Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> Our ability to quantify the likelihood of present-day extreme sea level (ESL) events is limited by the length of tide gauge records around the UK, and this results in substantial uncertainties in return level curves at many sites. In this work, we explore the potential for a state-of-the-art climate model, HadGEM3-GC3, to help refine our understanding of present-day coastal flood risk associated with extreme storm surges, which are the dominant driver of ESL events for the UK and wider European shelf seas. We use a 483-year present-day control simulation from HadGEM3-GC3-MM (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M1" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">4</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="20pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="f7b7a5d5bfd5c45cef6c295312dc1896"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="nhess-21-3693-2021-ie00001.svg" width="20pt" height="14pt" src="nhess-21-3693-2021-ie00001.png"/></svg:svg></span></span><span class="inline-formula"><sup>â</sup></span> ocean, approx. 60âkm atmosphere in mid-latitudes) to drive a north-west European shelf seas model and generate a new dataset of simulated UK storm surges. The variable analysed is the skew surge (the difference between the high water level and the predicted astronomical high tide), which is widely used in analysis of storm surge events. The modelling system can simulate skew surge events comparable to the catastrophic 1953 North Sea storm surge, which resulted in widespread flooding, evacuation of 32â000 people, and hundreds of fatalities across the UK alone, along with many hundreds more in mainland Europe. Our model simulations show good agreement with an independent re-analysis of the 1953 surge event at the mouth of the river Thames. For that site, we also revisit the assumption of skew surge and tide independence. Our model results suggest that at that site for the most extreme surges, tideâsurge interaction significantly attenuates extreme skew surges on a spring tide compared to a neap tide. Around the UK coastline, the extreme tail shape parameters diagnosed from our simulation correlate very well (Pearson's <span class="inline-formula"><i>r</i></span> greater than 0.85), in terms of spatial variability, with those used in the UK government's current guidance (which are diagnosed from tide gauge observations), but ours have smaller uncertainties. Despite the strong correlation, our diagnosed shape parameters are biased low relative to the current guidance. This bias is also seen when we replace HadGEM3-GC3-MM with a reanalysis, so we conclude that the bias is likely associated with limitations in the shelf sea model used here. Overall, the work suggests that climate model simulations may prove useful as an additional line of evidence to inform assessments of present-day coastal flood risk.
Highlights
The variable analysed is the skew surge, 10 which is widely used in analysis of storm surge events
Coles (2001) discusses some of the advantages and disadvantages of the statistical modelling approach; he says: “Caution is required in the interpretation of return level inferences especially for return levels corresponding to long return periods... estimates and their measures of precision are based on an assumption that the model is correct.”
Coles (2001) goes on to say: “ Though the [extreme 55 value statistical] model is supported by mathematical argument, its use in extrapolation is based on unverifiable assumptions, and measures of uncertainty on return levels should properly be regarded as lower bounds that could be much greater if uncertainty due to model correctness were taken into account.”
Summary
Around £150 billion of assets and 4 million people in the UK are at risk from coastal flooding (Haigh et al, 2017), and estimated damages to the UK from coastal flooding are of the order of £500 million per year (Edwards, 2017). In order to evaluate model performance, modellers use control simulations (with greenhouse gas forcing fixed at either pre-industrial or present-day levels) which 75 may extend over many hundreds or even thousands of years Ensemble simulations provide another potential source of data effectively covering a much longer period than the observations. Using the data from such simulations provides a further line of evidence in the effort to predict the magnitude and frequency of unprecedented events This method was applied to seasonal rainfall totals in the UK (Thompson et al, 2017), and Grabemann et al (2020) applied the method to extreme storm surges for locations in the German Bight, successfully identifying a number of simulated water levels exceeding those in the observational 80 record since 1906. Typical RMS errors when forced with numerical weather prediction model atmospheric data are of the order of 10 cm
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