Wavelet-Based Clustering of Sea Level Records

Thumbnail Image
Date
2016
Authors
Susana Alexandra Barbosa
Gouveia,S
Scotto,MG
Alonso,AM
Journal Title
Journal ISSN
Volume Title
Publisher
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.
Description
Keywords
Citation