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Variability, teleconnection, and predictability of Korean precipitation in relation to large scale climate indices

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dc.contributor.authorLee, Jai Hong-
dc.contributor.authorRamirez, Jorge A.-
dc.contributor.authorKim, Tae Woong-
dc.contributor.authorJulien, Pierre Y.-
dc.date.accessioned2021-06-22T10:40:59Z-
dc.date.available2021-06-22T10:40:59Z-
dc.date.issued2019-01-
dc.identifier.issn0022-1694-
dc.identifier.issn1879-2707-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/3920-
dc.description.abstractSpatiotemporal variability, teleconnection, and predictability of the Korean precipitation related to large scale climate indices were examined based on leading patterns of observed monthly Rx5day and total precipitation through an empirical orthogonal teleconnection (EOT). Cross-correlation and lag regression analyses for the leading modes and global atmospheric circulation dataset were employed on a monthly basis. The spatial pattern of the leading EOT modes for Rx5day and total precipitation represents a northern inland mode for boreal summer and a southern coastal mode in boreal winter. The temporal evolution of the leading EOT modes exhibits increasing trends during summer season and decadal variability for winter season. The leading EOT patterns of Rx5day precipitation show more widespread coherent patterns than those of total precipitation during warm and cold seasons, while the former explains less variance in precipitation variability than the latter. The tropical ENSO forcing has a coherent teleconnection with September and November-December precipitation patterns, while the Indian Ocean dipole is identified as a driver for precipitation variability in September and November. The monsoon circulation over the western North Pacific also exhibits a significant negative correlation with winter precipitation EOTs, while tropical cyclone indices are positively correlated with the fall precipitation EOTs. The leading patterns of the September and December Rx5day precipitation time series are predictable at up to six month lead time from the tropical Pacific sea surface temperatures (SSTs), while a somewhat weak predictable response from Indian Ocean SSTs was only detected at longer lead times. In addition, predictability from the Pacific SSTs for above normal precipitation is greater than that for below normal precipitation.-
dc.format.extent14-
dc.language영어-
dc.language.isoENG-
dc.publisherElsevier BV-
dc.titleVariability, teleconnection, and predictability of Korean precipitation in relation to large scale climate indices-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.jhydrol.2018.08.034-
dc.identifier.scopusid2-s2.0-85055692188-
dc.identifier.wosid000455694400002-
dc.identifier.bibliographicCitationJournal of Hydrology, v.568, pp 12 - 25-
dc.citation.titleJournal of Hydrology-
dc.citation.volume568-
dc.citation.startPage12-
dc.citation.endPage25-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaGeology-
dc.relation.journalResearchAreaWater Resources-
dc.relation.journalWebOfScienceCategoryEngineering, Civil-
dc.relation.journalWebOfScienceCategoryGeosciences, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryWater Resources-
dc.subject.keywordPlusINDIAN-OCEAN DIPOLE-
dc.subject.keywordPlusSOUTHERN-OSCILLATION-
dc.subject.keywordPlusEL-NINO-
dc.subject.keywordPlusRAINFALL VARIABILITY-
dc.subject.keywordPlusMONSOON RAINFALL-
dc.subject.keywordPlusENSO-
dc.subject.keywordPlusPACIFIC-
dc.subject.keywordPlusTEMPERATURE-
dc.subject.keywordPlusPATTERNS-
dc.subject.keywordPlusMODE-
dc.subject.keywordAuthorPrecipitation variability-
dc.subject.keywordAuthorTeleconnection-
dc.subject.keywordAuthorEl Nino Southern Oscillation-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0022169418306310?via%3Dihub-
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ERICA 공학대학 (DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING)
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