Simulation of the Arctic—North Atlantic Ocean Circulation with a Two-Equation K-Omega Turbulence Parameterization
The results of large-scale ocean dynamics simulation taking into account the parameterization of vertical turbulent exchange are considered. Numerical experiments were carried out using k − ω turbulence model embedded to the Institute of Numerical Mathematics Ocean general circulation Model (INMOM)....
| Published in: | Journal of Marine Science and Engineering |
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| Main Authors: | , , |
| Format: | Text |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute
2018
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| Subjects: | |
| Online Access: | https://doi.org/10.3390/jmse6030095 |
| Summary: | The results of large-scale ocean dynamics simulation taking into account the parameterization of vertical turbulent exchange are considered. Numerical experiments were carried out using k − ω turbulence model embedded to the Institute of Numerical Mathematics Ocean general circulation Model (INMOM). Both the circulation and turbulence models are solved using the splitting method with respect to physical processes. We split k − ω equations into the two stages describing transport-diffusion and generation-dissipation processes. At the generation-dissipation stage, the equation for ω does not depend on k. It allows us to solve both turbulence equations analytically that ensure high computational efficiency. The coupled model is used to simulate the hydrophysical fields of the North Atlantic and Arctic Oceans for 1948–2009. The model has a horizontal resolution of 0.25 ∘ and 40 σ -levels along the vertical. The numerical results show the model’s satisfactory performance in simulating large-scale ocean circulation and upper layer dynamics. The sensitivity of the solution to the change in the coefficients entering into the analytical solution of the k − ω model which describe the influence of some physical factors is studied. These factors are the climatic annual mean buoyancy frequency (AMBF) and Prandtl number as a function of the Richardson number. The experiments demonstrate that taking into account the AMBF improves the reproduction of large-scale ocean characteristics. Prandtl number variations improve the upper mixed layer depth simulation. |
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