Start date: October 2024

Application deadline: 10th January 2024

Supervisory team: Dr Davide Proment, Dr Alberto Alberello, Prof. Ian Renfrew.

About the project

The Antarctic sea ice seasonal cycle is the Earth’s heartbeat, but current climate models are unable to reproduce its often baffling regional and inter-annual variabilities. The extreme Southern Ocean waves, winds, and currents play a major role in regulating sea ice extent and properties, and, hence, atmosphere-ocean fluxes and ice advance/retreat. This four-year PhD project will develop reliable mathematical models for pancake ice cycle in the presence of waves, winds, and currents, aiming at better predicting the evolution of floe size distribution and deriving a parametrisation for implementation in Earth system models.

Research methodology

The project will use theoretical and numerical methods for solving wave/ice models and kinetic equations mimicking the ice merging/fragmentation process; machine learning techniques will be used for data driven model parametrisation. The research will unfold as follows: (year 1) literature review, wave/ice model in 1D; (year 2) wave/ice model in 2D and kinetic equation models; (year 3) model extension to include ocean currents and wind; (year 4) statistics of extreme events. The parametrisation of the floe size distribution will start in year 2, while the machine learning data driven techniques in year 3. Scientific collaborations with Dr Fabien Montiel (Otago) for the merging/fragmentation ice models and Prof. Marcello Vichi (Cape Town) for field data acquisition, with the possibility of a field trip in the Indian/Southern Ocean, will take place in due course.

Training

The student will take part to the weekly research seminars across the Faculty of Science (Mathematics, Environmental Sciences, COAS) and take mathematics/physics modules of the MAGIC consortium. Other training offered like numerical modelling, use of HPC, scientific dissemination and writing will be available. The student will present their findings to meetings in the UK (UK Sea-ice meeting) and internationally (EGU). This PhD project is part of the ARIES DTP, and as such the student will participate to all its training activities.

Person specification

We are looking for a highly motivated, enthusiastic, and outstanding candidate holding a degree in Mathematics, Physics, Environmental Sciences, or similar. Experience in mathematical and numerical modelling is highly recommended.

Funding notes

This project has been shortlisted for funding by the ARIES NERC DTP.

Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship, which covers fees, stipend (£18,622 p.a. for 2023/24) and research funding. International applicants are eligible for fully-funded ARIES studentships including fees. Please note however that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK.

Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses.

Application process

ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage aries.dtp@uea.ac.uk and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside significant relevant non-academic experience.

For further information, please visit www.aries-dtp.ac.uk

Project Code PROMENT_UMTH24ARIES