The depth of the convective boundary layer is of first-order importance for air quality monitoring and prediction. . Previous studies (White, 1993; Angevine et al., 1994) have shown success in determining the convective boundary layer mixing depth with wind profiling radars. Although this procedure has considerable skill in determining the boundary layer depth, it can fail for several reasons, including errors in the estimation of the SNR due to ground clutter, radio-frequency interference, or due to atmospheric point targets such as birds. The algorithm can likewise fail if there is an elevated layer of high refractivity associated with the residual inversion associated with the previous day's boundary layer.

A new method for estimating the mixing depth of the convective boundary layer is developed for use with wind-profiling radars. This method applies Fuzzy Logic methods to give an improved determination of the atmospheric signal in radar spectra. The method then also applies Fuzzy Logic to calculate the depth of the convective boundary layer using vertical profiles of both radar derived Cn2 and of the variance of vertical velocity. A comparison to independent boundary layer depth observations at two radar wind profiler sites (Angiola, California, and Houston, Texas) shows that the new method gives significantly more accurate estimates of the boundary layer depth than previously used methods.