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Cambridge NERC Doctoral Training Partnerships

Graduate Research Opportunities

Supervisors: Colm-cille Caulfield (DAMTP & BP Institute) and Ali Mashayek (Imperial College London

Importance of the area of research:

Evidence is accumulating that deep ocean turbulence exerts a leading order control on the global climate system through regulating the oceanic uptake and redistribution of heat, carbon, nutrients and other tracers. Observations of such turbulence, and our ability to model it numerically, have both been extremely limited historically. However, recently major international field programmes have shed light on deep ocean turbulence through state-of-the-art observations of turbulence generated by deep ocean waves that can have amplitudes measured in the tens to hundreds of metres. Computational resources are just now also becoming available to allow us to simulate such flows at adequately high resolution. An exciting opportunity is emerging to use simulations and observations in tandem to understand the physics of such turbulence, and thus to represent the key effects of this wave-induced turbulence in climate models, which inevitably have too coarse a resolution to describe the intricate and fascinating wave-driven dynamics directly.

Project summary:

This project will advance our understanding of deep ocean turbulence mediated by wave-breaking through an iterative combination of observational data analysis and high resolution numerical simulations. Improving the parameterisation of such turbulence is a key challenge for larger-scale predictive climate modelling, and is central to understanding transport of heat, carbon and nutrients in the oceans. The project will involve close collaborations with, and visits to various institutes with which the co-supervisors have long-standing collaborations, including  Scripps Institution of Oceanography (UC San Diego), Woods Hole Oceanographic Institution (Massachusetts), the Met Office, and the National Oceanographic Centre Southampton.

What the student will do:

The student will interact with oceanographers to understand and correctly interpret recent ocean turbulence observations. Armed with this knowledge informed directly by observations, the student will then construct mathematical theoretical models to describe the underlying physics. The student will simulate idealisations of the observed flows (which nevertheless capture the key physics)  to gain detailed understanding of deep ocean turbulence driven by wave breaking. The student will then connect this understanding to the "big picture" ocean circulation and climate system by interacting with centres of research excellence (both in the UK and the US) that focus on large scale ocean modelling. The core objective of the student will be not only to enhance our theoretical understanding of ocean turbulence but to transfer that understanding to climate models, through a highly collaborative and multi-disciplinary Ph.D. project.

Please contact the lead supervisor directly for further information relating to what the successful applicant will be expected to do, training to be provided, and any specific educational background requirements.


Mashayek, A., Salehipour, H., Bouffard, D., Caulfield, C. P., Ferrari, R., Nikurashin, M., Peltier & W. R., Smyth, W. D. 2017. Efficiency of turbulent mixing in the abyssal ocean circulation. Geophysical Research Letters, vol. 44, pp. 6296-6306, DOI: 10.1002/2016GL072452

Mashayek, A., Caulfield, C. P. & Peltier, W. R. 2013. Time-dependent, non-monotonic mixing in stratified turbulent shear flows: implications for oceanographic estimates of buoyancy flux. Journal of Fluid Mechanics, vol. 736, pp. 570-593, DOI: 10.1017/jfm.2013.551

Mashayek, A., Ferrari, R., Merrifield, S., Ledwell, J. R., St Laurent, L. & Garabato, A. Naveira 2017. Topographic enhancement of vertical turbulent mixing in the Southern Ocean. Nature Communications, vol. 8, Article Number: 14197, DOI: 10.1038/ncomms14197

Follow this link to find out about applying for this project.

Other projects available from the Lead Supervisor can be viewed here.

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