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dc.creatorPepler, Acacia S.-
dc.creatorDíaz, Leandro Baltasar-
dc.creatorProdhomme, Chloé-
dc.creatorDoblas Reyes, Francisco J.-
dc.creatorKumar, Arun-
dc.date2017-06-08T20:15:40Z-
dc.date2017-06-08T20:15:40Z-
dc.date2015-09-
dc.date2017-06-07T20:45:20Z-
dc.date.accessioned2019-04-29T15:51:08Z-
dc.date.available2019-04-29T15:51:08Z-
dc.date.issued2015-09-
dc.identifierPepler, Acacia S.; Díaz, Leandro Baltasar; Prodhomme, Chloé; Doblas Reyes, Francisco J.; Kumar, Arun; The ability of a multi-model seasonal forecasting ensemble to forecast the frequency of warm, cold and wet extremes; Elsevier Science; Weather and Climate Extremes; 9; 9-2015; 68-77-
dc.identifier2212-0947-
dc.identifierhttp://hdl.handle.net/11336/17818-
dc.identifier.urihttp://rodna.bn.gov.ar:8080/jspui/handle/bnmm/303718-
dc.descriptionDynamical models are now widely used to provide forecasts of above or below average seasonal mean temperatures and precipitation, with growing interest in their ability to forecast climate extremes on a seasonal time scale. This study assesses the skill of the ENSEMBLES multi-model ensemble to forecast the 90th and 10th percentiles of both seasonal temperature and precipitation, using a number of metrics of ‘extremeness’. Skill is generally similar or slightly lower to that for seasonal means, with skill strongly influenced by the El Niño-Southern Oscillation. As documented in previous studies, much of the skill in forecasting extremes can be related to skill in forecasting the seasonal mean value, with skill for extremes generally lower although still significant. Despite this, little relationship is found between the skill of forecasting the upper and lower tails of the distribution of daily values.-
dc.descriptionFil: Pepler, Acacia S.. University Of New South Wales; Australia-
dc.descriptionFil: Díaz, Leandro Baltasar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmosfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmosfera; Argentina-
dc.descriptionFil: Prodhomme, Chloé. Institut Català de Ciències del Clima; España-
dc.descriptionFil: Doblas Reyes, Francisco J.. Institut Català de Ciències del Clima; España. Institució Catalana de Recerca i Estudis Avancats; España. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; España-
dc.descriptionFil: Kumar, Arun. National Oceanic and Atmospheric Administration; Estados Unidos-
dc.formatapplication/pdf-
dc.formatapplication/pdf-
dc.languageeng-
dc.publisherElsevier Science-
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.wace.2015.06.005-
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S2212094715300062-
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/-
dc.sourcereponame:CONICET Digital (CONICET)-
dc.sourceinstname:Consejo Nacional de Investigaciones Científicas y Técnicas-
dc.sourceinstacron:CONICET-
dc.subjectExtremes-
dc.subjectSeasonal forecasting-
dc.subjectENSO-
dc.subjectClimate model-
dc.subjectEnsemble-
dc.subjectInvestigación Climatológica-
dc.subjectCiencias de la Tierra y relacionadas con el Medio Ambiente-
dc.subjectCIENCIAS NATURALES Y EXACTAS-
dc.titleThe ability of a multi-model seasonal forecasting ensemble to forecast the frequency of warm, cold and wet extremes-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.typeinfo:ar-repo/semantics/articulo-
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