Mathematical Geosciences

, Volume 48, Issue 2, pp 149–162 | Cite as

Wavelet-Based Clustering of Sea Level Records

  • S. M. BarbosaEmail author
  • S. Gouveia
  • M. G. Scotto
  • A. M. Alonso


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.


Wavelets Clustering Sea level Time series 



Tide gauge data kindly provided by DMI (K. Madsen), SMHI (T. Hammarklint) and UHSLC. S.M. Barbosa acknowledges support of the FCT—Fundação para a Ciência e a Tecnologia (contract under programme IF2013 and project UID/EEA/50014/2013). This work was supported by the European Regional Development Fund (FEDER) through the COMPETE programme and by the Portuguese Government through the FCT, in the scope of the project UID/MAT/04106/2013 (Centro de I&D em Matemática e Aplicações, and projects PEst-OE/EEI/UI0127/2014 and UID/CEC/00127/2013 (Instituto de Engenharia Electrónica e Informática de Aveiro, IEETA/UA, S. Gouveia acknowledges the postdoctoral grant by FCT (ref. SFRH/BPD/87037/2012). A.M. Alonso acknowledges support of the Ministerio de Economía y Competitividad projects ECO2011-25706 and ECO2012-38442.


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Copyright information

© International Association for Mathematical Geosciences 2015

Authors and Affiliations

  1. 1.INESC TEC-INESC Technology and Science, Rua Dr. Roberto FriasPortoPortugal
  2. 2.Institute of Electronics and Informatics Engineering of Aveiro (IEETA) and CIDMAUniversidade de AveiroAveiroPortugal
  3. 3.CEMAT, Instituto Superior TécnicoUniversidade de LisboaLisboaPortugal
  4. 4.Department of Statistics and Instituto Flores de LemusUniversidad Carlos III de MadridMadridSpain

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