Multiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamics

dc.bibliographicCitation.firstPage837eng
dc.bibliographicCitation.issue3eng
dc.bibliographicCitation.journalTitleEarth System Dynamics : ESDeng
dc.bibliographicCitation.lastPage855eng
dc.bibliographicCitation.volume12eng
dc.contributor.authorAlberti, Tommaso
dc.contributor.authorDonner, Reik V.
dc.contributor.authorVannitsem, Stéphane
dc.date.accessioned2022-01-19T07:37:15Z
dc.date.available2022-01-19T07:37:15Z
dc.date.issued2021
dc.description.abstractAtmosphere and ocean dynamics display many complex features and are characterized by a wide variety of processes and couplings across different timescales. Here we demonstrate the application of multivariate empirical mode decomposition (MEMD) to investigate the multivariate and multiscale properties of a reduced order model of the ocean–atmosphere coupled dynamics. MEMD provides a decomposition of the original multivariate time series into a series of oscillating patterns with time-dependent amplitude and phase by exploiting the local features of the data and without any a priori assumptions on the decomposition basis. Moreover, each oscillating pattern, usually named multivariate intrinsic mode function (MIMF), represents a local source of information that can be used to explore the behavior of fractal features at different scales by defining a sort of multiscale and multivariate generalized fractal dimensions. With these two complementary approaches, we show that the ocean–atmosphere dynamics presents a rich variety of features, with different multifractal properties for the ocean and the atmosphere at different timescales. For weak ocean–atmosphere coupling, the resulting dimensions of the two model components are very different, while for strong coupling for which coupled modes develop, the scaling properties are more similar especially at longer timescales. The latter result reflects the presence of a coherent coupled dynamics. Finally, we also compare our model results with those obtained from reanalysis data demonstrating that the latter exhibit a similar qualitative behavior in terms of multiscale dimensions and the existence of a scale dependency of the statistics of the phase-space density of points for different regions, which is related to the different drivers and processes occurring at different timescales in the coupled atmosphere–ocean system. Our approach can therefore be used to diagnose the strength of coupling in real applications.eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/7849
dc.identifier.urihttps://doi.org/10.34657/6890
dc.language.isoengeng
dc.publisherGöttingen : Copernicus Publ.eng
dc.relation.doihttps://doi.org/10.5194/esd-12-837-2021
dc.relation.essn2190-4987
dc.rights.licenseCC BY 4.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/eng
dc.subject.ddc550eng
dc.subject.otherData reductioneng
dc.subject.otherDynamicseng
dc.subject.otherOceanographyeng
dc.subject.otherPhase space methodseng
dc.subject.otherSignal processingeng
dc.subject.otherAtmosphere-ocean systemeng
dc.subject.otherIntrinsic Mode functionseng
dc.subject.otherMulti-fractal propertyeng
dc.subject.otherMultivariate empirical mode decomposition (MEMD)eng
dc.subject.otherMultivariate time serieseng
dc.subject.otherOcean-atmosphere dynamicseng
dc.subject.otherPhase space densitieseng
dc.subject.otherQualitative behavioreng
dc.subject.otherFractal dimensioneng
dc.titleMultiscale fractal dimension analysis of a reduced order model of coupled ocean–atmosphere dynamicseng
dc.typeArticleeng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorPIKeng
wgl.subjectGeowissenschafteneng
wgl.typeZeitschriftenartikeleng
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