Well balanced residual distribution for the ALE spherical shallow water equations on moving adaptive meshes

Abstract : We consider the numerical approximation of the Shallow Water Equations (SWEs) in spherical geometry for oceanographic applications. To provide enhanced resolution of moving fronts present in the flow we consider adaptive discrete approximations on moving triangulations of the sphere. To this end, we restate all Arbitrary Lagrangian Eulerian (ALE) transport formulas, as well as the volume transformation laws, for a 2D manifold. Using these results, we write the set of ALE-SWEs on the sphere. We then propose a Residual Distribution discrete approximation of the governing equations. Classical properties as the DGCL and the C-property (well balancedness) are reformulated in this more general context. An adaptive mesh movement strategy is proposed. The discrete framework obtained is thoroughly tested on standard benchmarks in large scale oceanography to prove their potential as well as the advantage brought by the adaptive mesh movement.
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Luca Arpaia, Mario Ricchiuto. Well balanced residual distribution for the ALE spherical shallow water equations on moving adaptive meshes. Journal of Computational Physics, Elsevier, 2020, 405, pp.109173. ⟨10.1016/j.jcp.2019.109173⟩. ⟨hal-02422335⟩

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