A comparison of WRF model simulations with SAR wind data in two case studies of orographic lee waves over the Eastern Mediterranean Sea (Articolo in rivista)

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Label
  • A comparison of WRF model simulations with SAR wind data in two case studies of orographic lee waves over the Eastern Mediterranean Sea (Articolo in rivista) (literal)
Anno
  • 2013-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1016/j.atmosres.2012.08.009 (literal)
Alternative label
  • Mario Marcello Miglietta; Stefano Zecchetto; Francesco De Biasio (2013)
    A comparison of WRF model simulations with SAR wind data in two case studies of orographic lee waves over the Eastern Mediterranean Sea
    in Atmospheric research (Print); Elsevier Science Inc., New York (Stati Uniti d'America)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Mario Marcello Miglietta; Stefano Zecchetto; Francesco De Biasio (literal)
Pagina inizio
  • 127 (literal)
Pagina fine
  • 146 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.sciencedirect.com/science/article/pii/S0169809512002761/pdfft?md5=81502cedc11c2c7a5d6c58654a4713fc&pid=1-s2.0-S0169809512002761-main.pdf (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 120-121 (literal)
Rivista
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ISAC CNR, I-73100 Lecce, Italy, CNR-ISE, Pallanza Verbania; ISAC-CNR, Padova, Italy; ISAC-CNR, Padova, Italy (literal)
Titolo
  • A comparison of WRF model simulations with SAR wind data in two case studies of orographic lee waves over the Eastern Mediterranean Sea (literal)
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 well reproduce the statistical properties of precipitation, the crucial variable for the growth of crops. (literal)
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