Journal article
Evaluation of a scalar eddy transport coefficient based on geometric constraints
- Abstract:
- A suite of idealized models is used to evaluate and compare several previously proposed scalings for the eddy transport coefficient in downgradient mesoscale eddy closures. Of special interest in this comparison is a scaling introduced as part of the eddy parameterization framework of Marshall et al. (2012), which is derived using the inherent geometry of the Eliassen–Palm eddy flux tensor. The primary advantage of using this coefficient in a downgradient closure is that all dimensional terms are explicitly specified and the only uncertainty is a nondimensional parameter, α, which is bounded by one in magnitude. In each model a set of passive tracers is initialized, whose flux statistics are used to invert for the eddy- induced tracer transport. Unlike previous work, where this technique has been employed to diagnose the tensor coefficient of a linear flux-gradient relationship, the idealization of these models allows the lateral eddy transport to be described by a scalar coefficient. The skill of the extant scalings is then measured by comparing their predicted values against the coefficients diagnosed using this method. The Marshall et al. (2012) scaling is shown to scale most closely with the diagnosed coefficients across all simulations. It is shown that the skill of this scaling is due to its functional dependence on the total eddy energy, and that this scaling provides an excellent match to the diagnosed fluxes even in the limit of constant α. Possible extensions to this work, including how to incorporate the resultant transport coefficient into the Gent and McWilliams parameterization, are discussed.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 6.3MB, Terms of use)
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- Publisher copy:
- 10.1016/j.ocemod.2016.12.004
Authors
- Publisher:
- Elsevier
- Journal:
- Ocean Modelling More from this journal
- Volume:
- 109
- Pages:
- 44–54
- Publication date:
- 2016-12-12
- Acceptance date:
- 2016-12-11
- DOI:
- EISSN:
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1463-5011
- ISSN:
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1463-5003
- Keywords:
- Pubs id:
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pubs:664972
- UUID:
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uuid:4ea018f9-1124-40fe-9655-ca0f81a5ad85
- Local pid:
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pubs:664972
- Source identifiers:
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664972
- Deposit date:
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2016-12-12
Terms of use
- Copyright holder:
- Elsevier Ltd
- Copyright date:
- 2016
- Notes:
- Copyright © 2016 Elsevier Ltd. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.ocemod.2016.12.004
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