Mathematical Geosciences

, Volume 48, Issue 2, pp 149–162

Wavelet-Based Clustering of Sea Level Records

  • S. M. Barbosa
  • S. Gouveia
  • M. G. Scotto
  • A. M. Alonso

DOI: 10.1007/s11004-015-9623-9

Cite this article as:
Barbosa, S.M., Gouveia, S., Scotto, M.G. et al. Math Geosci (2016) 48: 149. doi:10.1007/s11004-015-9623-9


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 

Funding information

Funder NameGrant NumberFunding Note
Fundação para a Ciência e a Tecnologia
  • SFRH/BPD/87037/2012
Fundação para a Ciência e a Tecnologia
  • UID/EEA/50014/2013
Fundação para a Ciência e a Tecnologia
  • UID/MAT/04106/2013, UID/CEC/00127/2013, PEst-OE/EEI/UI0127/2014
Ministerio de Economía y Competitividad
  • ECO2011-25706 and ECO2012-38442

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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