Please note that the Closing Date for the Funded PhD Project below has now been extended to Thursday 30th April 2026

We would like to advertise a funded PhD Project titled “The impact of atmospheric extremes on the North Atlantic subpolar oceanic circulation” within the University of Reading, UK from September 2026.

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.

Full details on this PhD and how to apply can be found here: https://www.findaphd.com/phds/project/the-impact-of-atmospheric-extremes-on-the-north-atlantic-subpolar-oceanic-circulation/?p193585