I am taking a real long-shot here: Could we use the ever-improving world of seasonal forecasting to help re-jig the timings of our reinsurance contracts? I am probably howling at the moon, but at least allow me to explain.
The North Atlantic Oscillation (NAO) is globally-influenced modulation of the overall wind pattern in the North Atlantic. Historically, it has fluctuated with a timescale of decades as per the graph below. For example, during the 1950s to the 1970s, the NAO was more negative, and became more positive during the 1980s and 1990s.
Typically, in the positive NAO seasons, we expect the airflow approaching North-West Europe to come from the Atlantic – bringing with it the potential for windstorms. In a NAO negative phase, winters are typically more dominated by quieter weather with more high pressure preventing the transit of low-pressure systems through North-West Europe.
Recent work from the Met Office has highlighted a level of skill in forecasting the state of the North Atlantic Index across a forthcoming winter: but how does knowledge of the forthcoming North Atlantic Oscillation help us, and how could we use it?
A fair amount of European wind contracts renew at January 1st. This means that a year’s contract spans two half-winter seasons: but the second half-winter season is 9 months after the inception of the contract: arguably too far ahead in time for any ‘usable’ accuracy in long-range forecasts.
However, for those contracts that begin in September or October for example, there is a whole windstorm season within that year’s contract, beginning straight after the inception of the contract - with the potential to benefit from seasonal forecasts for the entire forthcoming winter.
Some recent work I have been doing at the University of Reading, funded by the Lighthill Risk Network and Climate-KIC was involved with understanding the shift of windstorm risk over time. However, we’ve also taken the opportunity to look at risk during simulated winters with positive and negative NAO.
The simulation we used had 6,100 winters. The chart to the right shows the EP curve difference between positive and negative NAO years.
The difference is pretty marked: positive NAO winters have a much higher risk, as is evidenced by the EP curve here.
Whether this sizeable demarcation between positive and negative NAO winters is simply an artefact of the model is yet to be understood, but if it is representative, then clearly the data suggests that (accurate) knowledge of the forthcoming winter NAO would make quite a difference in the pricing of a contract.
We’ve used the Aggregate Exceedance Probability AEP curve here to show the sumtotal of losses in a season, which brings us to another potentially important element of the NAO phase study: clustering of storms. "The chart below highlights the number of >€0.5bn events in any one winter across all the simulations, again binned by positive and negative NAO.
Clearly, positive NAO phases have a bias towards more storms in any one season. To contrast the two bar charts simply, the chance of a multiple (>=2) event season in a negative NAO phase is around 16% (crudely, once every 6 years), whereas in a positive NAO phase it’s 35% - more like once every 3 years.
Things are more marked when we look in the tail: the chance of 3 events or more changes from around 1 in every 35 years to 1 in every 10 years when comparing negative and positive NAO years, respectively.
The big caveat here is that it is simply a model, nothing more, however it is worth adding that in discussions of these results with AIR, they were able to confirm a sizeable magnitude of difference in EP losses between positive and negative NAO phases in their European Windstorm Model, so maybe these results are more than just “interesting”.
If the marked difference between positive and negative NAO seasons is not just an artefact of the model and we are starting to see proper skill in forecasting the state of the NAO season - would it not be beneficial for all risk-takers to align the reinsurance year for European wind contracts to benefit from the ever-improving skill of seasonal forecasting?
Read more articles by Richard Dixon here.
About Richard Dixon:
Richard has spent the last 17 years in the insurance industry building and researching catastrophe models at a model vendor and then evaluating them whilst working for brokers and reinsurers. He now is a consultant to the insurance industry at CatInsight, specialising in model evaluation. Most recently he was Head of Catastrophe Research at Hiscox, being responsible for their internal "View of Risk". Prior to working in the insurance industry, he obtained a PhD in meteorology at Reading University, specialising in extra-tropical cyclones. For more information, visit Richard Dixon's blog: www.catinsight.co.uk.
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