Spatial Modeling and Future Projection of Extreme Precipitation Extents

Extreme precipitation events with large spatial extents may have more severe impacts than localized events as they can lead to widespread flooding. It is debated how climate change may affect the spatial extent of precipitation extremes, whose investigation often directly relies on simulations of precipitation from climate models. Here, we use a different strategy to investigate how future changes in spatial extents of precipitation extremes differ across climate zones and seasons in two river basins (Danube and Mississippi). We rely on observed precipitation extremes while exploiting a physics-based average-temperature covariate, enabling us to project future precipitation extents based on projected temperatures. We include the covariate into newly developed time-varying <em>r</em>-Pareto processes using suitably chosen spatial risk functionals <em>r</em>. This model captures temporal non-stationarity in the spatial dependence structure of precipitation extremes by linking it to the temperature covariate, derived from reanalysis data (ERA5-Land) for model calibration and from bias-corrected climate simulations (CMIP6) for projections. Our results show an increasing trend in the margins, with both significantly positive or negative trend coefficients depending on season and river (sub-)basin. During major rainy seasons, the significant trends indicate that future spatial extreme events will become relatively more intense and localized in several sub-basins.