Enhancing Precipitation Predictions with the Cloud-Associated Parameterizations Testbed using Artificial Intelligence
Hsi-Yen Ma | 22-ERD-013
We will develop a new modeling framework utilizing an existing Cloud-Associated Parameterizations Testbed framework augmented with advanced machine learning and artificial intelligence techniques to improve precipitation prediction across scales for the Department of Energy's Energy Exascale Earth System Model. This work will inform development of advanced solutions to ensure that the nation's energy infrastructure is resilient to extreme weather events and hydrological changes.
Publications, Presentations, and Patents
Lafferty, David, Hsi-Yen Ma, and Wen-Ying Wu. “Atmospheric Feature Tracking and Associated Precipitation Extremes." Lawrence Livermore National Laboratory Climate and Weather Seminar Series. Livermore, California, August 10, 2022.
Kobayashi, Daigo, Hsi-Yen Ma, Wen-Ying Wu, and David Lafferty. “Improving Climate Prediction through Machine Learning.” Lawrence Livermore National Laboratory Climate and Weather Seminar Series. Livermore, California, August 10, 2022.