Sub-grid scale modeling and data-driven model improvement for the shallow-water equations

Abstract

We apply the stochastic mode-reduction strategy to the finite-volume discretizations of the shallow water equations in physical space to derive a closed stochastic system (reduced equations) for coarse variables defined as averages of fine-scale variables over a fixed window. This approach is particularly suitable for oceanic applications where it is necessary to properly model the geometry and boundary conditions of the basin. Performance of stochastic parametrizations will be analyzed in the context of reduced equation i"n the equilibrium and nonequilibrium regimes for different parameter settings such as steep and low-grade topography, thin topograph"ic barrier.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 29, 2017
Source ID
N000141712845

Entities

People

  • Ilya Timofeyev

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Houston System

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • Space