Wavelet-Based Clustering of Sea Level Records

• Autor(a) principal: Susana Alexandra Barbosa
• Data de Publicação: 2016
• Outros Autores: Gouveia,S, Scotto,MG, Alonso,AM
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://repositorio.inesctec.pt/handle/123456789/4120; http://dx.doi.org/10.1007/s11004-015-9623-9

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.