Predictability of the energy cascade in 2D turbulence
classification
🌊 nlin.CD
keywords
energyerrorcascadegrowthmeansnumericalpredictabilityturbulence
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The predictability problem in the inverse energy cascade of two-dimensional turbulence is addressed by means of direct numerical simulations. The growth rate as a function of the error level is determined by means of a finite size extension of the Lyapunov exponent. For error within the inertial range, the linear growth of the error energy, predicted by dimensional argument, is verified with great accuracy. Our numerical findings are in close agreement with the result of TFM closure approximation.
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