The Evaluation of a New Method to Detect Mixing Layer Heights Using Lidar Observations

Abstract

AbstractA new automatic mixing layer height detection method for lidar observations of aerosol backscatter profiles is presented and evaluated for robustness. The new detection method incorporates the strengths of Steyn et al.’s error function–ideal profile (ERF) method and Davis et al.’s wavelet covariance transform (WCT) method. These two methods are critical components of the new method, and their robustness is also evaluated and then contrasted to the new method. The new method is applied to aerosol backscatter observations in two ways: 1) by looking for the most realistic mixing height throughout the entire profile and 2) by searching for mixing height below significant elevated obscurations (e.g., clouds or aerosol layers). The first approach is referred to as the hybrid method and the second as the hybrid-lowest method. Coincident radiosounding observations of mixing heights are used to independently reference the lidar-based estimates.There were 4030 cases examined over a 5-yr period for mixing heights. The efficacy of the lidar-based methods was determined based on diurnal, seasonal, stability, and sky obscuration conditions. Of these conditions, the hybrid method performed best for unstable and cloudy situations. It determined mixing heights reliably (less than ±0.30-km bias) for close to 70% of those cases. The hybrid-lowest method performed best in stable and clear-sky conditions; it determined mixing heights reliably for over 70% of those cases. The WCT method performed the best overall.