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dc.contributor.authorGil Alana, Luis A. 
dc.contributor.authorMonge Moreno, Manuel 
dc.contributor.authorRomero Rojo, María Fátima
dc.date.accessioned2020-01-16T13:01:39Z
dc.date.available2020-01-16T13:01:39Z
dc.date.issued2019
dc.identifier.issn0739-0572spa
dc.identifier.urihttp://hdl.handle.net/10641/1809
dc.description.abstractThis paper addresses analysis of the global monthly sea surface temperatures using a reconstructed dataset that goes back to 1884. We use fractional integration methods to examine features such as persistence, seasonality, and time trends in the data. The results show that seasonality is a relevant issue, finding evidence of seasonal unit roots. With the seasonal component removed, persistence is also very significant, and, when looking at the data month by month, evidence of significant linear trends is detected in all cases. According to these results, monthly sea surface temperatures increase by between 0.07° and 0.11°C every 100 years.spa
dc.language.isoengspa
dc.publisherJournal of Atmospheric and Oceanic Technologyspa
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectStatistical techniquesspa
dc.subjectTime seriesspa
dc.titleSea Surface Temperatures: Seasonal Persistence and Trends.spa
dc.typearticlespa
dc.description.versionpre-printspa
dc.rights.accessRightsopenAccessspa
dc.description.extent550 KBspa
dc.identifier.doi10.1175/JTECH-D-19-0090.1spa
dc.relation.publisherversionhttps://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-19-0090.1spa


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Atribución-NoComercial-SinDerivadas 3.0 España
Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España