PhD position on Extreme Weather and Infrastructure Risks
University of Birmingham, UK
Closing date: 8 January 2025
There is a phd opportunity at the University of Birmingham: The Midlatitude Jet and Multivariate Compound Weather Extremes: Risks to UK Infrastructure
Storm Isha (21st -22nd January 2024) brought gusts of 69-81 mph to the northern UK. Damage to infrastructure resulted in widespread power cuts and travel disruption. Storm Isha was closely followed by Storm Jocelyn (22nd-24th Jan 2024), driving further damage and hindering the response to Storm Isha. The number of extreme extratropical storms is projected to increase throughout the 21st century (Priestley and Catto, 2022) motivating a pressing need to quantify the risks such events pose.
Critical infrastructure such as power and rail are vulnerable to a range of weather hazards, including wind, temperature extremes and heavy rainfall (e.g. Jia et al., 2024). Compound events are combinations of hazards that drive increased risk (e.g. Zscheischler et al. 2020). These include successive hazards that lead to more severe impacts, and events where multiple variables drive damage, e.g. combined extreme rainfall and wind. Such extremes are significantly driven by circulation patterns in the mid- to upper-troposphere (e.g. Röthlisberger et al. 2016); for example Storms Isha & Jocelyn were influenced by a stronger than normal midlatitude westerly jet stream. Methods which can anticipate the impact to infrastructure from these extremes are of great importance for improving infrastructure resilience.
This PhD project will identify the key meteorological drivers of infrastructure failure in the UK, with the aim to estimate current and future risk. It will begin by exploring how cutting-edge statistical methods can facilitate the integration of infrastructure fault and meteorological data, to better identify the weather regimes and jet structures underlying severe impacts to infrastructure. The next step is to estimate present-day risk, exploring plausible but unseen extreme events (Osinski et al., 2016; Thompson et al., 2017) and future risk via analysis of jet changes and jet-surface weather linkages in climate change projections. Depending on student preferences, there is also scope to explore seasonal forecasting of compound extremes and infrastructure risk via our Met Office collaboration.
This project would best suit a student with a numerical background, for example Meteorology, Physics, or Maths, with experience coding in Python or similar (e.g. R, Matlab).