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Spatial and temporal clustering analysis of extreme wave events around the UK coastline

Spatial and temporal clustering analysis of extreme wave events around the UK coastline
Spatial and temporal clustering analysis of extreme wave events around the UK coastline
Densely populated coastal regions are vulnerable to extreme wave events, which can cause loss of life and considerable damage to coastal infrastructure and ecological assets. Here, an event-based analysis approach, across multiple sites, has been used to assess the spatial footprint and temporal clustering of extreme storm-wave events around the coast of the United Kingdom (UK). The correlated spatial and temporal characteristics of wave events are often ignored even though they amplify flood consequences. Waves that exceeded the 1 in 1-year return level were analysed from 18 different buoy records and declustered into distinct storm events. In total, 92 extreme wave events are identified for the period from 2002 (when buoys began to record) to mid-2016. The tracks of the storms of these events were also captured. Six main spatial footprints were identified in terms of extreme wave events occurrence along stretches of coastline. The majority of events were observed between November and March, with large inter-annual differences in the number of events per season associated with the West Europe Pressure Anomaly (WEPA). The 2013/14 storm season was an outlier regarding the number of wave events, their temporal clustering and return levels. The presented spatial and temporal analysis framework for extreme wave events can be applied to any coastal region with sufficient observational data and highlights the importance of developing statistical tools to accurately predict such processes.
SEA LEVEL, waves, flooding, cliamte change
1054-3139
Santos, Victor Malagon
c2dc574f-b241-4b29-8efe-02aae5d0ab61
Haigh, Ivan
945ff20a-589c-47b7-b06f-61804367eb2d
Wahl, Thomas
fbac2b37-5fd8-41d1-85b1-024e9f61ff34
Santos, Victor Malagon
c2dc574f-b241-4b29-8efe-02aae5d0ab61
Haigh, Ivan
945ff20a-589c-47b7-b06f-61804367eb2d
Wahl, Thomas
fbac2b37-5fd8-41d1-85b1-024e9f61ff34

Santos, Victor Malagon, Haigh, Ivan and Wahl, Thomas (2017) Spatial and temporal clustering analysis of extreme wave events around the UK coastline. ICES Journal of Marine Science, 5 (3), [28]. (doi:10.3390/jmse5030028).

Record type: Article

Abstract

Densely populated coastal regions are vulnerable to extreme wave events, which can cause loss of life and considerable damage to coastal infrastructure and ecological assets. Here, an event-based analysis approach, across multiple sites, has been used to assess the spatial footprint and temporal clustering of extreme storm-wave events around the coast of the United Kingdom (UK). The correlated spatial and temporal characteristics of wave events are often ignored even though they amplify flood consequences. Waves that exceeded the 1 in 1-year return level were analysed from 18 different buoy records and declustered into distinct storm events. In total, 92 extreme wave events are identified for the period from 2002 (when buoys began to record) to mid-2016. The tracks of the storms of these events were also captured. Six main spatial footprints were identified in terms of extreme wave events occurrence along stretches of coastline. The majority of events were observed between November and March, with large inter-annual differences in the number of events per season associated with the West Europe Pressure Anomaly (WEPA). The 2013/14 storm season was an outlier regarding the number of wave events, their temporal clustering and return levels. The presented spatial and temporal analysis framework for extreme wave events can be applied to any coastal region with sufficient observational data and highlights the importance of developing statistical tools to accurately predict such processes.

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Accepted/In Press date: 10 July 2017
e-pub ahead of print date: 14 July 2017
Keywords: SEA LEVEL, waves, flooding, cliamte change

Identifiers

Local EPrints ID: 412754
URI: http://eprints.soton.ac.uk/id/eprint/412754
ISSN: 1054-3139
PURE UUID: 4d6c1f95-1694-469f-b9b9-19dc41c25a39
ORCID for Ivan Haigh: ORCID iD orcid.org/0000-0002-9722-3061

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Date deposited: 01 Aug 2017 16:31
Last modified: 28 Apr 2022 01:57

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Contributors

Author: Victor Malagon Santos
Author: Ivan Haigh ORCID iD
Author: Thomas Wahl

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