Non-stationary frequency analysis of extreme precipitation over Italy using projections from a Convection Permitting Model

Climate change is changing the intensity and frequency of extreme precipitation. Understanding the impact of climate change on extreme precipitation quantiles is fundamental for managing flood risk and taking adaptation measures. Convection-Permitting Models (CPM), run at spatial resolutions for which deep convection is resolved (4 km), have been demonstrated to be more accurate than Regional Climate Models (RCM, ~10 km resolution) in describing the intensity of extremely short-duration events. This study uses the projections of a CPM to evaluate quantiles of precipitation extremes at the national scale (Italy) with a high spatiotemporal resolution. Indeed, VHR-PROIT, a recent downscale product of the CMCC model at a convection-permitting scale of 2. 2 km, with 1h temporal resolution, is used as a dataset. So far, this is the only CPM projection that covers the entire Italy in both emission scenarios (RCP 4. 5 and RCP 8. 5) and for a temporal coverage of 90 years (1981-2070). A non-stationary implementation of the Simplified Metastatistical Extreme Value (SMEV) non-asymptotic approach is used to evaluate continuous changes in precipitation quantiles for different durations (1h, 3h, 6h, 12h and 24h) over the period 1981-2070 (1981-2005 historical + 2006-2070 emission scenarios). We adopt a two-parameter Weibull distribution to model the marginal distribution of the ordinary precipitation events. Three different models are compared: i) a stationary SMEV, with the two parameters constant over the entire time series; ii) a non-stationary model in which the higher-order parameter is kept constant; iii) a fully non-stationary model in which both parameters are allowed to change linearly in time. The results show a clear geographical organization of the projected changes, with both increases and decreases in precipitation quantiles depending on the zone, the emission scenario, the precipitation duration and the return period of interest. The non-asymptotic approach allows us to discuss the results in terms of dynamic and thermodynamic drivers. The research is carried out within the RETURN multi-Risk sciEnce for resilienT comUnities undeR a changiNg climate Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan NRRP, Mission 4, Component 2, Investment 1. 3 D. D. 1243 2/8/2022, PE0000005).