On data-driven augmentation of low-resolution ocean model dynamics

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Title: On data-driven augmentation of low-resolution ocean model dynamics
Authors: Ryzhov, EA
Kondrashov, D
Agarwal, N
Berloff, PS
Item Type: Journal Article
Abstract: The problem of augmenting low-resolution ocean circulation models with the information extracted from the data relevant to the unresolved subgrid processes is addressed. A highly nonlinear model of eddy-resolving oceanic circulation – quasigeostrophic wind-driven double gyres – is considered. The model solutions are characterized by a vigorous dynamic coupling between the resolved large-scale and small-scale (eddy) flow features. This solution provides the data for augmenting the low-resolution model with the same configuration. The eddy forcing field, which contains the essential information about coupling between the large and eddy scales, is obtained, modified, coarse-grained and added to augment the low-resolution model. The implemented modification involves novel data-adaptive harmonic decomposition analysis and dynamical constraining based on the low-resolution nonlinear advection operator. The resulting augmentation of the low-resolution model significantly improves the solution, including its time-mean circulation and low-frequency variability. This result also paves the way for a systematic data-driven emulation of unresolved and under-resolved scales of motion.
Issue Date: 1-Oct-2019
Date of Acceptance: 4-Sep-2019
URI: http://hdl.handle.net/10044/1/73192
DOI: https://doi.org/10.1016/j.ocemod.2019.101464
ISSN: 1463-5003
Publisher: Elsevier BV
Journal / Book Title: Ocean Modelling
Volume: 142
Copyright Statement: © 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/.
Sponsor/Funder: Natural Environment Research Council (NERC)
The Leverhulme Trust
Natural Environment Research Council (NERC)
Funder's Grant Number: NE/R011567/1
Keywords: 0405 Oceanography
0911 Maritime Engineering
Publication Status: Published
Embargo Date: 2020-09-05
Article Number: 101464
Online Publication Date: 2019-09-05
Appears in Collections:Mathematics
Centre for Environmental Policy
Applied Mathematics and Mathematical Physics
Faculty of Natural Sciences

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