A Discussion on Diapycnal Mixing Efficiency in Stably Stratified Geophysical Flows

Subhas Karan Venayagamoorthy, Colorado State University, Department of Civil and Environmental Engineering, Fort Collins, CO, United States, Amrapalli Garanaik, Colorado State University, Department of Civil and Environmental Engineering, Fort Collins, United States, Louis St Laurent, Woods Hole Oceanographic Institution, Physical Oceanography, Woods Hole, MA, United States and Derek D Stretch, University of KwaZulu-Natal, Civil Engineering, Durban, South Africa
Abstract:
The diapycnal mixing efficiency is a measure of the amount of turbulent kinetic energy that is irreversibly converted into background potential energy in stably stratified flows. Despite the prevalence of a number of studies on mixing efficiency, no unifying parameterization of the mixing efficiency exists to date primarily due to the variability of geophysical flows and ambiguous use of certain parameters such as the buoyancy Reynolds number (Reb). In particular, there is an ongoing debate in the oceanographic mixing community regarding the utility of Reb, particularly with regard to how mixing efficiency varies with this parameter. Specifically, is there a robust and universal relationship between the intensity of turbulence (which is given by the turbulent Reynolds number ReL) and the strength of the stratification that can support an unbiased description of mixing efficiency based on Reb? This is an important question to consider when parameterizations developed from low ReL simulations or laboratory experiments are used to describe geophysical turbulence. In such low ReL studies, high Reb is readily achieved with weak stratification despite low turbulent Reynolds number ReL. However, oceanic and atmospheric turbulence can be sustained in the presence of strong stratification at much higher turbulence Reynolds numbers. In this talk, a discussion on the mixing efficiency and implications for estimates of diapycnal mixing in the ocean will be presented using data from direct numerical simulations, laboratory experiments, and field observations.