AS1.1 | Understanding and forecasting the severe weather
EDI
Understanding and forecasting the severe weather
Co-organized by HS13/NP5
Conveners: Yong Wang, Masoud Rostami | Co-conveners: Maxime TaillardatECSECS, Lesley De Cruz, Bijan Fallah, Monika FeldmannECSECS, Stéphane Vannitsem

This session explores advancements in understanding and forecasting the severe weather, such as moist convection, and Mei-yu frontal systems, focusing on severe weather phenomena. It integrates AI methods, numerical modeling with particular attention to moist-convective models with intermediate complexity, e.g. Aeolus 2.0 & mcTRSW models, and observational techniques to enhance forecasting accuracy. Key topics include AI-based weather forecasting, ensemble prediction, mesoscale models, AI-driven nowcasting, and remote sensing technologies. The session also delves into the dynamics of moist convection, cloud formation, precipitation patterns, and their relationship with extreme weather and climate change. A segment on Mei-yu frontal systems highlights field experiments, cloud microphysics, and model improvements for better precipitation forecasts. The session fosters interdisciplinary discussions on breakthroughs and challenges in weather science.