Addition of Langmuir Turbulence in a Hierarchy of Vertical Mixing Parameterizations for Ocean Climate Modeling

Climate projections from computational modeling systems are important for predicting and assessing impacts of anthropogenic climate change. Global ocean simulations are a major component of these coupled systems. These ocean simulations produce well known regional and seasonal biases in mixed layer depth that suggest missing and/or insufficiently represented physical processes within the vertical turbulent mixing parameterization. One process that has been demonstrated to help correct these biases is Langmuir turbulence, which is driven by interaction between the Eulerian current vorticity and the Stokes drift of the surface waves. In this study we investigate a hierarchy of vertical turbulent mixing schemes for use in global ocean modeling systems. These schemes, which model the vertical profiles of turbulent viscosity and diffusivity, can be modified to include the Langmuir turbulence impact. This investigation utilizes a suite of realistic ocean conditions and forcing scenarios to demonstrate the sensitivity of the upper-ocean boundary layer evolution to the modeling choices. Since Langmuir turbulence is typically parameterized from the Stokes drift, which must be either simulated or determined from an empirical model, the sensitivity of the mixing to the method of modeling the Stokes drift is also investigated. Results indicate sensitivity of the mixed layer evolution to the choice of the vertical mixing parameterization and the method for including Langmuir turbulence within the simulation. This is in agreement with other recent findings, and suggests that Langmuir turbulence must be carefully considered along with the vertical turbulent mixing parameterization to improve ocean model performance.