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Mathematical Models and Computer Simulations

, Volume 10, Issue 2, pp 176–185 | Cite as

Gas-Dynamic General Circulation Model of the Lower and Middle Atmosphere of the Earth

  • B. N. Chetverushkina
  • I. V. Mingalev
  • K. G. Orlov
  • V. M. Chechetkin
  • V. S. Mingalev
  • O. V. Mingalev
Article

Abstract

This paper presents a brief description of the General Circulation Model of the lower and middle atmosphere of the Earth, which is designed to study atmospheric dynamics in a wide range of spatial-temporal scales. The model is based on numerical integration of the complete system of equations that describe the dynamics of a viscous atmospheric gas using a spatial grid with a high resolution. The model takes into account the surface relief and the presence of atmosphere aerosols in the form of microdroplets of water ice particles, as well as the phase transitions of water vapor to aerosol particles and back.

Keywords

general circulation model atmospheric dynamics numerical simulation 

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References

  1. 1.
    A. S. Monin, Theoretical Principles of Geophysical Hydrodynamics (Gidrometeoizdat, Leningrad, 1988) [in Russian].Google Scholar
  2. 2.
    L. J. Donner et al., “The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3,” J. Clim. 24, 3438–3519 (2011).CrossRefGoogle Scholar
  3. 3.
    G. S. Rivin et al., “The COSMO-ru system of nonhydrostatic mesoscale short-range weather forecasting of the hydrometcenter of Russia: the second stage of implementation and development,” Russ. Meteorol. Hydrol. 49, 400–410 (2015).CrossRefGoogle Scholar
  4. 4.
    V. P. Dymnikov, V. N. Lykosov, and E. M. Volodin, “Problems of modeling climate and climate change,” Izv., Atmos. Ocean. Phys. 42, 568–586 (2006).CrossRefGoogle Scholar
  5. 5.
    V. N. Lykosov et al., Supercomputer Modeling in Climate System Physics (Mosk. Gos. Univ., Moscow, 2012) [in Russian].Google Scholar
  6. 6.
    B. N. Chetverushkin and E. V. Shilnikov, “Software package for 3D viscous gas flow simulation on multiprocessor computer systems,” Comput. Math. Math. Phys. 48, 295–305 (2008).MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    O. M. Belotserkovskii, A. M. Oparin, I. V. Mingalev, V. S. Mingalev, O. V. Mingalev, and V. M. Chechetkin, “Formation of large-scale vortices in shear flows of the lower atmosphere of the Earth in the region of tropical latitudes,” Cosm. Res. 47, 446–479 (2009).CrossRefGoogle Scholar
  8. 8.
    I. V. Mingalev, K. G. Orlov, and V. S. Mingalev, “The mechanism of formation of polar cyclones and possibility their predictions by using satellite observation data,” Sovrem. Probl. Distants. Zondir. Zemli Kosmosa 8 (1), 255–262 (2011).Google Scholar
  9. 9.
    I. V. Mingalev, N. M. Astaf’eva, K. G. Orlov, V. S. Mingalev, O. V. Mingalev, and V. M. Chechetkin, “Possibility of a detection of tropical cyclones and hurricanes formation according to satellite remote sensing,” Sovrem. Probl. Distants. Zondir. Zemli Kosmosa 8 (3), 290–296 (2011).Google Scholar
  10. 10.
    I. V. Mingalev, K. G. Orlov, and V. S. Mingalev, “A mechanism of formation of polar cyclones and possibility of their prediction using satellite observations,” Cosm. Res. 50, 160–169 (2012).CrossRefGoogle Scholar
  11. 11.
    I. V. Mingalev, K. G. Orlov, V. S. Mingalev, O. V. Mingalev, N. M. Astaf’eva, and V. M. Chechetkin, “Numerical simulation of formation of cyclone vortex flows in the intratropical zone of convergence and their early detection,” Cosm. Res. 50, 233–248 (2012).CrossRefGoogle Scholar
  12. 12.
    I. V. Mingalev, N. M. Astafieva, K. G. Orlov, V. S. Mingalev, O. V. Mingalev, and V. M. Chechetkin, “A simulation study of the formation of large-scale cyclonic and anticyclonic vortices in the vicinity of the intertropical convergence zone,” ISRN Geophys. 2013, 215362(2013).CrossRefGoogle Scholar
  13. 13.
    I. Mingalev, K. Orlov, and V. Mingalev, “A modeling study of the initial formation of polar lows in the vicinity of the arctic front,” Adv. Meteorol. 2014, 970547(2014).CrossRefGoogle Scholar
  14. 14.
    I. V. Mingalev, N. M. Astafieva, K. G. Orlov, V. S. Mingalev, O. V. Mingalev, and V. M. Chechetkin, “Numerical modeling of the initial formation of cyclonic vortices at tropical latitudes,” Atmos. Clim. Sci. 4, 899–906 (2014).Google Scholar
  15. 15.
    A. M. Obukhov, Turbulence and Dynamics of the Atmosphere (Gidrometeoizdat, Leningrad, 1988) [in Russian].Google Scholar
  16. 16.
    P. C. Reist, Introduction to Aerosol Science (Macmillan, London, New York, 1984).Google Scholar
  17. 17.
    B. N. Chetverushkin, Mathematical Modeling of Problems in the Dynamics of Radiating Gas (Nauka, Moscow, 1985) [in Russian].zbMATHGoogle Scholar
  18. 18.
    B. A. Fomin, “A k-distribution technique for radiative transfer simulation in inhomogeneous atmosphere: 1. FKDM, fast k-distribution model for the longwave,” J. Geophys. Res. 109, D02110 (2004). doi 10.1029/ 2003JD003802CrossRefGoogle Scholar
  19. 19.
    B. A. Fomin and M. P. Correa, “A k-distribution technique for radiative transfer simulation in inhomogeneous atmosphere: 2. FKDM, fast k-distribution model for the shortwave,” J. Geophys. Res. 110, D02106 (2005). doi 10.1029/2004JD005163CrossRefGoogle Scholar
  20. 20.
    A. V. Shilkov and M. N. Gerthev, “Verification of the Lebesgue averaging method,” Math. Models Comput. Simul. 8, 93–107 (2016).MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    V. S. Mingalev, I. V. Mingalev, O. V. Mingalev, A. M. Oparin, and K. G. Orlov, “Generalization of the hybrid monotone second-order finite difference scheme for gas dynamics equations to the case of unstructured 3D grid,” Comput. Math. Math. Phys. 50, 877–899 (2010). doi 10.1134/S0965542510050118MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    V. A. Bakhtin, V. A. Kryukov, B. N. Chetverushkin, and E. V. Shil’nikov, “Extension of the DVM parallel programming model for clusters with heterogeneous nodes,” Dokl. Math. 84, 879–881 (2011).MathSciNetCrossRefGoogle Scholar
  23. 23.
    J. M. Picone, A. E. Hedin, D. P. Drob, and A. C. Aikin, “NRLMSISE-00 empirical model of the atmosphere: statistical comparisons and scientific issues,” J. Geophys. Res. 107 (A12), 1468–1483 (2002).CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • B. N. Chetverushkina
    • 1
  • I. V. Mingalev
    • 2
  • K. G. Orlov
    • 2
  • V. M. Chechetkin
    • 1
    • 3
    • 4
  • V. S. Mingalev
    • 2
  • O. V. Mingalev
    • 2
  1. 1.Keldysh Institute of Applied MathematicsRussian Academy of SciencesMoscowRussia
  2. 2.Polar Geophysical InstituteRussian Academy of SciencesMurmanskRussia
  3. 3.National Research Nuclear University MEPhIMoscowRussia
  4. 4.National Research Centre Kurchatov InstituteMoscowRussia

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