Abstract
An intensification of extreme rainfall events have characterized several areas of peninsular and insular Italy since the early 2000s, suggesting an upward ongoing trend likely driven by climate change. In the present study temporal changes in 1-, 3-, 6-, 12- and 24-h annual maxima rainfall series from more than 200 sites in Sicily region (Italy) are examined. A regional study is performed in order to reduce the uncertainty in change detection related to the limited length of the available records of extreme rainfall series. More specifically, annual maxima series are treated according to a regional flood index - type approach to frequency analysis, by assuming stationarity on a decadal time scale. First a cluster analysis using at-site characteristics is used to determine homogeneous rainfall regions. Then, potential changes in regional L-moment ratios are analyzed using a 10-year moving window. Furthermore, the shapes of regional growth curves, derived by splitting the records into separate decades, are compared. In addition, a jackknife procedure is used to assess uncertainty in the fitted growth curves and to identify significant trends in quantile estimates. Results reveal that L-moment ratios show a general decreasing trend and that growth curves for the last decade (2000–2009) usually do not stand above the others, with the only exception of the ones related to the outer western part of Sicily. On the other hand, rainfall quantile estimates for the same period are the highest values almost all over the region. An explanation can be found in the increase of subregional average medians, largely caused by recent severe local storms.
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This study is part of the research activities carried out within the research contract n. F68C13000060008 between Sicilia e-Ricerca SpA and the University of Messina (European Regional Development Fund – PO FESR Sicilia 2007-2013, Linea di intervento 2.3.1. C).
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Bonaccorso, B., Aronica, G.T. Estimating Temporal Changes in Extreme Rainfall in Sicily Region (Italy). Water Resour Manage 30, 5651–5670 (2016). https://doi.org/10.1007/s11269-016-1442-3
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DOI: https://doi.org/10.1007/s11269-016-1442-3