Ocean Mixing Parameterisation via Categorisation of Nonlinear Flow Structures - Project 2: Experimental Validation

One of the key challenges for large-scale climate models is to accurately parameterise the mixing which occurs in the oceans. Such mixing occurs at small-scales, well below the grid-resolution of the climate models, and consists of the turbulent exchange of heat and salt between neighbouring regions of fluid. In order to build a robust parameterisation of this mixing, we must take a data-driven approach in which oceanographic data are algorithmically categorised according to the type of dynamics they represent.

Mixing at small scales in the ocean is mediated by a class of flows called stratified shear flows. Within such flows, there are three potential routes, or instabilities, leading to turbulence, each with a distinct degree and vigorousness of mixing. Recently, Dr Tom Eaves proposed a categorisation scheme for oceanographic data taken at a single instant in time, which aims to distinguish between these three instabilities at linear and nonlinear levels (predicting what type of mixing will happen next, and what type of mixing just occurred, respectively).

This project will investigate the fidelity of the categorisation scheme, taking it beyond the simplified flows considered in Dr Eaves’ initial study, primarily through the completion of a carefully-controlled parametric experimental modelling study on stratified shear flows. We will use data from this study to determine the extent to which the linear and nonlinear categorisation algorithms agree with one another (i.e. to what extent predictions at one time about what is about to happen agree with predictions at some later time about what just occurred).

This project will make use of experimental flume facilities within the Environmental Fluid Mechanics laboratory at the University of Dundee, as well as specialist measurement equipment including micro-conductivity probes for high-resolution density profiling and particle image velocimetry/laser-induced fluorescence (PLIF) for turbulent flow field measurements generated by shear-induced mixing. This data will be used as direct validation of the computational methods utilised in Project 1 and to help inform the mathematics underlying the categorisation schemes to build and interrogate nonlinear flow structures associated with stratified shear flows.

Key skills developed through the project include the experimental modelling of turbulent fluid flows, mathematical high-Reynolds-number fluid dynamics, and the development/application of advanced techniques for the measurement of fluid flows.

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