Accounting for Climate Change in Extreme Sea Level Estimation

TL;DR

This paper introduces a novel non-stationary statistical method for estimating extreme sea levels that incorporates climate change effects, improving coastal flood risk assessments.

Contribution

It develops a joint probability approach using a non-stationary GPD model with climate covariates, addressing climate change impacts on extreme sea levels.

Findings

Effective modeling of skew surge trends across coastlines.

Application to UK tide gauge data demonstrates method viability.

Enhanced risk estimates considering climate change effects.

Abstract

Extreme sea level estimates are fundamental for mitigating against coastal flooding as they provide insight for defence engineering. As the global climate changes, rising sea levels combined with increases in storm intensity and frequency pose an increasing risk to coastline communities. We present a new method for estimating extreme sea levels that accounts for the effects of climate change on extreme events that are not accounted for by mean sea level trends. We follow a joint probabilities methodology, considering skew surge and peak tides as the only components of sea levels. We model extreme skew surges using a non-stationary generalised Pareto distribution (GPD) with covariates accounting for climate change, seasonality and skew surge-peak tide interaction. We develop methods to efficiently test for extreme skew surge trends across different coastlines and seasons. We illustrate our methods using data from four UK tide gauges.