Developing Low‐Likelihood Climate Storylines for Extreme Precipitation Over Central Europe

Abstract Heavy precipitation and associated flooding during the cold season, such as the 1993 flood in central Europe (CEU), are a major threat to society and ecosystems. Due to the lack of long homogenous climate data and methodological frameworks, it is challenging to estimate how extreme precipitation could get and what the physical drivers are. This study presents two complementary strategies to extrapolate beyond the precipitation records: (a) statistical estimates based on fitting generalized extreme value distributions, providing their probabilistic information on return periods and, (b) ensemble boosting, a model‐based re‐initialization of heavy precipitation in large ensembles, providing a physical coherent storyline in space and time, however, with no direct quantification of its probability. Both show that 3‐day accumulated precipitation maxima can be substantially exceeded over CEU of around 30%–40%, but even higher magnitudes cannot be ruled out in the near future. An empirical orthogonal function analysis reveals that certain sea level pressure patterns, partly reminding of atmospheric rivers are more often associated with heavy precipitation than more moderate events. Additionally, ensemble boosting is a suitable tool for case studies to analyze how extreme heavy precipitation as for the event in 1993 can be simulated. By boosting a 1993‐analog, one‐quarter of the resulting storylines show increased rainfall than observed, due to a stronger north‐south pressure gradient that may have exacerbated the flooding. Overall, the precipitation estimates demonstrate that ensemble boosting is a complementary method to statistical tools and suitable for stress testing, for example, infrastructure protection measures against potentially unseen heavy precipitation events