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Convective Storm VIL and lightning nowcasting Using Satellite and Weather Radar Measurements Based on Multi-Task Learning Models

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Advances in Atmospheric Sciences 2023年第5期40卷 887-899页

作者： Yang LI Yubao LIU Rongfu SUN Fengxia GUO Xiaofeng XU Haixiang XU Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration Nanjing University of Information Science and TechnologyNanjing 210044China Precision Regional Earth Modeling and Information Center Nanjing University of Information Science and TechnologyNanjing 210044China Jibei Electric Power Company Beijing 100054China China Meteorological Administration Beijing 100081China

Convective storms and lightning are among the most important weather phenomena that are challenging to *** this study,a novel multi-task learning(MTL)encoder-decoder U-net neural network was developed to forecast convective storms and lightning with lead times for up to 90 min,using GOES-16 geostationary satellite infrared brightness temperatures(IRBTs),lightning flashes from Geostationary lightning Mapper(GLM),and vertically integrated liquid(VIL)from Next Generation Weather Radar(NEXRAD).To cope with the heavily skewed distribution of lightning data,a spatiotemporal exponent-weighted loss function and log-transformed lightning normalization approach were *** effects of MTL,single-task learning(STL),and IRBTs as auxiliary input features on convection and lightning nowcasting were *** results showed that normalizing the heavily skew-distributed lightning data along with a log-transformation dramatically outperforms the min-max normalization method for nowcasting an intense lightning *** MTL model significantly outperformed the STL model for both lightning nowcasting and VIL nowcasting,particularly for intense lightning *** MTL also helped delay the lightning forecast performance decay with the lead ***,incorporating satellite IRBTs as auxiliary input features substantially improved lightning nowcasting,but produced little difference in VIL ***,the MTL model performed better for forecasting both lightning and the VIL of organized convective storms than for isolated cells.

关键词： convection/lightning nowcasting multi-task learning geostationary satellite weather radar U-net model

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