Stochastic compressible Navier-Stokes equations under location uncertainty and their approximations for ocean modelling
Gilles Tissot, \'Etienne M\'emin, Quentin Jamet

TL;DR
This paper develops a stochastic version of the compressible Navier-Stokes equations for ocean modeling, combining theoretical derivations with numerical simulations to better capture physical uncertainties in ocean dynamics.
Contribution
It introduces a novel stochastic framework for compressible Navier-Stokes equations under location uncertainty, applied to ocean vertical mixing and large-eddy simulations.
Findings
Stochastic transport can reproduce penetrative convection effects.
Compression effects are negligible in internal energy but significant in potential energy.
The framework enhances physical uncertainty representation in ocean models.
Abstract
This paper presents a joint theoretical and numerical study of a stochastic version of the compressible Navier-Stokes equations within the location uncertainty (LU) framework, applied to problems related to upper ocean vertical mixing. This approach builds on an extended stochastic form of the Reynolds transport theorem, incorporating stochastic source terms. As in the deterministic case, this conservation theorem is applied to mass, mass of species (such as salinity), momentum, and total energy, leading to transport equations for the primitive variables: density, mass fraction of species, velocity, and temperature. We subsequently apply the Boussinesq approximations to this general system, and recover existing formulations of the incompressible stochastic Navier-Stokes and stochastic Boussinesq equations. We employ this new framework in a Boussinesq large-eddy simulation of…
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Taxonomy
TopicsStochastic processes and financial applications · Fluid Dynamics and Turbulent Flows · Markov Chains and Monte Carlo Methods
