Artigo Revisado por pares

Atmospheric circulation patterns related to heavy snowfall days in Andorra, Pyrenees

2005; Wiley; Volume: 25; Issue: 3 Linguagem: Inglês

10.1002/joc.1103

ISSN

1097-0088

Autores

Pere Esteban, P. D. Jones, Javier Martín Vide, M. Mases,

Tópico(s)

Cryospheric studies and observations

Resumo

International Journal of ClimatologyVolume 25, Issue 3 p. 319-329 Research Article Atmospheric circulation patterns related to heavy snowfall days in Andorra, Pyrenees Pere Esteban, Corresponding Author Pere Esteban [email protected] Group of Climatology, University of Barcelona, Catalonia, SpainBaldiri i Reixac s/n, Torre A 5a planta, 08028, Barcelona, Catalonia, SpainSearch for more papers by this authorPhilip D. Jones, Philip D. Jones Climatic Research Unit, University of East Anglia, Norwich, UKSearch for more papers by this authorJavier Martín-Vide, Javier Martín-Vide Group of Climatology, University of Barcelona, Catalonia, SpainSearch for more papers by this authorMontse Mases, Montse Mases Centre de Recerca en Ciències de la Terra, IEA, Encamp, AndorraSearch for more papers by this author Pere Esteban, Corresponding Author Pere Esteban [email protected] Group of Climatology, University of Barcelona, Catalonia, SpainBaldiri i Reixac s/n, Torre A 5a planta, 08028, Barcelona, Catalonia, SpainSearch for more papers by this authorPhilip D. Jones, Philip D. Jones Climatic Research Unit, University of East Anglia, Norwich, UKSearch for more papers by this authorJavier Martín-Vide, Javier Martín-Vide Group of Climatology, University of Barcelona, Catalonia, SpainSearch for more papers by this authorMontse Mases, Montse Mases Centre de Recerca en Ciències de la Terra, IEA, Encamp, AndorraSearch for more papers by this author First published: 01 March 2005 https://doi.org/10.1002/joc.1103Citations: 135AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Abstract Heavy snowfalls over mountain regions are often a direct cause of avalanches. Specific synoptic-scale atmospheric situations are responsible for these kinds of extreme snowfall event, and this is indeed the case for Andorra, a small country located in the Pyrenees, between France and Spain. Based on days with an intensity of at least 30 cm of snow in a 24 h period, the present study uses principal component analysis (PCA) and clustering techniques to characterize the synoptic circulation patterns for these days during the winter season. The area of analysis encompasses the region 30–60°N by 30°W–15°E and the period covers the winter seasons from 1986–87 to 2000–01. The methodology proposed involves a preprocessing approach consisting of a spatial standardization of the data used for the PCA, an alternative approximation to decide the centroids and the number of groups for the K-means clustering, and the rejection of the iterations for this algorithm. This approach enables the synoptic classification of every heavy snowfall day, and composite maps were constructed for sea-level pressure, 500 hPa geopotential height, and 1000–500 m thickness (the 5270 m, 5400 m and 5520 m contour lines). The results show seven circulation patterns, most of them with an Atlantic component of the wind, and others with a clear Mediterranean advection that could be combined with cold continental air. The results, as weather charts, could be a useful tool to assist meteorological models in heavy snowfall forecasting, and the day's classification obtained opens up future possibilities for detailed meteorological and climatological analysis of the established types. 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Citing Literature Volume25, Issue315 March 2005Pages 319-329 ReferencesRelatedInformation

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