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FitzRoy is presented, the first system that simultaneously achieves state-of-the-art predictive skill and physical realism over the continental United States and establishes a new frontier for high-fidelity precipitation forecasting.
Machine learning applied to high-resolution numerical weather prediction forecasts is gaining popularity for prediction of high-impact weather events, but questions remain on how to design such systems. Building off prior work, we describe sensitivity experiments using a random forest (RF) system for excessive rainfa...
This study examines several gridded datasets that are commonly, or could be, used in climate and drought monitoring in the contiguous United States (CONUS). The focus is on accumulations at durations from months to water years, which are most relevant to drought, and on the western CONUS where complex terrain complic...
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