Micropulse Lidar Signals: Uncertainty Analysis

Abstract

Elastic backscatter lidars are used to determine the vertical distribution of cloud and aerosol layers. One such lidar is the micropulse lidar (MPL). A recent paper by Campbell et al. described an algorithm used to process MPL signals. The paper presented procedures that correct for various instrument effects present in the raw signals. The primary instrument effects include afterpulse (detector noise induced from the firing of the laser) and overlap (poor near-range data collection). The outgoing energy of the laser pulses and the statistical uncertainty of the MPL detector must also be correctly determined in order to assess the accuracy of MPL observations. The uncertainties associated with each of these instrument effects, and their contribution to the net uncertainty in corrected MPL signals, were not discussed in the earlier paper. Here in the uncertainties associated with each instrument parameter in the MPL signal are discussed. The uncertainties are propagated through the entire correction process to give a net uncertainty on the final corrected MPL signal. The results show that in the near range, the overlap uncertainty dominates. At altitudes above the overlap region, the dominant source of uncertainty is caused by uncertainty in the pulse energy. However, if the laser energy is low, then during midday, high solar background levels can significantly reduce the signal-to-noise ratio of the detector. In such a case, the statistical uncertainty of the detector count rate becomes dominant at altitudes above the overlap region.