Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/16641
Title: | Wavelet-based clustering of sea level records |
Author: | Barbosa, S. M. Gouveia, S. Scotto, M. G. Alonso, A. M. |
Keywords: | Wavelets Clustering 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 |
URI: | http://hdl.handle.net/10773/16641 |
DOI: | 10.1007/s11004-015-9623-9 |
ISSN: | 1874-8961 |
Appears in Collections: | CIDMA - Artigos IEETA - Artigos |
Files in This Item:
File | Description | Size | Format | |
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2016 Barbosa-MathGeosci.pdf | Main article | 2.2 MB | Adobe PDF |
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