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An approach for the forecasting of wind strength tailored to routine observational daily wind gust data

dc.contributor.authorValero Rodríguez, Francisco
dc.contributor.authorPascual, A.
dc.contributor.authorMartín, M.L.
dc.date.accessioned2023-06-19T13:41:57Z
dc.date.available2023-06-19T13:41:57Z
dc.date.issued2014-02
dc.description© 2013 Elsevier B.V. This work has been partially supported by the research projects CGL2011-25327, UE Safewind G.A. No. 21374, VA025A10-2 and AYA2011-29967-C05-02. The authors wish to thank the Spanish Meteorological Agency (AEMET: Agencia Estatal de Meteorología) for providing the Spanish wind data sets and the European Centre for Weather Medium Forecast (ECWMF) for providing the large-scale atmospheric data.
dc.description.abstractDaily wind gusts observed over Spain have been estimated by means of the statistical downscaling analogue model ANPAF developed by the authors. The model diagnoses large-scale atmospheric circulation patterns and subsequently estimates wind probabilities. Several data sets have been used: daily 1000 geopotential height (Z1000) field over the North Atlantic and the observational daily wind gust (WGU). Next, to give an additional value to the ERA-Interim wind gust data base (ERI), wind gust estimations from the analogue model were obtained to compare them with the wind gust data set from the ERA-Interim. The analogue method is based on finding in the historic geopotential height data base, a principal component subset of geopotential height patterns that are the most akin to a geopotential height pattern used as an input. Then, once the analogues are determined associated wind gusts are estimated from them. Finally, within validation stage are shown some results relative to the comparison between the wind gust estimated and ERI data. The probabilistic results are shown by means of Brier Skill Scores. The results show that the ANPAF model gives good wind gust information in the inner Iberian Peninsula and highlight that the Atlantic atmospheric patterns are, in general, better to predict gusts in such area. Though in only few stations the ANPAF model provides less additional value than the ERA-Interim data base for extreme wind gust values, the analogue model generally provides pretty information in estimating wind gust in Spain to the ERI data set.
dc.description.departmentDepto. de Física de la Tierra y Astrofísica
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Economía y Competitividad (MINECO)
dc.description.sponsorshipMinisterio de Ciencia e Innovación (MICINN)
dc.description.sponsorshipUE Safewind G.A.
dc.description.sponsorshipAgencia Estatal de Meteorología (AEMET)
dc.description.sponsorshipEuropean Centre for Weather Medium Forecast (ECWMF)
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/63848
dc.identifier.doi10.1016/j.atmosres.2013.09.019
dc.identifier.issn0169-8095
dc.identifier.officialurlhttp://dx.doi.org/10.1016/j.atmosres.2013.09.019
dc.identifier.urihttps://hdl.handle.net/20.500.14352/34284
dc.journal.titleAtmospheric research
dc.language.isoeng
dc.page.final65
dc.page.initial58
dc.publisherElsevier Science Inc
dc.relation.projectIDCGL2011-25327
dc.relation.projectIDAYA2011-29967-C05-02
dc.relation.projectID21374
dc.relation.projectIDVA025A10-2
dc.rights.accessRightsrestricted access
dc.subject.cdu52
dc.subject.keywordDownscaling technique
dc.subject.keywordIberian peninsula
dc.subject.keywordClimate-change
dc.subject.keywordPrecipitation
dc.subject.keywordPattterns
dc.subject.keywordConnections
dc.subject.keywordImprovement
dc.subject.keywordReanalysis
dc.subject.keywordSystem
dc.subject.keywordSpain
dc.subject.ucmFísica atmosférica
dc.subject.unesco2501 Ciencias de la Atmósfera
dc.titleAn approach for the forecasting of wind strength tailored to routine observational daily wind gust data
dc.typejournal article
dc.volume.number137
dspace.entity.typePublication
relation.isAuthorOfPublication552fa01a-13cf-4384-a0fa-468914cc2b06
relation.isAuthorOfPublication.latestForDiscovery552fa01a-13cf-4384-a0fa-468914cc2b06

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