Merge pull request #92 from nsea-log/cs_release-v103

Curriculum specialist's fixes and changes for release-v1.0.3
neuromatch · Jul 22, 2024 · f43e654 · f43e654
2 parents d32a6ca + 7981478
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diff --git a/projects/docs/continuing_your_project_after_the_course.md b/projects/docs/continuing_your_project_after_the_course.md
@@ -1,8 +1,8 @@
 # Climatematch Impact Scholars program
 
-Scientific discovery takes time. Recognizing this, Neuromatch and Climatematch Academy, in collaboration with the [**Learning the Earth with Artificial Intelligence and Physics (LEAP)**](https://leap.columbia.edu/), a National Science Foundation (NSF)-funded Science & Technology Center based at Columbia University, offer the Climate Impact Scholars program. This program provides selected student groups with access to computing resources for 10 months after the courses end, allowing scholars to further develop projects initiated during the courses or to explore new projects provided by the academies or our partners. 
-Scholars will benefit from the mentorship of experienced researchers who will provide guidance, constructive feedback, and professional insights over the course of 10 months, from October to July, enhancing the quality and impact of their work. 
+Scientific discovery takes time. Recognizing this, Neuromatch and Climatematch Academy, in collaboration with the [**Learning the Earth with Artificial Intelligence and Physics (LEAP)**](https://leap.columbia.edu/), a National Science Foundation (NSF)-funded Science & Technology Center based at Columbia University, offer the Climate Impact Scholars program. This program provides selected student groups with access to computing resources for 6 months after the courses end, allowing scholars to further develop projects initiated during the courses or to explore new projects provided by the academies or our partners. 
+Scholars will benefit from the mentorship of experienced researchers who will provide guidance, constructive feedback, and professional insights over the course of 10 months, from October 2024 to March 2025, enhancing the quality and impact of their work. 
 Additionally, scholars will have the chance to present their research to seasoned experts, gaining valuable feedback and engaging with a broader scientific community. 
 This program also includes the opportunity to showcase their projects at the Academies Open Ceremony, inspiring future scholars and demonstrating the significance of their research.
 
-Please refer to [this link](https://neuromatch.io/impact-scholars/) for a detailed outline and description of the Impact Scholars Program.
+Please refer to [this link](https://impact-scholars.neuromatch.io/impact-scholars/intro.html) for a detailed outline and description of the Impact Scholars Program.
diff --git a/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb b/tutorials/Projects_GoodResearchPractices/Projects_Tutorial8.ipynb
@@ -99,7 +99,7 @@
     "  return tab_contents\n",
     "\n",
     "\n",
-    "video_ids = [('Youtube', 'HEsrjlyza5o'), ('Bilibili', 'BV1494y1B7qs')]\n",
+    "video_ids = [('Youtube', 'HEsrjlyza5o'), ('Bilibili', 'BV1NtbyeeEqA')]\n",
     "tab_contents = display_videos(video_ids, W=730, H=410)\n",
     "tabs = widgets.Tab()\n",
     "tabs.children = tab_contents\n",

diff --git a/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb b/tutorials/W1D1_ClimateSystemOverview/W1D1_Tutorial5.ipynb
@@ -216,7 +216,7 @@
     "  return tab_contents\n",
     "\n",
     "\n",
-    "video_ids = [('Youtube', 'SyvFyT3jVM8'), ('Bilibili', 'BV1ho4y1C7Eo')]\n",
+    "video_ids = [('Youtube', 'SyvFyT3jVM8'), ('Bilibili', 'BV1PhbyeaEMk')]\n",
     "tab_contents = display_videos(video_ids, W=730, H=410)\n",
     "tabs = widgets.Tab()\n",
     "tabs.children = tab_contents\n",

diff --git a/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial6.ipynb b/tutorials/W1D2_Ocean-AtmosphereReanalysis/W1D2_Tutorial6.ipynb
@@ -66,7 +66,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "execution": {},
     "tags": [
      "colab"
     ]
@@ -82,9 +81,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import xarray as xr\n",
@@ -101,8 +98,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -130,8 +126,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -158,8 +153,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -177,7 +171,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "tags": []
    },
    "outputs": [],
@@ -235,7 +228,6 @@
    "execution_count": null,
    "metadata": {
     "cellView": "form",
-    "execution": {},
     "pycharm": {
      "name": "#%%\n"
     },
@@ -271,9 +263,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# import preprocessed ECCO data. This data is full depth temperature data over 1992 to 2016 (annual mean)\n",
@@ -301,9 +291,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Quick plot of the ocean temperature in Kelvin\n",
@@ -324,9 +312,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# take the temporal mean over the period 1992 to 1994\n",
@@ -348,9 +334,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot the zonal mean section of this data\n",
@@ -390,9 +374,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "theta_area_int = (\n",
@@ -403,9 +385,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# define reference density of salt water and the specific heat capacity\n",
@@ -460,9 +440,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "area_of_ocean = (\n",
@@ -492,9 +470,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -508,8 +484,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -540,9 +515,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# this cell may take a while to run!\n",
@@ -624,9 +597,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots()\n",
@@ -667,9 +638,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# to_remove explanation\n",
@@ -683,8 +652,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "cellView": "form",
-    "execution": {}
+    "cellView": "form"
    },
    "outputs": [],
    "source": [
@@ -713,9 +681,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# first let's plot where heat is stored in the mean\n",
@@ -769,9 +735,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# we already defined an object that's the mean over years 1992 to 1994 (subset_theta)\n",
@@ -799,9 +763,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "execution": {}
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# plot 2 maps to compare changes in heat content in those two layers\n",
@@ -920,7 +882,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.19"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

diff --git a/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb b/tutorials/W1D4_Paleoclimate/W1D4_Tutorial2.ipynb
@@ -51,7 +51,7 @@
     "\n",
     "### An Overview of Isotopes in Paleoclimate\n",
     "\n",
-    "In this tutorial, and many of the remaining tutorials on this day, you will be looking at data of hydrogen and oxygen isotopes (δD and δ<sup>18</sup>O). As you learned in the video, isotopes are forms of the same element that contain the same numbers of protons but different numbers of neutrons. The two oxygen isotopes that are most commonly used in paleoclimate are oxygen 16 (<sup>16</sup>O), which is the which is the **\"lighter\"** oxygen isotope, and oxygen 18 (<sup>16</sup>O), which is the **\"heavier\"** oxygen isotope. The two hydrogen isotopes that are most commonly used in paleoclimate are hydrogen (H), which is the **\"lighter\"** oxygen isotope, and deuterium (D), which is the **\"heavier\"** oxygen isotope. \n",
+    "In this tutorial, and many of the remaining tutorials on this day, you will be looking at data of hydrogen and oxygen isotopes (δD and δ<sup>18</sup>O). As you learned in the video, isotopes are forms of the same element that contain the same numbers of protons but different numbers of neutrons. The two oxygen isotopes that are most commonly used in paleoclimate are oxygen 16 (<sup>16</sup>O), which is the which is the **\"lighter\"** oxygen isotope, and oxygen 18 (<sup>18</sup>O), which is the **\"heavier\"** oxygen isotope. The two hydrogen isotopes that are most commonly used in paleoclimate are hydrogen (H), which is the **\"lighter\"** oxygen isotope, and deuterium (D), which is the **\"heavier\"** oxygen isotope. \n",
     "\n",
     "![image-1.png](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D4_Paleoclimate/images/t2_image1.png?raw=true)\n",
     "\n",