Parallel assimilation of observed data in the hydrodynamic model of the ocean circulation

  • K. P. BelyaevEmail author
  • A. A. Kuleshov
  • I. N. Smirnov
  • C. A. S. Tanajura


The parallel use of the Kalman ensemble filter technique for assimilating data from observations in theHYCOMmodel of theWorldOcean is described. Data from satellite observations of the sea’s surface temperature and the sea’s surface height are assimilated both separately and conjointly. Numerical experiments on correcting model calculations using data from observations are performed. The results from the corrections are compared to model calculations without assimilation. The effectiveness of the employed parallelization algorithm is confirmed.


assimilation of observational data ocean circulation model parallel calculations numerical experiments 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    M. Valdivieso, K. Haines, and M. Balmaseda, “An assessment of air–sea heat fluxes from ocean and coupled reanalyses,” Climate Dyn. 10, 1–26 (2015).Google Scholar
  2. 2.
    V. I. Agoshkov, V. M. Ipatova, V. B. Zalesnyi, E. I. Parmuzin, and V. P. Shutyaev, “Problems of variational assimilation of observational data for ocean ceneral circulation models and methods for their solution,” Izv., Atmos. Ocean. Phys. 46, 677–712 (2010).CrossRefGoogle Scholar
  3. 3.
    M. N. Kaurkin, R. A. Ibraev, and K. P. Belyaev, “Data assimilation in the ocean circulation model of high spatial resolution using the methods of parallel programming,” Russ. Meteorol.Hydrol. 41, 479–486 (2016).CrossRefGoogle Scholar
  4. 4.
    V. V. Knysh, G. K. Korotaev, A. I. Mizyuk, and A. S. Sarkisyan, “Assimilation of hydrological observation data for calculating currents in seas and oceans,” Izv., Atmos. Ocean. Phys. 48, 57–73 (2012).CrossRefGoogle Scholar
  5. 5.
    G. Evensen, Data Assimilation: The Ensemble Kalman Filter, 2nd ed. (Springer, Berlin, 2009).CrossRefzbMATHGoogle Scholar
  6. 6.
    K. P. Belyaev, C. A. S. Tanajura, and N. P. Tuchkova, “Comparison of methods for ARGO drifters data assimilation into a hydrodynamical model of the ocean,” Oceanology 52, 593–603 (2012).CrossRefGoogle Scholar
  7. 7.
    C. A. S. Tanajura and K. A. Belyaev, “Sequential data assimilation method based on the properties of a diffusion-type process,” Appl.Math. Model. 33, 2165–2174 (2009).MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    E. Kalnay, H. Li, T. Miyoshi, et al., “4D-Var or ensemble Kalman filter,” Tellus, Ser. A: Dyn. Meteorol. Oceanogr. 59, 758–773 (2007).CrossRefGoogle Scholar
  9. 9.
    R. Bleck and D. B. Boudra, “Initial testing of a numerical ocean circulation model using a hybrid quasiisopycnal vertical coordinate,” J. Phys. Oceanogr. 11, 755–770 (1981).CrossRefGoogle Scholar
  10. 10.
    R. Bleck, “An oceanic general circulation model framed in hybrid isopycnic Cartesian coordinates,” Ocean Model. 4 (1), 55–88 (2002).CrossRefGoogle Scholar
  11. 11.
    S. M. Griffies, A. Biastoch, and C. Boning, et al., “Coordinated ocean-ice reference experiments (COREs),” OceanModel. 26 (12), 1–46 (2009).Google Scholar
  12. 12.
    E. Kalnay, Atmospheric Modeling, Data Assimilation and Predictability (Cambridge Univ. Press, Cambridge, 2003).Google Scholar
  13. 13.
    J. Xie and J. Zhu, “Ensemble optimal interpolation schemes for assimilating Argo profiles into a hybrid coordinate ocean model,” Ocean Model. 33, 283–298 (2010).CrossRefGoogle Scholar
  14. 14.
    K. P. Belyaev, A. A. Kuleshov, and C. A. S. Tanajura, “An application of a data assimilation method based on the diffusion stochastic process theory using altimetry data in Atlantic,” Russ. J. Numer. Anal.Math. Model. 31, 137–148 (2016).MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Allerton Press, Inc. 2017

Authors and Affiliations

  • K. P. Belyaev
    • 1
    Email author
  • A. A. Kuleshov
    • 2
  • I. N. Smirnov
    • 3
  • C. A. S. Tanajura
    • 4
  1. 1.Shirshov Institute of OceanologyRussian Academy of SciencesMoscowRussia
  2. 2.Keldysh Institute of Applied MathematicsRussian Academy of SciencesMoscowRussia
  3. 3.Department of Computational Mathematics and CyberneticsMoscow State UniversityMoscowRussia
  4. 4.Federal University of BahiaSalvadorBrazil

Personalised recommendations