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Predictability and prediction skill of the MJO in two operational forecasting systems

DC Field Value Language
dc.contributor.authorKim, Hye-Mi-
dc.contributor.authorWebster, Peter J.-
dc.contributor.authorToma, Violeta E.-
dc.contributor.authorKim, Daehyun-
dc.date.accessioned2024-05-07T01:34:06Z-
dc.date.available2024-05-07T01:34:06Z-
dc.date.created2024-04-19-
dc.date.created2024-04-19-
dc.date.issued2014-07-
dc.identifier.citationJournal of Climate, Vol.27 No.14, pp.5364-5378-
dc.identifier.issn0894-8755-
dc.identifier.urihttps://hdl.handle.net/10371/201003-
dc.description.abstractThe authors examine the predictability and prediction skill of the Madden-Julian oscillation (MJO) of two ocean-atmosphere coupled forecast systems of ECMWF [Variable Resolution Ensemble Prediction System (VarEPS)] and NCEP [Climate Forecast System, version 2 (CFSv2)]. The VarEPS hindcasts possess five ensemble members for the period 1993-2009 and the CFSv2 hindcasts possess three ensemble members for the period 2000-09. Predictability and prediction skill are estimated by the bivariate correlation coefficient between the observed and predicted Wheeler-Hendon real-time multivariate MJO index (RMM). MJO predictability is beyond 32 days lead time in both hindcasts, while the prediction skill is about 27 days in VarEPS and 21 days in CFSv2 as measured by the bivariate correlation exceeding 0.5. Both predictability and prediction skill of MJO are enhanced by averaging ensembles. Results show clearly that forecasts initialized with (or targeting) strong MJOs possess greater prediction skill compared to those initialized with (or targeting) weak or nonexistent MJOs. The predictability is insensitive to the initialMJOphase (or forecast target phase), although the prediction skill varies with MJO phases. A few common model issues are identified. In both hindcasts, the MJO propagation speed is slower and the MJO amplitude is weaker than observed. Also, both ensemble forecast systems are underdispersive, meaning that the growth rate of ensemble error is greater than the growth rate of the ensemble spread by lead time. © 2014 American Meteorological Society.-
dc.language영어-
dc.publisherAmerican Meteorological Society-
dc.titlePredictability and prediction skill of the MJO in two operational forecasting systems-
dc.typeArticle-
dc.identifier.doi10.1175/JCLI-D-13-00480.1-
dc.citation.journaltitleJournal of Climate-
dc.identifier.wosid000339135200009-
dc.identifier.scopusid2-s2.0-84904479641-
dc.citation.endpage5378-
dc.citation.number14-
dc.citation.startpage5364-
dc.citation.volume27-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorKim, Daehyun-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusMADDEN-JULIAN OSCILLATION-
dc.subject.keywordPlusSUMMER INTRASEASONAL OSCILLATION-
dc.subject.keywordPlusMODEL-
dc.subject.keywordPlusVARIABILITY-
dc.subject.keywordPlusTROPICS-
dc.subject.keywordPlusEVENTS-
dc.subject.keywordPlusPERIOD-
dc.subject.keywordPlusINDEX-
dc.subject.keywordPlusOCEAN-
dc.subject.keywordAuthorClimate models-
dc.subject.keywordAuthorClimate prediction-
dc.subject.keywordAuthorHindcasts-
dc.subject.keywordAuthorMadden-Julian oscillation-
dc.subject.keywordAuthorModel comparison-
dc.subject.keywordAuthorModel errors-
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  • College of Natural Sciences
  • Department of Earth and Environmental Sciences
Research Area Climate Change, Earth & Environmental Data, Severe Weather, 기후과학, 위험기상, 지구환경 데이터과학

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