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Challenging Vertical Turbulence Mixing Schemes in a Tidally Energetic Environment: 1. 3‐D Shelf‐Sea Model Assessment
Author(s) -
Luneva Maria V.,
Wakelin Sarah,
Holt Jason T.,
Inall Mark E.,
Kozlov Igor E.,
Palmer Matthew R.,
Toberman Matthew,
Zubkova Evgenia V.,
Polton Jeff A.
Publication year - 2019
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1029/2018jc014307
Subject(s) - pycnocline , mixed layer , stratification (seeds) , hydrography , thermocline , biogeochemical cycle , environmental science , benthic zone , oceanography , richardson number , turbulence , geology , atmospheric sciences , climatology , meteorology , physics , chemistry , seed dormancy , botany , germination , dormancy , environmental chemistry , biology
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.