Preprints
https://doi.org/10.5194/egusphere-2023-2267
https://doi.org/10.5194/egusphere-2023-2267
23 Oct 2023
 | 23 Oct 2023

Global application of a regional frequency analysis on extreme sea levels

Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates

Abstract. Coastal regions face increasing threats from rising sea levels and extreme weather events, highlighting the urgent need for accurate assessments of coastal flood risk. This study presents a novel approach to estimating global Extreme Sea Level (ESL) exceedance probabilities, using a Regional Frequency Analysis (RFA) approach. The research combines observed and modelled hindcast data to produce a high-resolution (~1 km) dataset of ESL exceedance probabilities, including wave setup, along the entire global coastline, excluding Antarctica.

The RFA approach offers several advantages over traditional methods, particularly in regions with limited observational data. It overcomes the challenge of short and incomplete observational records by substituting long historical records with a collection of shorter but spatially distributed records. This spatially distributed data not only retains the volume of information but also addresses the issue of sparse tide gauge coverage in less populated areas and developing nations. The RFA process is illustrated using Cyclone Yasi (2011) as a case study, demonstrating how the approach can significantly improve the characterisation of ESLs in regions prone to tropical cyclone activity.

In conclusion, this study provides a valuable resource for quantifying global coastal flood risk, offering an innovative methodology that can contribute to preparing for, and mitigating against, coastal flooding.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Review comment on egusphere-2023-2267', Anonymous Referee #1, 16 Nov 2023
    • AC1: 'Reply on RC1', Thomas Collings, 28 Feb 2024
  • RC2: 'Comment on egusphere-2023-2267', Anonymous Referee #2, 18 Dec 2023
    • AC2: 'Reply on RC2', Thomas Collings, 28 Feb 2024
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates

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Short summary
Coastal areas are at risk of flooding from rising sea levels and extreme weather events. This study uses a new way to figure out how likely coastal flooding is around the world. The method uses data from observations and computer models to create a detailed map of where these floods might happen at the coast. The approach can predict flooding in areas where there is little or no data. The results can be used to help get ready for and prevent this type of flooding.