Background
European wind storms cause insured losses of around €1.4 billion per year. However, these losses fluctuate over time, making it challenging for insurers to estimate their financial exposure. Previous work has found that year-to-year variations in European wind storms are related to patterns of large-scale atmospheric circulation. However, relatively little is known about multi-decadal variability in European wind storms and the ability of climate forecasts to predict these hazards and provide actionable information to insurers. In particular, climate models struggle to capture atmospheric circulation variability. This means estimated current and future wind storm risks based on climate models need to be carefully interpreted using a combination of physical science and decision theory. We will support you to develop an exciting project related to European wind storms that addresses cutting-edge societally-relevant research questions at the interface of climate and decision sciences.
PhD Opportunity
Some example topics that could be explored are:
• What drives multi-decadal variability in European wind storms?
Understanding the nature of long timescale variability in European wind storm risk could help insurers to price policies. This question could be addressed using long-term observations to characterise extreme wind storms on timescales of decades and link this with population data to estimate losses. This could focus on the statistics of wind storms or the risk of specific impactful events. The fluctuations could be related to climate drivers like sea surface temperature variability.
• Can climate forecasts predict decadal variability in European wind storms?
Evaluating whether climate forecasts skilfully predict European wind storm risk and its variations through time is crucial for whether climate forecasts can be used by insurers. This question could involve analysing decadal climate forecasts for the recent past and comparing the forecasted wind storms with observations to understand whether there is skill and if so, what are the sources of predictability.
• Can decadal climate forecasts of wind storms support planning and decision making by insurers?
All forecasts contain uncertainties which grow for longer-term predictions due to weaker predictable signals. Understanding forecast uncertainties and the tolerance of users to incorporate uncertainties in their decision making is crucial for developing climate services. This question could involve developing novel methods for assessing the uncertainties and linking directly to decision-making.
These are example topics and we are happy to discuss others. The project is supervised by Prof Amanda Maycock (Earth & Environment, Leeds), Prof Jennifer Catto (Maths & Statistics, Exeter) and Prof Barbara Summers (Business School, Leeds). Lloyds Banking Group are CASE partner. Dr Oliver Halliday will provide the context for how Lloyds Banking make decisions about their products (e.g. using catastrophe models).
Other information
We are seeking students with a quantitative background (e.g. Atmospheric Science, Physics, Maths, Engineering, Computer Science) and an interest in decision science who want to apply their skills to a problem of strong societal consequence and with a direct industrial application.
https://environment.leeds.ac.uk/see/staff/1404/professor-amanda-maycock
https://business.leeds.ac.uk/research-cdr/staff/357/professor-barbara-summers
https://experts.exeter.ac.uk/25960-jennifer-catto
Pages 1-6 of https://www.metoffice.gov.uk/binaries/content/assets/metofficegovuk/pdf/research/ukcp/ukcp18-factsheet-storms.pdf
https://nhess.copernicus.org/articles/23/2841/2023/
https://www.nature.com/articles/s41467-023-40102-6
