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Finite-volume discretization of the quasi-geostrophic equations with implicit dissipation
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We present in this work a new discretization of the multi-layer
quasi-geostrophic (QG) model that relies on implicit dissipation rather
than additional explicit dissipation.It is first based on the staggered discretization of the potential
vorticity (PV) and the stream-function in order to solve the PV
advection with a finite volume method.This ensures the exact material conservation of the PV.We compute PV fluxes with a WENO-5 interpolation whose implicit
dissipation replaces the usual explicit (hyper-)viscous dissipation.We propose a new method for solving reversibly the elliptic equation
which is nontrivial with this staggered discretization.The presented discretization does not require the tuning of any
additional parameter, \textit{e.g.} additional
hyper-viscosity.We test the proposed method on a challenging idealized wind-driven
double-gyre configuration at eddy-resolving, eddy-permitting, and
non-eddy-resolving resolutions.In the eddy-permitting and non-eddy-resolving resolutions, our method
produces an eastward jet contrary to usual discretizations without
parametrization.Moreover, our method produces statistics that have a stronger coherence
across resolutions than usual discretizations.We release a very short, concise, and efficient PyTorch implementation
of our method to facilitate future data assimilation or machine-learning
developments upon this new discretization.
Title: Finite-volume discretization of the quasi-geostrophic equations with implicit dissipation
Description:
We present in this work a new discretization of the multi-layer
quasi-geostrophic (QG) model that relies on implicit dissipation rather
than additional explicit dissipation.
It is first based on the staggered discretization of the potential
vorticity (PV) and the stream-function in order to solve the PV
advection with a finite volume method.
This ensures the exact material conservation of the PV.
We compute PV fluxes with a WENO-5 interpolation whose implicit
dissipation replaces the usual explicit (hyper-)viscous dissipation.
We propose a new method for solving reversibly the elliptic equation
which is nontrivial with this staggered discretization.
The presented discretization does not require the tuning of any
additional parameter, \textit{e.
g.
} additional
hyper-viscosity.
We test the proposed method on a challenging idealized wind-driven
double-gyre configuration at eddy-resolving, eddy-permitting, and
non-eddy-resolving resolutions.
In the eddy-permitting and non-eddy-resolving resolutions, our method
produces an eastward jet contrary to usual discretizations without
parametrization.
Moreover, our method produces statistics that have a stronger coherence
across resolutions than usual discretizations.
We release a very short, concise, and efficient PyTorch implementation
of our method to facilitate future data assimilation or machine-learning
developments upon this new discretization.
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