A highly efficient second-order accurate long-time dynamics preserving scheme for some geophysical fluid models
By: Daozhi Han, Xiaoming Wang
Potential Business Impact:
Predicts weather patterns more accurately for longer.
We develop and analyze a highly efficient, second-order time-marching scheme for infinite-dimensional nonlinear geophysical fluid models, designed to accurately approximate invariant measures-that is, the stationary statistical properties (or climate) of the underlying dynamical system. Beyond second-order accuracy in time, the scheme is particularly well suited for long-time simulations due to two key features: it requires solving only a fixed symmetric positive-definite linear system with constant coefficients at each step; and it guarantees long-time stability, producing uniformly bounded solutions in time for any bounded external forcing, regardless of initial data. For prototypical models such as the barotropic quasi-geostrophic equation, the method preserves dissipativity, ensuring that numerical solutions remain bounded in a function space compactly embedded in the phase space as time tends to infinity. Leveraging this property, we rigorously prove convergence of both global attractors and invariant measures of the discrete system to those of the continuous model in the vanishing time-step limit. A central innovation of the method is a mean-reverting scalar auxiliary variable (mr-SAV) formulation, which preserves the dissipative structure of externally forced systems within an appropriate phase space. For the infinite-dimensional models considered, we additionally employ fractional-order function spaces to establish compactness of numerical solutions in topologies compatible with the phase space.
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