1,1,1,3,5,7,1,3,4,5,3,1,9,10,11,- 1Freie Universität Berlin, Institute for Meteorology, Berlin, Germany (jens.grieger@fu-berlin.de)
- 2University of Stuttgart, Stuttgart, Germany
- 3Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
- 4Deutscher Wetterdienst, Regionales Klimabüro Potsdam, Germany
- 5Institute of Geosciences, Section Meteorology, University of Bonn, Bonn, Germany
- 6Faculty of Mathematics, Ruhr-University Bochum, Bochum, Germany
- 7Deutsches Klimarechenzentrum GmbH (DKRZ), Data Analysis, Hamburg, Germany
- 8Freie Universität Berlin, Disaster Research Unit, Berlin, Germany
- 9Justus Liebig University Giessen, ZEU, Giessen, Germany
- 10Universität Potsdam, Institut für Umweltwissenschaften und Geographie, Geoökologie, Potsdam, Germany
- 11German Research Centre for Geosciences (GFZ), Section Hydrology, Potsdam, Germany
ClimXtreme is a research programme funded by the German Federal Ministry of Research, Technology and Space (BMFTR) that comprises 25 individual projects and aims to improve understanding of European extreme weather events and associated uncertainties under anthropogenic climate change. As part of the cross‑project collaboration, a coordinated approach is being established to initiate and sustain targeted stakeholder communication and support it throughout the project period. The aim is to develop information, data and tools targeted to stakeholder needs. To this end, Hazard‑specific Stakeholder Interaction (HaSSi) groups coordinate collaborative work on windstorms, heavy precipitation, and heat/drought. This contribution shows the manifold approaches and perspectives of our research programme to better understand heavy precipitation events in a changing climate.
We use observations and climate model data, including large ensembles from global- to kilometre-scale resolution. This improves the understanding of physical processes and scale dependency. Large ensembles also help to deal with the uncertainty of climate change signals across multiple models. Characteristics of extreme precipitation can be analysed by object-oriented approaches. It allows to assess whether climate change will lead to events that will cover larger areas, last longer or travel larger distances. Newly developed statistical methods help to deal with uncertainties and the issue of short data series when investigating extremes. This includes models of spatio-temporal structures of precipitation extremes as well as further developments of Intensity-Duration-Frequency (IDF) relation, where parameters to estimate the IDF relation are functions of large scale variables. To assess impacts of heavy precipitation events, hydrological models for different catchment sizes are applied.
This allows ClimXtreme to perform research on various precipitation extremes under climate change as well as to assess individual events as case studies from a variety of perspectives as done for example for a precipitation extreme in June 2024 leading to severe flooding in southern Germany [1]. The study clearly shows that quantities of extremity strongly depend on the exact measure and the methodology used. A comprehensive view on these events is crucial especially when communicating results to stakeholders.
[1] http://dx.doi.org/10.17169/refubium-44009
How to cite: Grieger, J., Ruff, F., Forster, C., Fauer, F., Feldmann, H., Fischer-Frenzel, P., Friederichs, P., Haufs, E., Lucio-Eceiza, E. E., Meredith, E. P., Merkes, S. T., Pinto, J. G., Schröter, J., Szemkus, S., Tonn, M., Ulbrich, U., Vlachopoulos, O., Voit, P., Vorogushyn, S., and Zimmermann, T.: ClimXtreme addressing heavy precipitation events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19066, https://doi.org/10.5194/egusphere-egu26-19066, 2026.
