Recipient organisationUniversity of ReadingSource-published name: University of Reading
Funding£638K
PeriodMar 2026 — Sept 2029
In plain English
AI plain-English summary
Storm Ciarán, which killed 16 people and cut power to 1.2 million homes in France, was driven by a rare type of weather system called a diabatic Rossby wave (DRW)—and no one has yet studied how climate change will affect them. Most research on extreme winter storms has focused on their physical traits, like size and wind speed, rather than the mechanisms that drive them. DRWs are small, cloud-heating-driven systems that can explosively deepen into intense cyclones when they interact with the jet stream. Because they rely on moisture, higher humidity from a warming world will almost certainly strengthen them. Yet current climate models may not represent these small features accurately, raising doubts about projections of future extreme storms. This project will use a new suite of high-resolution climate simulations—previously impossible due to limits in model resolution—to test how well models capture DRWs and how they might change. It will also develop a detection tool for the Met Office to improve forecasting of these high-impact events. If successful, the work will give infrastructure planners and emergency services clearer warnings about the worst-case winter storms to come.
View original technical description
Our research will provide improved confidence in how climate change will impact a specific type of extreme extratropical cyclone (ETC). ETCs, also known as winter storms, pose a major weather hazard in the mid-latitudes due to their associated high winds and heavy rainfall. Despite substantial effort understanding how climate change will influence ETCs, important uncertainties remain. The emerging consensus is a trend towards slightly fewer ETCs overall in a warmer world, with notable regional exceptions including northwest Europe. But, concerningly, projections also suggest an increase in both the number and intensity of the most extreme ETCs across many regions. A complication in assessing future ETC risk is the wide variability between cases, both in terms of their physical characteristics (e.g. size, structure, intensity, impacts) and their fundamental driving mechanisms (e.g. the role of upper- vs. lower-tropospheric structures, and the role of cloud latent heating). Any statements about future changes necessarily combine both aspects, but research to date has overwhelmingly focussed on the physical characteristics rather than the driving mechanisms. Here we take the latter, mechanistic, approach and focus on how climate change will impact one specific, but highly pertinent, class of ETC: diabatic Rossby waves (DRWs). DRWs are a small and relatively rare type of weather system driven by cloud latent heating. They are important because they can explosively deepen into intense ETCs if they favourably interact with the jet stream. Storm Ciarán (November 2023) is a recent example of a DRW system developing into an intense ETC which caused highly damaging winds over the UK and northwest Europe including 16 fatalities and the loss of electricity for 1.2 million people in France. In fact, a recent study demonstrated their importance by estimating that 15% of all the explosively deepening ETCs in the Euro-Atlantic region (~5 storms/year) exhibit DRW precursors. The pivotal role of cloud latent heating in their development means it is virtually inevitable that climate change will impact DRWs: higher specific humidity levels will result in stronger cloud latent heating. However, there has been no assessment to date of how climate change will impact DRWs, nor the extent to which current state-of-the-art climate models represent them. Given their small size and diabatic nature, we hypothesise that (1) the projected increase in extreme ETCs in future is in part due to an increased dominance of the DRW mechanism, and (2) that current climate models struggle to represent such features faithfully, thereby raising a crucial question of the reliability of future projections of the most extreme ETCs. We will utilise the unique capabilities of a new large suite of high-resolution climate model simulations to assess for the first time the ability of state-of-the-art climate models to simulate DRWs and their response to climate change. This analysis has not been possible previously due to limitations in model resolution and output diagnostics. We will also use Met Office operational global ensemble forecasts to assess DRW predictability and support the implementation of a novel DRW detection tool to facilitate forecasting of these high-impact events. Our mechanistic, process-based evaluation of DRWs will inform societal preparations for worst-case ETCs, leading to appropriate infrastructure development and mitigation plans for future climate risk.
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