Measured Statistics of Multicomponent Gust Patterns in Atmospheric Turbulence

Abstract

Non-Gaussian statistical properties of severe atmospheric turbulence, recorded at both high and low altitudes, are illustrated by analyzing the outputs of linear filters tuned to respond to multicomponent gust patterns comprising sequences of velocity increments, or ramp gusts. The measured probability distributions of filter outputs typically have strong tails which can be fitted by a model of exponential form. Although it is known that exponential distributions can be reproduced by considering sequences of Gaussian patches, as assumed in the power-spectral-density method for gust-loads prediction, it is demonstrated, by comparing the outputs of pairs of filters which are tuned to respond to gust patterns comprising different numbers of component increments, that the measured severe turbulence has non-Gaussian properties that cannot be reproduced in this way. In particular, the ratio of the response of a filter tuned to a complex gust pattern to that of a filter tuned to a single-ramp gust varies as a function of gust amplitude, reducing as the amplitude increases. This result is consistent with the hypothesis that the more severe gusts, associated with the tails of the distributions, tend to occur in short bursts and is in conflict with the result predicted by the power-spectral-density method, which is that the above ratio is independent of the amplitude. Reference is made to the representation of the burst phenomenon in the statistical-discrete-gust model of extreme turbulence.