Abstract
Abstract. In this paper we produce projections of seasonal precipitation for four Mediterranean areas: Apulia region (Italy), Ebro river basin (Spain), Po valley (Italy) and Antalya province (Turkey). We performed the statistical downscaling using Canonical Correlation Analysis (CCA) in two versions: in one case Principal Component Analysis (PCA) filter is applied only to predictor and in the other to both predictor and predictand. After performing a validation test, CCA after PCA filter on both predictor and predictand has been chosen. Sea level pressure (SLP) is used as predictor. Downscaling has been carried out for the scenarios A2 and B2 on the basis of three GCM's: the CCCma-GCM2, the Csiro-MK2 and HadCM3. Three consecutive 30-year periods have been considered. For Summer precipitation in Apulia region we also use the 500 hPa temperature (T500) as predictor, obtaining comparable results. Results show different climate change signals in the four areas and confirm the need of an analysis that is capable of resolving internal differences within the Mediterranean region. The most robust signal is the reduction of Summer precipitation in the Ebro river basin. Other significative results are the increase of precipitation over Apulia in Summer, the reduction over the Po-valley in Spring and Autumn and the increase over the Antalya province in Summer and Autumn.
Highlights
In the last few years the use of very powerful computers has permitted the development of more and more sophisticated climatic models
In this study we followed the STARDEX (Goodess, 2005) suggestion of applying Canonical Correlation Analysis (CCA) methods locally with the following peculiarities: that the analysis is extended to the whole year, considering independently changes in single seasons (Dec-Jan-Feb, Mar-Apr-May, Jun-Jul-Aug, Sep-OctNov); that we use a set of relatively small targets, which are identified as major agricultural areas; and that we analyze each of them separately with the same procedure
The CCA methods relies on the presence of a linear link between regional precipitation and the large scale predictor field and of the invariance of such link in the projected climate, which is assumed to be a small perturbation of the present condition
Summary
In the last few years the use of very powerful computers has permitted the development of more and more sophisticated climatic models. Even the finest available resolution is sufficient for describing the pressure and temperature fields, but it is not suitable for precipitation (von Storch et al, 1993; von Storch and Zwiers, 1999; Zorita and von Storch, 1999) For this reason, regional downscaling is crucial for describing the precipitation climate of the Mediterranean region, which is characterized by very large space variability. Several authors developed statistical downscaling techniques for climatic predictions in order to provide scenarios for selected small regions or complement the results of dynamical models. In this study we followed the STARDEX (Goodess, 2005) suggestion of applying CCA methods locally with the following peculiarities: that the analysis is extended to the whole year, considering independently changes in single seasons (Dec-Jan-Feb, Mar-Apr-May, Jun-Jul-Aug, Sep-OctNov); that we use a set of relatively small targets, which are identified as major agricultural areas; and that we analyze each of them separately with the same procedure.
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