Preprints
https://doi.org/10.5194/gmd-2021-195
https://doi.org/10.5194/gmd-2021-195

Submitted as: model description paper 04 Oct 2021

Submitted as: model description paper | 04 Oct 2021

Review status: this preprint is currently under review for the journal GMD.

Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface

Victor Onink1,2,3, Erik van Sebille3, and Charlotte Laufkötter1,2 Victor Onink et al.
  • 1Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
  • 2Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • 3Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, The Netherlands

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.

Victor Onink et al.

Status: open (until 29 Nov 2021)

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Victor Onink et al.

Model code and software

Model and analysis code for: "Empirical Lagrangian parametrization for wind-driven mixing of buoyant particulates at the ocean surface" Victor Onink https://doi.org/10.5281/zenodo.4912693

Victor Onink et al.

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Short summary
Turbulent mixing is a vital process in 3D modelling of particle transport in the ocean. However, since turbulence occurs on very short spatial and time scales, large-scale ocean models generally have highly-simplified turbulence representations. We have developed new parametrizations for the vertical turbulent transport of buoyant particles that can be easily applied in large-scale particle tracking model. The predicted vertical concentration profiles match well with microplastic observations.