Multi-fractal analysis of nocturnal boundary layer time series from the Boulder Atmospheric Observatory.

Time series from a nocturnal boundary layer are analyzed using fractal techniques. The behavior of the self-affine fractal dimension, D A , is found to drop during a gravity wave train and rise with turbulence. D A is proposed as a time series conditional sampling criterion for distinguishing waves from turbulence. Only weak correlations are found between DA and bulk turbulence measures such as Brunt-Vaisala frequency, Richardson number, and buoyancy length. The advantages of DA analysis over turbulent kinetic energy (TKE), its component variances, FFT spectra, and self-similar fractals are also discussed in terms of local versus global basis functions, dimensional suitability, noise, algorithmic complexity, and other factors. DA was found to be the only measure capable of reliably distinguishing the wave from turbulence.http://archive.org/details/multifractalanal00decaLieutenant, United States NavyApproved for public release; distribution is unlimited

A self-affine multi-fractal wave turbulence discrimination method using data from single point fast response sensors in a nocturnal atmospheric boundary layer

We present DA, a self-affine, multi-fractal which may become the first routine wave/turbulence discriminant for time series data. Using nocturnal atmospheric data, we show the advantages of D A over self-similar fractals and standard turbulence measures such as FFTs, Richardson number, Brunt-Vaisala frequency, buoyancy length scale, variances, turbulent kinetic energy, and phase averaging. DA also shows promise in resolving "wave-break" events. Since it uses local basis functions, DA may be an ideal tool to detect intermittent turbulence, coherent structures, and discrete wave trains in general. DA may also be a measure of chaos in general.U.S. Air Force, Space Division, Los Angeles, CAhttp://archive.org/details/selfaffinemultif00kamaMPIR FY76169100412NAApproved for public release; distribution is unlimited