About this role
About the Partnership
This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP). The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/
For eligible successful applicants, the studentships comprises:
An stipend for 3.5 years (currently £20,780 p.a. for 2026/27) in line with UK Research and Innovation rates Payment of university tuition fees The budget for project costs is £9,000 which can be used for computer, lab, and fieldwork costs necessary for you to conduct your research. There is also a conference budget of £2,000 and individual Training Budget of £1,000 for specialist training
Project Aims and Methods
The stratified atmospheric boundary layer is a key component in high-impact weather and climate predictions. Forecast applications include: polar surface temperatures, the timing of thunderstorms and night-time low temperatures. There is a need to improve the way the stratified boundary layer is represented (parametrized) in these simulations and also interrogate the models with high-quality observations. In this project, we will investigate extending the current parametrization to beyond the first order typically currently used, to second order and using state-of-the art observations for the British Antarctic Survey.
This work is also timely as it connects to the NERC ParaChute project which aims to improve the boundary layer parametrization for high-resolution numerical weather prediction.
In this project, the student will develop skills in:
the structure of weather and climate models, interrogating weather and climate models with observations from the British Antarctic Survey, computational modelling of the atmosphere using python and FORTRAN, optimising momentum and flux balances using AI tools.
This training will equip them for a career in atmospheric science.