The frequency of heavy rainfall events varies greatly from year to year. A link between the occurrence of heavy rainfall events in Germany and climate change is therefore possible, but cannot be determined from observations alone [1]. At the global level, the Intergovernmental Panel on Climate Change (IPCC) assumes an increase in heavy precipitation over land areas. This assumes more frequent and more intense precipitation [2].

Trends

In the ClimXtreme consortium, this correlation was investigated by Hundhausen, among others [3]. They found an increase in intensity of 6 to 8.5% per degree of global warming for Germany, with rare and short-lived events showing the strongest trends. 

The subproject on Extreme Precipitation under Climate Change Conditions (B2.4 XPreCCC) found out, that the intensity of recently-observed precipitation extremes has been amplified by climate change. Future changes in the characteristics of convective precipitation extremes differ depending on the circulation pattern.

Mechanisms and factors affecting extreme precipitation in the context of climate change

In the aftermath of an extreme weather event, we often ask what role climate change played. The answer can depend heavily on how the event is defined. For example, many recent studies of heatwaves or heavy rainfall events have considered not only temperature or rainfall accumulation, but also the weather conditions that enabled the observed extreme values.

The subproject “Most Extreme Precipitation” (A2 MExRain) analyzed future changes of simulated daily 100-year precipitation events over central Europe. The extreme precipitation intensifies significantly over all catchments and for all climate models, but the amplitude strongly varies among the models due to differences in regional moist processes. This extends the robustness of similar previous findings of single case studies and statistical approximations of these very extreme events.

CARLOFFF (C2, "Convective Atmospheres: Linking Radar-based Event Descriptors and Losses From Flash Floods") use a novel downscaling approach to investigate historical and future changes in heavy rainfall events in Germany [4]. They find that large-scale factors promoting convective heavy precipitation (short, intense and locally confined) are increasing, as are factors that inhibit it. This leads to a high degree of uncertainty in the assessment, even though their analysis confirms an increase in extreme precipitation in Germany. 

Statistical Approaches

The subproject “Compact Description and Statistical Modeling for Non-Stationary Spatial Weather Extremes” (B3.1 CoDEx) developed and tested a statistical model for spatial heavy rainfall, taking relevant covariates (such as the elevation profile) into account, in order to generate synthetic precipitation fields. It also presents a new, wavelet-based approach for analysing the spatio-temporal characteristics of precipitation events. The results based in RadKlim observations and NUKLEUS climate simulation show that heavy precipitation events generally become more intense under climate change, but without a clear preference for specific event sizes or durations.

In IDF-AF (B2.5, "Precipitation Extremes - Linking Consistent Intensity-Duration-Frequency Relation to Large Scale Atmospheric Flow"), extreme precipitation was investigated for multiple time scales from minutes to days in one consistent extreme-value-statistics model and probabilites for exceeding annual values were determined. Integrating large-scale climate variables into this model revealed that the probability of extreme precipitation in Germany is increasing over time across all seasons, with rising temperatures and humidity consistently driving stronger events, while the effects of the North Atlantic Oscillation and atmospheric blocking remain season-dependent [5]. These historical covariate relationships are used to project future Intensity-Duration-Frequency (IDF) curves under climate change scenarios, setting the stage for advanced spatial interpolation at ungauged sites. Different gridded data sets can be combined to improve spatial coverage of IDF relationships [6].

Hail 

For hail, another form of precipitation besides rain, the very small spatial scales and the scarcity of available data make long-term analyses and a clear link with climate change difficult (C12 HailClim). Based on 20 years of radar-derived hail events over Germany, this relatively short time period - in the context of climate change - shows an increase in hail activity in southern Germany, while declining trends are observed in large parts of the rest of the country.  Extending the analysis with a self-developed XGBoost model driven by climate-model scenarios indicates that, despite some inter-model differences, most projections consistently point to an increase in hail occurrence in southern Germany under a warmer climate while changes across the rest of Germany are weaker and less robust (for further information see [7]). 

Severe convective storm (SCS) hazards are becoming an increasing threat to society and property in a warming world. Using a statistical framework and climate models, CHECC-II (C11, "Convective Hazard Evolution under Climate Change") developed future projections for lightning, hail > 2 cm, hail > 5 cm, and tornadoes > (E/I)F1 for different warming scenarios (+1.5°, +2.0°C, +3.0°C) according to the SSP58.5 scenario. In addition, the models were used to develop an event set spanning 7500 years of stochastically generated hail and tornado swaths across Germany, allowing the project to estimate the risk associated with extreme convective events beyond what has been observed historically.

Attribution

The heavy precipitation that led to flooding in Western Europe in July 2021, particularly in the Ahr region, was investigated using probabilistic attribution methodology. AXE_G during ClimXtreme-Phase I attribute an increase in the intensity of maximum daily precipitation of 3 to 19% and an increase in probability by a factor of 1.2 to 9 for the affected region to climate change [8].

In the second phase of ClimXtreme, two rapid probabilistic attribution studies have been published about extreme precipitation events: During ClimXtreme phase II, AXE_G_II (B1.2, "Application and extension of the pre-operational attribution system for weather and climate extremes") investigated the long precipitation period in December 2023 which led to flooding in Northwest Germany showing an increasing but not significant trend [9]. Researchers also analyzed the extreme precipitation in Southern Germany in May and June 2024 which also led to severe flooding. Here, the trend also showed an increase due to anthropogenic climate change but it was not significant either [10].

Impacts

CARLOFFF (C02, "Convective Atmospheres: Linking Radar-based Event Descriptors and Losses From Flash Floods") propose a new approach for more robustly determining peak discharges of flash floods with long return periods [11]. To this end, they use historical heavy precipitation events that occurred in the vicinity of the catchment area under investigation. In this way, they extend conventional extreme value statistics for isolated catchments.

CROP4Europe (C03, "Impacts of compound weather extremes on crops in Germany") developed a fast AI-based crop-yield modelling tool that can produce yield development for grain maize and spring barley across the wider European domain using only daily min and max temperature and precipitation data, making accurate large-scale seasonal and climate-risk assessments extremely faster than the ECroPS crop growth model which was surrogated. The tool reproduces key crop-growth patterns well enough to support operational screening of yield anomalies, including the identification of regions with potential yield losses linked to heat and moisture stress. CROP4Europe also connects generated crop-yields and yield impacts to broader climate drivers intermediated by extreme events indices related to heat and moisture, helping stakeholders understand not only where yield risks occur, but also which climate conditions may be driving them, supporting seasonal reporting, risk monitoring, and future impact assessments.

Conclusion

The results of the research project ClimXtreme show that, as a result of climate change, heavy rainfall events in Germany and Europe are tending to become more intense and frequent, even though annual and regional variability remains high and any conclusions regarding precipitation trends are subject to a high degree of uncertainty. Several studies within the ClimXtreme consortium confirm a link between warming, higher humidity and increasing intensity of heavy rainfall. 

 At the same time, it is clear that the impacts depend on large-scale weather patterns: depending on circulation patterns, future changes may vary considerably from region to region. For Germany and Central Europe, models suggest an increase in some regions and a decrease in others in extreme precipitation, including convective heavy rain events and possible associated flash floods.

The studies presented thus show that the analysis of individual events depends heavily on the definition chosen and the weather conditions taken into account. Probabilistic attribution also shows that individual events, such as the 2021 floods in western Germany, have already been exacerbated by climate change. Subsequent events in Germany also point in this direction, although not always to a statistically significant extent. 

Improved statistical methods, IDF curves and spatially robust models are therefore important for risk assessment. Overall, the findings emphasise that heavy rainfall and its consequences for water management, civil protection and agriculture should be given greater consideration in future adaptation strategies.

For specific questions, please feel free to contact the research groups using the contact information provided. For general questions, please send an email to info@climxtreme.de.