Innovative sampling of atmospheric extremes and impacts on ocean circulation in the subpolar North Atlantic

About the Project

Greenhouse gas emissions are driving climate warming, raising the risk of crossing tipping points – rapid and effectively irreversible shifts in major Earth-system components. One potential tipping point is the collapse of the North Atlantic subpolar gyre (SPG), a counter clockwise circulation in the Atlantic. An SPG collapse could produce major climate impacts, including cooling over Europe.

The SPG is influenced by the atmosphere above it. Variations in heat exchange and precipitation can significantly modify the subpolar ocean circulation, suggesting that anomalous or extreme atmospheric events may trigger SPG changes.

Project Aim

This project integrates mathematical, statistical, and modelling techniques to quantify how extreme atmospheric events influence subpolar Atlantic circulation. By linking atmospheric variability to oceanic responses, it aims to illuminate pathways through which atmospheric extremes may destabilize the SPG, improving our ability to assess climate tipping-point risks.

Objectives

• Identify atmospheric forcings likely to induce SPG transitions.
• Determine the dynamics and likelihood of such atmospheric events.
• Develop rare event simulation (RES) methods to accelerate simulations of these events.

The project begins with a conceptual SPG model - a low-dimensional dynamical system capturing key physical processes - to determine the stochastic forcings most likely to trigger circulation transitions. Its simplicity allows rapid exploration and testing of methods such as action minimisation, Langevin MCMC, and committor learning to characterise probable transition pathways and underlying mechanisms.

Building on these insights, the project will assess how likely such atmospheric events are in a more realistic context using an intermediate complexity Earth System Model. To efficiently sample rare atmospheric events the project will employ RES algorithms, which run ensembles of simulations in parallel and iteratively focus computational effort on trajectories most likely to produce extremes.

Optimising RES requires knowledge of the model’s statistical dynamics, which is difficult in high-dimensional climate models. To overcome this, you will develop machine-learned statistical emulators of key variables controlling subpolar atmospheric variability. These emulators provide inexpensive approximations of system dynamics, helping identify conditions favourable to extremes and informing the design of efficient RES algorithms.

Beyond its scientific goals, the project contributes to growing efforts to apply RES methods to a broad range of climate extremes. You will work within an interdisciplinary team studying high-impact changes in the Greenland Ice Sheet and SPG, gaining expertise across climate dynamics, applied mathematics, statistics, and machine learning.

University of Reading:

The University of Reading, located west of London, England, is ranked at 194 globally, according to the QS World University Rankings 2026. 98% of research at the University is of international standing (REF 2021, combining the University’s world leading, internationally excellent and internationally recognised submissions). The University’s main Whiteknights Campus is set in 120 hectares of beautiful, award winning parkland, less than a 30-minute train ride to London Paddington and is approximately 30 miles from London Heathrow airport.

This PhD is a collaboration between the Department of Mathematics and the National Centre for Atmospheric Science (NCAS) at Reading’s prestigious Meteorology Department. The PhD is funded under the PROMOTE project under ARIA’s Forecasting Tipping Points programme. Excellent training opportunities exist through NCAS and the ARIA programme. Although separately funded, the student will be able to take part in activities of the Mathematics for our Future Climate doctoral school and will be closely aligned to the school’s 2026 cohort.

Eligibility:

• Applicants should have a good master’s degree in mathematics, physics, meteorology, oceanography, or a closely related discipline by the start of the PhD programme. We also encourage applications from individuals who hold a bachelor’s degree followed by substantial, highly relevant work or research experience.
• International applicants will also need to meet the University’s English Language requirements.

The University of Reading is committed to a policy of equal opportunities and non-discriminatory treatment for all members of its community.

How to apply: Submit an application for a PhD in Mathematics via our online application system.

Include:

• a CV, including your personal information (no photo); a concise timeline of your education and other employment including voluntary work, periods of extended leave, time spent caring for others, etc.
• contact details for two referees that you are happy for us to contact.
  • You must supply academic or business email addresses (for example, Gmail is not acceptable and will prevent your application from being considered). You should not upload any references.
• personal statement: your motivation for wanting to study for a PhD and why you are applying to this project; anything we should know to better understand your CV, transcript, references (for example, if there are mitigating circumstances then let us know, but we do not need to know the details of the circumstances).
• supporting documents (transcripts, certificates, and English language proficiency (if relevant))
• International students must include a clear statement and evidence of how they will cover the international tuition fees at the bottom of their personal statement. If this is not included then, unfortunately, the application will be rejected as the CDT cannot cover these costs.

Further information: Department of Mathematics and Statistics PhD webpage

Enquiries: Dr. Jeroen Wouters email: j.wouters@reading.ac.uk

Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria.

Funding Notes

• Maintenance allowance of £20,780 per year
• UK/Republic of Ireland tuition fees covered
• 3.5 year duration

Starts September 2026

Quote reference DRC26-008 in the funding section of the application.

If you are applying to an international funding scheme, we encourage you to get in contact as we may be able to support you in your application.

Students who do not meet the requirements for home status are classified as international students. International students are welcome to apply but MUST be able to meet the cost of the difference between the home tuition fees and the international tuition fees (the project has no funds for this). They must also pay additional costs, including visa costs and the Immigration Health Surcharge.