Simulation of the Arctic—North Atlantic Ocean Circulation with a Two-Equation K-Omega Turbulence Parameterization

Abstract

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.

Sensitivity of the ocean circulation model to the k–omega vertical turbulence parametrization

“…алгоритм, использующий аналитическое решение (18), (19), мы называем «алгоритмом расщепления турбулентности» (аРТ) [10,13,14].…”

“…Важными факторами повышения адекватности моделирования крупномасштабной циркуляции океана является подбор модельных параметров и использование в расчетах данных наблюдений. В наших работах [13,14] изучена возможность повышения адекватности МОцО с помощью учета в A и B данных наблюдений о среднегодовой климатической частоте плавучести. С этой точки зрения алгоритм является достаточно гибким.…”

“…В рамках традиционной модели, основанной на «примитивных» уравнениях, это -подсеточный процесс, подлежащий параметризации. Параметризация подсеточных процессов остается одной из актуальнейших задач моделирования и прогноза гидрофизических и метеорологических полей [4][5][6][7][8][9][10][11][12][13][14].…”

Circulation Mechanisms of the Stabilization of the Ocean Active Layer Regional Dynamics

“…Расчеты проводятся на срок: январь 1948 г. -декабрь 2009 г. Проведено несколько экспериментов с разными вариантами параметров в коэффициентах аналитического решения уравнений турбулентности на стадии генерации-диссипации (Moshonkin et al, 2018). Дальнейший анализ бароклинных мод течений показал непротиворечивость результатов, полученных в этих экспериментах.…”

Investigation of the Barents Sea Upper Layer Response to the Polar Low in 1975

“…To solve the problem of a comprehensive study of the marine response to the PL passage, all of the above systems are not suitable mainly due to the rough spatial resolution of the marine models used in them. The MARS is a complex of numerical models and it consists of a regional non-hydrostatic atmospheric circulation model -Weather Research Forecast Model (WRF) [29] with a spatial resolution of 15 km for calculating meteorological parameters, of threedimensional σ-model of the Institute of Numerical Mathematics Ocean Model (INMOM) sea circulation and sea ice [30][31][32] in the version for the Barents, White, Pechora and Kara Seas with a spatial resolution of 2.7 km [20] for calculating hydrological parameters and ice characteristics, of Russian atmospheric-wave model (RAVM) [33] with spatial resolution as in the atmospheric model for calculating wind-wave characteristics. Non-hydrostatic atmospheric circulation model WRF with the used spatial resolution can reproduce mesoscale atmospheric processes, such as, for example, the Novaya Zemlya bora formation [34].…”