Conditional Sampling of Coherent Structures in Atmospheric Turbulence Using the Wavelet Transform

Abstract

The development and evaluation of a technique to detect and retrieve coherent structures embedded in a record of atmospheric surface-layer temperature fluctuations is described. This new detection scheme, based on a local wavelet transform, is used to conditionally sample the organized structures from the more random background turbulence. This method provides a much needed alternative to the commonly used but not so objective variable interval time averaging. When conditional sampling using the wavelet transform is applied, the series is decomposed into two signals, one with high wavelet coefficients and one with low coefficients, corresponding to the strong events and to random turbulence of the flow, respectively. A test of the method shows it to be successful in detecting and retrieving localized structures in a record of temperature fluctuations.