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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2018. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in he balance of salinity variance in a partially stratified estuary: Implications for exchange flow, mixing, and stratification. Journal of Physical Oceanography, 48(12), (2018) 2887-2899., doi: 10.1175/JPO-D-18-0032.1.
    Description: Salinity variance dissipation is related to exchange flow through the salinity variance balance equation, and meanwhile its magnitude is also proportional to the turbulence production and stratification inside the estuary. As river flow increases, estuarine volume-integrated salinity variance dissipation increases owing to more variance input from the open boundaries driven by exchange flow and river flow. This corresponds to the increased efficient conversion of turbulence production to salinity variance dissipation due to the intensified stratification with higher river flow. Through the spring–neap cycle, the temporal variation of salinity variance dissipation is more dependent on stratification than turbulence production, so it reaches its maximum during the transition from neap to spring tides. During most of the transition time from spring to neap tides, the advective input of salinity variance from the open boundaries is larger than dissipation, resulting in the net increase of variance, which is mainly expressed as vertical variance, that is, stratification. The intensified stratification in turn increases salinity variance dissipation. During neap tides, a large amount of enhanced salinity variance dissipation is induced by the internal shear stress near the halocline. During most of the transition time from neap to spring tides, dissipation becomes larger than the advective input, so salinity variance decreases and the stratification is destroyed.
    Description: TW was supported by the National Key R&D Program of China (Grant 2017YFA0604104), National Natural Science Foundation of China (Grant 41706002), Natural Science Foundation of Jiangsu Province (Grant BK20170864), and MEL Visiting Fellowship (MELRS1617). WRG was supported by NSF Grant OCE 1736539. Part of this work is finished during TW’s visit in MEL and WHOI. We would like to acknowledge John Warner for providing the codes of the Hudson estuary model, and Parker MacCready, the editor, and two reviewers for their insightful suggestions on improving the manuscript.
    Description: 2019-06-06
    Keywords: Estuaries ; Dynamics ; Mixing ; Density Currents
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-25
    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.
    Description: 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: NSF Grant Number: OCE 0926427; ONR Grant Number: N00014-08-1-1115
    Description: 2017-07-28
    Keywords: Estuary ; Salt wedge ; Numerical mixing ; Turbulence closure ; Numerical model
    Repository Name: Woods Hole Open Access Server
    Type: Article
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