Advancing understanding, modelling and prediction of extreme events in a changing climate

Expected Outcome:Project results are expected to contribute to all of the following expected outcomes:Improved understanding of past and present extreme events in the context of climate change in Europe and globally, as well as the interaction between different hazards, their cumulative and/or cascading effects.Enhanced seamless prediction and projection modelling and attribution capabilities for extreme events and their likelihood to support preparedness, response and resilience to climate change by EU and national and regional actors. The EU Union Preparedness Strategy, the EU Adaptation Strategy and the European Climate Adaptation Plan can act as a guidance in these efforts.Up-to-date contributions towards latest climate science, risk assessments, adaptation strategies and policies and improved early warning systems for single and multi-hazard events. Scope:Climate change is intensifying the frequency and severity of extreme events. Understanding and predicting extreme events and the interaction between different types of hazards is critical for building resilience and safeguarding communities.Actions are expected to draw upon multiple lines of evidence from a hierarchy of models (including high resolution Earth system models and digital twins) and data of past and recent climate to further our understanding of processes, pre-conditioning and causality driving extreme events under climate change conditions, including anthropogenic factors and internal variability. Other innovative and efficient modelling and analysis methods, including AI-based approaches, to better predict, emulate and reveal climate change related extreme and unprecedented high impact events, and to capture their likelihood are particularly welcome.Extreme events should be addressed in their broadest sense and types, encompassing isolated, compound or cascading events affecting lives, livelihoods, ecosystems, socio-economic sectors and infrastructures, from large-scale continental to local-sca