Abstract

The portable automated lidar (PAL) has been shown to be effective in observing cloud dynamics and aerosol optical properties in the troposphere. The continuous monitoring of the atmosphere has indicated that the detection range is limited during daytime due to noise from the sky radiance. Here we apply the wavelet denoising method to improve the signal-to-noise ratio (SNR) of the time-dependent PAL data. As a result, SNR increased by 7.9% when compared to data smoothing based on moving average. Moreover, the analysis of wavelet coefficients enables direct retrieval of the cloud base height. It is found through manual comparison that this method shows 4.4 times less false positive and 2.2 times less false negative detection on average, when compared to a conventional method such as the threshold method.

© 2011 AOS