The July 2021 flood in central Europe was one of the five costliest disasters in Europe in the last half century, with an estimated total damage of EUR 32 billion. The aim of this study is to analyze and assess the flood within an interdisciplinary approach along its entire process chain: the synoptic setting of the atmospheric pressure fields, the processes causing the high rainfall totals, the extraordinary streamflows and water levels in the affected catchments, the hydro-morphological effects, and the impacts on infrastructure and society. In addition, we address the question of what measures are possible to generate added value to early response management in the immediate aftermath of a disaster. The superposition of several factors resulted in widespread extreme precipitation totals and water levels well beyond a 100-year event: slow propagation of the low pressure system Bernd, convection embedded in a mesoscale precipitation field, unusually moist air masses associated with a significant positive anomaly in sea surface temperature over the Baltic Sea, wet soils, and steep terrain in the affected catchments. Various hydro-morphodynamic processes as well as changes in valley morphology observed during the event exacerbated the impact of the flood. Relevant effects included, among many others, the occurrence of extreme landscape erosion, rapidly evolving erosion and scour processes in the channel network and urban space, recruitment of debris from the natural and urban landscape, and deposition and clogging of bottlenecks in the channel network with eventual collapse. The estimation of inundation areas as well as the derived damage assessments were carried out during or directly after the flood and show the potential of near-real-time forensic disaster analyses for crisis management, emergency personnel on-site, and the provision of relief supplies. This study is part one of a two-paper series. The second part (Ludwig et al., 2022) puts the July 2021 flood into a historical context and into the context of climate change.

Heavy precipitation over western Germany and neighboring countries in July 2021 led to widespread floods, with the Ahr and Erft river catchments being particularly affected. Following the event characterization and process analysis in Part 1, here we put the 2021 event in the historical context regarding precipitation and discharge records and in terms of the temporal transformation of the valley morphology. Furthermore, we evaluated the role of ongoing and future climate change on the modification of rainfall totals and the associated flood hazard, as well as implications for flood management. The event was among the five heaviest precipitation events of the past 70 years in Germany. However, consideration of the large LAERTES-EU regional climate model (RCM) ensemble revealed a substantial underestimation of both return levels and periods based on extreme value statistics using only observations. An analysis of homogeneous hydrological data of the last 70 years demonstrated that the event discharges exceeded by far the statistical 100-year return levels. Nevertheless, the flood peaks at the Ahr river were comparable to the reconstructed major historical events of 1804 and 1910, which were not included in the flood risk assessment so far. A comparison between the 2021 and past events showed differences in terms of the observed hydro-morphodynamic processes which enhanced the flood risk due to changes in the landscape organization and occupation. The role of climate change and how the 2021 event would unfold under warmer or colder conditions (within a −2 to +3 K range) was considered based on both a pseudo global warming (PGW) model experiments and the analysis of an RCM ensemble. The PGW experiments showed that the spatial mean precipitation scales with the theoretical Clausius–Clapeyron (CC) relation, predicting a 7 % to 9 % increase per degree of warming. Using the PGW rainfall simulations as input to a hydrological model of the Ahr river basin revealed a strong and non-linear effect on flood peaks: for the +2 K scenario, the 18 % increase in areal rainfall led to a 39 % increase of the flood peak at gauge Altenahr. The analysis of the high-resolution convection-permitting KIT-KLIWA RCM ensemble confirmed the CC scaling for moderate spatial mean precipitation but showed a super CC scaling of up to 10 % for higher intensities. Moreover, the spatial extent of such precipitation events is also expected to increase.

During a 15-day episode from 26 May to 9 June 2016, Germany was affected by an exceptionally large number of severe thunderstorms. Heavy rainfall, related flash floods and creek flooding, hail, and tornadoes caused substantial losses running into billions of euros (EUR). This paper analyzes the key features of the severe thunderstorm episode using extreme value statistics, an aggregated precipitation severity index, and two different objective weather-type classification schemes. It is shown that the thunderstorm episode was caused by the interaction of high moisture content, low thermal stability, weak wind speed, and large-scale lifting by surface lows, persisting over almost 2 weeks due to atmospheric blocking.For the long-term assessment of the recent thunderstorm episode, we draw comparisons to a 55-year period (1960–2014) regarding clusters of convective days with variable length (2–15 days) based on precipitation severity, convection-favoring weather patterns, and compound events with low stability and weak flow. It is found that clusters with more than 8 consecutive convective days are very rare. For example, a 10-day cluster with convective weather patterns prevailing during the recent thunderstorm episode has a probability of less than 1 %.

Widespread flooding events are among the major natural hazards in central Europe. Such events are usually related to intensive, long-lasting precipitation over larger areas. Despite some prominent floods during the last three decades (e.g., 1997, 1999, 2002, and 2013), extreme floods are rare and associated with estimated long return periods of more than 100 years. To assess the associated risks of such extreme events, reliable statistics of precipitation and discharge are required. Comprehensive observations, however, are mainly available for the last 50–60 years or less. This shortcoming can be reduced using stochastic data sets. One possibility towards this aim is to consider climate model data or extended reanalyses. This study presents and discusses a validation of different century-long data sets, decadal hindcasts, and also predictions for the upcoming decade combined to a new large ensemble. Global reanalyses for the 20th century with a horizontal resolution of more than 100 km have been dynamically downscaled with a regional climate model (Consortium for Small-scale Modeling – CLimate Mode; COSMO-CLM) towards a higher resolution of 25 km. The new data sets are first filtered using a dry-day adjustment. Evaluation focuses on intensive widespread precipitation events and related temporal variabilities and trends. The presented ensemble data are within the range of observations for both statistical distributions and time series. The temporal evolution during the past 60 years is captured. The results reveal some long-term variability with phases of increased and decreased precipitation rates. The overall trend varies between the investigation areas but is mostly significant. The predictions for the upcoming decade show ongoing tendencies with increased areal precipitation. The presented regional climate model (RCM) ensemble not only allows for more robust statistics in general, it is also suitable for a better estimation of extreme values.

Enduring and extensive heavy precipitation events associated with widespread river floods are among the main natural hazards affecting central Europe. Since such events are characterized by long return periods, it is difficult to adequately quantify their frequency and intensity solely based on the available observations of precipitation. Furthermore, long-term observations are rare, not homogeneous in space and time, and thus not suitable to running hydrological models (HMs) with respect to extremes. To overcome this issue, we make use of the recently introduced LAERTES-EU (LArge Ensemble of Regional climaTe modEl Simulations for EUrope) data set, which is an ensemble of regional climate model simulations providing over 12 000 simulated years. LAERTES-EU is adapted for use in an HM to calculate discharges for large river basins by applying quantile mapping with a parameterized gamma distribution to correct the mainly positive bias in model precipitation. The Rhine basin serves as a pilot area for calibration and validation. The results show clear improvements in the representation of both precipitation (e.g., annual cycle and intensity distributions) and simulated discharges by the HM after the bias correction. Furthermore, the large size of LAERTES-EU also improves the statistical representativeness for high return values above 100 years of discharges. We conclude that the bias-corrected LAERTES-EU data set is generally suitable for hydrological applications and posterior risk analyses. The results of this pilot study will soon be applied to several large river basins in central Europe.