Abstract

<p>Subdaily extreme precipitation may trigger fast hydro-geomorphic responses, such as flash floods and debris flows, which cause numerous fatalities and large damage. High-resolution climate models, called convection-permitting models (CPMs), represent convective processes more realistically than coarser resolution models. These processes are crucial for the correct representation of subdaily extremes, and thus CPMs provide higher confidence in the estimate of future extreme precipitation. However, because of their high computational cost, the existing CPM runs are available for relatively short time periods (10–20 years at most) that are too short for deriving precipitation frequency analyses with conventional extreme value methods. Recent approaches are based on many “ordinary” events rather than on just yearly maxima or a few values over a high threshold. They demonstrate the capability to provide reliably estimate of return levels associated with long return periods from short data record, thus they offer the chance to be effectively applied to the analysis of CPM data.</p><p>In the present study, we estimate the changes in subdaily precipitation extremes from COSMO-crCLIM model simulations at 2.2 km resolution, for three 10-year time slices (historical 1996-2005, near-future 2041-2050, and far future 2090-2099 – under the RCP8.5 scenario). We focus on the Eastern Alpine transect, characterized by a complex orography, where significant changes in subdaily annual maxima have been already observed. We apply an ordinary-event statistical method for the estimation of the extreme precipitation with duration ranging from 1 h to 24 h. We analyze the changes between the time periods in both the annual maxima, the quantiles, and the distribution parameters. We find that, although the storms' frequency will generally decrease in the region, the mean annual maxima will increase continuously in the near and far future, especially at shorter durations. Investigation of extreme return levels shows a similar trend, with larger changes in the far future at the shorter duration. Interestingly, the emerging spatial patterns in the changes can be associated to the orographic features of the study area: the stronger increasing changes are located in the high elevation zone, while the flat zone shows weak decrease and weak increase in the near and far future, respectively.</p><p>These analysis and results are useful for improving our knowledge about the projected future changes in extreme precipitation and thus for improving the strategies for risk management and adaptation.</p>

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