Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area

Claudia Pizzigalli, L. Palatella, Matteo Zampieri, P. Lionello, M.M. Miglietta, P. Paradisi

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

In this paper we present and discuss a comparison between statistical and regional climate modeling techniques for downscaling GCM prediction . The comparison is carried out over the “Capitanata” region, an area of agricultural interest in south-eastern Italy, for current (1961-1990) and future (2071–2100) climate. The statistical model is based on Canonical Correlation Analysis (CCA), associated with a data pre-filtering obtained by a Principal Component Analysis (PCA), whereas the Regional Climate Model REGCM3 was used for dynamical downscaling. Downscaling techniques were applied to estimate rainfall, maximum and minimum temperatures and average number of consecutive wet and dry days. Both methods have comparable skills in estimating stations data. They show good results for spring, the most important season for agriculture. Both statistical and dynamical models reproduce the statistical properties of precipitation well, the crucial variable for the growth of crops.
Original languageEnglish (US)
Pages (from-to)2
JournalItalian Journal of Agronomy
Volume7
Issue number1
DOIs
StatePublished - Mar 28 2012

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