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dc.contributor.authorGibergans Bàguena, José
dc.contributor.authorOrtego Martínez, María Isabel
dc.contributor.authorTolosana Delgado, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada III
dc.date.accessioned2011-06-16T08:58:20Z
dc.date.available2011-06-16T08:58:20Z
dc.date.created2011
dc.date.issued2011
dc.identifier.citationGibergans-Báguena, J.; Ortego, M.I.; Tolosana-Delgado, R. Pluviometric regionalization of Catalunya: a compositional data methodology. A: International Workshop on Compositional Data Analysis. "4th International Workshop on Compositional Data Analysis". Sant Feliu de Guíxols: Centro Internacional de Métodos Numéricos en Ingeniería (CIMNE), 2011, p. 1-9.
dc.identifier.isbn978-84-87867-76-7
dc.identifier.urihttp://hdl.handle.net/2117/12783
dc.description.abstractThe aim of this paper is to introduce a methodology for de¯ning groups from regionalized com- positional 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 de¯ne 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 com-positional 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 de¯ned 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 de¯ne 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.
dc.format.extent9 p.
dc.language.isoeng
dc.publisherCentro Internacional de Métodos Numéricos en Ingeniería (CIMNE)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències
dc.subject.lcshProbability and statistics
dc.subject.lcshCatalonia
dc.titlePluviometric regionalization of Catalunya: a compositional data methodology
dc.typeConference report
dc.subject.lemacCatalunya
dc.subject.lemacProbabilitats
dc.contributor.groupUniversitat Politècnica de Catalunya. NRG - Riscos Naturals i Geoestadística
dc.contributor.groupUniversitat Politècnica de Catalunya. LIM/UPC - Laboratori d'Enginyeria Marítima
dc.relation.publisherversionhttp://congress.cimne.com/codawork11/
dc.rights.accessOpen Access
local.identifier.drac5768196
dc.description.versionPostprint (published version)
local.citation.authorGibergans-Báguena, J.; Ortego, M.I.; Tolosana-Delgado, R.
local.citation.contributorInternational Workshop on Compositional Data Analysis
local.citation.pubplaceSant Feliu de Guíxols
local.citation.publicationName4th International Workshop on Compositional Data Analysis
local.citation.startingPage1
local.citation.endingPage9


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