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    Turbulent and numerical mixing in a salt wedge estuary : dependence on grid resolution, bottom roughness, and turbulence closure

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    Ralston_et_al-2017-Journal_of_Geophysical_Research__Oceans.pdf (9.175Mb)
    Date
    2017-01-28
    Author
    Ralston, David K.  Concept link
    Cowles, Geoffrey W.  Concept link
    Geyer, W. Rockwell  Concept link
    Holleman, Rusty C.  Concept link
    Metadata
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    Citable URI
    https://hdl.handle.net/1912/8871
    As published
    https://doi.org/10.1002/2016JC011738
    DOI
    10.1002/2016JC011738
    Keyword
     Estuary; Salt wedge; Numerical mixing; Turbulence closure; Numerical model 
    Abstract
    The 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.
    Description
    Author 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.
    Collections
    • Applied Ocean Physics and Engineering (AOP&E)
    Suggested Citation
    Journal of Geophysical Research: Oceans 122 (2017): 692–712
     

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