Abstract
Abstract A threshold-based detection algorithm for cloud and aerosol layer heights in elevated micropulse lidar data (0.523 μm) is described. Thresholds for differentiating cloud and aerosol signals from that of the molecular atmosphere are based on the signal uncertainties of the level 1.0 Micropulse Lidar Network (MPLNET) data product. To illustrate the algorithm, data from 1 to 10 June 2003 collected by an MPLNET instrument at the South Pole are discussed for polar stratospheric cloud-height retrievals. Additional tests are run for algorithm sensitivity relative to variable solar background scenes. The algorithm is run at multiple temporal resolutions. Results derived at a base resolution are used to screen attenuation-limited profiles from longer time averages to improve performance. A signal normalization step using a theoretical molecular scattering profile limits the application of the technique in the lower atmosphere for a ground-based instrument. This would not be the case for some nadir-viewing lidars, and the application of the algorithm to airborne and satellite datasets is speculated.
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