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Pluviometric Regionalization of Catalunya: a Compositional Data Methodology

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

Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada

Other contributions: Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada
Author: Gibergans-Báguena, J.
Ortego, M.I.
Tolosana Delgado, Raimon
Date: 2018 June 5
Abstract: The aim of this paper is to introduce a methodology for defining groups from regionalized compositional data, through a hierarchical clustering algorithm aware of both the spatial dependence and the compositional character of the data set. This method is used to define a regionalization of Catalunya (NE Spain) with respect to its precipitation patterns in the Winter season. This region is characterized by a highly contrasted topography, which plays a dominant role in the spatial distribution of precipitation. Each rain gauge station is characterized by the relative frequencies of occurrence of six intervals of daily precipitation amount (classes ranging from “no rain” for precipitation below 3 mm, to “heavy storm” above 50 mm). Recognizing that frequencies are compositional data, the spatial dependence of this data set has been characterized by variograms of the set of all pair-wise log-ratios, in the fashion of the variation matrix. Then, a Mahalanobis distance between stations has been defined using these variograms to ensure that gauges with high spatial correlation get smaller distances. This spatially-dependent distance criterion has been used in a Ward hierarhical cluster method to define the regions. Results reveal 5 quite homogeneous groups of stations, which can be mostly ascribed a physical meaning. Finally, possible links to regional circulation patterns are discussed
Document access: http://hdl.handle.net/2072/319393
Language: eng
Publisher: Universitat de Girona. Departament d’Informàtica i Matemàtica Aplicada
Rights: Tots els drets reservats
Subject: Anàlisi multivariable -- Congressos
Multivariate analysis -- Congresses
Estadística matemàtica -- Congressos
Mathematical statistics -- Congresses
Pluviometria -- Congressos
Precipitation (Meteorology) -- Mesurement
Title: Pluviometric Regionalization of Catalunya: a Compositional Data Methodology
Type: info:eu-repo/semantics/conferenceObject
Repository: Recercat

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