Mesoscale Convective System

Mesoscale convective systems (MCSs) are large thunderstorm complexes crucial to understand for accurate weather forecasting and severe weather warnings. Current research focuses on improving MCS detection and prediction using advanced deep learning models, such as U-Net architectures for downscaling high-resolution weather data and generative diffusion models for emulating complex storm dynamics at kilometer scales. These efforts leverage multi-scale spatiotemporal information from satellite imagery and numerical weather prediction models to enhance the accuracy and resolution of forecasts, ultimately improving preparedness for extreme weather events. The improved understanding and prediction of MCSs have significant implications for mitigating the impacts of severe weather on society and infrastructure.