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Updated: Sep 4, 2025

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Image-based Lagrangian Particle Tracking in Bed-load Experiments
Published on: July 20, 2017
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Simulating Lagrangian Subgrid-Scale Dispersion on Neutral Surfaces in the Ocean
Daan Reijnders1, Eric Deleersnijder2, Erik van Sebille1
1Institute for Marine and Atmospheric Research Utrecht Utrecht University Utrecht The Netherlands.
Summary
We introduce a new 3D Markov-1 model for Lagrangian dispersion, improving trajectory accuracy in ocean models. This method better represents eddy effects than traditional random walks, reducing spurious dianeutral flux.
Area of Science:
- Oceanography
- Fluid Dynamics
- Computational Science
Background:
- Coarse-resolution ocean models require parameterizations for mesoscale turbulent eddies.
- Lagrangian dispersion is typically modeled using random walks, analogous to Eulerian diffusion.
- Previous 3D studies on Lagrangian dispersion parameterizations were limited to random walks (Markov-0).
Purpose of the Study:
- To develop and implement a three-dimensional isoneutral formulation of the Markov-1 model for Lagrangian dispersion.
- To implement an anisotropic, shear-dependent random walk dispersion formulation.
- To compare the performance of Markov-1 and random walk dispersion in oceanographic simulations.
Main Methods:
- Developed a 3D isoneutral Markov-1 model.
- Implemented an anisotropic, shear-dependent random walk parameterization.
- Compared models using idealized and realistic coarse-resolution ocean model output.
Main Results:
- Markov-1 and random walk dispersion produced similar particle distributions over time in ocean model output.
- Markov-1 yielded Lagrangian trajectories more representative of eddy-resolving simulations.
- Markov-1 resulted in a reduced spurious dianeutral flux.
Conclusions:
- The 3D Markov-1 model offers improved Lagrangian trajectory representation compared to random walks in coarse ocean models.
- Markov-1 parameterization is a promising advancement for accurately simulating dispersion in oceanographic studies.
- This work advances the understanding and modeling of eddy-driven dispersion in the ocean.
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