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Simulating Lagrangian Subgrid-Scale Dispersion on Neutral Surfaces in the Ocean
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To capture the effects of mesoscale turbulent eddies, coarse-resolution
Eulerian ocean models resort to tracer diffusion parameterizations.
Likewise, the effect of eddy dispersion needs to be parameterized when
computing Lagrangian pathways using coarse flow fields. Dispersion in
Lagrangian simulations is traditionally parameterized by random walks,
equivalent to diffusion in Eulerian models. Beyond random walks, there
is a hierarchy of stochastic parameterizations, where stochastic
perturbations are added to Lagrangian particle velocities,
accelerations, or hyper-accelerations. These parameterizations are
referred to as the 1st, 2nd and 3rd order ‘Markov models’ (Markov-N),
respectively. Most previous studies investigate these parameterizations
in two-dimensional setups, often restricted to the ocean surface. On the
other hand, the few studies that investigated Lagrangian dispersion
parameterizations in three dimensions, where dispersion is largely
restricted to neutrally buoyant surfaces, have focused only on random
walk (Markov-0) dispersion. Here, we present a three-dimensional
isoneutral formulation of the Markov-1 model. We also implement an
anisotropic, shear-dependent formulation of random walk dispersion,
originally formulated as a Eulerian diffusion parameterization. Random
walk dispersion and Markov-1 are compared using an idealized setup as
well as more realistic coarse and coarsened (50 km) ocean model output.
While random walk dispersion and Markov-1 produce similar particle
distributions over time when using our ocean model output, Markov-1
yields Lagrangian trajectories that better resemble trajectories from
eddy-resolving simulations. Markov-1 also yields a smaller spurious
dianeutral flux.
Title: Simulating Lagrangian Subgrid-Scale Dispersion on Neutral Surfaces in the Ocean
Description:
To capture the effects of mesoscale turbulent eddies, coarse-resolution
Eulerian ocean models resort to tracer diffusion parameterizations.
Likewise, the effect of eddy dispersion needs to be parameterized when
computing Lagrangian pathways using coarse flow fields.
Dispersion in
Lagrangian simulations is traditionally parameterized by random walks,
equivalent to diffusion in Eulerian models.
Beyond random walks, there
is a hierarchy of stochastic parameterizations, where stochastic
perturbations are added to Lagrangian particle velocities,
accelerations, or hyper-accelerations.
These parameterizations are
referred to as the 1st, 2nd and 3rd order ‘Markov models’ (Markov-N),
respectively.
Most previous studies investigate these parameterizations
in two-dimensional setups, often restricted to the ocean surface.
On the
other hand, the few studies that investigated Lagrangian dispersion
parameterizations in three dimensions, where dispersion is largely
restricted to neutrally buoyant surfaces, have focused only on random
walk (Markov-0) dispersion.
Here, we present a three-dimensional
isoneutral formulation of the Markov-1 model.
We also implement an
anisotropic, shear-dependent formulation of random walk dispersion,
originally formulated as a Eulerian diffusion parameterization.
Random
walk dispersion and Markov-1 are compared using an idealized setup as
well as more realistic coarse and coarsened (50 km) ocean model output.
While random walk dispersion and Markov-1 produce similar particle
distributions over time when using our ocean model output, Markov-1
yields Lagrangian trajectories that better resemble trajectories from
eddy-resolving simulations.
Markov-1 also yields a smaller spurious
dianeutral flux.
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