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Update W1D3_Tutorial1.ipynb
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jlpearso authored Jul 17, 2024
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"\n",
"These applications have strong implications on communities through food security, culture activities, and other economic activities.\n",
"\n",
"## ![modis ndvi](https://github.com/neuromatch/course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_ndvi.gif?raw=true)|\n",
"## ![modis ndvi](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_ndvi.gif?raw=true)|\n",
"\n",
"Credit: [NASA](https://earthobservatory.nasa.gov/global-maps/MOD_NDVI_M)\n"
]
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"\n",
"Clouds are one of the major sources of uncertainty in future climate projections. Satellite data is valuable to help us deepen our understanding of cloud processes to better incorporate the effects of clouds in climate models.\n",
"\n",
"## ![modis cloud](https://github.com/neuromatch/course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_cloud.gif?raw=true)|\n",
"## ![modis cloud](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_cloud.gif?raw=true)|\n",
"\n",
"Cloud fraction, or the portion of a pixel covered by clouds. Credit: [NASA](https://earthobservatory.nasa.gov/global-maps/MODAL2_M_CLD_FR)\n"
]
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"- Quantify the variations in rainfall rates across different regions over time. This information can support water resource planning and management to meet the needs of local communities.\n",
"- Investigate the frequency and potential causes of extreme rainfall events and examine their impacts on societal and natural systems. Examples include studying hurricanes and extreme rainfall events.\n",
"\n",
"## ![rainfall](https://github.com/neuromatch/course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_gpm_imerg_rainfall.gif?raw=true)|\n",
"## ![rainfall](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_gpm_imerg_rainfall.gif?raw=true)|\n",
"\n",
"Credit: [NASA](https://earthobservatory.nasa.gov/global-maps/GPM_3IMERGM)\n"
]
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"- Monitoring SST is essential for studying large-scale ocean circulation and climate variability, such as the El Niño-Southern Oscillation (ENSO). Changes in SST patterns can provide valuable information about the occurrence and strength of ENSO events, which have significant impacts on global weather patterns.\n",
"- SST plays a pivotal role in the study and prediction of tropical cyclones. Warm SST provides the necessary energy for the formation and intensification of tropical cyclones, making SST data critical for understanding and forecasting these powerful storm systems.\n",
"\n",
"## ![modis sst](https://github.com/neuromatch/course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_sst.gif?raw=true) |\n",
"## ![modis sst](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_sst.gif?raw=true) |\n",
"\n",
"Credit: [NASA](https://earthobservatory.nasa.gov/global-maps/MYD28M)\n"
]
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"- How have phytoplankton populations changed in response to shifting sea surface temperatures in different ocean basins?\n",
"- By combining phytoplankton data with socioeconomic information, can we gain a comprehensive understanding of how the changing climate affects the fishing industry and the communities reliant on it.\n",
"\n",
"## ![modis chl](https://github.com/neuromatch/course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_chl.gif?raw=true) |\n",
"## ![modis chl](https://github.com/neuromatch/climate-course-content/blob/main/tutorials/W1D3_RemoteSensing/asset/img/t1_modis_chl.gif?raw=true) |\n",
"\n",
"Credit: [NASA](https://earthobservatory.nasa.gov/global-maps/MY1DMM_CHLORA)\n"
]
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