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

Handle URI:
http://hdl.handle.net/10754/550217
Title:
Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area
Authors:
Pizzigalli, Claudia; Palatella, L.; Zampieri, M.; Lionello, P.; Miglietta, M.M.; Paradisi, P.
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.
KAUST Department:
KAUST Supercomputing Laboratory (KSL)
Citation:
Dynamical and statistical downscaling of precipitation and temperature in a Mediterranean area 2012, 7 (1):2 Italian Journal of Agronomy
Journal:
Italian Journal of Agronomy
Issue Date:
28-Mar-2012
DOI:
10.4081/ija.2012.e2
Type:
Article
ISSN:
2039-6805; 1125-4718
Additional Links:
http://agronomy.it/index.php/agro/article/view/ija.2012.e2
Appears in Collections:
Articles; KAUST Supercomputing Laboratory (KSL)

Full metadata record

DC FieldValue Language
dc.contributor.authorPizzigalli, Claudiaen
dc.contributor.authorPalatella, L.en
dc.contributor.authorZampieri, M.en
dc.contributor.authorLionello, P.en
dc.contributor.authorMiglietta, M.M.en
dc.contributor.authorParadisi, P.en
dc.date.accessioned2015-04-16T13:58:54Zen
dc.date.available2015-04-16T13:58:54Zen
dc.date.issued2012-03-28en
dc.identifier.citationDynamical and statistical downscaling of precipitation and temperature in a Mediterranean area 2012, 7 (1):2 Italian Journal of Agronomyen
dc.identifier.issn2039-6805en
dc.identifier.issn1125-4718en
dc.identifier.doi10.4081/ija.2012.e2en
dc.identifier.urihttp://hdl.handle.net/10754/550217en
dc.description.abstractIn 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.en
dc.relation.urlhttp://agronomy.it/index.php/agro/article/view/ija.2012.e2en
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution Noncommercial License (by-nc 3.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.en
dc.subjectdownscaling techniquesen
dc.subjectCapitanata planeen
dc.subjectclimate changeen
dc.titleDynamical and statistical downscaling of precipitation and temperature in a Mediterranean areaen
dc.typeArticleen
dc.contributor.departmentKAUST Supercomputing Laboratory (KSL)en
dc.identifier.journalItalian Journal of Agronomyen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionDipartimento di Scienze dei Materiali, Università del Salento, Lecce, Italyen
dc.contributor.institutionIstituto di Scienze dell'Atmosfera e del Clima (ISAC-CNR), Lecce, Italyen
dc.contributor.institutionCNISM UdR Lecce, Dipartimento di Ingegneria dell'Innovazione, Università del Salento, Lecce, Italyen
dc.contributor.institutionCentro Euro-Mediterraneo per i Cambiamenti Climatici, Lecce, Italyen
dc.contributor.institutionIstituto per lo Studio degli Ecosistemi (ISE-CNR), Verbania Pallanza, Italyen
dc.contributor.institutionIstituto di Scienza e Tecnologie dell'Informazione A. Faedo (ISTI-CNR), Pisa, Italyen
kaust.authorZampieri, Matteoen
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