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dc.contributor.authorRalston, David K.  Concept link
dc.contributor.authorCowles, Geoffrey W.  Concept link
dc.contributor.authorGeyer, W. Rockwell  Concept link
dc.contributor.authorHolleman, Rusty C.  Concept link
dc.date.accessioned2017-04-04T20:06:04Z
dc.date.available2017-07-28T08:30:37Z
dc.date.issued2017-01-28
dc.identifier.citationJournal of Geophysical Research: Oceans 122 (2017): 692–712en_US
dc.identifier.urihttps://hdl.handle.net/1912/8871
dc.descriptionAuthor Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 122 (2017): 692–712, doi:10.1002/2016JC011738.en_US
dc.description.abstractThe Connecticut River is a tidal salt wedge estuary, where advection of sharp salinity gradients through channel constrictions and over steeply sloping bathymetry leads to spatially heterogeneous stratification and mixing. A 3-D unstructured grid finite-volume hydrodynamic model (FVCOM) was evaluated against shipboard and moored observations, and mixing by both the turbulent closure and numerical diffusion were calculated. Excessive numerical mixing in regions with strong velocities, sharp salinity gradients, and steep bathymetry reduced model skill for salinity. Model calibration was improved by optimizing both the bottom roughness (z0), based on comparison with the barotropic tidal propagation, and the mixing threshold in the turbulence closure (steady state Richardson number, Rist), based on comparison with salinity. Whereas a large body of evidence supports a value of Rist ∼ 0.25, model skill for salinity improved with Rist ∼ 0.1. With Rist = 0.25, numerical mixing contributed about 1/2 the total mixing, while with Rist = 0.10 it accounted for ∼2/3, but salinity structure was more accurately reproduced. The combined contributions of numerical and turbulent mixing were quantitatively consistent with high-resolution measurements of turbulent mixing. A coarser grid had increased numerical mixing, requiring further reductions in turbulent mixing and greater bed friction to optimize skill. The optimal Rist for the fine grid case was closer to 0.25 than for the coarse grid, suggesting that additional grid refinement might correspond with Rist approaching the theoretical limit. Numerical mixing is rarely assessed in realistic models, but comparisons with high-resolution observations in this study suggest it is an important factor.en_US
dc.description.sponsorshipNSF Grant Number: OCE 0926427; ONR Grant Number: N00014-08-1-1115en_US
dc.language.isoen_USen_US
dc.publisherJohn Wiley & Sonsen_US
dc.relation.urihttps://doi.org/10.1002/2016JC011738
dc.subjectEstuaryen_US
dc.subjectSalt wedgeen_US
dc.subjectNumerical mixingen_US
dc.subjectTurbulence closureen_US
dc.subjectNumerical modelen_US
dc.titleTurbulent and numerical mixing in a salt wedge estuary : dependence on grid resolution, bottom roughness, and turbulence closureen_US
dc.typeArticleen_US
dc.description.embargo2017-07-28en_US
dc.identifier.doi10.1002/2016JC011738


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