Wavelet analysis of atmospheric turbulence structures: What can we gain from this new technique?

The authors examined three specific methods for using the wavelet transform to derive information on the turbulence structure in the atmospheric boundary layer from raw data. The scale-time cross section method yields a qualitative picture of turbulence structures occurring at different times and different scales, the wavelet variance method provides a relatively objective estimate of principal scales associated with organized structures, and the wavelet cross correlation helps in identifying motions that are most important in turbulent transport and spatial coherence. The wavelet analysis can also be used to decompose the data for different scales and to detect coherent structures objectively by using the transform coefficient at the principal scale detected by the variance method (Collineau and Brunet, 1993; Coulter and Li, 1995). These methods can improve their capability to unfold the data for hidden information that is difficult to obtain from traditional spectral analysis and thus can provide a useful tool for understanding multiscale phenomena in the atmospheric boundary layer