Lead Supervisor: Christopher O’Reilly, Department of Meteorology, University of Reading

Email: c.h.oreilly@reading.ac.uk

Co-supervisor: Jon Robson, National Centre for Atmospheric Science (NCAS), University of Reading; Adam Scaife, University of Exeter & Met Office; Antje Weisheimer, ECMWF & University of Oxford

On interannual timescales, most of the regional climate variability in the extratropics is linked to variability in the large-scale atmospheric circulation. In recent years there has been emerging evidence of seasonal predictability of the large-scale atmospheric circulation in the northern extratropics at lead times of a year or more. An important recent example of this was the study of Scaife et al. (2022), in which it is demonstrated that atmospheric angular momentum exhibits predictability over a year in advance. Previous studies have also highlighted circulation skill in certain regions at lead-times of over a year (e.g. Dunstone et al. (2018); Befort et al. (2020)). These developments in predictability are exciting, with developments in multi-year predictions being hugely valuable for a range of sectors. However, there are many fundamental issues regarding the mechanisms underlying the predictability that remain poorly understood.

In this project we will investigate the mechanisms underlying multi-year climate predictability in an aim to understand and ultimately improve future climate prediction. The project brings together a supervisory team with a wealth of expertise and experience, including co-supervisors with positions at ECMWF and Met Office, world-leading operational climate prediction centres. This project provides an opportunity for a student to receive extensive training in climate science, dynamics and modelling, whilst working at the cutting-edge of climate prediction science.

Training Opportunities

During this project the student will receive training in the science of climate dynamics and climate modelling. There will be opportunities to learn from supervisors and colleagues working on multi-year forecasts at world-leading operational centres.

Student Profiles

This project would be suitable for students with a keen interest in the physics of the natural world, especially the dynamics of the atmospheric/climate system and associated predictability. The project is particularly suitable for students with an undergraduate degree in physics, mathematics, computer science, meteorology or a closely related environmental/physical science.

Funding Particulars

This project is partially funded by the Royal Society