July 2026 – Training for AI tools for extreme events

Training for AI tools for extreme events will be coordinated by Fondazione CMCC and delivered together with UANTWERPEN. It will consist of the AI-driven identification of large-scale patterns associated with extreme events for better seasonal forecasting. Building on the knowledge gained by Fondazione CMCC in previous projects (CLINT, CYCLOPS, etc.) relative to the improvement of the seasonal forecast of heatwaves and/or extreme precipitation over certain domains (e.g., European area, Mediterranean subbasins, Como Lake, etc), we aim to apply a similar approach over Romania sub-domains. The AI-driven association of large-scale conditions to observed local extreme events (lagged in space and time) in ERA5 data will be the base of the improved seasonal forecast. Then, instead of directly forecasting the probability of extreme events on the seasonal time horizon, we evaluate the probability of multiple large-scale conditions that lead to such extreme events. This is consistent with the model’s superior ability to represent large-scale conditions rather than single extreme events when compared to the observations.