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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.identifier.citationTellus A. 2005, 57(3), p. 435-447es_ES
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.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
Appears in Collections:Artículos científicos 2005-2009

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