Large eddy simulation and K-profile parameterization of submesoscale oil droplet plume dispersion in Langmuir turbulence

As the oil plumes from deep water blowouts reach the ocean mixed layer (OML), their near-surface dispersions are highly influenced by the wind and wave-generated submesoscale Langmuir turbulence in the OML. In this study, we use large eddy simulations (LES) to model the oil dispersion at scales < 1 km. We find that despite the complex patterns of the instantaneous surface oil slick, the time-averaged surface oil plume can be parameterized as a Gaussian-type plume. The mean surface plume grows linearly downstream, with the centerline inclined clockwise (in the Northern Hemisphere) with respect to the wind and wave direction due to the Ekman transport. The inclination angle increase as the droplet size decreases, while the plume growth rate varies non-monotonically with oil droplet size. Using LES data, we evaluate the eddy viscosity and diffusivity following the K-profile parameterization (KPP) framework. We also evaluate the stress-strain misalignments caused by Stokes drift and the enhancement of eddy viscosity and diffusivity caused by Langmuir circulations. Improvements to the KPP model will be discussed. This study is supported by a Gulf of Mexico Research Initiative research grant.