资源环境科技发展态势分析平台

We introduce a general framework to predict the fate of buoyant materials in the oceanic mixed layer. The framework is based on the estimation of a turbulence velocity scale for the vertical mixing of buoyant materials. By combining this velocity scale with the material's terminal rise velocity and a K-profile parameterization, we are able to derive an analytical prediction for the vertical profile of material concentration that is shown to be a reasonably accurate and general representation for oceanic mixed layer regimes driven by various levels of wind shear, Stokes drift, and buoyancy flux. The analytically predicted profile allows us to estimate relevant parameters for the fate of buoyant materials, such as the depth of a plume's center of mass and the horizontal transport. We show that the predictions agree with large-eddy simulations driven by various combinations of wind shear, Stokes drift, and buoyancy fluxes.

Plain Language Summary The flow of the ocean near the surface is influenced by many different natural phenomena. The three most important are waves, wind, and the cooling of seawater. These influences make the ocean behave in very distinct ways, which is a challenge for investigators trying to understand and predict the fate of pollutants that may happen to be dispersed in the water (e.g., oil or plastic). In practice this means that it is difficult for investigators to know, for example, whether oil will form a slick at the surface or be mixed downward into the water column, or where the oil will be transported. We present a framework that is general enough to be valid over a wide range of conditions that are naturally found in ocean. With this framework it is possible to make predictions that hold over a more realistic general range of situations without the need for large computer simulations. We demonstrate its applicability by making hypothetical predictions for the transport and mixing of oil and comparing them with computer models of the same conditions, as well as applying it to data measured in the Gulf of Mexico.