of ISDS 96 - 23 , Duke UniversityIDENTIFICATION OF LOW - DIMENSIONAL ENERGYCONTAINING / FLUX TRANSPORTING EDDYMOTION IN THE ATMOSPHERIC SURFACE LAYERUSING WAVELET

The partitioning of turbulent perturbations into a \low-dimensional" part responsible for much of the turbulent energy and uxes and a \high-dimensional" passive part that contributes little to turbulent energy and transport dynamics is investigated using atmospheric surface layer (ASL) measurements. It is shown that such a partitioning scheme can be achieved by transforming the ASL measurements into a domain that concentrates the \low-dimensional" part into few coeecients and thus permits a global threshold of the remaining coeecients. In this transformation-thresholding approach, Fourier rank reduction (FRR), and orthonormal wavelet and wavelet packet methods are considered. The eeciencies of these three thresholding methods to extract the events responsible for much of the heat and momentum turbulent uxes are compared for a wide range of atmospheric stability conditions. The inter-comparisons are performed in four ways: (i) compression ratios, (ii) energy conservation, (iii) turbulent ux conservation, and (iv) ne-scale ltering via departures from Kolmogorov's K41 power-laws. For orthonormal wavelet and wavelet packets analysis, wavelet functions with varying time-frequency localiza-tion properties are also considered. Our study showed that wavelet and wavelet packet Lorentz thresholding can also achieve high compression ratios (98%) with minimal loss in energy (3% loss) and uxes (4%). However , these compression ratios and energy and ux conservation measures are comparable to the linear Fourier rank reduction method if a Lorentz 2 gabriel katul and brani vidakovic threshold function is applied to the later. Finally, it is demonstrated that orthonormal wavelet and wavelet packets thresholding are insensitive to the analyzing wavelet.