Spatial modeling and future projection of extreme precipitation extents

TL;DR

This study models how the spatial extent of extreme precipitation events may change under climate warming, using observed data and temperature-dependent statistical models to project future trends across different climate zones and seasons.

Contribution

It introduces a novel physics-based, temperature-dependent spatial dependence model for precipitation extremes, enabling future projections based on observed data and climate simulations.

Findings

Decreasing spatial extent of precipitation extremes in warming climates during rain seasons.

Negative correlation between temperature and spatial extent of precipitation extremes.

Projected increase in local precipitation intensity with decreasing spatial extent.

Abstract

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 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 mean temperature covariate, which enables us to project future precipitation extents. We include the covariate into newly developed time-varying $r$-Pareto processes using a suitably chosen spatial aggregation functional $r$. This model captures temporal non-stationarity in the spatial dependence structure of precipitation extremes by linking it to the temperature covariate, which we derive from observations for model calibration and from debiased climate simulations (CMIP6) for projections. For both river basins, our results show negative correlation between the spatial extent and the temperature covariate for most of the rain season and an increasing trend in the margins, indicating a decrease in spatial precipitation extent in a warming climate during rain seasons as precipitation intensity increases locally.