DUGi

Pluviometric Regionalization of Catalunya: a Compositional Data Methodology

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@2072@@273427

The aim of this paper is to introduce a methodology for defining groups from regionalized compositionaldata, through a hierarchical clustering algorithm aware of both the spatial dependenceand the compositional character of the data set. This method is used to define a regionalization ofCatalunya (NE Spain) with respect to its precipitation patterns in the Winter season. This regionis characterized by a highly contrasted topography, which plays a dominant role in the spatialdistribution of precipitation. Each rain gauge station is characterized by the relative frequenciesof occurrence of six intervals of daily precipitation amount (classes ranging from “no rain” forprecipitation below 3 mm, to “heavy storm” above 50 mm). Recognizing that frequencies are compositionaldata, the spatial dependence of this data set has been characterized by variograms of theset of all pair-wise log-ratios, in the fashion of the variation matrix. Then, a Mahalanobis distancebetween stations has been defined using these variograms to ensure that gauges with high spatialcorrelation get smaller distances. This spatially-dependent distance criterion has been used in aWard hierarhical cluster method to define the regions. Results reveal 5 quite homogeneous groupsof stations, which can be mostly ascribed a physical meaning. Finally, possible links to regionalcirculation patterns are discussed

Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada