On the use and misuse of the Osborn model: Implications for improved estimates of ocean mixing rates
ORAL
Abstract
The Osborn model is widely used for quantification of diapycnal diffusivity Kρ in in oceanic flows.Two main simplifications are routinely made when estimating mixing rates in stably stratified flows when using the Osborn model. First, a constant value is frequently assumed for the mixing coefficient Γ. Second, dissipation rates of turbulent kinetic energy ε are inferred using either the Thorpe length scales or from microstructure measurements using the isotropy assumption. Data from three independent direct numerical simulations of homogeneous stratified turbulence are used as a testbed to highlight impacts of these assumptions on estimates of Kρ. A systematic analysis is used to evaluate the inferred diffusivities to exact DNS diffusivities as a function of the turbulent Froude number Frt. Use of a constant mixing coefficient Γ results in an under-prediction of Kρ by up to a factor of 5 for strongly stratified conditions (i.e., at low Frt) and an over-prediction of Kρ by up to two orders of magnitude in weakly stratified conditions (i.e., high Frt). The use of inferred dissipation rates ε based on the assumption of isotropy results in an over-prediction of Kρ by a factor of 2 for low Frt and converges on the exact Kρ for Frt > 1. However, the use of kinematic length scales, such as the Thorpe scale, to infer ε result in significant errors. The implications of these findings for improved estimates of ocean mixing rates are illustrated using an example application.
–
Publication: Klema, M.R. and Venayagamoorthy, S. K. (2023) Mixing rates in stably stratified flows with respect to the turbulent Froude number and turbulent scales, Environmental Fluid Mechanics, https://doi.org/10.1007/s10652-023-09925-1
Presenters
-
Subhas Karan Venayagamoorthy
Environmental Fluid Mechanics Laboratory at Colorado State University, Colorado State University
Authors
-
Subhas Karan Venayagamoorthy
Environmental Fluid Mechanics Laboratory at Colorado State University, Colorado State University
-
Matthew Klema
Fort Lewis College