| Summary: | The evaluation of climate change and its environmental and socio-economical effects in the Alpine region can not prescind from considering variability and trends of solid and liquid precipitation over long periods. In the frame of the interregional project STRADA (ADAptation STRategy to climate change) aiming at the long term time series data rescue, daily rainfall and snow precipitation (fresh snow and snow depth) time series recorded in Western Italian Alps manual stations have been recovered and considered for the climatological analysis. The time series are almost continuous except for short gaps which have been filled on monthly and seasonal basis using the Singular Spectrum Analysis technique based on temporal correlation of the time series (Ghil et al., 2001, Kondrashov et al., 2006). The so-obtained time series have been used to determinate and compare the climatological rain and snow indices over different time periods and to investigate on the presence of trends in snow (rain) precipitation amount, number of snowy (wet) days and mean snow depth. The presence of significant oscillatory modes embedded in the seasonal snow (rain) precipitation time series has been investigated using the Singular Spectrum Analysis. The identification of inter-annual and inter-decadal cycles allows to put in relation the snow (rain) precipitation over Western Alps and large scale forcings represented by the North Atlantic Oscillation (NAO) index, the Western Mediterranean Oscillation (WMO) index and the El Nino Southern Oscillation (ENSO) index. The aim is to explore the precipitation variability over different temporal scales in relation to large scale climate modes.
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