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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.
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