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Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information
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dc.contributor.authorPérez Zanón, Núriaes_ES
dc.contributor.authorCaron, Louis-Philippees_ES
dc.contributor.authorTerzago, Silviaes_ES
dc.contributor.authorSchaeybroeck, Bert Vanes_ES
dc.contributor.authorLledó, Llorençes_ES
dc.contributor.authorManubens, Nicolaues_ES
dc.contributor.authorRoulin, Emmanueles_ES
dc.contributor.authorÁlvarez-Castro, Carmenes_ES
dc.contributor.authorBatté, Laurianees_ES
dc.contributor.authorBretonnière, Pierre-Antoinees_ES
dc.contributor.authorCorti, Susannaes_ES
dc.contributor.authorDelgado Torres, Carloses_ES
dc.contributor.authorDomínguez Alonso, Martaes_ES
dc.contributor.authorFabiano, Federicoes_ES
dc.contributor.authorGiuntoli, Ignazioes_ES
dc.contributor.authorHardenberg, Jost vones_ES
dc.contributor.authorSánchez García, Eroteidaes_ES
dc.contributor.authorTorralba, Verónicaes_ES
dc.contributor.authorVerfaillie, Deborahes_ES
dc.date.accessioned2022-08-11T13:59:26Z-
dc.date.available2022-08-11T13:59:26Z-
dc.date.issued2022-
dc.identifier.citationGeoscientific Model Development. 2022, 15(15), 6115–6142es_ES
dc.identifier.issn1991-959X-
dc.identifier.issn1991-9603-
dc.identifier.urihttp://hdl.handle.net/20.500.11765/13919-
dc.description.abstractDespite the wealth of existing climate forecast data, only a small part is effectively exploited for sectoral applications. A major cause of this is the lack of integrated tools that allow the translation of data into useful and skillful climate information. This barrier is addressed through the development of an R package. Climate Services Toolbox (CSTools) is an easy-to-use toolbox designed and built to assess and improve the quality of climate forecasts for seasonal to multi-annual scales. The package contains process-based, state-of-the-art methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination, and multivariate verification, as well as basic and advanced tools to obtain tailored products. Due to the modular design of the toolbox in individual functions, the users can develop their own post-processing chain of functions, as shown in the use cases presented in this paper, including the analysis of an extreme wind speed event, the generation of seasonal forecasts of snow depth based on the SNOWPACK model, and the post-processing of temperature and precipitation data to be used as input in impact models.es_ES
dc.description.sponsorshipThis research has been supported by the Horizon 2020 (S2S4E; grant no. 776787), EUCP (grant no. 776613), ERA4CS (grant no. 690462), and the Ministerio de Ciencia e Innovación (grant no. FPI PRE2019-088646).es_ES
dc.language.isoenges_ES
dc.publisherEuropean Geosciences Uniones_ES
dc.publisherCopernicus Publicationses_ES
dc.rightsLicencia CC: Reconocimiento CC BYes_ES
dc.subjectClimate forecast dataes_ES
dc.subjectClimate Services Toolboxes_ES
dc.subjectClimate informationes_ES
dc.subjectClimate dataes_ES
dc.titleClimate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast informationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.5194/gmd-15-6115-2022es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
Colecciones: Artículos científicos 2019-2022


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