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Do We Need to Parameterize Mesoscale Convective Organization to Mitigate the MJO-Mean State Trade-Off?

DC Field Value Language
dc.contributor.authorAhn, Min-Seop-
dc.contributor.authorKim, Daehyun-
dc.contributor.authorPark, Sungsu-
dc.contributor.authorHam, Yoo-Geun-
dc.date.accessioned2024-05-07T01:32:27Z-
dc.date.available2024-05-07T01:32:27Z-
dc.date.created2020-04-24-
dc.date.created2020-04-24-
dc.date.issued2019-02-
dc.identifier.citationGeophysical Research Letters, Vol.46 No.4, pp.2293-2301-
dc.identifier.issn0094-8276-
dc.identifier.urihttps://hdl.handle.net/10371/200972-
dc.description.abstractModifications in cumulus parameterizations that improve Madden-Julian oscillation (MJO) simulation tend to degrade the mean state-known as the MJO-mean state trade-off. The impacts of parameterizing mesoscale convective organization on the relationship between the MJO and the mean state simulation fidelity are examined. A series of experiments are made with a general circulation model that parameterizes the mesoscale convective organization and simulates well both the MJO and the mean state. In the control simulation, a prognostic nondimensional variable (Omega) represents the degree of convective organization. In order to examine the effect of the parameterized convective organization, fixed Omega values are imposed in a series of constrained experiments. The fixed-Omega simulations show a negative relationship between the MJO and the mean state simulation fidelity. The control simulation is deviated from the negative relationship, suggesting the parameterized mesoscale convective organization helps general circulation models to mitigate the MJO-mean state trade-off.-
dc.language영어-
dc.publisherAmerican Geophysical Union-
dc.titleDo We Need to Parameterize Mesoscale Convective Organization to Mitigate the MJO-Mean State Trade-Off?-
dc.typeArticle-
dc.identifier.doi10.1029/2018GL080314-
dc.citation.journaltitleGeophysical Research Letters-
dc.identifier.wosid000461855600043-
dc.identifier.scopusid2-s2.0-85062321359-
dc.citation.endpage2301-
dc.citation.number4-
dc.citation.startpage2293-
dc.citation.volume46-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorKim, Daehyun-
dc.contributor.affiliatedAuthorPark, Sungsu-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusPART I-
dc.subject.keywordPlusINTRASEASONAL VARIABILITY-
dc.subject.keywordPlusPRECIPITATION-
dc.subject.keywordPlusSCHEME-
dc.subject.keywordPlusOSCILLATION-
dc.subject.keywordPlusCUMULUS-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusIMPACT-
dc.subject.keywordAuthorGCM-
dc.subject.keywordAuthormesoscale convective organization parameterization-
dc.subject.keywordAuthorMJO simulation-
dc.subject.keywordAuthormean state simulation-
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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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