EGU25-11604, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-11604
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Optimizing convection-permitting model configurations for accurate simulation of extreme precipitation events with the regional climate model REMO-iMOVE
Laura Detjen1, Diana Rechid1, and Jürgen Böhner2
Laura Detjen et al.
  • 1Climate Service Center Germany (GERICS), Helmholtz-Zentrum Hereon, Hamburg, Germany (laura.detjen@hereon.de)
  • 2Institute of Geography, University of Hamburg, Hamburg, Germany

The increasing frequency and intensity of extreme events due to global warming, such as heavy rainfall and consequent floods, underline the need for research on the driving factors of these extremes. Accurate simulations of meteorological extremes at convection-permitting scale are crucial for understanding their spatial and temporal characteristics. Recently, various studies have demonstrated the added value of using convection-permitting regional climate models to simulate extreme precipitation. Further improvements of these regional models can therefore lay the foundation for better impact assessment, as well as for developing adaptation measures to tackle climate change. 

In this study, we investigate the optimal model configuration for the regional climate model REMO2020-iMOVE to capture extreme precipitation events, using the heavy rainfall that led to the devastating Ahr valley flood of July 2021 as a case study. Our simulations are performed with the non-hydrostatic version of REMO with ERA5 reanalysis data as forcing at a horizontal resolution of 3 km. By including the vegetation module iMOVE, we aim to improve the representation of vegetation-atmosphere interactions and, in a future step, investigate the effects of land use and land cover changes on extreme events. Here, we explore the impact of different model setups such as different domain sizes and initialization times on the simulation results. Furthermore, we validate our findings against observations and assess uncertainty within the model. This research provides insight into optimizing regional climate models to improve our understanding of extreme weather events. 

How to cite: Detjen, L., Rechid, D., and Böhner, J.: Optimizing convection-permitting model configurations for accurate simulation of extreme precipitation events with the regional climate model REMO-iMOVE, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11604, https://doi.org/10.5194/egusphere-egu25-11604, 2025.