GreyswanstormsurgesposegreaterriskofEastCoastfloodingthanclimatechangeKevinHosburgh,IvanHaighJudithWolf,MichelaDeDominicis,TimHunt,SeanLongfeild,HugoWinter,AmelieJoly-LaugelAssociateProfessorincoastalOceanographyOceanandEarthScience,NationalOceanographyCentre,UniversityofSouthampton
1. Introduction • Current observational record of extreme sea
levels is not long enough to derive robust statistics for the most extreme events:
• Two big past events in North Sea (31st Jan – 1st Feb 1953; 5-6 Dec 2013)
Jan 1953 Dec 2013
Begs the obvious question – could they have been worse?
1. Introduction “Grey swan” as a metaphor for a high-consequence event that we might expect on the grounds of natural variability, is physically credible, but is not in our record;
The SUCCESS project (Synthesising Unprecedented Coastal Conditions: Extreme Storm Surges) - worked with partners (EA & EDF Energy) with significant assets at risk from extreme water levels.
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2. Methods
A. Guided by complete analysis of all North Atlantic storms since 1950 - we created 6 artificial storms based on Dec 2013 - NWP tool (Met Office):
B. Simulated storm surge and waves – 12 km NW European Shelf numerical model.
lower central pressure by 1
standard deviation (SD)
make central pressure the
minimum obtained for each location
slow movement of depression
down by 1 SD
speed movement of depression up
by 1 SD
adjusted to the 1953
storm track
Move storm track south by
1SD
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3. Results
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3. Results
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3. Results
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3. Results
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4. Conclusions
• With grey swan storms, we were able to produce storm surges at all ports along the UK East Coast that were consistently higher (up to 1 m) than those experienced during the December 2013 event;
• We found that the most extreme storm surges in the southern North Sea and Thames Estuary were caused by slowing down the speed of the storm;
• Natural variability of weather could be as important as mean sea level change (1 m by 2100) in driving coastal extreme sea levels over the next century; and
• This research was limited in time and budget and was only able to synthesize a relatively small number of grey swan storms; further understanding gained by developing techniques to replicate this approach with a much larger statistical sample of storms.
GreyswanstormsurgesposegreaterriskofEastCoastfloodingthanclimatechangeKevinHosburgh,IvanHaighJudithWolf,MichelaDeDominicis,TimHunt,SeanLongfeild,HugoWinter,AmelieJoly-LaugelAssociateProfessorincoastalOceanographyOceanandEarthScience,NationalOceanographyCentre,UniversityofSouthampton
