AI-Constrained Bottom-Up Ecohydrology and Improved Prediction of Seasonal, Interannual, and Decadal Flood and Drought Risks
more »
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Univ. of Tennessee, Knoxville, TN (United States)
- Univ. of Washington, Seattle, WA (United States)
- Univ. of California, Irvine, CA (United States)
- Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
- Univ. of Georgia, Athens, GA (United States)
- Univ. of Tokyo (Japan)
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
- Univ. of New South Wales, Sydney, NSW (Australia)
- Univ. of Western Sydney, NSW (Australia)
- Brookhaven National Lab. (BNL), Upton, NY (United States)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Florida State Univ., Tallahassee, FL (United States)
- Argonne National Lab. (ANL), Argonne, IL (United States)
Focal Areas: (2) Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system composed of a hierarchy of models (3)Insight gleaned from complex data (both observed & simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI
- 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:
- 1769668
- Report Number(s):
- AI4ESP--1060
- Country of Publication:
- United States
- Language:
- English
Similar Records
AI-Based Integrated Modeling and Observational Framework for Improving Seasonal to Decadal Prediction of Terrestrial Ecohydrological Extremes
AI-Driven Data Discovery to Improve Earth System Predictability
Improve wildfire predictability driven by extreme water cycle with interpretable physically-guided ML/AI
Technical Report
·
Thu Apr 15 00:00:00 EDT 2021
·
OSTI ID:1769666
AI-Driven Data Discovery to Improve Earth System Predictability
Technical Report
·
Thu Apr 15 00:00:00 EDT 2021
·
OSTI ID:1769671
Improve wildfire predictability driven by extreme water cycle with interpretable physically-guided ML/AI
Technical Report
·
Thu Apr 15 00:00:00 EDT 2021
·
OSTI ID:1769720