Collaborative Research: CAIG Deep learning for Deep Chlorophyll Maxima: Predicting vertica — NSF Award to University of Maryland C
Marine phytoplankton are responsible for approximately half of the planet’s net primary production (NPP) and are undergoing rapid change in response to shifting surface ocean heat budgets. Satellite remote sensing has provided nearly three decades of surface ocean color data, enabling us to infer phytoplankton distribu
| Award title | Collaborative Research: CAIG Deep learning for Deep Chlorophyll Maxima: Predicting vertica |
|---|---|
| Award ID | 2530839 |
| Awardee | University of Maryland Center for Environmental Sciences |
| City | CAMBRIDGE |
| State | MD |
| Amount obligated | $705,374 |
| Principal investigator | Greg Silsbe |
| Program | GEO CI - GEO Cyberinfrastrctre |
| Start date | 09/01/2025 |
| Abstract | Marine phytoplankton are responsible for approximately half of the planet’s net primary production (NPP) and are undergoing rapid change in response to shifting surface ocean heat budgets. Satellite remote sensing has provided nearly three decades of surface ocean color data, enabling us to infer phytoplankton distribution and improve NPP estimates in the surface mixed layer with unprecedented spatial coverage. However, phytoplankton below the ocean mixed layer contribute substantially to global |
| Source | NSF Awards |
$799/mo
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