Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/10974
Automatic Forecasts Algorithms
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dc.contributor.authorRio, Joaoes_ES
dc.contributor.authorSilva, Pedroes_ES
dc.contributor.authorNovo, Ildaes_ES
dc.date.accessioned2019-12-05T15:29:42Z-
dc.date.available2019-12-05T15:29:42Z-
dc.date.issued2019-
dc.identifier.citationSexto Simposio Nacional de Predicción, Memorial Antonio Mestre. Madrid: Agencia Estatal de Meteorología, 2019, p. 187-192es_ES
dc.identifier.urihttp://hdl.handle.net/20.500.11765/10974-
dc.descriptionPonencia presentada en: VI Simposio Nacional de Predicción, celebrado en los servicios centrales de AEMET, en Madrid, del 17 al 19 de septiembre de 2018.es_ES
dc.description.abstractThe need for forecasts at an increasingly higher number of locations and time frequency requires a fully automated forecast system. Due to model biases, statistical post-processing is required to improve the quality of the forecasts in variables such as temperature, humidity and wind speed. The automatic forecasting algorithms developed at IPMA provide forecasts up to 10 days and use ECMWF and AROME data.es_ES
dc.language.isoenges_ES
dc.publisherAgencia Estatal de Meteorologíaes_ES
dc.rightsLicencia CC: Reconocimiento–NoComercial–SinObraDerivada CC BY-NC-NDes_ES
dc.subjectAutomatic weather forecastinges_ES
dc.subjectAlgorithmses_ES
dc.subjectECMWF high-resolution and ensemble systemes_ES
dc.subjectAROMEes_ES
dc.titleAutomatic Forecasts Algorithmses_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherversionhttps://dx.doi.org/10.31978/639-19-010-0.187es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
Appears in Collections:6º Simposio Nacional de Predicción (2018)


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