Recent trends in seasonal and annual precipitation indices in Tuscany (Italy)

• DOI: 10.1007/s00704-013-1053-3
• Publication Date: 2013-12-03T08:37:29Z
• Authors: Giorgio Bartolini; Alessandro Messeri; Daniele Grifoni; Daniele Mannini; Simone Orlandini
• Keywords: 13. Climate action; 15. Life on land; 01 natural sciences; cluster analysis; extreme event; global warming; precipitation (climatology); precipitation intensity; rainfall; seasonal variation; trend analysis; 0105 earth and related environmental sciences

Global warming alters the hydrological cycle since a rise in temperature leads to an increase in the moisture-holding capacity of the atmosphere at a rate of about 7% per °C. This fact could influence the global, but also local characteristics of precipitation, such as total amount and intensity. Therefore, it is important to study changes in rainfall regime in regions with complex orography, like Tuscany, where there are strong spatial gradients in precipitation amounts. The aim of this study is to look for temporal change in precipitations from 1955 to 2007 searching for spatial differences. Daily data of 21 meteorological stations were analyzed to identify trends in seasonal and annual precipitation indices. Cluster analysis applied to principal components was applied to identify homogeneous groups of stations. Annual rainfall amount showed a decrease especially in north-western areas, due to winter and spring seasons. Wet days highlighted a decrease in all Tuscany, due to the same seasons. In northern Tuscany the decrease in rainfall amount was mainly determined by a lower frequency of rainy events which in turn caused a decrease in the occurrence of extreme daily precipitation events (75th, 90th and 95th percentile). In central-southern Tuscany no significant changes were observed except for an increase in precipitation fraction, due to extreme events and in mean daily total amount for wet days. These results are consistent with recent findings for the Mediterranean area and confirms the usefulness of cluster analysis for the analysis of the spatial distribution of precipitations.