Aerosol Typing Based on Multiwavelength Lidar Observations and Meteorological Model Data

摘要

Three different aerosol classification methods have been used to characterize lidar observations: Mahalanobis distance automatic aerosol type classification, Neural Network Aerosol Typing Algorithm (NATALI) and Source and Analysis (SCAN) aerosol classification. The data selection has been made through the EARLINET database depending on the 3b+2a+1δ optical property availability. One hundred aerosol layers from four EARLINET stations (Bucharest, Kuopio, Leipzig and Potenza) have been classified. We present a typical case study of aerosol characterization observed by the MUSA system over Potenza on the 11~(th)of April 2016 (20:30-21:30?UTC).