Assessing the temporal clustering of coastal storm tide hazards under natural variability in a near 500-year model run

Abstract

The temporal clustering of storms can present successive natural hazards for coastal areas in the form of extreme sea levels, storm surges and waves. Studies have investigated the prevalence of the temporal clustering of such hazards but are hindered by the rarity of the phenomena combined with short records and a lack of data availability around the coastline. This has made it difficult to determine if the levels of clustering reported were typical for the location or were being masked by natural variability or climate change over different timescales. In this study, we assess a near 500-year model simulation of extreme sea levels and storm surges forced with pre-industrial meteorological conditions to quantify the levels of temporal clustering seen from natural variability around Great Britain. We then utilise a 50-year rolling window to see how clustering statistics can change through time when dealing with time periods that are representative of the average length of a record in the United Kingdom National Tide Gauge Network. When using near 500-year timeseries, we highlight that many clustering statistics return values close to their statistical expectancies. However, when analysing discrete 50-year windows, results can vary dramatically. The percentage of years with an extreme sea level or surge exceedance at a given location at the 1 in 1-, 5-, and 10-year return level, can vary by up to ~33%, ~24%, and ~18%, the mean number of days between consecutive sea level or surge exceedances can vary by ~231, ~14,780, and ~17,793 days, and the extremal index can vary by ~0.37, ~0.64, and ~0.79, respectively. Although these results represent the best estimate of the levels of clustering to be expected under natural variability, a comparison of the longest records in the tide gauge network and their nearest model grid nodes shows a tendency for the model to underestimate the clustering statistics that are calculated from the measured data (apart from the extremal index). As such, these can be considered to represent the minimum levels of temporal clustering around Great Britain, as the potential underestimation of clustering, combined with climatic change and sea level rise, means that the temporal clustering of sea levels and storm surges are likely to be far greater over the next 500 years.

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Identifiers

ORCID for Luke Joe Jenkins: orcid.org/0000-0002-7206-7242

ORCID for Ivan D. Haigh: orcid.org/0000-0002-9722-3061

ORCID for Hachem Kassem: orcid.org/0000-0002-5936-6037

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