PhD Studentship - Understanding the Risk of Damaging and Disruptive U.S. Winter Weather in a Changing Climate

About the Project

Summary of Award

100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate).

Overview of Project

Recent destructive and disruptive extreme U.S. winter weather events in February 2021, December 2022, and January 2024 caused power outages, property damage, business disruption, and fatalities. The February 2021 event, a Cold Air Outbreak (CAO), brought extremely cold Arctic air southwards across the U.S., causing US$ 27.2bn in economic damage (Figure 1). This event was one of the costliest global weather events in 2021 and greatly surpassed historical events, shocking the (re)insurance industry, as damage since 2000 from this hazard had been low. Improving the understanding of this variability is essential for mitigating risk and accurately pricing insurance premiums.

Various meteorological phenomena (e.g., windstorms, CAOs, lake-effect snow) can cause extreme wind, freeze and snow. However, they are often studied independently in academia, complicating risk assessments for (re)insurers and financial sectors. A new CAO tracking algorithm, akin to existing windstorm tracking algorithms, enables a combined risk assessment of extreme U.S. windstorms and CAOs. Offering an opportunity to bridge the gap between academic research, where these phenomena are studied independently, and the (re)insurance industry, where losses from multiple hazards are aggregated, leading to more comprehensive risk management.

This new CAO tracking algorithm offers exciting prospects for research and risk assessment. It can help answer key questions about how costly CAOs develop and assess their frequency and severity in a present-day and future climates. Ultimately, this work aims to improve resilience to damaging weather events by improved risk assessment, while also enhancing societal preparedness and awareness of U.S. winter weather risks.

Research questions

This project has three core research objectives:

1. Quantify the collective present-day risk of extreme U.S. winter weather (extra-tropical storms, CAOs and other weather phenomena) and determine the sensitivity to various methods used to identify such hazards in various historical datasets.
2. Determine how ‘extreme’ the Feb. 2021 U.S. Cold Air Outbreak was and examine the synoptic development of this and other significant extreme U.S. winter weather events.
3. Assess how the frequency and severity of extreme U.S. winter weather may change in a future climate in response to global warming using a multi-model ensemble.
4. Combine windstorm and CAO tracks and hazard footprints with exposure (e.g., population and building density/value) and vulnerability datasets to determine regional risk and damages in the present-day climate, and changes in risk in a future warmer climate.

Methodology

The methodology uses robust scientific approaches, and methods as described in the following published research papers (see reference list entries 1 and 2). The feasibility of the methods has been confirmed during a previous 3-month MSc Dissertation project at the University of Reading. The methodology may follow, but is not strictly limited to, these broad steps:

a) Applying the CAO and windstorm tracking algorithm to historical atmospheric datasets (i.e., reanalyses – e.g., ERA5) to ascertain genesis locations, tracks and intensities of past events

b) Comparing frequency and intensity of past events to other identification and tracking methods from literature, to ascertain uncertainty

c) Using additional utilities of the CAO and windstorm tracking algorithm (TRACK) (e.g., compositing tool) and exploring atmospheric dynamic drivers for CAO and windstorm develop and progression over the U.S.

d) Applying the CAO and windstorm tracking algorithm to future-climate atmospheric datasets (e.g., CMIP6 models) to ascertain future changes in genesis locations, tracks and intensities compared to past events

e) Intersecting CAO and windstorm present-day and future climate event footprints with exposure data (e.g., LitPOP) and past loss data (e.g., Brelsford et al. (2024), to ascertain the societal risk.

The thesis will result in three research publications, linked to the first three objectives.

Anticipated outcomes & benefits for the sponsoring organisation and other stakeholders

This project strives to produce and publish open-access research papers and discussions (e.g., presentations at domestic and international conferences), benefitting academia, AXA XL and other (re)insurance companies, and other financial sectors. This project will also lead to societal

Start Date

21st September 2026

Duration of Award

3.5 years

Sponsor

NERC

Eligibility Criteria

A 2:1 Honours degree, or international equivalent in a subject relevant to the proposed PhD project (inc. Physical sciences, engineering, computing and mathematics,).

Enthusiasm for research, the ability to think and work independently, excellent analytical skills and strong verbal and written communication skills are also essential requirements.

An overall IELTS score of 6.5, with at least 5.5 in each of the four sub-skills, for international applicants.

The feasibility of this projects research approach has been tested during a previous MSc project at the University of Reading. Consequently, there are limited risks associated with this project, and we believe strongly that this project can deliver high-impact research that is applicable to many industries, whilst answering key scientific gaps in knowledge. This project requires specific and essential skills; however, these can be learnt throughout the PhD and with help from supervisory team.

These may include:

• Learning how to use complex computer code e.g., TRACK algorithm
• Understanding analytic techniques used outside of academia and used within the insurance industry
• Complex meteorological science concepts required for the project