4.6 Article

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

Journal

INTERNATIONAL JOURNAL OF CLIMATOLOGY
Volume 25, Issue 3, Pages 319-329

Publisher

WILEY
DOI: 10.1002/joc.1103

Keywords

heavy snowfall days; principal component analysis; clustering; atmospheric circulation patterns; Pyrenees; Andorra; avalanche forecasting

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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 degrees N by 30 degrees W-15 degrees 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. Copyright (c) 2005 Royal Meteorological Society.

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