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

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    Description:
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    Type
    Article
    Authors
    Pizzigalli, Claudia
    Palatella, L.
    Zampieri, Matteo
    Lionello, P.
    Miglietta, M.M.
    Paradisi, P.
    KAUST Department
    KAUST Supercomputing Laboratory (KSL)
    Physical Science and Engineering (PSE) Division
    Date
    2012-03-28
    Permanent link to this record
    http://hdl.handle.net/10754/550217
    
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    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.
    Citation
    Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area 2012, 7 (1):2 Italian Journal of Agronomy
    Publisher
    PAGEPress Publications
    Journal
    Italian Journal of Agronomy
    DOI
    10.4081/ija.2012.e2
    Additional Links
    http://agronomy.it/index.php/agro/article/view/ija.2012.e2
    ae974a485f413a2113503eed53cd6c53
    10.4081/ija.2012.e2
    Scopus Count
    Collections
    Articles; KAUST Supercomputing Laboratory (KSL); Physical Science and Engineering (PSE) Division

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