Spatio-temporal analysis of extreme coastal hazards during the 2013–14 UK winter storms: integrated observations and high resolution synoptic CFD storm-surge modelling

 

The 2013–14 UK winter storm series featured an unusually high number of storm events that caused 10 deaths, widespread flooding, coastal erosion, and damage to critical infrastructure. Official direct damage estimates of £1.3 billion were likely too low because they did not account for indirect disruptions, highlighting the broad economic and structural impacts of large storms. The observational analysis drew on wave, tidal, wind, and precipitation data from 44 tide gauges, 52 wave buoys, and 15 climate stations, giving good coverage of the UK coastline. Findings showed that thresholds for storm surge and wave height were exceeded more often than in previous winters, indicating unusually frequent episodes of storm surges and extreme waves. The maximum storm surge recorded at Lowestoft during Storm Xaver reached 2.2 m and contributed to extensive damage along the East Coast.

To complement observations, storm surge propagation was simulated using the Regional Ocean Modelling System (ROMS), providing a detailed 1 km resolution around the entire UK coastline. The simulations were validated against tide gauge data and successfully reproduced surge amplification from the North Atlantic into the UK’s shallow coastal zones, supporting their use in a nationwide coastal hazard prediction framework. Sensitivity tests using multiple nested domain configurations, along with a heuristic method for assigning land–ocean categories to coastal grid cells, improved numerical stability and revealed an optimal domain setup that balanced performance and computational cost. Further analysis offers insights into how climate change, storm tracks, and cyclogenesis influence surge maxima. These results provide practical guidance for early warning systems, infrastructure planning, and coastal management in a changing climate, and they can be applied to global disaster-risk resilience modelling.