Forecasting the weather, in particular severe and extreme weather, remains an important subject in meteorology. This session highlights recent research and advancements in forecasting methods, with a strong emphasis on AI-based methods and their integration into operational and impact-oriented forecasting systems. We welcome contributions that explore applications in nowcasting, mesoscale and convection permitting modelling, ensemble prediction, and seamless approaches that optimally integrate multiple forecast sources.
Topics may include:
• Data-driven forecasting, including ensemble methods, across global, regional and local scales
• Integration of data-driven models within data assimilation algorithms
• Operational workflows: implementation, monitoring, versioning of data and models, data, training, and inference pipelines
• AI-driven nowcasting methods and systems utilizing observational data and weather analysis
• Enhancement of mesoscale and convection-permitting models through AI techniques
• Application of novel remote sensing technologies in data assimilation processes
• Utilization of ensemble prediction techniques for improved forecasting
• Development of ensemble-based products for severe/extreme weather forecasting
• Seamless deterministic and probabilistic forecast prediction in data-driven, statistical, numerical and data-blending approaches
• Post-processing techniques, statistical methods in prediction
• Impact-oriented weather forecasting
• Presentation of results from relevant international research projects of EU, WMO, and EUMETNET etc.