This study analyses 371 yearly series of 1-day precipitation maxima extracted from a data set of high-quality homogenized rain gauge records covering an area of about 25,000 km2 in the western part of northern-central Italy that includes eastern Liguria and northern Tuscany and is very prone to severe floods and shallow landslides. Return levels of 1-day extreme precipitation (corresponding to 10-, 50-, and 100-year return periods as predicted by a generalized extreme value distribution (GEV)) are estimated both for station sites and for the nodes of a high-resolution grid (30 arcsec). GEV parameters are estimated by regional frequency analysis using the station-year approach. Grid-point index floods are estimated from yearly cumulative precipitation normals exploiting the very high correlation existing at local scale between station index flood and the corresponding yearly precipitation normals. Results clearly show the high vulnerability of this region to extreme precipitation events and highlight the different role played by total annual precipitation normals and by both scale and shape parameters in regulating the longer period return levels. The results presented in this paper allow better estimating the climatology of extreme events in the study area, contributing to a more effective hazard assessment at different spatial and temporal scales.
High-resolution analysis of 1-day extreme precipitation in a wet area centered over eastern Liguria, Italy / Brunetti, M.; Bertolini, A.; Soldati, M.; Maugeri, M.. - In: THEORETICAL AND APPLIED CLIMATOLOGY. - ISSN 1434-4483. - 135:1-2(2019), pp. 341-353. [10.1007/s00704-018-2380-1]
High-resolution analysis of 1-day extreme precipitation in a wet area centered over eastern Liguria, Italy
Soldati M.;
2019
Abstract
This study analyses 371 yearly series of 1-day precipitation maxima extracted from a data set of high-quality homogenized rain gauge records covering an area of about 25,000 km2 in the western part of northern-central Italy that includes eastern Liguria and northern Tuscany and is very prone to severe floods and shallow landslides. Return levels of 1-day extreme precipitation (corresponding to 10-, 50-, and 100-year return periods as predicted by a generalized extreme value distribution (GEV)) are estimated both for station sites and for the nodes of a high-resolution grid (30 arcsec). GEV parameters are estimated by regional frequency analysis using the station-year approach. Grid-point index floods are estimated from yearly cumulative precipitation normals exploiting the very high correlation existing at local scale between station index flood and the corresponding yearly precipitation normals. Results clearly show the high vulnerability of this region to extreme precipitation events and highlight the different role played by total annual precipitation normals and by both scale and shape parameters in regulating the longer period return levels. The results presented in this paper allow better estimating the climatology of extreme events in the study area, contributing to a more effective hazard assessment at different spatial and temporal scales.File | Dimensione | Formato | |
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Brunetti et al_2018_in_press.pdf
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THEORETICAL_AND_APPLIED_CLIMATOLOGY_2019_135_341-353.pdf
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