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dc.contributor.authorLin Ye, Jue
dc.contributor.authorGarcía León, Manuel
dc.contributor.authorGracia Garcia, Vicente
dc.contributor.authorOrtego Martínez, María Isabel
dc.contributor.authorLionello, Piero
dc.contributor.authorSánchez-Arcilla Conejo, Agustín
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2017-05-02T15:35:22Z
dc.date.available2019-05-01T00:30:43Z
dc.date.issued2017-04
dc.identifier.citationLin Ye, J., Garcia, M., Gracia, V., Ortego, M.I., Piero Lionello, Sanchez-Arcilla, A. Multivariate statistical modelling of future marine storms. "Applied ocean research", Abril 2017, vol. 65, p. 192-205.
dc.identifier.issn0141-1187
dc.identifier.otherhttps://arxiv.org/abs/1903.05727
dc.identifier.urihttp://hdl.handle.net/2117/103920
dc.description.abstractExtreme events, such as wave-storms, need to be characterized for coastal infrastructure design purposes. Such description should contain information on both the univariate behaviour and the joint-dependence of storm-variables. These two aspects have been here addressed through generalized Pareto distributions and hierarchical Archimedean copulas. A non-stationary model has been used to highlight the relationship between these extreme events and non-stationary climate. It has been applied to a Representative Concentration Pathway 8.5 Climate-Change scenario, for a fetch-limited environment (Catalan Coast). In the non-stationary model, all considered variables decrease in time, except for storm-duration at the northern part of the Catalan Coast. The joint distribution of storm variables presents cyclical fluctuations, with a stronger influence of climate dynamics than of climate itself.
dc.format.extent14 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria civil::Enginyeria hidràulica, marítima i sanitària::Ports i costes
dc.subject.lcshStorms--Forecasting
dc.subject.lcshStorms--Statistical methods
dc.subject.otherWave storm
dc.subject.otherCatalan Coast
dc.subject.otherHierarchical Archimedean copula
dc.subject.otherGeneralized Pareto distribution
dc.subject.otherNon-stationarity
dc.subject.otherGeneralized additive model
dc.titleMultivariate statistical modelling of future marine storms
dc.typeArticle
dc.subject.lemacTempestes
dc.contributor.groupUniversitat Politècnica de Catalunya. LIM/UPC - Laboratori d'Enginyeria Marítima
dc.contributor.groupUniversitat Politècnica de Catalunya. COSDA-UPC - COmpositional and Spatial Data Analysis
dc.identifier.doi10.1016/j.apor.2017.04.009
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0141118717300743
dc.rights.accessOpen Access
local.identifier.drac20094829
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/730030/EU/Copernicus Evolution and Aplications with Sentinel Enhancements and Land Effluents for Shores and Seas/CEASELESS
dc.relation.projectidceaseless
local.citation.authorLin Ye, J.; Garcia, M.; Gracia, V.; Ortego, M.I.; Lionello, Piero; Sanchez-Arcilla, A.
local.citation.publicationNameApplied ocean research
local.citation.volume65
local.citation.startingPage192
local.citation.endingPage205


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