1983
DOI: 10.1175/1520-0450(1983)022<1738:poniad>2.0.co;2
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Precipitation over Northern Italy: A Description by Means of Principal component Analysis

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Cited by 31 publications
(24 citation statements)
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“…Particular problems of this nature are highlighted for the Brenta catchment where all the RCMs have poor skill in reproducing the annual distribution of mean precipitation. Northern Italy has a highly variable precipitation regime due to the complex topography provided by the Alps to the north, the Apennines to the south and the Po Valley in the centre of this region (Molteni et al, 1983). Dividing the Brenta study region into northern and southern sub-regions indicates that the northern Alpine region has higher mean precipitation, which is at a maximum during summer (not shown).…”
Section: Reproducing Observed Meansmentioning
confidence: 99%
“…Particular problems of this nature are highlighted for the Brenta catchment where all the RCMs have poor skill in reproducing the annual distribution of mean precipitation. Northern Italy has a highly variable precipitation regime due to the complex topography provided by the Alps to the north, the Apennines to the south and the Po Valley in the centre of this region (Molteni et al, 1983). Dividing the Brenta study region into northern and southern sub-regions indicates that the northern Alpine region has higher mean precipitation, which is at a maximum during summer (not shown).…”
Section: Reproducing Observed Meansmentioning
confidence: 99%
“…With regard to the Mediterranean region, eigenvector studies were often applied to categorise the area into homogeneous fields in terms of a specific climatic variable (Goossens, 1985;Maheras, 1985;Serra et al, 1999). In other cases, they enabled the investigators to specify temperature and/or rainfall patterns (Cacciamani et al, 1994;Fernandez Mills, 1995;Romero et al, 1999), to analyse the Mediterranean rainfall distribution (Molteni et al, 1983), or to examine the large scale circulation over the Mediterranean and study their linkages to some climatic factor such as winter time precipitation (Quadrelli et al, 2001).…”
Section: Introductionmentioning
confidence: 97%
“…Each principal component has a score for each place and represents an orthogonal pattern in the spatial domain (Molteni et al, 1983). Molteni et al (1983), Pandzic (1988), and Mallants and Feyen (1990) are examples of the large body of precipitation spatial analyses that use principal components methodology. In those studies, though the power of this method as a data reductor is evident, its difficulty and its deficiencies as an interpretational tool can be detected.…”
Section: Classification Of the Spatial Distribution Of Torrential Raimentioning
confidence: 95%
“…Alternatively, in a T-mode analysis (temporal), a series of temporal elements is correlated, each element being characterized by a group of observed values; frequently, as in our study, these values are spatially referenced. Each principal component has a score for each place and represents an orthogonal pattern in the spatial domain (Molteni et al, 1983). Molteni et al (1983), Pandzic (1988), and Mallants and Feyen (1990) are examples of the large body of precipitation spatial analyses that use principal components methodology.…”
Section: Classification Of the Spatial Distribution Of Torrential Raimentioning
confidence: 99%