Spatial variability of precipitation extremes over Italy using a fine-resolution gridded product
Benedetta Moccia, Simon Michael Papalexiou, Fabio Russo, Francesco Napolitano
Abstract
Italy. Knowing magnitude and frequency of extreme precipitation is necessary to reduce their impact on vulnerable areas. Here we investigate the performance of the Generalized Extreme Value (GEV) distribution, using a fine-resolution satellite-based gridded product, to analyze 13,247 daily rainfall annual maxima samples. A non-extreme value distribution with a power-type behavior, that is, the Burr Type XII (BrXII), is also evaluated and used to test the reliability of the GEV in describing extreme rainfall. (1) in 44.9 % of the analyzed samples the GEV predicts an upper rainfall limit; we deem this is an artifact due to sample variations; (2) we suggest the GEV+ distribution, that is, the GEV with shape parameters restricted only to positive values as a more consistent model complying with the nature of extreme precipitation; (3) GEV, GEV+, and BrXII performed equally well in describing the observed annual precipitation, yet all distributions underestimate the observed sample maximum; (4) the BrXII, for large return periods, predicts larger rainfall amounts compared to GEV indicating that GEV estimates could underestimate the risk of extremes; and (5) the correlation between the predicted rainfall and the elevation is investigated. Based on the results of this study, we suggest instead of using the classical GEV to use the GEV+ and non-extreme value distributions such as the BrXII to describe precipitation extremes.