Using wavelets to identify coherent structures and evaluate conditional averages in atmospheric boundary layer data

Pamela Rawe
Masters Essay, The John Hopkins University
December 1999, Baltimore MD

ABSTRACT: High-resolution wind velocity and temperature data in the atmospheric surface layer are collected with a double array of sonic anemometers. The data are used to study the relation between the sub-grid scale (SGS) heat flux and dissipation of temperature variance and large-scale coherent structures (sweeps and ejections). Conditional averaging is used to isolate the effects of large-scale temperature ramps present in the flow on the SGS fluxes and dissipation. The conditional averaging requires a criterion to detect coherent structures. A new condition is proposed and tested based on a ramp like wavelet transform that peaks when ramp structures are present in the temperature signal. The sensitivity of the results is explored by changing the parameters that define the wavelet. The results show that coherent ramp like structures have a strong effect on SGS flows and dissipation. In particular, the part of the ramp that detects the onset of sweeps is associated with an increase in SGS dissipation, while the onset of an ejection is associated with a decrease in SGS dissipation.