Modelling Ocean Climate Variability

Sarkisyan, A. S.; Sündermann, Jürgen

doi:10.1007/978-1-4020-9208-4

Cited by 42 publications

(28 citation statements)

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“…New measurement methods and modern computing technologies allow for describing complex hydrodynamic processes, and analyzing the fine structure of hydrophysical fields, their mesoscale, and sub-mesoscale variability [1][2][3][4][5][6]. The development of numerical models, increasing their adequacy and accuracy, is also associated with an increase in spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

“…The development of numerical models, increasing their adequacy and accuracy, is also associated with an increase in spatial resolution. Reproduction and analysis of marine processes stimulate the construction of effective methods for calculating the dynamics of coastal currents in a wide range of spatio-temporal variability [2,3,[7][8][9][10][11][12][13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…Two main parts can be singled out in the operator of the governing equations. The first one is the classical established basis, viz., a subsystem describing the dynamics of rotating fluid in the framework of approximations traditional in oceanology [2,25]. The second one includes physical parameterizations of various kinds, which change as we gain a better understanding of natural phenomena [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

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Numerical Modeling of Marine Circulation, Pollution Assessment and Optimal Ship Routes

Zalesny

Agoshkov

Aps

et al. 2017

JMSE

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Methods and technology have been developed to solve a wide range of problems in the dynamics of sea currents and to assess their "impact" on objects in the marine environment. Technology can be used for monitoring and forecasting sea currents, for solving the problems of minimizing risks and analyzing marine disasters associated with the choice of the optimal course of the ship, and assessing the pollution of coastal zones, etc. The technology includes a numerical model of marine circulation with improved resolution of coastal zones, a method for solving the inverse problem of contamination of the sea with a passive impurity, and a variational algorithm for constructing the optimal trajectory of the vessel. The methods and technology are illustrated by solving problems of Baltic Sea dynamics. The model of sea dynamics is governed by primitive equations that are solved on a grid with an improved resolution of the selected coastal zone-in this case, the Gulf of Finland. The equations of the model are formulated in a bipolar orthogonal coordinate system with an arbitrary arrangement of poles and the sigma coordinate in the vertical direction. An increase in the horizontal resolution of the allocated zone is achieved due to the displacement of the north pole in the vicinity of the city of St. Petersburg. A class of dangerous technogenic situations and natural phenomena (sea accidents, which can be investigated with the help of the proposed methodology), includes tanker accidents in the case of a possible collision with a stationary object (with "dynamic danger") or a moving object (including another ship), accidents on oil-producing platforms and oil pipelines, and coastal pollution.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical Modeling of Marine Circulation, Pollution Assessment and Optimal Ship Routes

Zalesny

Agoshkov

Aps

et al. 2017

JMSE

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“…Such models are numerical tools used to understand and predict global ocean circulation (CHASSIGNET and VERRON, 2005;SARKISYAN and SUENDERMANN, 2009), its interaction with the atmosphere (MARCHUK, 1987), and the regional variability of seas and oceans (NECHAEV, 2003). Special emphasis is placed on such models when dealing with assimilation of observed data (WENZEL et al, 2001;CHASSIGNET and VERRON, 2005;NERGER, 2006;BLUM et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Variational Data Assimilation Technique in Mathematical Modeling of Ocean Dynamics

Agoshkov

Zalesny

2011

Pure Appl. Geophys.

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Problems of the variational data assimilation for the primitive equation ocean model constructed at the Institute of Numerical Mathematics, Russian Academy of Sciences are considered. The model has a flexible computational structure and consists of two parts: a forward prognostic model, and its adjoint analog. The numerical algorithm for the forward and adjoint models is constructed based on the method of multicomponent splitting. The method includes splitting with respect to physical processes and space coordinates. Numerical experiments are performed with the use of the Indian Ocean and the World Ocean as examples. These numerical examples support the theoretical conclusions and demonstrate the rationality of the approach using an ocean dynamics model with an observed data assimilation procedure.

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“…In OGCMs, vertical mixing is parameterized using a second-order differential operator with variable exchange coefficients K U , K T and K S [1][2][3][4][5]. The two basic approaches are used to determine these coefficients: (1) they are defined as functions of stratification and velocity shift or the local Richardson number [1,[6][7][8]; (2) they can be found using additional turbulence models [3,[9][10][11][12][13][14][15]. The first approach is more simple and efficient from the computational point of view.…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Arctic – North Atlantic Ocean Circulation with a Two-Equation k-omega Turbulence Parameterization

Moshonkin¹,

Zalesny²,

Гусев³

2018

Preprint

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Abstract:A method for solving the turbulence equations embedded in the sigma ocean general ocean circulation model is proposed. Like the general circulation model, the turbulence equations are solved using the splitting method by physical processes. The turbulence equations are split into two main stages describing transport-diffusion and generation-dissipation processes. Parameterization of turbulence in the framework of equations allows, at the generation-dissipation stage, to use both numerical and analytical solutions and to ensure high efficiency of the algorithm. 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-omega 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. The coupled model is used to simulate the hydrophysical fields of the North Atlantic and Arctic Oceans for . The model has a horizontal resolution of 0.25 degree and 40 sigma-levels along the vertical. The sensitivity of the solution to the changes in mixing parameterization is studied. Experiments demonstrate that taking into account the climatic annual mean buoyancy frequency improves the reproduction of large-scale ocean characteristics. There is a positive effect of Prandtl number variations for reproducing the upper mixed layer depth. The experiments also demonstrate the computational effectiveness of the proposed approach in solving the turbulence equations.

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Modelling Ocean Climate Variability

Cited by 42 publications

References 0 publications

Numerical Modeling of Marine Circulation, Pollution Assessment and Optimal Ship Routes

Numerical Modeling of Marine Circulation, Pollution Assessment and Optimal Ship Routes

Variational Data Assimilation Technique in Mathematical Modeling of Ocean Dynamics

Simulation of the Arctic – North Atlantic Ocean Circulation with a Two-Equation k-omega Turbulence Parameterization

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Modelling Ocean Climate Variability

Cited by 42 publications

References 0 publications

Numerical Modeling of Marine Circulation, Pollution Assessment and Optimal Ship Routes

Numerical Modeling of Marine Circulation, Pollution Assessment and Optimal Ship Routes

Variational Data Assimilation Technique in Mathematical Modeling of Ocean Dynamics

Simulation of the Arctic &ndash; North Atlantic Ocean Circulation with a Two-Equation k-omega Turbulence Parameterization

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Product

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Simulation of the Arctic – North Atlantic Ocean Circulation with a Two-Equation k-omega Turbulence Parameterization