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  • Estuarine mixing  (1)
  • Mixing  (1)
Document type
Years
  • 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 Journal of Physical Oceanography 48 (2018): 607-623, doi:10.1175/JPO-D-17-0189.1.
    Description: The roles of straining and dissipation in controlling stratification are derived analytically using a vertical salinity variance method. Stratification is produced by converting horizontal variance to vertical variance via straining, that is, differential advection of horizontal salinity gradients, and stratification is destroyed by the dissipation of vertical variance through turbulent mixing. A numerical model is applied to the Changjiang estuary in order to demonstrate the salinity variance balance and how it reveals the factors controlling stratification. The variance analysis reveals that dissipation reaches its maximum during spring tide in the Changjiang estuary, leading to the lowest stratification. Stratification increases from spring tide to neap tide because of the increasing excess of straining over dissipation. Throughout the spring–neap tidal cycle, straining is almost always larger than dissipation, indicating a net excess of production of vertical variance relative to dissipation. This excess is balanced on average by advection, which exports vertical variance out of the estuarine region into the plume. During neap tide, tidal straining shows a general tendency of destratification during the flood tide and restratification during ebb, consistent with the one-dimensional theory of tidal straining. During spring tide, however, positive straining occurs during flood because of the strong baroclinicity induced by the intensified horizontal salinity gradient. These results indicate that the salinity variance method provides a valuable approach for examining the spatial and temporal variability of stratification in estuaries and coastal environments.
    Description: X. Li was supported by the China Scholarship Council. W. R. Geyer was supported by NSF Grants OCE 1736539 and OCE 1634480. J. Zhu was supported by the National Natural Science Foundation of China (41476077 and 41676083). H. Wu was supported by the National Natural Science Foundation of China (41576088 and 41776101).
    Description: 2018-09-08
    Keywords: Ocean ; Estuaries ; Freshwater ; Mixing ; Numerical analysis/modeling ; Regional models
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-27
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kalra, T. S., Li, X., Warner, J. C., Geyer, W. R., & Wu, H. Comparison of physical to numerical mixing with different tracer advection schemes in estuarine environments. Journal of Marine Science and Engineering, 7(10), (2019): 338, doi: 10.3390/jmse7100338.
    Description: The numerical simulation of estuarine dynamics requires accurate prediction for the transport of tracers, such as temperature and salinity. During the simulation of these processes, all the numerical models introduce two kinds of tracer mixing: (1) by parameterizing the tracer eddy diffusivity through turbulence models leading to a source of physical mixing and (2) discretization of the tracer advection term that leads to numerical mixing. Physical and numerical mixing both vary with the choice of horizontal advection schemes, grid resolution, and time step. By simulating four idealized cases, this study compares the physical and numerical mixing for three different tracer advection schemes. Idealized domains only involving physical and numerical mixing are used to verify the implementation of mixing terms by equating them to total tracer variance. Among the three horizontal advection schemes, the scheme that causes the least numerical mixing while maintaining a sharp front also results in larger physical mixing. Instantaneous spatial comparison of mixing components shows that physical mixing is dominant in regions of large vertical gradients, while numerical mixing dominates at sharp fronts that contain large horizontal tracer gradients. In the case of estuaries, numerical mixing might locally dominate over physical mixing; however, the amount of volume integrated numerical mixing through the domain compared to integrated physical mixing remains relatively small for this particular modeling system.
    Description: This study was funded through the Coastal Model Applications and Field Measurements Project and the Cross-shore and Inlets Project, US Geological Survey Coastal Marine Hazards and Resources Program.
    Keywords: Physical mixing ; Numerical mixing ; Advection schemes ; Estuarine mixing
    Repository Name: Woods Hole Open Access Server
    Type: Article
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