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dc.contributor.authorLledó, Llorenç
dc.contributor.authorDoblas-Reyes, Francisco
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2020-07-28T15:52:58Z
dc.date.available2020-07-28T15:52:58Z
dc.date.issued2020-07
dc.identifier.citationLledó, L.; Doblas-Reyes, F. Predicting daily mean wind speed in Europe weeks ahead from MJO status. "Monthly Weather Review", Juliol 2020, vol. 148, núm. 8, p. 3413-3426.
dc.identifier.issn1520-0493
dc.identifier.urihttp://hdl.handle.net/2117/327891
dc.description.abstractThe Madden–Julian oscillation (MJO), a prominent feature of the tropical atmospheric circulation at subseasonal time scales, is known to modulate atmospheric variability in the Euro-Atlantic region. However, current subseasonal prediction systems fail to accurately reproduce the physical processes involved in these teleconnection mechanisms. This paper explores the observed impact of strong MJO events on surface wind speed over Europe. It is found that some MJO phases are accompanied by strong wind anomalies in Europe. After showing that this teleconnective mechanism is not present in the predictions of the ECMWF monthly forecasting system, a methodology to reconstruct forecasts of daily mean wind speed in the continent weeks ahead is proposed. This method combines MJO forecasts from the S2S project database and the observed teleconnection impacts in the historical records. Although it is found that strong MJO events cannot be skillfully predicted more than 10 days ahead with current prediction systems, a theoretical experiment shows that this method can effectively transform a dynamical MJO forecast into a probabilistic wind speed prediction in Europe.
dc.description.sponsorshipThe research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation program under Grant 776787 (S2S4E) and from the Ministerio de Ciencia, Innovación y Universidades (MICINN) as part of the CLINSA project (CGL2017-85791-R). The authors acknowledge Australian Bureau of Meteorology for providing the MJO RMM historical indices, and the S2S project for providing the MJO indices from ECMWF MFS forecasts and ERA-Interim. The authors want to thank Nicolau Manubens for technical support with the startR R package, which allows processing big memory arrays by chunks in a cluster and then merges the results back together. Many analyses would have not been possible without this package. The CSTools R package was also used to produce some figures. Pierre-Antoine Bretonnière and Margarida Samsó helped downloading and formatting the surface wind datasets. The authors want to thank Frederic Vitart and Laura Ferranti for helping with the interpretation of some results, and Verónica Torralba for helping to structure the material.
dc.format.extent14 p.
dc.language.isoeng
dc.publisherAmerican Meteorological Society
dc.relation.urihttps://ams.silverchair-cdn.com/ams/content_public/journal/mwr/148/8/10.1175_mwr-d-19-0328.1/1/10.1175_mwr-d-19-0328.s1.pdf?Expires=1598903288&Signature=WXdgUVxuCxaMKDKI9sMYC5JWIyUZXa08Xuh~AgZchO7rA8pgMjqHl0NPBDsG0mXxNsMTxnHkpGCP1mjrs~TQ~1BASLcZR3QtddpsXkL3-a4-Prrmp8FClGt9sMwIGOnDqO6LfUWqPhrqZq8nhMxZcM4Gg0P-lrnhBSoqPLa3fnM7zIRliUCIHC1qIBSceixcYpOUXok~WkykvrunxoUocbH3vAbhlthGYpVp2AEYDpjxUSpsJ-DPi~P0Bw0qZA-JIkzbLNnvOwLHLXqDUiaw7fREwNEVmSHzQbSassAhB2BekvXn5R5e37xAYBnWZ7Jxw-I2kgx8C3OG2jWpO1iBYQ__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible
dc.subjectÀrees temàtiques de la UPC::Energies
dc.subject.lcshComputer simulation
dc.subject.lcshClimatology
dc.subject.lcshMadden-Julian oscillation
dc.subject.lcshRenewable energy sources
dc.subject.lcshTeleconnections (Climatology)
dc.subject.otherMadden-Julian oscillation
dc.subject.otherRenewable energy
dc.subject.otherClimate services
dc.subject.otherStatistical forecasting
dc.subject.otherSeasonal forecasting
dc.subject.otherTeleconnections,
dc.titlePredicting daily mean wind speed in Europe weeks ahead from MJO status
dc.typeArticle
dc.subject.lemacSimulació per ordinador
dc.subject.lemacEstadística -- Programes d'ordinador
dc.subject.lemacClimatologia
dc.subject.lemacEnergies renovables
dc.subject.lemacTeleconnections
dc.identifier.doi10.1175/MWR-D-19-0328.1
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://journals.ametsoc.org/mwr/article/148/8/3413/347632/Predicting-Daily-Mean-Wind-Speed-in-Europe-Weeks
dc.rights.accessOpen Access
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/776787/EU/Sub-seasonal to Seasonal climate forecasting for Energy/S2S4E
dc.relation.projectidinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CGL2017-85791-R/ES/PREDICCION DECADAL CLIMATICA PARA SERVICIOS CLIMATICOS A CORTO PLAZO Y ADAPTACION/
local.citation.publicationNameMonthly Weather Review
local.citation.volume148
local.citation.number8
local.citation.startingPage3413
local.citation.endingPage3426


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