Articles | Volume 26, issue 7
https://doi.org/10.5194/nhess-26-3273-2026
© Author(s) 2026. 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-26-3273-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Jul 2026
Research article |
| 15 Jul 2026
| 15 Jul 2026
Benefits of the simplified MEV for analyzing hourly precipitation extremes in a changing climate
GFZ Helmholtz Centre for Geosciences, Section Hydrology, Potsdam 14473, Germany
Benjamin Poschlod
Research Unit Sustainability and Climate Risks, Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg 20148, Germany
Bruno Merz
GFZ Helmholtz Centre for Geosciences, Section Hydrology, Potsdam 14473, Germany
Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam 14476, Germany
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Short summary
Predicting hourly rainfall extremes under climate change is crucial yet highly uncertain. Using convection-permitting climate model data over Germany, we compare stationary and non-stationary general extreme value (GEV) and simplified metastatistical extreme value (sMEV) methods. We show that the sMEV approach exhibits lower uncertainty across return periods. Moreover, the non-stationary sMEV better captures climate-change-induced changes, though care is needed when projecting future extremes.
Predicting hourly rainfall extremes under climate change is crucial yet highly uncertain. Using...
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