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Predictability of isotropic turbulence by massive ensemble forecasting

Alberto Vela-Martín

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Phys. Rev. Fluids 9, L122601 – Published 4 December, 2024

DOI: https://doi.org/10.1103/PhysRevFluids.9.L122601

Abstract

The predictability of isotropic turbulence is studied with unprecedented detail using massive Monte Carlo ensembles. Predictability loss is characterized by the smoothing of the ensemble-averaged flow field with the forecasting time, which is accurately captured by the ensembles. It is shown that this process is well described in scale and physical space by a Gaussian low-pass filter, with a characteristic length scale that increases in time following a self-similar scaling. These results simplify the quantification of uncertainty in turbulence forecasts and open the possibility to efficiently assess the predictability of local inertial- and large-scale flow patterns.

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Outline

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Phys. Rev. Fluids 9, L122601– Published 4 December, 2024
  • Received 10 August 2023
  • Accepted 17 September 2024
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