Stochastic subgrid tensor for geophysical flow modeling

Valentin Resseguier 1 Etienne Mémin 1 Bertrand Chapron 2
1 FLUMINANCE - Fluid Flow Analysis, Description and Control from Image Sequences
IRMAR - Institut de Recherche Mathématique de Rennes, IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture, Inria Rennes – Bretagne Atlantique
Abstract : Stochastic models can be developed to perform ensemble forecasts of geophysical fluid dynamical systems and to betterhandle subgrid parametrizations. We propose to add to the smooth resolved velocity, an unresolved component, Gaussian, uncorrelated in time and inhomogeneous in space. This model changes the usual form of the material derivative of a tracer. This new form involves directly a multiplicative noise, an anisotropic and inhomogeneous diffusion, and a drift correction. As such, the rigorous derivation of this conservative model relates naturally the random forcing to the subgrid parametrization. Stochastic versions of classical models can then be derived from conservation of mass, energy and momentum. Numerical simulations of our stochastic version of Surface Quasi-Geostrophic model improves both the accuracy of a single simulation.
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Soumis le : mercredi 9 novembre 2016 - 17:49:39
Dernière modification le : mardi 19 juin 2018 - 11:12:07
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  • HAL Id : hal-01377741, version 1

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Valentin Resseguier, Etienne Mémin, Bertrand Chapron. Stochastic subgrid tensor for geophysical flow modeling. 8th European Postgraduate Fluid Dynamics Conference, Jul 2016, Varsovie, Poland. 〈https://epfdc2016.fuw.edu.pl/home〉. 〈hal-01377741〉

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