Exploring the climate change influence on short-duration convective precipitation extremes in the southeastern Alpine forelands

Short-duration extreme convective precipitation events (SDECPEs) are increasingly altered by climate change. Considering their severe risk, and high impact on our everyday lives, a profound understanding of such extreme precipitation is crucial. For their investigation we can leverage a newly developed class of Threshold-Exceedance-Amount (TEA) metrics, which enable the detection and tracking of weather and climate extremes. The compound indices based on these TEA metrics have proven to be a useful tool to investigate changes of different characteristics of temperature and precipitation extremes, both in isolation and in combination.

It is challenging, however, to perform such an analysis for SDECPEs, since their short durations of only about one to three hours and their highly localized character make them very weakly detectable in reanalysis datasets like ERA5-Land, with a spatial resolution of the order of 10 km (0.1° x 0.1° grid). High resolution datasets like from the WegenerNet climate station network in southeast Austria (100 m x 100 m, 5 min) and GeoSphere Austria’s INCA dataset (1 km x 1 km, 15 min) are far better suited for this purpose but offer only data over the most recent two decades. To our knowledge, there is currently no dataset that on its own fulfills all three key requirements (high spatial resolution, high temporal resolution, long data record) for the analysis of SDECPEs over time.

To get observations-based insight into the influence of climate change on SDECPEs in the southeast Alpine forelands, in particular their possible amplification, we aimed to bypass and overcome the weaknesses of any single dataset by a study consisting of two parts: (1) the high-resolution exploration of SDECPEs in the well-observed most recent two decades. Here we investigate the relationship between maximum hourly precipitation and average hourly precipitation on SDECPE-days and complement our findings with information about the temperature increase in the study region. (2) We perform a longer-term assessment of the development of SDECPEs based on reanalysis data. Using the knowledge gained from (1), we are able to model maximum hourly precipitation data and compare the changes in event characteristics to the ones of daily precipitation sums.

We show that our approach does reveal some evidence for a climate change induced amplification of SDECPEs in the southeast Alpine forelands. At the same time, the results vary strongly within the study region, mainly due to high natural variability.