Probing turbulence intermittency via Auto-Regressive Moving-Average models

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We suggest a new approach to probing intermittency corrections to the Kolmogorov law in turbulent flows based on the Auto-Regressive Moving-Average modeling of turbulent time series. We introduce an index Upsilon that measures the distance from a Kolmogorov-Obukhov model in the Auto-Regressive Moving-Average models space. Applying our analysis to Laser Doppler Velocimetry measurements in a von Karman swirling flow, we show that Upsilon is proportional to traditional intermittency corrections computed from structure functions. Therefore it provides the same information, using much shorter time series. We conclude that Upsilon is a suitable index to reconstruct intermittency in experimental turbulent fields.