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Scale-Aware Deterministic and Stochastic Parametrizations of Eddy-Mean Flow Interaction

Abstract:
The role of mesoscale eddies is crucial for the ocean circulation and its energy budget. The sub-grid scale eddy variability needs to be parametrized in ocean models, even at so-called eddy permitting resolutions. Porta Mana and Zanna (2014) propose an eddy parametrization based on a non-Newtonian stress which depends on the partially resolved scales and their variability. In the present study, we test two versions of the parametrization, one deterministic and one stochastic, at coarse and eddy-permitting resolutions in a double gyre quasi-geostrophic model. The parametrization leads to drastic improvements in the mean state and variability of the ocean state, namely in the jet rectification and the kinetic-energy spectra as a function of wavenumber and frequency for eddy permitting models. The parametrization also appears to have a stabilizing effect on the model, especially the stochastic version. The parametrization possesses attractive features for implementation in global models: very little computational cost, it is flow aware and uses the properties of the underlying flow. The deterministic coefficient is scale-aware, while the stochastic parameter is scale- and flow-aware with dependence on resolution, stratification and wind forcing.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.ocemod.2017.01.004

Authors

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Institution:
University of Oxford
Oxford college:
St Cross College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Atmos Ocean & Planet Physics
Role:
Author


Publisher:
Elsevier
Journal:
Ocean Modelling More from this journal
Volume:
111
Issue:
3
Pages:
66–80
Publication date:
2017-01-31
Acceptance date:
2017-01-22
DOI:
EISSN:
1463-5003
ISSN:
1463-5003


Keywords:
Pubs id:
pubs:680356
UUID:
uuid:59bd86b2-5e56-4b2a-aa42-f858e037299a
Local pid:
pubs:680356
Source identifiers:
680356
Deposit date:
2017-02-16
ARK identifier:

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