The aim of this study was to investigate the spatial and temporal distribution of rainfall in Piedmont, a region in north-western Italy, in order to evaluate the high intensity precipitation events that occurred in the 2004−2016 period. A daily precipitation series of 211 ground stations, belonging to 2 different meteorological monitoring networks, were analysed. As at first step, a quality control was performed on the daily precipitation series to evaluate the homogeneity of the series. The annual rainfall events were spatialised, using the ordinary kriging method, considering the whole set of weather stations. Moreover, 5 climatic areas were identified through a cluster analysis method. In order to better understand the extreme rainfall events, the main climatic precipitation indices were calculated, using ClimPACT2 software, and the thresholds by percentile were calculated for each cluster on a daily scale to identify the different precipitation types (weak, medium, heavy, very heavy [R95p]). Non-parametric (Kolmogorov-Smirnov and Wilcoxon) and parametric (Student’s t-test) tests were applied to the annual and seasonal number of events observed for each rainfall class in order to study the statistical relationship between the clusters. The results lead to the conclusion that the investigated area is characterised by an increase in precipitation. Considering the extreme events, this methodology shows that even though the north sector is the wettest, central Piedmont is the area in which the highest number of extreme events was recorded.

Rainfall variability from a dense rain gauge network in north-western Italy

Baronetti A.;
2018

Abstract

The aim of this study was to investigate the spatial and temporal distribution of rainfall in Piedmont, a region in north-western Italy, in order to evaluate the high intensity precipitation events that occurred in the 2004−2016 period. A daily precipitation series of 211 ground stations, belonging to 2 different meteorological monitoring networks, were analysed. As at first step, a quality control was performed on the daily precipitation series to evaluate the homogeneity of the series. The annual rainfall events were spatialised, using the ordinary kriging method, considering the whole set of weather stations. Moreover, 5 climatic areas were identified through a cluster analysis method. In order to better understand the extreme rainfall events, the main climatic precipitation indices were calculated, using ClimPACT2 software, and the thresholds by percentile were calculated for each cluster on a daily scale to identify the different precipitation types (weak, medium, heavy, very heavy [R95p]). Non-parametric (Kolmogorov-Smirnov and Wilcoxon) and parametric (Student’s t-test) tests were applied to the annual and seasonal number of events observed for each rainfall class in order to study the statistical relationship between the clusters. The results lead to the conclusion that the investigated area is characterised by an increase in precipitation. Considering the extreme events, this methodology shows that even though the north sector is the wettest, central Piedmont is the area in which the highest number of extreme events was recorded.
2018
Istituto di Geoscienze e Georisorse - IGG - Sede Pisa
Cluster analysis,
Extreme events,
Kriging,
Piedmont,
Rainfall
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/517194
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