We compare the properties of the turbulence induced by the breakdown of Kelvin–Helmholtz instability (KHI) at high Reynolds number in two classes of stratified shear flows where the background density profile is given by either a linear function or a hyperbolic tangent function, at different values of the minimum initial gradient Richardson number ${{Ri}}_0$ . Considering global and local measures of mixing defined in terms of either the irreversible mixing rate $\mathscr {M}$ associated with the time evolution of the background potential energy, or an appropriately defined density variance dissipation rate $\chi$ , we find that the proliferation of secondary instabilities strongly affects the efficiency of mixing early in the flow evolution, and also that these secondary instabilities are highly sensitive to flow perturbations that are added at the point of maximal (two-dimensional) billow amplitude. Nevertheless, mixing efficiency does not appear to depend strongly on the far field density structure, a feature supported by the evolution of local horizontally averaged values of the buoyancy Reynolds number ${Re}_b$ and gradient Richardson number ${Ri}_g$ . We investigate the applicability of various proposed scaling laws for flux coefficients $\varGamma$ in terms of characteristic length scales, in particular discussing the relevance of the overturning ‘Thorpe scale’ in stratified turbulent flows. Finally, we compare a variety of empirical model parameterizations used to compute diapycnal diffusivity in an oceanographic context, arguing that for transient flows such as KHI-induced turbulence, simple models that relate the ‘age’ of a turbulent event to its mixing efficiency can produce reasonably robust mixing estimates.

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Motivated by the variation of local shear produced by internal waves in the ocean, we use direct numerical simulations to investigate the effect of a time-dependent shear forcing on the evolution and mixing of turbulence produced by Kelvin–Helmholtz instability (KHI) at high Reynolds number. The forcing is implemented using a tilting coordinate system which causes the background shear to accelerate and decelerate periodically. We demonstrate that, with suitable timing between development of instability and the shear oscillation cycle, turbulence produced by KHI with a decelerating shear mixes in a distinctly different way from the flow with constant background shear, specifically with the energy for turbulent motions extracted from alternative sources. As a result, the total amount of mixing as measured by the change in background potential energy can in fact be significantly larger for flows in which the shear is decelerated, despite the fact that the total kinetic energy in the flow is significantly smaller. The mixing has characteristics more in common with convectively driven rather than shear-driven flows, supporting the argument for an underlying change in the mechanisms triggering the turbulence.

Motivated by oceanographic observational datasets, we propose a probabilistic neural network (PNN) model for calculating turbulent energy dissipation rates from vertical columns of velocity and density gradients in density stratified turbulent flows. We train and test the model on high-resolution simulations of decaying turbulence designed to emulate geophysical conditions similar to those found in the ocean. The PNN model outperforms a baseline theoretical model widely used to compute dissipation rates from oceanographic observations of vertical shear, being more robust in capturing the tails of the output distributions at multiple different time points during turbulent decay. A differential sensitivity analysis indicates that this improvement may be attributed to the ability of the network to capture additional underlying physics introduced by density gradients in the flow.