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Parallel Numerical Implementation of Mathematical Wave Hydrodynamics Models Taking into Account the Features of the Vertical Turbulent Exchange Using Remote Sensing Data

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Abstract

This paper presents a parallel implementation of the wave hydrodynamics model and the modern SWAN wind-wave model. The results of the parameterization of the vertical turbulent exchange using filtered expedition data, which are included in the hydrodynamics model to clarify the coefficient of turbulent exchange, which is inhomogeneous vertically, are presented. The contours of the image of the Sea of Azov are used, determined by the method of a local binary template obtained from the WorldView satellite, as the input data in the models. The results of the numerical experiments obtained based on the SWAN model and a three-dimensional model of wave hydrodynamics are presented and compared. The article describes the parallel implementation of the SWAN model, calculates the indicators for evaluating its parallel computational efficiency, and determines the computational scalability of the SWAN model depending on the number of computational threads. The indicators for evaluating the parallel computational efficiency of a three-dimensional wave model of hydrodynamics are presented.

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Funding

This study was supported by the Russian Science Foundation through grant no. 23-21-00210, https://rscf.ru/project/23-21-00210/.

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Authors and Affiliations

  1. Faculty of Informatics and Computer Science, Don State Technical University, Rostov-on-Don, Russia

    A. I. Sukhinov, S. V. Protsenko & N. D. Panasenko

  2. Chekhov Taganrog Institute, Rostov State University of Economics, Taganrog, Russia

    E. A. Protsenko & N. D. Panasenko

Authors
  1. A. I. Sukhinov
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  2. E. A. Protsenko
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  3. S. V. Protsenko
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  4. N. D. Panasenko
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Correspondence to A. I. Sukhinov, E. A. Protsenko or S. V. Protsenko.

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Sukhinov, A.I., Protsenko, E.A., Protsenko, S.V. et al. Parallel Numerical Implementation of Mathematical Wave Hydrodynamics Models Taking into Account the Features of the Vertical Turbulent Exchange Using Remote Sensing Data. Math Models Comput Simul 16, 267–279 (2024). https://doi.org/10.1134/S2070048224020170

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