Please use this identifier to cite or link to this item:
|Title:||Wavelet-based clustering of sea level records|
|Author:||Barbosa, S. M.|
Scotto, M. G.
Alonso, A. M.
|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.|
|Appears in Collections:||CIDMA - Artigos|
IEETA - Artigos
Files in This Item:
|2016 Barbosa-MathGeosci.pdf||Main article||2.2 MB||Adobe PDF||Request a copy|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.