Abstract

Reduced order models (ROMs) are computational models whose dimension is significantly lower than those obtained through classical numerical discretizations (e.g., finite element, finite difference, finite volume, or spectral methods). Thus, ROMs have been used to accelerate numerical simulations of many query problems, e.g., uncertainty quantification, control, and shape optimization. Projection-based ROMs have been particularly successful in the numerical simulation of fluid flows. In this brief survey, we summarize some recent ROM developments for the quasi-geostrophic equations (QGE) (also known as the barotropic vorticity equations), which are a simplified model for geophysical flows in which rotation plays a central role, such as wind-driven ocean circulation in mid-latitude ocean basins. Since the QGE represent a practical compromise between efficient numerical simulations of ocean flows and accurate representations of large scale ocean dynamics, these equations have often been used in the testing of new numerical methods for ocean flows. ROMs have also been tested on the QGE for various settings in order to understand their potential in efficient numerical simulations of ocean flows. In this paper, we survey the ROMs developed for the QGE in order to understand their potential in efficient numerical simulations of more complex ocean flows: We explain how classical numerical methods for the QGE are used to generate the ROM basis functions, we outline the main steps in the construction of projection-based ROMs (with a particular focus on the under-resolved regime, when the closure problem needs to be addressed), we illustrate the ROMs in the numerical simulation of the QGE for various settings, and we present several potential future research avenues in the ROM exploration of the QGE and more complex models of geophysical flows.

Highlights

  • We use four regimes: (i) a reconstructive regime, which is an easier test case, in which the Reduced Order Models (ROMs) is validated on the same time interval as the time interval used to train the ROM; (ii) a predictive regime, which is a harder test case, in which the ROM is trained on a short time interval and validated on a longer time interval; (iii) a resolved regime, in which the number of ROM basis functions is enough to represent the system’s dynamics; and (iv) an under-resolved regime, in which the number of ROM basis functions is not enough to represent the system’s dynamics

  • Since the quasi-geostrophic equations (QGE) computational cost is significantly lower than the computational cost of full fledged mathematical models of ocean flows, the QGE have often been used to test new numerical methods for geophysical flows, such as reduced order models (ROMs)

  • We summarized projection-based ROMs developed for the QGE

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Summary

Introduction

Reduced order modeling aims at answering the following question: For a given system, what is the model with the minimum number of degrees of freedom?. Projection ROMs have been used in the numerical simulation of both nonlinear [1,2,3] and linear [4] systems. Projection ROMs have been successful in the numerical simulation of complex fluid flows [2,5,6,7]. In this survey, we exclusively consider projection ROMs that answer question (1) as follows: To construct the ROM, use numerical or experimental data to find the “best” basis

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