Skilful precipitation nowcasting using deep generative models of radar.

ABSTRACT: Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socioeconomic needs of many sectors reliant on weather-dependent decision-making^1,2. State-of-the-art operational nowcasting methods typically advect precipitation fields with radar-based wind estimates, and struggle to capture important non-linear events such as convective initiations^3,4. Recently introduced deep learning methods use radar to directly predict future rain rates, free of physical constraints^5,6. While they accurately predict low-intensity rainfall, their operational utility is limited because their lack of constraints produces blurry nowcasts at longer lead times, yielding poor performance on rarer medium-to-heavy rain ev

SUBMITTER: Ravuri S 

PROVIDER: S-EPMC8481123 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature