Using machine learning and artificial intelligence to improve model-data integrated earth system model predictions of water and carbon cycle extremes
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
The research proposed here focuses on improving the predictive power of the land component of earth system models (ESMs) using (1) model-data fusion enabled by machine learning (ML) and artificial intelligence (AI), (2) predictive modeling through the combination of ML, AI, and big-data (comprising both model output and observations), and (3) insight of ESM structure and process mechanisms gleaned from complex data using ML and AI.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI ID:
- 1769794
- Report Number(s):
- AI4ESP1130
- Country of Publication:
- United States
- Language:
- English
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