Collaborative Research: CAIG: Understanding radiative feedbacks, ocean heat uptake, and en — NSF Award to Colorado State Universit
Models used to simulate weather and climate rely on sophisticated algorithms to represent the physics of the atmosphere, ocean, land surface, and cryosphere. These models have been quite successful but they have two important shortcomings: first, they are computationally intensive, typically running on world-class supe
| Award title | Collaborative Research: CAIG: Understanding radiative feedbacks, ocean heat uptake, and en |
|---|---|
| Award ID | 2530919 |
| Awardee | Colorado State University |
| City | FORT COLLINS |
| State | CO |
| Amount obligated | $783,920 |
| Principal investigator | Maria Rugenstein |
| Program | GEO CI - GEO Cyberinfrastrctre |
| Start date | 01/01/2026 |
| Abstract | Models used to simulate weather and climate rely on sophisticated algorithms to represent the physics of the atmosphere, ocean, land surface, and cryosphere. These models have been quite successful but they have two important shortcomings: first, they are computationally intensive, typically running on world-class supercomputers and generating terabytes of data which are challenging to host and serve. Second, they do not take advantage of the large amounts of observational data collected over de |
| Source | NSF Awards |
$799/mo
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