On data-driven augmentation of low-resolution ocean model dynamics
File(s)1-s2.0-S1463500319301623-main.pdf (2.14 MB)
Accepted version
Author(s)
Ryzhov, EA
Kondrashov, D
Agarwal, N
Berloff, PS
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.
Date Issued
2019-10-01
Date Acceptance
2019-09-04
Citation
Ocean Modelling, 2019, 142
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
Natural Environment Research Council (NERC)
The Leverhulme Trust
Natural Environment Research Council (NERC)
Grant Number
NE/R011567/1
RPG-2019-024
NE/T002220/1
Subjects
0405 Oceanography
0911 Maritime Engineering
Oceanography
Publication Status
Published
Article Number
101464
Date Publish Online
2019-09-05