Changing landscape of regional extreme weather events by intersecting large-scale weather types and local-scale potential impacts for the Alpine region

Extreme weather events and their resulting impacts threaten all levels of society. Climate change can amplify the frequency and intensity of associated hazards. One of the key-challenges for decision-makers in civil protection is adapting to the changing landscape of weather-induced impacts driven by climate change. It is therefore essential to assess and estimate the changing conditions for extreme weather events under climate change.This study investigates the changing landscape of regional extreme weather events in the Alpine region by utilizing weather circulation type classification through its relationship with weather-induced potential extreme events. Therein, large-scale weather types take the role of relevant precursors for regional extreme events. The local-scale potential impact events that are associated with prevailing weather types are derived by using percentile-based methods on high-resolution, gridded precipitation data. ERA5 mean sea level pressure and the classification scheme GWT ('Gross-Wetter-Typen') are used to derive 18 classes of cyclonic and anti-cyclonic weather types, representing a prevailing circulation on a daily basis for the whole Alpine region. Subsequently, unsupervised hierarchical clustering (Agglomerative clustering) is used to evaluate overlaps between cluster families in order to derive a subset of 'high-impact' weather types. The relationship between those weather types and local-scale extreme events is further characterized by analyzing percentile-based indicators from station data and high-resolution observational data. Finally, we extend our analysis by applying found relationships to state-of-the-art climate models from the Coupled Model Intercomparison Project 6 (CMIP6) to investigate the changing landscape for extreme weather events under different climate change scenarios.Our findings indicate that a subset of weather types, related to specific cyclonic circulation patterns, is mostly responsible as precursor for extreme precipitation events. Those patterns furthermore show increases in frequency under the scenario SSP3-7.0, that are consistent across the climate model ensemble. Associated changes of precipitation totals suggest increases in intensity, however these intensity changes are not as conclusive due to large inter-model spread.