Rotating shallow water flow under location uncertainty with a structure-preserving discretization
R\"udiger Brecht, Long Li, Werner Bauer, Etienne M\'emin

TL;DR
This paper presents a stochastic modeling approach for rotating shallow water equations that conserves energy and can be integrated into existing weather prediction models, enabling realistic ensemble simulations of unresolved flow components.
Contribution
It introduces a structure-preserving discretization for the stochastic rotating shallow water equations based on location uncertainty, ensuring energy conservation and practical ensemble generation.
Findings
Conserves global energy in stochastic simulations.
Applicable to existing geophysical models and numerical weather prediction cores.
Demonstrated on test cases including an inviscid f-plane and unstable jet on the sphere.
Abstract
We introduce a physically relevant stochastic representation of the rotating shallow water equations. The derivation relies mainly on a stochastic transport principle and on a decomposition of the fluid flow into a large-scale component and a noise term that models the unresolved flow components. As for the classical (deterministic) system, this scheme, referred to as modelling under location uncertainty (LU), conserves the global energy of any realization and provides the possibility to generate an ensemble of physically relevant random simulations with a good trade-off between the model error representation and the ensemble's spread. To maintain numerically the energy conservation feature, we combine an energy (in space) preserving discretization of the underlying deterministic model with approximations of the stochastic terms that are based on standard finite volume/difference…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
