Assessment shows the stochastic regional weather generator effectively predicts heavy-precipitation events, suggesting its utility for flood risk assessments in Germany.
We assess the ability of a regional weather generator to represent the extremity of heavy-precipitation events (HPEs) across spatial and temporal scales. To this end, we implement a multi-site non-stationary regional weather generator (nsRWG) for the area of Germany and generate 100 sets of synthetic daily precipitation data spanning 72 years. The weather extremity index (WEI) and its recent cross-scale modification (xWEI) are applied to quantify the cross-scale extremity of synthetic and observed HPEs and to compare their distributions. The results show that the nsRWG excels in replicating the extremity patterns for almost all seven durations (ranging from 1 to 7 d) considered. The frequency of small-scale 1 d rainfall is, however, slightly overestimated. The nsRWG aptly reproduces the potential influential areas of HPEs, whether of a short or long duration. It is capable of generating precipitation events mirroring the extremity patterns observed during past disaster-causing HPEs in Germany, while simultaneously accommodating their variations. This study demonstrates the potential of the nsRWG for simulating HPE-related hazards and assessing flood risks.
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Guan et al. (2025) studied this question.
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