participated in between 1947 and 1989. It also includes lists of wintering personnel at Heard Island, Macquarie Island, Mawson, Casey, Davis, Wilkes and various field parties. Some information about summer personnel has also been recorded. The voyages are presented in chronological order, and contain information such as the name of the ship, dates of the voyage, destination, ship's master, and personnel details. The document also contains some details of Antarctic and subantarctic flights undertaken in support of the voyages (e.g. by the RAAF - Royal Australian Air Force). A second file (a spreadsheet) provides the number of personnel wintering at ANARE (Australian National Antarctic Research Expeditions) stations between 1948 and 1982. These stations include Heard Island, Macquarie Island, Davis, Wilkes, Repstat (Replacement Station at Wilkes), Casey and the Amery Ice Shelf. proprietary
-waddington_0352584 A Unique Opportunity for In-Situ Measurement of Seasonally-Varying Firn Densification at Summit, Greenland SCIOPS STAC Catalog 2004-01-01 2009-01-01 -38.6, 72.5, -38.4, 72.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214595086-SCIOPS.umm_json This is a collaborative proposal by Principal Investigators at the University of Washington and the Desert Research Institute. They will make detailed measurements of the temporal and spatial variations of firn compaction to advance knowledge and understanding of ice deformation and across different fields, including remote sensing, snow morphology, and paleoclimatology. They will make detailed measurements through two winter and three summer seasons at Summit Greenland using the concept of Borehole Optical Stratigraphy, which will use a borehole camera to record details of the wall. These details can be tracked over time to determine vertical motion and strain, which in the shallow depth is dominated by firn compaction. Quantitative understanding of firn compaction is important for remote-sensing mass-balance studies, which seek to measure and interpret the changing height of the ice sheet; the surface can rise due to snow accumulation, and fall due to ice flow and increased densification rates. Quantitative knowledge of all three processes is essential. Evidence suggests that the rate of densification undergoes a seasonal cycle, related to the seasonal cycle of temperature. When interpreting ice core trapped-gas data for paleoclimate, it is important to know at what point the gas was actually trapped in the ice. The pores do not close off until deep in the firn, leading to a difference between the age of the ice and the age of the trapped gas. If summer high temperatures have more impact on compaction than mean annual temperatures, the gas-age/ice-age offset might be incorrectly calculated. Greater understanding of firn densification physics will help the interpretation of these records. This data covers accumulation rates occurring between 1980-2008, and the data were collected between 2004-2008. proprietary
waddington_0352584 A Unique Opportunity for In-Situ Measurement of Seasonally-Varying Firn Densification at Summit, Greenland ALL STAC Catalog 2004-01-01 2009-01-01 -38.6, 72.5, -38.4, 72.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214595086-SCIOPS.umm_json This is a collaborative proposal by Principal Investigators at the University of Washington and the Desert Research Institute. They will make detailed measurements of the temporal and spatial variations of firn compaction to advance knowledge and understanding of ice deformation and across different fields, including remote sensing, snow morphology, and paleoclimatology. They will make detailed measurements through two winter and three summer seasons at Summit Greenland using the concept of Borehole Optical Stratigraphy, which will use a borehole camera to record details of the wall. These details can be tracked over time to determine vertical motion and strain, which in the shallow depth is dominated by firn compaction. Quantitative understanding of firn compaction is important for remote-sensing mass-balance studies, which seek to measure and interpret the changing height of the ice sheet; the surface can rise due to snow accumulation, and fall due to ice flow and increased densification rates. Quantitative knowledge of all three processes is essential. Evidence suggests that the rate of densification undergoes a seasonal cycle, related to the seasonal cycle of temperature. When interpreting ice core trapped-gas data for paleoclimate, it is important to know at what point the gas was actually trapped in the ice. The pores do not close off until deep in the firn, leading to a difference between the age of the ice and the age of the trapped gas. If summer high temperatures have more impact on compaction than mean annual temperatures, the gas-age/ice-age offset might be incorrectly calculated. Greater understanding of firn densification physics will help the interpretation of these records. This data covers accumulation rates occurring between 1980-2008, and the data were collected between 2004-2008. proprietary
+waddington_0352584 A Unique Opportunity for In-Situ Measurement of Seasonally-Varying Firn Densification at Summit, Greenland SCIOPS STAC Catalog 2004-01-01 2009-01-01 -38.6, 72.5, -38.4, 72.7 https://cmr.earthdata.nasa.gov/search/concepts/C1214595086-SCIOPS.umm_json This is a collaborative proposal by Principal Investigators at the University of Washington and the Desert Research Institute. They will make detailed measurements of the temporal and spatial variations of firn compaction to advance knowledge and understanding of ice deformation and across different fields, including remote sensing, snow morphology, and paleoclimatology. They will make detailed measurements through two winter and three summer seasons at Summit Greenland using the concept of Borehole Optical Stratigraphy, which will use a borehole camera to record details of the wall. These details can be tracked over time to determine vertical motion and strain, which in the shallow depth is dominated by firn compaction. Quantitative understanding of firn compaction is important for remote-sensing mass-balance studies, which seek to measure and interpret the changing height of the ice sheet; the surface can rise due to snow accumulation, and fall due to ice flow and increased densification rates. Quantitative knowledge of all three processes is essential. Evidence suggests that the rate of densification undergoes a seasonal cycle, related to the seasonal cycle of temperature. When interpreting ice core trapped-gas data for paleoclimate, it is important to know at what point the gas was actually trapped in the ice. The pores do not close off until deep in the firn, leading to a difference between the age of the ice and the age of the trapped gas. If summer high temperatures have more impact on compaction than mean annual temperatures, the gas-age/ice-age offset might be incorrectly calculated. Greater understanding of firn densification physics will help the interpretation of these records. This data covers accumulation rates occurring between 1980-2008, and the data were collected between 2004-2008. proprietary
waldinventursihlwald_1.0 Supplementary Data Sample Plot Inventory Sihlwald ENVIDAT STAC Catalog 2020-01-01 2020-01-01 8.552084, 47.2538697, 8.552084, 47.2538697 https://cmr.earthdata.nasa.gov/search/concepts/C2789818127-ENVIDAT.umm_json # Supplementary Data Sample Plot Inventory Sihlwald The Sihlwald is one of the largest contiguous beech forests in the Swiss Plateau region. In the year 2000, timber harvesting was abandoned. Since 2007 the forest has been under strict protection as a natural forest reserve on an area of 1098 ha and since 2008 as a cantonal nature and landscape conservation area (SVO Sihlwald). Since 2010, it carries the national label ‘Nature discovery park’ (‘Naturerlebnispark’). As part of the national monitoring in nature forest reserves, a sampling inventory (calipering threshold of 7 cm) with 226 plots on an area of 917 ha was carried out in the Sihlwald in autumn and early winter 2017. The aim was to describe the state and development of the forest structure and make comparisons with earlier sampling inventories in the same area from 1981, 1989 and 2003. This dataset contains supplementary tables for the publication by Brändli et al. (2020). The metadata file describes the structure of the tables. proprietary
water-availability-of-swiss-forests-during-the-2015-and-2018-droughts_1.0 Water availability of Swiss forests during the 2015 and 2018 droughts ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789817096-ENVIDAT.umm_json The Swiss forests' water availability during the 2015 and 2018 droughts was modelled by implementing the mechanistic Soil-Vegetation-Atmosphere-Transport (SVAT) model LWF-Brook90 taking advantage of regionalized depth-resolved soil information and measured soil matric potential and eddy covariance data. Data include 1) csv of soil matrix potential and eddy covariance data, 2) csv of posterior model parameters, 3) geotiffs of plant-available water storage capacity until 1m soil depth and the potential rooting depth, 4) geotiffs of yearly average (2014-2019) of precipitation (P), actual evapotranspiration (ETa), evaporation as the sum of soil, snow and interception evaporation (E), actual transpiration (Ta), runoff (F) and total soil water storage (SWAT), 5) csv of simulated root water uptake aggregated for different soil depths per deciduous and coniferous trees across Switzerland at daily resolution and cumulative root fraction per soil depth for coniferous and deciduous sites, 6) geotiffs of the ratio of actual to potential transpiration (-) as mean of non-drought years 2014, 2016, 2017, 2019 and 2015 and 2018 for the month June, July, August, September and October, 7) geotiff of mean soil matric potential in the rooting zone in August 2018, 8) geotiffs of gravitational water capacity (mm) until 1 m soil depth and the maximum rooting depth (mrd), 9) geotiffs of uncertainties of the available water storage capacity (AWC) until 1m soil depth and the mean maximum rooting depth (mrd), 10) csv of average plant available - (AWC), gravitational (GWC) and residual (RES) water capacity per soil depth layer of the Swiss forest. proprietary
water-isotopes-plynlimon_1.0 Stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK ENVIDAT STAC Catalog 2019-01-01 2019-01-01 -3.7631607, 52.418789, -3.6402512, 52.4982845 https://cmr.earthdata.nasa.gov/search/concepts/C2789817232-ENVIDAT.umm_json The data base contains timeseries of stable water isotopes in precipitation and streamflow at Plynlimon, Wales, UK. One data set contains weekly stable water isotope data from the Lower Hafren and Tanllwyth catchments, and the other data set contains 7-hourly stable water isotope data from Upper Hafren. Both data sets also include chloride concentrations in precipitation and streamflow. proprietary
@@ -20995,15 +20996,15 @@ wfj2_1.0 WFJ2: Snow measurements from the Weissfluhjoch research site, Davos ENV
wfj_ice_layers_1.0 WFJ_ICE_LAYERS: Multi-instrument data for monitoring deep ice layer formation in an alpine snowpack ENVIDAT STAC Catalog 2020-01-01 2020-01-01 9.8093855, 46.8297006, 9.8093855, 46.8297006 https://cmr.earthdata.nasa.gov/search/concepts/C2789817883-ENVIDAT.umm_json The WFJ_ICE_LAYERS dataset contains multi-instrument snowpack measurements at high temporal resolution, which enable to monitor the formation of deep ice layers due to preferential water flow, at the Weissfluhjoch research site, Davos, Switzerland. It covers the winter 2016/2017, with a focus on the early melting season. This dataset includes traditional snowpack profiles (weekly resolution, 15/11/2016-29/05/2017), SnowMicroPen penetration resistance profiles (daily resolution, 01/02/2017-19/04/2017), snow temperatures measured at different heights in the snowpack (half-hourly resolution, 01/03/2017-15/04/2017) and the water front height derived from an upward-looking ground penetrating radar (3-hour resolution, 04/03/2017-08/04/2017). The measurements are complemented by initialization files for SNOWPACK model simulations with the ice reservoir parameterization at Weissfluhjoch for the winter 2016/2017. proprietary
wfj_rhossa_1.0 WFJ_RHOSSA: Multi-instrument stratigraphy data for the seasonal evolution of an alpine snowpack ENVIDAT STAC Catalog 2020-01-01 2020-01-01 9.8093934, 46.8296448, 9.8093934, 46.8296448 https://cmr.earthdata.nasa.gov/search/concepts/C2789817928-ENVIDAT.umm_json The WFJ_RHOSSA dataset contains multi-instrument, multi-resolution snow stratigraphy measurements for the seasonal evolution of the snowpack from the Weissfluhjoch research site, Davos, Switzerland. The measurements were initiated during the RHOSSA field campaign conducted in the winter season 2015–2016 with a focus on density (RHO) and specific surface area (SSA) measurements. The Instruments and methods used in the campaign at different spatial and temporal resolution are: SnowMicroPen, Density Cutter, IceCube, Traditional profiles, Stability tests and X-ray tomography. The measurements are complemented by simulation data from the model SNOWPACK. proprietary
white_model_parameters_652_1 Literature-Derived Parameters for the BIOME-BGC Terrestrial Ecosystem Model ORNL_CLOUD STAC Catalog 1947-06-15 2000-06-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2810678753-ORNL_CLOUD.umm_json Various aspects of primary production of a variety of plant species found in natural temperate biomes were compiled from literature and presented for use with process-based ecosystem simulation models or ecosystem studies. Information was selected according to the input parameter needs of the BIOME-BGC process-based simulation model. proprietary
-whitney_dem_1 A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica ALL STAC Catalog 2005-01-01 2007-05-01 110.522, -66.255, 110.544, -66.248 https://cmr.earthdata.nasa.gov/search/concepts/C1214311446-AU_AADC.umm_json This dataset includes a 10 metre resolution digital elevation model (DEM) of the Whitney Point area of the Windmill Islands, Antarctica and an orthophoto created using the DEM. The data are stored in the UTM zone 49 map projection. The horizontal datum is WGS84. The data were created by Robert Anders, Centre for Spatial Information Science, University of Tasmania, Australia to support the postgraduate research of Phillipa Bricher into the nesting sites of Adelie Penguins. See a related URL below for a map showing Whitney Point. proprietary
whitney_dem_1 A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica AU_AADC STAC Catalog 2005-01-01 2007-05-01 110.522, -66.255, 110.544, -66.248 https://cmr.earthdata.nasa.gov/search/concepts/C1214311446-AU_AADC.umm_json This dataset includes a 10 metre resolution digital elevation model (DEM) of the Whitney Point area of the Windmill Islands, Antarctica and an orthophoto created using the DEM. The data are stored in the UTM zone 49 map projection. The horizontal datum is WGS84. The data were created by Robert Anders, Centre for Spatial Information Science, University of Tasmania, Australia to support the postgraduate research of Phillipa Bricher into the nesting sites of Adelie Penguins. See a related URL below for a map showing Whitney Point. proprietary
+whitney_dem_1 A digital elevation model (DEM) and orthophoto of the Whitney Point area of the Windmill Islands, Antarctica ALL STAC Catalog 2005-01-01 2007-05-01 110.522, -66.255, 110.544, -66.248 https://cmr.earthdata.nasa.gov/search/concepts/C1214311446-AU_AADC.umm_json This dataset includes a 10 metre resolution digital elevation model (DEM) of the Whitney Point area of the Windmill Islands, Antarctica and an orthophoto created using the DEM. The data are stored in the UTM zone 49 map projection. The horizontal datum is WGS84. The data were created by Robert Anders, Centre for Spatial Information Science, University of Tasmania, Australia to support the postgraduate research of Phillipa Bricher into the nesting sites of Adelie Penguins. See a related URL below for a map showing Whitney Point. proprietary
wilhend_687_1 LBA Regional Vegetation and Soils, 1-Degree (Wilson and Henderson-Sellers) ORNL_CLOUD STAC Catalog 1900-01-01 1999-12-31 -85, -25, -30, 10 https://cmr.earthdata.nasa.gov/search/concepts/C2777328977-ORNL_CLOUD.umm_json This data set is a subset of a global vegetation and soils data set by Wilson and Henderson-Sellers (1985a). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The original global data set (Wilson and Henderson-Sellers 1985a) is an archive of soil type and land cover data derived for use in general circulation models (GCMs). The data were collated from maps depicting natural vegetation, forestry, agriculture, land use, and soil, and they were archived at a resolution of 1 latitude by 1 longitude. The data set indicates soil type, soil data reliability, primary vegetation, secondary vegetation, and land cover data reliability. Approximately 50 land cover classifications are used, including categories for agricultural and urban uses. The inclusion of secondary vegetation type is particularly useful in areas with cover types that may have a fragmented distribution, such as in areas of urban development. The soil type data are classified according to climatically important properties for GCMs, and they indicate color (light, medium, or dark), texture, and drainage quality of the soil. The land cover data are compatible with the soils data, forming a coherent and consistent data set. The reliability of the land cover data is ranked on a scale of 1 to 5 (high to low). The reliability of the soil data is ranked as high, good, moderate, fair, or poor.Recommendations for the use of these data, as well as more detailed information can be found in Wilson and Henderson-Sellers (1985b).Further data set information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/wilhend/comp/wilhend_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html. proprietary
willmott_673_1 LBA Regional Climate Data, 0.5-Degree Grid, 1960-1990 (Willmott and Webber) ORNL_CLOUD STAC Catalog 1960-01-01 1990-12-31 -85, -25, -30, 10 https://cmr.earthdata.nasa.gov/search/concepts/C2779732234-ORNL_CLOUD.umm_json "This data set is a subset of a 0.5-degree gridded temperature and precipitation data set for South America (Willmott and Webber 1998). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), defined as 10 N to 25 S, 30 to 85 W. The data are in ASCII GRID format. The data consist of the following: Monthly mean air temperature time series (1960-1990), in degrees C: monthly mean air temperatures for 1960-1990 cross validation errors associated with time series monthly mean air temperatures for 1960-1990, DEM assisted interpolation cross validation errors associated with DEM assisted interpolation time series Monthly mean air temperature climatology, in degrees C: climatic means of monthly and annual air temperatures cross validation errors associated with climatic means climatic means of monthly and annual mean air temperatures, DEM assisted interpolation cross validation errors associated with DEM assisted interpolation climatic means Monthly total precipitation time series (1960-1990), in millimeters: monthly precipitation totals for 1960-1990 cross validation errors associated with time series monthly precipitation totals for 1960-1990, climatologically aided interpolation cross validation errors associated with climatologically aided interpolation time series Monthly total precipitation climatology, in millimeters: climatic means of monthly and annual precipitation totals cross validation errors associated with climatic means More information about the full data set can be found at ""Willmott, Matsuura, and Collaborators' Global Climate Resource Pages"" (http://climate.geog.udel.edu/~climate) at the University of Delaware. To obtain the original documentation and data, follow the link for ""Available Climate Data,"" register or sign in, and follow the link for ""South American Climate Data."" Information on the LBA subset can be found at ftp://daac.ornl.gov/data/lba/physical_climate/willmott/comp/willmott_readme.pdf. " proprietary
wind-topo_model_0.1.0 Wind-Topo_model ENVIDAT STAC Catalog 2022-01-01 2022-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789817956-ENVIDAT.umm_json "Wind-Topo is a statistical downscaling model for near surface wind fields especially suited for highly complex terrain. It is based on deep learning and was trained (calibrated) using the hourly wind speed and direction from 261 automatic measurement stations (IMIS and SwissMetNet) located in Switzerland. The periods 1st October 2015 to 1st October 2016 and 1st October 2017 to 1st October 2018 were used for training. The model was validated using 60 other stations on the period 1st October 2016 to 1st October 2017. Wind-Topo was trained using COSMO-1 data and a 53-meter Digital Elevation Model as input. This dataset provides all the necessary code to understand, use and incorporate Wind-Topo in a new downscaling scheme. Specifically, the dataset contains the architecture of Wind-Topo and its optimized parameters, as well as a python script to downscale uniform wind fields with a prescribed vertical profile for any given 53-meter DEM. Accompanies the publication ""Wind-Topo: Downscaling near-surface wind fields to high-resolution topography in highly complex terrain with deep learning"" Dujardin and Lehning, Quarterly Journal of the Royal Meteorological Society, 2022. https://doi.org/10.1002/qj.4265 Please cite this publication if you use Wind-Topo or derive new models from it. The code can be used under the GNU Affero General Public License (AGPL)." proprietary
wind_dem_1 Digital Elevation Model of the Windmill Islands AU_AADC STAC Catalog 1999-07-11 1999-08-23 110, -67, 111, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214311463-AU_AADC.umm_json This DEM includes all the inshore and offshore islands, all the peninsulas and the lower slopes of the icecap leading up to Law Dome. The DEM has a cell size of 10 m. proprietary
windmill_bathy_surveys_1 Bathymetric surveys of Brown Bay, O'Brien Bay and Newcomb Bay in the Windmill Islands AU_AADC STAC Catalog 1997-02-01 1997-03-31 110.515, -66.297, 110.565, -66.258 https://cmr.earthdata.nasa.gov/search/concepts/C1214311438-AU_AADC.umm_json Bathymetric surveys of Brown Bay, O'Brien Bay and Newcomb Bay in the Windmill Islands. This dataset resulted from bathymetric surveys of Brown Bay, O'Brien Bay and Newcomb Bay in the Windmill Islands, carried out in February and March 1997 as part of ASAC Project 2201. The surveys were carried out by Jonny Stark and Tim Ryan in the workboat the 'Southern Comfort'. proprietary
-winston_bathy_1 A bathymetric survey of Winston Lagoon ALL STAC Catalog 1987-01-09 1987-01-14 73.23557, -53.20274, 73.83911, -52.95006 https://cmr.earthdata.nasa.gov/search/concepts/C1214311480-AU_AADC.umm_json During the 1986-87 Expedition to Heard Island, a 3m inflatable boat was depoted at the shores of Winston Lagoon, on the islands' south-east coast. The boat was to allow access to the important Long Beach Elephant Seal harems for periods when flooding from the lagoon prevented passage across its spit. The availability of the boat together with a 'Furuno' echo sounder, a stabilised, floating, transducer platform (constructed by a crew member from Nella Dan), and field assistance allowed a bathymetric survey of Winston Lagoon to be conducted. Winston Lagoon depth work was done from 9/1/1987-14/1/1987 in the rare calm periods. We (the researchers) lived in the nearby Paddick Valley hut and sheltered there in rough weather. We only ran transects in calm weather. The map used was the largest Heard Island map available in 1986. 30 transects were run across the lake from known points on the map recognisable from the shore. We calibrated the echo sounder (a marine device) for fresh water by checking a range of measured depths against a weighted fibre-glass tape. Water samples were taken from a range of depths to the bottom and the lake was fresh throughout. Lake was very opaque with a secchi depth of 0.46m. proprietary
winston_bathy_1 A bathymetric survey of Winston Lagoon AU_AADC STAC Catalog 1987-01-09 1987-01-14 73.23557, -53.20274, 73.83911, -52.95006 https://cmr.earthdata.nasa.gov/search/concepts/C1214311480-AU_AADC.umm_json During the 1986-87 Expedition to Heard Island, a 3m inflatable boat was depoted at the shores of Winston Lagoon, on the islands' south-east coast. The boat was to allow access to the important Long Beach Elephant Seal harems for periods when flooding from the lagoon prevented passage across its spit. The availability of the boat together with a 'Furuno' echo sounder, a stabilised, floating, transducer platform (constructed by a crew member from Nella Dan), and field assistance allowed a bathymetric survey of Winston Lagoon to be conducted. Winston Lagoon depth work was done from 9/1/1987-14/1/1987 in the rare calm periods. We (the researchers) lived in the nearby Paddick Valley hut and sheltered there in rough weather. We only ran transects in calm weather. The map used was the largest Heard Island map available in 1986. 30 transects were run across the lake from known points on the map recognisable from the shore. We calibrated the echo sounder (a marine device) for fresh water by checking a range of measured depths against a weighted fibre-glass tape. Water samples were taken from a range of depths to the bottom and the lake was fresh throughout. Lake was very opaque with a secchi depth of 0.46m. proprietary
+winston_bathy_1 A bathymetric survey of Winston Lagoon ALL STAC Catalog 1987-01-09 1987-01-14 73.23557, -53.20274, 73.83911, -52.95006 https://cmr.earthdata.nasa.gov/search/concepts/C1214311480-AU_AADC.umm_json During the 1986-87 Expedition to Heard Island, a 3m inflatable boat was depoted at the shores of Winston Lagoon, on the islands' south-east coast. The boat was to allow access to the important Long Beach Elephant Seal harems for periods when flooding from the lagoon prevented passage across its spit. The availability of the boat together with a 'Furuno' echo sounder, a stabilised, floating, transducer platform (constructed by a crew member from Nella Dan), and field assistance allowed a bathymetric survey of Winston Lagoon to be conducted. Winston Lagoon depth work was done from 9/1/1987-14/1/1987 in the rare calm periods. We (the researchers) lived in the nearby Paddick Valley hut and sheltered there in rough weather. We only ran transects in calm weather. The map used was the largest Heard Island map available in 1986. 30 transects were run across the lake from known points on the map recognisable from the shore. We calibrated the echo sounder (a marine device) for fresh water by checking a range of measured depths against a weighted fibre-glass tape. Water samples were taken from a range of depths to the bottom and the lake was fresh throughout. Lake was very opaque with a secchi depth of 0.46m. proprietary
wisperimpacts_1 Water Isotope System for Precipitation and Entrainment Research (WISPER) IMPACTS GHRC_DAAC STAC Catalog 2020-01-18 2023-02-28 -95.2426928, 33.2614038, -67.8781539, 48.2369386 https://cmr.earthdata.nasa.gov/search/concepts/C2175816611-GHRC_DAAC.umm_json The Water Isotope System for Precipitation and Entrainment Research (WISPER) IMPACTS dataset consists of condensed water contents, water vapor measurements, and isotope ratios in support of the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The dataset files are available in ASCII format from January 18, 2020, through February 28, 2023. proprietary
wml_bilderstudie_1.0 Relationship between physical forest characteristics, visual attractiveness and perception of ecosystem services in urban forests ENVIDAT STAC Catalog 2019-01-01 2019-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789818010-ENVIDAT.umm_json "This questionnaire survey was conducted as an online survey and aimed at investigating the relationship between physical forest characteristics, visual attractiveness of forest and the perception of ecological and cultural ecosystem services in urban forests. Each participant was shown 6 photos out of a pool of 50 photos taken from the Swiss National Forest Inventory (NFI) database. Physical forest characteristics were derived from the photos. The study was conducted as part of the ""WaMos meets LFI"" (WML) project." proprietary
wmlganzeschweiz_1.0 WaMos meets LFI, ganze Schweiz ENVIDAT STAC Catalog 2021-01-01 2021-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789818071-ENVIDAT.umm_json The data consists of a forest visitor survey conducted at 50 plots in the whole of Switzerland, once during the winter- and once during the summer season. Physical forest characteristics according to the Swiss National Forest Inventory NFI were collected from the same plots in winter and summer. Visibility was measured using terrestrial laser scanning. At some plots, sound measurements were also conducted. proprietary