Wavelet-Based Clustering of Sea Level Records

dc.contributor.author Susana Alexandra Barbosa en
dc.contributor.author Gouveia,S en
dc.contributor.author Scotto,MG en
dc.contributor.author Alonso,AM en
dc.date.accessioned 2017-12-14T17:50:47Z
dc.date.available 2017-12-14T17:50:47Z
dc.date.issued 2016 en
dc.description.abstract The classification ofmultivariate time series in terms of their corresponding temporal dependence patterns is a common problem in geosciences, particularly for large datasets resulting from environmental monitoring networks. Here a wavelet-based clustering approach is applied to sea level and atmospheric pressure time series at tide gauge locations in the Baltic Sea. The resulting dendrogram discriminates three spatially-coherent groups of stations separating the southernmost tide gauges, reflecting mainly high-frequency variability driven by zonal wind, from the middle-basin stations and the northernmost stations dominated by lower-frequency variability and the response to atmospheric pressure. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/4120
dc.identifier.uri http://dx.doi.org/10.1007/s11004-015-9623-9 en
dc.language eng en
dc.relation 6363 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Wavelet-Based Clustering of Sea Level Records en
dc.type article en
dc.type Publication en
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