A method for preserving nominally-resolved flow patterns in low-resolution ocean simulations: Constrained dynamics. (October 2022)

• Record Type: Journal Article
• Authors: Shevchenko, I.; Berloff, P.
• Is Part Of: Ocean modelling. Volume 178(2022)
• Publication Date: 2022-10
• Subjects: Nonlinear ocean dynamics -- Mesoscale eddies and their parameterizations -- Dynamical systems -- Constrained optimization; Oceanography -- Periodicals; Océanographie -- Périodiques; Oceanography; Periodicals; 551.46
• DOI: 10.1016/j.ocemod.2022.102098
• Languages: English
• ISSNs: 1463-5003

Abstract

Abstract: Inability of low-resolution ocean models to simulate many important aspects of the large-scale general circulation is a common problem. In the view of physics, the main reason for this failure are the missed dynamical effects of the unresolved small scales of motion on the explicitly resolved large-scale circulation. Complimentary to this mainstream physics-based perspective, we propose to address this failure from the dynamical systems point of view, namely, as the persistent tendency of phase space trajectories representing the low-resolution solution to escape the right region of the corresponding phase space, which is occupied by the reference eddy-resolving solution. Based on this concept, we propose to use methods of constrained optimization to confine the low-resolution solution to remain within the correct phase space region, without attempting to amend the eddy physics by introducing a process-based parameterization. This approach is advocated as a novel framework for data-driven hyper-parameterizations of mesoscale oceanic eddies in non-eddy-resolving models. We tested the idea in the context of classical, baroclinic beta-plane turbulence model and showed that non-eddy-resolving solution can be substantially improved towards the reference eddy-resolving benchmark. Highlights: Method for preserving nominally-resolved patterns in coarse-grid models is proposed. Method has been tested on the Lorenz 63 and multilayer QG model. Method preserves nominally-resolved flow patterns in low-resolution ocean models.