Clustering Time Series of Sea Levels: Extreme Value Approach
Publication: Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 136, Issue 4
Abstract
In this paper, long hourly tide gauge records from the North Atlantic are analyzed. A new time series clustering approach which combines Bayesian methodology, extreme value theory, and classification techniques is adopted for the analysis of the regional variability of sea-level extremes. The tide gauge records are clustered on the basis of their corresponding predictive distributions for 25-, 50-, and 100-year return values. The results of the cluster analysis show a clear distinction between the higher latitude stations for which the return values are largest and the remaining locations. This distinction reflects in the U.S. east coast the transition between the Scottian shelf and Gulf of Maine area and the mid-Atlantic Bight area. For the stations at lower latitudes the results show a grouping based on return levels that is not a function of geographical proximity but reflects local effects in extreme sea levels associated with the specific location of each tide gauge.
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Acknowledgments
We would like to express our gratitude to the associate editor and the three referees. They offered extremely valuable perspectives on our work and effective suggestions for improvements. The three writers are supported by “Acções Integradas Luso-Espanholas” under the Grants No. UNSPECIFIEDE-83/09 and No. UNSPECIFIEDHP2008-008.
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Information
Published In
Journal of Waterway, Port, Coastal, and Ocean Engineering
Volume 136 • Issue 4 • July 2010
Pages: 215 - 225
Copyright
© 2010 ASCE.
History
Received: Nov 7, 2008
Accepted: Dec 1, 2009
Published online: Dec 28, 2009
Published in print: Jul 2010
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