Windstorm and Flood correlation in UK

Insurers use catastrophe models to assess the risk related to catastrophic events such as floods and windstorms and, in turn, to inform their pricing, manage their risk accumulation, and allocate their capital for regulatory purposes. One of the major challenges when it comes to catastrophe modelling is to ensure that any likelihood of adverse scenarios correlating across different perils is appropriately captured. When this correlation of risk is underestimated, it can lead to weaker financial protection. Insurers’ European catastrophe models generally assume windstorms and inland floods to be independent perils, while recent storm case studies such as Storm Kyrill in 2007 and Storm Desmond in 2015 have suggested that these two hazards occur simultaneously in the same weather systems, increasing joined risk.  The purpose of this study is to quantify the correlation in the UK, by analysing historical wind speed and precipitation extremes. It employed an event-based approach that utilises the Copernicus C3S Footprint dataset, as well as E-OBS daily gridded precipitation data, to investigate whether the windstorms between 1979 to 2021 correlate with precipitation extremes. The Storm Severity Index (SSI), accompanied by a newly developed Precipitation Severity Index (PSI), were used to assess the severity of each windstorm, and inform the subsequent correlation analysis. Among the major findings, it is shown that 1) wind and precipitation extremes exhibit a probability of simultaneous occurrence; 2) the highest SSI (category 1 and 2) windstorms are the most correlated to precipitation extremes; 3) rainfall events with the highest PSI most likely follow a clustering series of storms, leading to prolonged and heavy rainfall (e.g. storm Ciara, 2020 and storm Desmond, 2015); and 4) the SSI severity category of each storm might play a role in whether wind and precipitation extremes occur in the same location or not. The key takeaway of this study suggests the importance of incorporating the correlation between these two hazards (wind and precipitation that leads to floods) into insurers' catastrophe models. Further analysis will look at river flow data and wind and flood losses.