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dc.contributor.authorDeza, Juan Ignacio
dc.contributor.authorBarreiro, Marcelo
dc.contributor.authorMasoller Alonso, Cristina
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Física
dc.date.accessioned2016-01-25T15:08:37Z
dc.date.available2016-01-25T15:08:37Z
dc.date.issued2015-03-01
dc.identifier.citationDeza, J.Ignacio, Barreiro, M., Masoller, C. Assessing the direction of climate interactions by means of complex networks and information theoretic tools. "Chaos", 01 Març 2015, vol. 25, núm. 3, p. 1-11.
dc.identifier.issn1054-1500
dc.identifier.urihttp://hdl.handle.net/2117/81989
dc.descriptionCopyright 2015 AIP Publishing. This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing
dc.description.abstractAn estimate of the net direction of climate interactions in different geographical regions is made by constructing a directed climate network from a regular latitude-longitude grid of nodes, using a directionality index (DI) based on conditional mutual information (CMI). Two datasets of surface air temperature anomalies-one monthly averaged and another daily averaged-are analyzed and compared. The network links are interpreted in terms of known atmospheric tropical and extratropical variability patterns. Specific and relevant geographical regions are selected, the net direction of propagation of the atmospheric patterns is analyzed, and the direction of the inferred links is validated by recovering some well-known climate variability structures. These patterns are found to be acting at various time-scales, such as atmospheric waves in the extratropics or longer range events in the tropics. This analysis demonstrates the capability of the DI measure to infer the net direction of climate interactions and may contribute to improve the present understanding of climate phenomena and climate predictability. The work presented here also stands out as an application of advanced tools to the analysis of empirical, real-world data. (C) 2015 AIP Publishing LLC.
dc.format.extent11 p.
dc.language.isoeng
dc.publisherInstitute of Physics (IOP)
dc.subjectÀrees temàtiques de la UPC::Física
dc.subjectÀrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia
dc.subject.lcshClimatology
dc.subject.lcshInformation theory
dc.subject.otherclimate networks
dc.subject.otherdirectionality
dc.subject.otherinformation theory
dc.titleAssessing the direction of climate interactions by means of complex networks and information theoretic tools
dc.typeArticle
dc.subject.lemacClimatologia
dc.subject.lemacInformació, Teoria de la
dc.contributor.groupUniversitat Politècnica de Catalunya. DONLL - Dinàmica no Lineal, Òptica no Lineal i Làsers
dc.identifier.doi10.1063/1.4914101
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://scitation.aip.org/content/aip/journal/chaos/25/3/10.1063/1.4914101
dc.rights.accessOpen Access
local.identifier.drac15620841
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/6PN/FIS2012-37655-C02-01
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/FP7/289447/EU/Learning about Interacting Networks in Climate/LINC
local.citation.authorDeza, J.Ignacio; Barreiro, M.; Masoller, C.
local.citation.publicationNameChaos
local.citation.volume25
local.citation.number3
local.citation.startingPage1
local.citation.endingPage11


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