Combining artificial intelligence, Earth observations, and climate models to improve predictability of ice-biogeochemistry interactions
Focal Area: Predictive Modeling. We describe how artificial intelligence (AI) can be combined with state-of-the-science Earth system models to better predict future regional climate responses. To demonstrate, we describe a case study in biogeochemical interactions with sea ice. Science Challenge: Bi...
| Main Authors: | , , |
|---|---|
| Language: | unknown |
| Published: |
2022
|
| Subjects: | |
| Online Access: | http://www.osti.gov/servlets/purl/1769689 https://www.osti.gov/biblio/1769689 https://doi.org/10.2172/1769689 |
| Summary: | Focal Area: Predictive Modeling. We describe how artificial intelligence (AI) can be combined with state-of-the-science Earth system models to better predict future regional climate responses. To demonstrate, we describe a case study in biogeochemical interactions with sea ice. Science Challenge: Biogeochemical models are poorly constrained for high latitude systems. Machine learning methods and edge computing can be combined with Earth system models, such as the Energy Exascale Earth System Model (E3SM), to gain insight into ice-biogeochemical interactions and improve sea ice extent prediction. |
|---|