ABSTRACT:In the region of the European Alps, national and regional meteorological services operate rain-gauge networks, which together, constitute one of the densest in situ observation systems in a large-scale high-mountain region. Data from these networks are consistently analyzed, in this study, to develop a pan-Alpine grid dataset and to describe the region's mesoscale precipitation climate, including the occurrence of heavy precipitation and long dry periods. The analyses are based on a collation of high-resolution rain-gauge data from seven Alpine countries, with 5500 measurements per day on average, spanning the period 1971-2008. The dataset is an update of an earlier version with improved data density and more thorough quality control. The grid dataset has a grid spacing of 5 km, daily time resolution, and was constructed with a distance-angular weighting scheme that integrates climatological precipitation-topography relationships. Scales effectively resolved in the dataset are coarser than the grid spacing and vary in time and space, depending on station density. We quantify the uncertainty of the dataset by cross-validation and in relation to topographic complexity, data density and season. Results indicate that grid point estimates are systematically underestimated (overestimated) at large (small) precipitation intensities, when they are interpreted as point estimates. Our climatological analyses highlight interesting variations in indicators of daily precipitation that deviate from the pattern and course of mean precipitation and illustrate the complex role of topography. The daily Alpine precipitation grid dataset was developed as part of the EU funded EURO4M project and is freely available for scientific use.

The winter precipitation variability over the Alpine region is described by a standard principal component analysis (PCA), performed starting from monthly precipitation anomalies for the 1971-1992 winters. With respect to the temporal variability, significant trends are found over some areas within the domain. In particular, the Alpine orography signature enables identification of 2 major sectors, located north and south of the chain, which exhibit an increase and a more significant decrease, respectively, in precipitation during the period examined. The relationship between surface and upper air data is then investigated by means of covariance maps of the precipitation principal components (PCs) with the 500 hPa geopotential height monthly anomalies and also by studying the correlation between the same PCs and some indices of large-scale circulation patterns, such as the North Atlantic Oscillation (NAO) and the Northern Hemisphere blocking frequency. The 2 leading precipitation patterns are characterized by significant relationships with large-scale anomalies: the NAO explains most of the Alpine precipitation variance, and a strong link is also found with Euro-Atlantic blocking. No significant connection is found between winter Alpine precipitation variability and the El Niño signature as deduced by sea-surface temperature anomalies.

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Daily precipitation data from a dense observational network covering Emilia-Romagna, a region of Northern Italy, are described and analysed. Data are available for all stations for the period 1951-2004 and for a selected group of stations located over the Reno hydrological basin for the period 1925-2004. Indices describing seasonal values of mean precipitation and frequency of extreme events are computed starting from daily data and are used to describe the temporal and spatial variability of precipitation over the region.Data referring to the period 1951-2004 are used to describe trends of relevant precipitation indices over the same period in all seasons, and the relation between the variability of these indices and major Euro-Atlantic large-scale circulation indices over winter.Data referring to the period 1925-2004 are used to analyse the decadal and long-term variability over the Reno Basin and its relation with the winter daily discharge of the river. This analysis allows identifying the presence of a clear decadal periodicity in river discharge, strongly related with the decadal variability in both total precipitation and frequency of intense events.

Abstract:This chapter presents an overview of the occurrences and effects of droughts through a study of the Standard Precipitation Index (SPI) in the Emilia-Romagna region, which is located in the northern-central part of the Italian peninsula. The link between this index and large-scale atmospheric circulation was investigated and the SPI index was also used to predict drought. The study describes the development of a method of forecasting SPI index based on an earlier Interregional project (SEDEMED), involving a statistical downscaling scheme model using as input the large-scale seasonal forecasts obtained from Atmospheric Global Circulation Models. The downscaling scheme, which has already been used with relatively good results to predict surface parameters of temperature and precipitation, is applied to the SPI index, providing a statistical regionalization of this indicator Keywords: Drought, NAO, EB, SPI , Z500 METEOROLOGICAL DROUGHTS: INTRODUCTIONDrought is a natural phenomenon that occurs when precipitation is significantly lower than normal. Low precipitation can lead to severe hydrological deficit and cause serious problems for agriculture, the hydroelectric sector and industry, as well as deficit in the drinking water supply, with heavy consequences for the local population. In the long run, if a drought lasts many months or even years and involves a large area, it can permanently damage the environment and cause significant economic losses. In the Italian climate, droughts are not only possible, but also relatively frequent. Europe and the entire Mediterranean area have suffered major droughts in recent years. In the '70s and '80s north-western Europe was often subject to drought conditions (in 1972 and 1976, and from 1988 to 1992) and in the last few years drought conditions have also been experienced in large areas of central and southern Europe and in countries like France, Italy, Portugal and Spain. The more and more frequent occurrence of sequences of heavy precipitation and flooding followed by periods characterized by low precipitation and drought has fueled fears that hydrological cycles could be changing, as a result of global warming. In the current literature, there are different definitions of drought depending on the duration of the phenomenon, on its spatial extension and on its effects or impacts on human activities. Different approaches and different choices of indicators may be used to describe the problem in relation to the different definitions. In this chapter, attention is focused only on meteorological and agricultural droughts and on the indicators correspondingly used to describe them."Meteorological drought" is defined as the lack of precipitation (expressed relative to a climatic value) for a sufficiently long period (a number of consecutive days of dry weather) to cause severe hydrologic imbalance in the area affected. Defined in this way "meteorological drought" depends on the area under examination and, more specifically, on what are the "normal" climatic conditions of ...

Optimum statistical downscaling models for three winter precipitation indices in the Emilia-Romagna region, especially related to extreme events, were investigated. For this purpose, the indices referring to the number of events exceeding the long-term 90 percentile of rainy days, simple daily intensity and maximum number of consecutive dry days were calculated as spatial averages over homogeneous sub-regions identified by the cluster analysis. The statistical downscaling model (SDM) based on the canonical correlation analysis (CCA) was used as downscaling procedure. The CCA was also used to understand the large-/regional-scale mechanisms controlling precipitation variability across the analysed area, especially with respect to extreme events. The dynamic (mean sea-level pressure-SLP) and thermodynamic (potential instability-δQ and specific humidity-SH) variables were considered as predictors (either individually or together). The large-scale SLP can be considered a good predictor for all sub-regions in the dry index case and for two sub-regions in the case of the other two indices, showing the importance of dynamical forcing in these cases. Potential instability is the best predictor for the highest mountain region in the case of heavy rainfall frequency, when it can be considered as a single predictor. The combination of dynamic and thermodynamic predictors improves the SDM's skill for all sub-regions in the dry index case and for some sub-regions in the simple daily intensity index case.The selected SDMs are stable in time only in terms of correlation coefficient for all sub-regions for which they are skilful and only for some sub-regions in terms of explained variance. The reasons are linked to the changes in the atmospheric circulation patterns influencing the local rainfall variability in Emilia-Romagna as well as the differences in temporal variability over some sub-regions and sub-intervals. It was concluded that the average skill over an ensemble of the most skilful and stable SDMs for each region/sub-interval gives more consistent results.

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