Integration of AI/ML with Data Assimilation for Earth System Prediction
- Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES)
Focal Area(s): Development of dynamically consistent AI/ML methods that can integrate with the data assimilation cycle to improve the efficiency and effectiveness of state estimation and prediction at short to medium range forecast horizons. Science Challenge: This white paper addresses a first step toward complete integration of AI/ML and DA. Here, we address model emulation and its application to simple coupled atmosphere-ocean dynamics for use in data assimilation applications.
- Research Organization:
- Artificial Intelligence for Earth System Predictability (AI4ESP) Collaboration (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI ID:
- 1769728
- Report Number(s):
- AI4ESP--1102
- Country of Publication:
- United States
- Language:
- English
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