Evaluation and projections of extreme precipitation using a spatial extremes framework

Abstract

Extreme precipitation events are a major natural hazard and cause significant socio-economic damages. Precipitation events are spatially extended and, thus, can cause large water accumulations, which can lead to flooding events. In order to help design flood protection infrastructure, a detailed investigation of the temporal and spatial dependencies of extreme precipitation is essential. Here, we use a statistical spatial extremes framework to systematically study the historical and projected spatial-temporal characteristics of extreme precipitation in Germany. For this purpose, we use data from 10 high-resolution global climate model-regional climate model (GCM-RCM) combinations from the EURO-CORDEX initiative and derive a statistical spatial extremes precipitation model.Our results show that there are large spreads in reproducing the temporalspatial characters of extreme precipitation. Few climate simulations can well present the temporal clustering of observed extreme precipitation in both summer and winter. In reproducing the spatial dependencies of the observations, most GCM-RCM combinations behave well in summer, while in winter most RCMs produce too many spatially localized extreme precipitation events. The derived statistical model, which accounts for both the spatial and temporal variability, performs well in representing the spatial dependency and intensity characteristics in summer. Furthermore, global warming will have a significant impact on the temporal and spatial dependencies of extreme precipitation in Germany. There will be more temporal-dependent and homogeneous extreme precipitation in summer; and more temporalindependent and localized extreme precipitation in winter. The intensity quantified by the 25-year return level of the 10 GCM-RCM combinations is increasing; with relative changes ranging from 5.33% to 53.24% in summer and from −15.38% to 32.33% in winter under RCP8.5. A future projection by

Unveiling the Evolution of Extreme Rainfall Across Space and Time in a Warming Climate

“…Yang & Villarini, 2019). These results are in line with the findings of Yang et al (2023), who utilized EURO-CORDEX initiative and found that extreme events in Germany will become more temporally spread and homogenous in space as temperatures rise in future. The event loading trends are consistent with the findings of (Fadhel et al, 2018), who observed dominance of rear loaded storms in West Yorkshire in North England.…”

Comparison of Future Design Rainfall with Current Design Rainfall: A Case Study in New South Wales, Australia

“…However, other parts of the world have the potential to have different outcomes due to topographic and climatic variability. For example, Yang et al [50] observed increased extreme rainfall in summer and a −15.38% to +32.33% change in extreme rainfall in winter in Germany. This research acknowledges the impacts of global warming on the spatial and temporal variability of extreme rainfall.…”

Impact of aridity rise and arid lands expansion on carbon‐storing capacity, biodiversity loss, and ecosystem services

“…The loss of plant cover and soil degradation can trigger a feedback loop by decreasing rainfall due to changes in cloud properties caused by atmospheric dust (Rosenfeld et al., 2001). These interactions may result in significant differences in different arid world regions linked to different human activities and management strategies and methods (Yang et al., 2023).…”