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Application of a global coastal regional frequency analysis

Application of a global coastal regional frequency analysis
Application of a global coastal regional frequency analysis
Inundation from storm tides and ocean waves is one of the greatest threats coastal communities endure; a threat that is increasing with sea-level rise and changes in storminess. Stakeholders require high resolution hazard data to make informed decisions on how best to mitigate and adapt to coastal flooding. Using a synthesis of observational, hindcast and modelled data, we apply a regional frequency analysis (RFA) approach to characterise extreme water level exceedance probabilities across all global coastlines. This is the first time an RFA has been applied to coastal water levels on a global scale. Wave setup is included in regions which are considered exposed to onshore wave action. The RFA is shown to increase return levels in areas prone to tropical cyclones. Using Cyclone Yasi as a case-study, we detail the RFA methodology and demonstrate how it uses information from rare, extreme events to better characterise return period water levels in areas which haven’t yet been impacted in the observational record, simply due to chance. The results are output at approximate 1km resolution along the entire global coastline (excluding Antarctica) and have been corrected for use with digital elevation models, for applications such as inundation modelling.
Collings, Thomas
65369a07-9e83-4b89-8ad2-d32f8369ed19
Quinn, Niall
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Haigh, Ivan
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Green, Joshua
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Probyn, Izzy
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Wilkinson, Hamish
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Collings, Thomas
65369a07-9e83-4b89-8ad2-d32f8369ed19
Quinn, Niall
7e7288ed-f2b8-4918-aa16-65ae08cfd901
Haigh, Ivan
945ff20a-589c-47b7-b06f-61804367eb2d
Green, Joshua
b20fb9a5-1fd9-4646-96b0-64620bed7aa3
Probyn, Izzy
ec953e6c-99db-4d18-8e45-b09b1b8da8f0
Wilkinson, Hamish
8e2d0c8a-c7d3-44d8-a747-d0064a8fa38d

Collings, Thomas, Quinn, Niall, Haigh, Ivan, Green, Joshua, Probyn, Izzy and Wilkinson, Hamish (2023) Application of a global coastal regional frequency analysis. EGU General Assembly, , Vienna, Austria. 24 - 28 Apr 2023. 1 pp . (doi:10.5194/egusphere-egu23-8604).

Record type: Conference or Workshop Item (Paper)

Abstract

Inundation from storm tides and ocean waves is one of the greatest threats coastal communities endure; a threat that is increasing with sea-level rise and changes in storminess. Stakeholders require high resolution hazard data to make informed decisions on how best to mitigate and adapt to coastal flooding. Using a synthesis of observational, hindcast and modelled data, we apply a regional frequency analysis (RFA) approach to characterise extreme water level exceedance probabilities across all global coastlines. This is the first time an RFA has been applied to coastal water levels on a global scale. Wave setup is included in regions which are considered exposed to onshore wave action. The RFA is shown to increase return levels in areas prone to tropical cyclones. Using Cyclone Yasi as a case-study, we detail the RFA methodology and demonstrate how it uses information from rare, extreme events to better characterise return period water levels in areas which haven’t yet been impacted in the observational record, simply due to chance. The results are output at approximate 1km resolution along the entire global coastline (excluding Antarctica) and have been corrected for use with digital elevation models, for applications such as inundation modelling.

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EGU23-8604-print - Version of Record
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More information

In preparation date: 15 May 2023
e-pub ahead of print date: 29 June 2023
Venue - Dates: EGU General Assembly, , Vienna, Austria, 2023-04-24 - 2023-04-28

Identifiers

Local EPrints ID: 478369
URI: http://eprints.soton.ac.uk/id/eprint/478369
PURE UUID: 3a454975-7d00-4978-9a21-f10a99548e22
ORCID for Ivan Haigh: ORCID iD orcid.org/0000-0002-9722-3061
ORCID for Joshua Green: ORCID iD orcid.org/0000-0002-2230-4633

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Date deposited: 29 Jun 2023 16:42
Last modified: 17 Mar 2024 04:13

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Contributors

Author: Thomas Collings
Author: Niall Quinn
Author: Ivan Haigh ORCID iD
Author: Joshua Green ORCID iD
Author: Izzy Probyn
Author: Hamish Wilkinson

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