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|Title:||Wavelet-Based Clustering of Sea Level Records|
|Authors:||Susana Alexandra Barbosa|
|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.|
|Appears in Collections:||CSIG - Articles in International Journals|
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