Global application of a regional frequency analysis on extreme sea levels

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

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

Global application of a regional frequency analysis on extreme sea levels

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

Fathom-REPRESA flood hazard data

Flood hazard data from Fathom for Mozambique, Malawi and Madagascar. Donated in support of the REPRESA project