Using high-resolution regional climate models to estimate return levels of daily extreme precipitation over Bavaria

Abstract + 6.6  % and a spatial Spearman rank correlation of ρ = 0.72. The higher-resolution 5 km WRF setup is found to improve the performance in terms of bias (+ 4.7  %) and spatial correlation (ρ = 0.82). However, the finer topographic details of the WRF-ERA5 return levels cannot be evaluated with the observation data because their spatial resolution is too low. Hence, this comparison shows no further improvement in the spatial correlation (ρ = 0.82) but a small improvement in the bias (2.7 %) compared to the 5 km resolution setup. + 2.5  %; ρ = 0.79) and the generalized Pareto (GP) distributions (bias is + 2.9  %; ρ = 0.81) show almost equivalent results for the 10-year return period, whereas the metastatistical extreme value (MEV) distribution leads to a slight underestimation (bias is - 7.8  %; ρ = 0.84). For the 100-year return level, however, the MEV distribution (bias is + 2.7  %; ρ = 0.73) outperforms the GEV distribution (bias is + 13.3  %; ρ = 0.66), the GEV distribution with fixed shape parameter (bias is + 12.9  %; ρ = 0.70), and the GP distribution (bias is + 11.9  %; ρ = 0.63). Hence, for applications where the return period is extrapolated, the MEV framework is recommended. From these results, it follows that high-resolution regional climate models are suitable for generating spatially homogeneous rainfall return level products. In regions with a sparse rain gauge density or low spatial representativeness of the stations due to complex topography, RCMs can support the observational data. Further, RCMs driven by global climate models with emission scenarios can project climate-change-induced alterations in rainfall return levels at regional to local scales. This can allow adjustment of structural design and, therefore, adaption to future precipitation conditions.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: Using high-resolution regional climate models to estimate return levels of daily extreme precipitation over Bavaria ; volume:21 ; number:11 ; year:2021 ; pages:3573-3598 ; extent:26 ; Natural hazards and earth system sciences ; 21, Heft 11 (2021), 3573-3598 (gesamt 26)

Contributors, Places and Time

• Creator: Poschlod, Benjamin

Further information

• DOI: 10.5194/nhess-21-3573-2021
• URN: urn:nbn:de:101:1-2021120204545107276706
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:22 AM CEST