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Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface
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This study developed simplified mathematical models for how wind-driven turbulence mixes buoyant particles — including microplastics — in the ocean surface layer. Better parameterizations of near-surface mixing are important for predicting where floating microplastics concentrate and how they eventually sink.
Abstract. Turbulent mixing is a vital component of vertical particulate transport, but ocean global circulation models (OGCMs) generally have low resolution representations of near-surface mixing. Furthermore, turbulence data is often not provided in reanalysis products. We present 1D parametrizations of wind-driven turbulent mixing in the ocean surface mixed layer, which are designed to be easily included in 3D Lagrangian model experiments. Stochastic transport is computed by Markov-0 or Markov-1 models, and we discuss the advantages/disadvantages of two vertical profiles for the vertical diffusion coefficient Kz. All vertical diffusion profiles and stochastic transport models lead to stable concentration profiles for buoyant particles, which for particles with rise velocities of 0.03 and 0.003 m s−1 agree relatively well with concentration profiles from field measurements of microplastics. Markov-0 models provide good model performance for integration timesteps of Δt ≈ 30 seconds, and can be readily applied in studying the behaviour of buoyant particulates in the ocean. Markov-1 models do not consistently improve model performance relative to Markov-0 models, and require an additional parameter that is poorly constrained.
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Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface
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This study found that current models tend to overestimate how quickly wind and waves mix floating microplastics down into the water, because they don't fully account for how buoyancy slows particles' vertical movement in turbulent water. This matters because more accurate models help scientists better predict where microplastics actually concentrate in the ocean, key information for understanding where marine life (and eventually, our seafood) encounters the most contamination.
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Using large eddy simulations, this paper modeled how wind-driven waves affect the vertical distribution of buoyant particles near the ocean surface, providing the physical framework for the companion paper on microplastic debris distribution. The models explain why floating microplastics are often mixed down below the surface, reducing the concentrations observed in surface sampling.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.