4.7 Article

Challenging Vertical Turbulence Mixing Schemes in a Tidally Energetic Environment: 1.3-D Shelf-Sea Model Assessment

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
Volume 124, Issue 8, Pages 6360-6387

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2018JC014307

Keywords

turbulence closure assessment; 3-D modeling; pycnocline mixing

Categories

Funding

  1. UK Natural Environment Research Council (NERC)
  2. NERC [NE/L003325/1, NE/K001698/1]
  3. RFBR [16-35-60072 mol_a_dk]
  4. Russian Science Foundation [17-77-30019]
  5. Russian Science Foundation [17-77-30019] Funding Source: Russian Science Foundation
  6. NERC [NE/K001698/1, NE/L003325/1] Funding Source: UKRI

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Mixing in the ocean and shelf seas is critical for the vertical distribution of dynamically active properties, such as density and biogeochemical tracers. Eight different decadal simulations are used to assess the skill of vertical turbulent mixing schemes (TMS) in a 3-D regional model of tidally active shelf seas. The TMS differ in the type of stability functions used and in the Ozmidov/Deardorff/Galperin limiter of the turbulence length scales. We review the dependence of the critical Richardson and Prandtl numbers to define the diffusiveness of the TMS. The skill in representing bias and variability of stratification profiles is assessed with five different metrics: surface and bottom temperatures and pycnocline depth, thickness, and strength. The assessment is made against hydrography from three data sets (28,000 profiles in total). Bottom and surface temperatures are found to be as sensitive to TMS choice as to horizontal resolution or heat flux formulation, as reported in other studies. All TMS underrepresent the pycnocline depth and benthic temperatures. This suggests physical processes are missing from the model, and these are discussed. Different TMSs show the best results for different metrics, and there is no outright winner. Simulations coupled with an ecosystem model show the choice of TMS strongly affects the ecosystem behavior: shifting the timing of peak chlorophyll by 1 month, showing regional chlorophyll differences of order 100%, and redistributing the production of chorophyll between the pycnocline and mixed layer.

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