AN AUTOMATED ALGORITHM FOR DETECTION OF HYDROMETEOR RETURNS IN MICROPULSE LIDAR DATA

A cloud detection algorithm for a low power micropulse lidar is presen ted that attempts to identify all of the significant power returns fro m the vertical column above the lidar at all times, The main feature o f the algorithm is construction of lidar power return profiles during periods of clear sky against which cloudy-sky power returns are compar ed. This algorithm supplements algorithms designed to detect cloud-bas e height in that the tops of optically thin clouds are identified and it provides an alternative approach to algorithms that identify signif icant power returns by analysis of changes in the slope of the backsca ttered powers with height. The cloud-base heights produced by the curr ent algorithm during nonprecipitating periods are comparable with the results of a cloud-base height algorithm applied to the same data. Alt hough an objective validation of algorithm performance on high, thin c irrus is lacking because of no truth data, the current algorithm produ ces few false positive and false negative classifications as determine d through manual comparison of the original photoelectron count data t o the final cloud mask image.