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Predictability of 3D Isotropic Turbulence —Effect of Data Assimilation—

  • Kazuki Hayashi
  • Takashi Ishihara
  • Yukio Kaneda
Conference paper

Abstract

In numerical simulation of turbulent flows, it is usually difficult to obtain exact initial conditions and it is well known that initial uncertainty in high wavenum-bers spreads toward large scale through nonlinear dynamics. These imply the limitation of the numerical prediction. We present here a series of numerical experiments to study the effect of data assimilation on the predictability of isotopic 3D turbulence. In the experiment we have two parameters K c and T to control the data assimilation, where K c is the maximum of the assimilated wavenumber range and T is the time interval of the assimilation. It is found not only that we can suppress the growth of uncertainty by data assimilation but also that we can reduce it under appropriate conditions on K c and T. It is also found that there exists a critical K c * such that if K c < K c * the uncertainty grows for any T.

Keywords

Data Assimilation Difference Spectrum Numerical Weather Prediction Initial Uncertainty Large Wavenumbers 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    G.K. Batchelor: The theory of homogeneous turbulence (Cambridge University Press, Cambridge 1953)MATHGoogle Scholar
  2. 2.
    Heinz-Otto Kreiss, J. Ystrom: A numerical study of the solution to the 3D incompressible Navier-Stokes equations. Research report, UCLA, Los Angeles (1998)Google Scholar

Copyright information

© Springer Japan 2003

Authors and Affiliations

  • Kazuki Hayashi
    • 1
  • Takashi Ishihara
    • 1
  • Yukio Kaneda
    • 1
  1. 1.Department of Computational Science and EngineeringGraduate School of EngineeringJapan

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