Direct numerical simulation uncovers strain rate as the primary driver of extreme uncertainty production in turbulent flows, highlighting fundamental limits in predicting localized chaotic dynamics.
We investigate the exponential growth of uncertainty energy in three-dimensional (3-D) Navier–Stokes turbulence, emphasising the intermittent and highly localised amplification/production of uncertainty, a critical factor in understanding the predictability of turbulent systems. From the Navier–Stokes equations, one can identify some key fields contributing to the growth/decay of uncertainty-production term upper P Subscript upper Delta P Δ P : strain rate, vorticity and vortex deformation. The dynamics of these fields is examined in the upper Q minus upper R Q − R Q-R plane, where upper Q Q Q and upper R R R are the second and third invariants of the velocity gradient tensor, to understand their role in the evolution of uncertainty-production term upper P Subscript upper Delta P Δ P . We proceed by estimating committor functions across the entire spatiotemporal domain of the direct numerical simulation (DNS) of turbulence in a periodic domain at different Reynolds numbers. Our estimates of the probability of rare extreme events of the local uncertainty-production term as a function of uncertainty energy, strain rate, vorticity and vortex deformation confirm the role of strain rate in driving uncertainty. Where strain rate and vorticity are too close to their space-average values, stable probabilistic forecasts appear impossible solely based on the fields considered here.
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Ge et al. (2026) studied this question.
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