INTERMITTENCY, LOCAL ISOTROPY, AND NON-GAUSSIAN STATISTICS IN ATMOSPHERIC SURFACE-LAYER TURBULENCE

Orthonormal wavelet expansions are applied to atmospheric surface laye r velocity and temperature measurements above a uniform bare soil surf ace that exhibit a long inertial subrange energy spectrum. In order to investigate intermittency effects on Kolmogorov's theory, a direct re lation between the nth-order structure function and the wavelet coeffi cients is derived. This relation is used to examine deviations from th e classical Kolmogorov theory for velocity and temperature in the iner tial subrange. The local nature of the orthonormal wavelet transform i n physical space aided the identification of events directly contribut ing to intermittency buildup at inertial subrange scales. These events occur at edges of large eddies and contaminate the Kolmogorov inertia l subrange scaling. By suppressing these events, the statistical struc ture of the inertial subrange for the velocity and temperature, as des cribed by Kolmogorov's theory, is recovered. The suppression of interm ittency on the nth-order structure function is carried out via a condi tional wavelet sampling scheme. The conditioned wavelet statistics rep roduced the Kolmogorov scaling (up to n = 6) in the inertial subrange and result in a zero intermittency factor. The conditional wavelet sta tistics for the mixed velocity temperature structure functions are als o presented. It was found that the conditional wavelet statistics for these mixed moments result in a thermal intermittency parameter consis tent with other laboratory and field measurements. The relationship be tween Kolmogorov's theory and near-Gaussian statistics for velocity an d temperature gradients is also considered.