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Title: Wavelet-based clustering of sea level records
Author: Barbosa, S. M.
Gouveia, S.
Scotto, M. G.
Alonso, A. M.
Keywords: Wavelets
Sea level
Time series
Issue Date: Feb-2016
Publisher: Springer Verlag
Abstract: The classification of multivariate 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.
Peer review: yes
DOI: 10.1007/s11004-015-9623-9
ISSN: 1874-8961
Appears in Collections:CIDMA - Artigos
IEETA - Artigos

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