Publication:
Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information

dc.contributor.authorPérez-Zanón, N
dc.contributor.authorCaron, L.-P
dc.contributor.authorTerzago, S.
dc.contributor.authorVan Schaeybroeck, B
dc.contributor.authorLledó, L.
dc.contributor.authorManubens, N
dc.contributor.authorRoulin, E.
dc.contributor.authorCorti, S.
dc.contributor.authorÁlvarez Castro, María del Carmen
dc.contributor.authorBatté, L.
dc.contributor.authorBretonnière, P.-A.
dc.contributor.authorDelgado-Torres, C.
dc.contributor.authorFabiano, F.
dc.contributor.authorGiuntoli, I.
dc.contributor.authorvon Hardenberg, J
dc.contributor.authorSánchez-García, E.
dc.contributor.authorTorralba, V.
dc.contributor.authorVerfaillie, D.
dc.date.accessioned2025-01-31T22:35:42Z
dc.date.available2025-01-31T22:35:42Z
dc.date.issued2022-08-04
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.
dc.description.sponsorshipDepartamento Sistemas Físicos, Químicos y Naturales
dc.format.mimetypeapplication/pdf
dc.identifier.citationGeoscientific Model Development, Vol. 15, Núm. 15, pp. 6115-6142
dc.identifier.doi10.5194/GMD-15-6115-2022
dc.identifier.urihttps://hdl.handle.net/10433/23050
dc.language.isoen
dc.publisherEGU journals
dc.relation.projectIDMedscope (ERA4CS-JPI) grant no. 690462
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSeasonal forecast
dc.subjectCimate services
dc.subjectRpackage
dc.subjectClimate predictions
dc.titleClimate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information
dc.typejournal article
dc.type.hasVersionVoR
dspace.entity.typePublication
relation.isAuthorOfPublication7dae5448-fe26-4dbc-951b-d2d3dd8b042a
relation.isAuthorOfPublication.latestForDiscovery7dae5448-fe26-4dbc-951b-d2d3dd8b042a

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
gmd-15-6115-2022.pdf
Size:
13.29 MB
Format:
Adobe Portable Document Format