The influence of mesoscale eddies on coarsely resolved density: An examination of subgrid-scale parameterization

Citation
St. Gille et Re. Davis, The influence of mesoscale eddies on coarsely resolved density: An examination of subgrid-scale parameterization, J PHYS OCEA, 29(6), 1999, pp. 1109-1123
Citations number
35
Categorie Soggetti
Aquatic Sciences","Earth Sciences
Journal title
JOURNAL OF PHYSICAL OCEANOGRAPHY
ISSN journal
00223670 → ACNP
Volume
29
Issue
6
Year of publication
1999
Pages
1109 - 1123
Database
ISI
SICI code
0022-3670(199906)29:6<1109:TIOMEO>2.0.ZU;2-O
Abstract
Coarse-resolution numerical models of ocean circulation rely on parameteriz ations of unresolved mesoscale eddy effects. In order to investigate the ro le of eddy-flux divergences in the density equation, the GFDL Modular Ocean Model (MOM) has been configured as a simple flat-bottomed channel model wi th sufficient resolution to represent mesoscale eddies. Eady-type baroclini c instability and a wind-forced channel have been considered. As an analog to the large-scale components addressed by low-resolution models, the influ ence of eddy fluxes on the zonal-mean density held was evaluated. Results s how that eddy-flux divergences are larger than mean-flux divergences. The e ffect of mesoscale eddies on the mean density field is often hypothesized t o take an advective form that conserves mean density so that eddy effects a re adiabatic in the zonal mean. However. in both of the examples studied a significant component of the mesoscale eddy effect on the zonal mean is dia batic and makes mean density nonconservative. The associated diapycnal flux es result from zonally averaging terms representing processes that are loca lly adiabatic. Subgrid-scale parameterizations (such as eddy diffusion) represent the unre solved eddy-flux divergence as a function of the resolved density field. Th e authors computed optimal coefficients for a variety of parameterizations and evaluated their skill. When the model output is time-averaged, quasi-ad iabatic parameterizations, such as the one proposed by Gent and McWilliams, are able to explain as much as 43% of the mean-squared eddy-flux divergenc e. However, for shorter averaging periods or instantaneous snapshots, even for the spatially averaged model fields, parameterization skill drops.