Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/1346
Analysis and downscaling multi-model seasonal forecasts in Peru using self-organizing maps
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dc.contributor.authorGutiérrez Llorente, José Manueles_ES
dc.contributor.authorCano Trueba, Rafaeles_ES
dc.contributor.authorCofiño, Antonio S.es_ES
dc.contributor.authorSordo, Carmen María-
dc.date.accessioned2016-03-18T09:37:30Z-
dc.date.available2016-03-18T09:37:30Z-
dc.date.issued2005-
dc.identifier.citationTellus A. 2005, 57(3), p. 435-447es_ES
dc.identifier.issn0280-6495-
dc.identifier.issn1600-0870-
dc.identifier.urihttp://hdl.handle.net/20.500.11765/1346-
dc.description.abstractWe present an application of Self-Organizing Maps (SOM) for analyzing multi-model ensemble seasonal forecasts from the DEMETER project in the tropical area of Northern Peru. SOM is an automatic data-mining clustering technique which allows summarizing a high-dimensional data space in terms of a set of reference vectors (cluster centroids). Moreover, it has outstanding analysis and visualization properties, since the reference vectors can be projected into a 2D lattice preserving their high-dimensional topology.es_ES
dc.description.sponsorshipThe authors are also grateful to the Comisión Interministerial de Ciencia y Tecnología (CICYT, CGL2004-02652 grant) for partial support of this work.-
dc.formatapplication/pdf-
dc.language.isoenges_ES
dc.publisherTaylor & Francises_ES
dc.rightsLicencia CC: Reconocimiento CC BYes_ES
dc.subjectPredicción estacional-
dc.subjectDEMETER projectes_ES
dc.subjectEnsemble seasonal forecastses_ES
dc.subjectSelf-organizing mapses_ES
dc.titleAnalysis and downscaling multi-model seasonal forecasts in Peru using self-organizing mapses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttp://dx.doi.org/10.3402/tellusa.v57i3.14672es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
Appears in Collections:Artículos científicos 2005-2009


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