Using seasonal forecasts to enhance our understanding of extreme wind and precipitation impacts from extratropical cyclones

Abstract. Considerable effort is spent at insurance and reinsurance companies to estimate the risk posed by extratropical cyclones (ETCs). Among these risks, strong near surface wind speeds and heavy precipitation can be particularly damaging, threatening infrastructure, human life, and billions of pounds in insured losses. Here, we use nearly 700 years' worth of extended wintertime seasonal forecast model output to estimate the impacts of wind and precipitation associated with European ETCs. Insured losses from winds are estimated with a storm severity index (SSI) and risk of flooding estimated from country-aggregated precipitation totals. Using the Met Office's seasonal forecast model, we follow the UNprecedented Simulated Extreme ENsemble (UNSEEN) method, here applied to ETC impacts. After demonstrating that the model represents ETCs with good accuracy, the likelihood of occurrence of unprecedented ETC impacts are quantified for several countries within Europe. The probability that an ETC will have an impact be more extreme than any observed (i.e. an unprecedented or unseen ETC impact) is generally between 0.5 % and 1.6 % for wind and between 0.2 % and 0.7 % for precipitation across the countries considered. The North Atlantic Oscillation (NAO) is shown to be strongly related to European ETC impact from wind: strongly positive and negative NAO values approximately double and halve the likelihood of an unprecedented wind impact, respectively. The state of the NAO is largely unrelated to the likelihood of extreme cyclone-related precipitation. The dataset created allows for the estimation of impacts from high-return-period storms, which is of great interest to insurance companies that must be prepared for the potential costs incurred.