Articles | Volume 21, issue 11
https://doi.org/10.5194/nhess-21-3573-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-3573-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2021
Research article |
| 25 Nov 2021
| 25 Nov 2021
Using high-resolution regional climate models to estimate return levels of daily extreme precipitation over Bavaria
Benjamin Poschlod
CORRESPONDING AUTHOR
Department of Geography, Ludwig-Maximilians-Universität
München, 80333 Munich, Germany
now at: Research Department, Berchtesgaden National Park,
83471 Berchtesgaden, Germany
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Cited
20 citations as recorded by crossref.
- Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework P. Laux et al. https://doi.org/10.1016/j.jhydrol.2025.133607
- Role of mean and variability change in changes in European annual and seasonal extreme precipitation events R. Wood https://doi.org/10.5194/esd-14-797-2023
- Frequency analysis of extreme rainfall over the Japanese archipelago by leveraging gauge-adjusted radar and satellite estimates S. Mtibaa https://doi.org/10.1016/j.jhydrol.2024.131425
- Estimation of design precipitation using weather radar in Germany: A comparison of statistical methods K. Lengfeld & F. Marra https://doi.org/10.1016/j.ejrh.2024.101952
- Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations G. Formetta et al. https://doi.org/10.1016/j.advwatres.2024.104851
- Climate extremes and risks: links between climate science and decision-making J. Sillmann et al. https://doi.org/10.3389/fclim.2024.1499765
- How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation? E. Dallan et al. https://doi.org/10.5194/hess-27-1133-2023
- Bayesian hierarchical modelling of intensity-duration-frequency curves using a climate model large ensemble A. Rischmuller et al. https://doi.org/10.5194/ascmo-12-1-2026
- A global perspective on the spatial representation of climate extremes from km-scale models L. Brunner et al. https://doi.org/10.1088/1748-9326/ade1ef
- A critical evaluation of the metastatistical approach to extremes with focus on bias, uncertainty bands, and goodness-of-fit test T. Schmith et al. https://doi.org/10.1007/s00477-026-03260-9
- Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future B. Poschlod https://doi.org/10.1016/j.wace.2022.100492
- Uncertainty estimation of regionalised depth–duration–frequency curves in Germany B. Shehu & U. Haberlandt https://doi.org/10.5194/hess-27-2075-2023
- Predicting extreme sub-hourly precipitation intensification based on temperature shifts F. Marra et al. https://doi.org/10.5194/hess-28-375-2024
- The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis F. Zabel & B. Poschlod https://doi.org/10.5194/gmd-16-5383-2023
- Updating catastrophe models to today’s climate – An application of a large ensemble approach to extreme rainfall A. Lang & B. Poschlod https://doi.org/10.1016/j.crm.2024.100594
- Quantifying patch size distributions of forest disturbances in protected areas across the European Alps M. Maroschek et al. https://doi.org/10.1111/jbi.14760
- Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble F. Willkofer et al. https://doi.org/10.5194/hess-28-2969-2024
- Preliminary Model Study for Forecasting a Hot Weather Process in Guangdong Province Using CMA-TRAMS W. Wang et al. https://doi.org/10.4236/acs.2024.141006
- A method to derive satellite-based extreme precipitation return levels in poorly gauged areas M. Siena et al. https://doi.org/10.1016/j.jhydrol.2023.130295
- Forecasting Global Rainfall in a Changing Climate: A Machine Learning Approach Using Köppen-Geiger Zones Z. Wang et al. https://doi.org/10.1007/s41748-025-00876-9
20 citations as recorded by crossref.
- Future precipitation extremes and urban flood risk assessment using a non-stationary and convection-permitting climate-hydrodynamic modeling framework P. Laux et al. https://doi.org/10.1016/j.jhydrol.2025.133607
- Role of mean and variability change in changes in European annual and seasonal extreme precipitation events R. Wood https://doi.org/10.5194/esd-14-797-2023
- Frequency analysis of extreme rainfall over the Japanese archipelago by leveraging gauge-adjusted radar and satellite estimates S. Mtibaa https://doi.org/10.1016/j.jhydrol.2024.131425
- Estimation of design precipitation using weather radar in Germany: A comparison of statistical methods K. Lengfeld & F. Marra https://doi.org/10.1016/j.ejrh.2024.101952
- Sub-daily precipitation returns levels in ungauged locations: Added value of combining observations with convection permitting simulations G. Formetta et al. https://doi.org/10.1016/j.advwatres.2024.104851
- Climate extremes and risks: links between climate science and decision-making J. Sillmann et al. https://doi.org/10.3389/fclim.2024.1499765
- How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation? E. Dallan et al. https://doi.org/10.5194/hess-27-1133-2023
- Bayesian hierarchical modelling of intensity-duration-frequency curves using a climate model large ensemble A. Rischmuller et al. https://doi.org/10.5194/ascmo-12-1-2026
- A global perspective on the spatial representation of climate extremes from km-scale models L. Brunner et al. https://doi.org/10.1088/1748-9326/ade1ef
- A critical evaluation of the metastatistical approach to extremes with focus on bias, uncertainty bands, and goodness-of-fit test T. Schmith et al. https://doi.org/10.1007/s00477-026-03260-9
- Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future B. Poschlod https://doi.org/10.1016/j.wace.2022.100492
- Uncertainty estimation of regionalised depth–duration–frequency curves in Germany B. Shehu & U. Haberlandt https://doi.org/10.5194/hess-27-2075-2023
- Predicting extreme sub-hourly precipitation intensification based on temperature shifts F. Marra et al. https://doi.org/10.5194/hess-28-375-2024
- The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysis F. Zabel & B. Poschlod https://doi.org/10.5194/gmd-16-5383-2023
- Updating catastrophe models to today’s climate – An application of a large ensemble approach to extreme rainfall A. Lang & B. Poschlod https://doi.org/10.1016/j.crm.2024.100594
- Quantifying patch size distributions of forest disturbances in protected areas across the European Alps M. Maroschek et al. https://doi.org/10.1111/jbi.14760
- Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble F. Willkofer et al. https://doi.org/10.5194/hess-28-2969-2024
- Preliminary Model Study for Forecasting a Hot Weather Process in Guangdong Province Using CMA-TRAMS W. Wang et al. https://doi.org/10.4236/acs.2024.141006
- A method to derive satellite-based extreme precipitation return levels in poorly gauged areas M. Siena et al. https://doi.org/10.1016/j.jhydrol.2023.130295
- Forecasting Global Rainfall in a Changing Climate: A Machine Learning Approach Using Köppen-Geiger Zones Z. Wang et al. https://doi.org/10.1007/s41748-025-00876-9
Saved (final revised paper)
Latest update: 09 Jun 2026
Short summary
Three regional climate models (RCMs) are used to simulate extreme daily rainfall in Bavaria statistically occurring once every 10 or even 100 years. Results are validated with observations. The RCMs can reproduce spatial patterns and intensities, and setups with higher spatial resolutions show better results. These findings suggest that RCMs are suitable for assessing the probability of the occurrence of such rare rainfall events.
Three regional climate models (RCMs) are used to simulate extreme daily rainfall in Bavaria...
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