资源环境科技发展态势分析平台

Light detection and ranging (lidar) measurements have been widely used to profile the ambient aerosol extinction coefficient (sigma(ext)). The particle extinction-to-backscatter ratio (lidar ratio, LR), which strongly depends on the aerosol dry particle number size distribution (PNSD) and aerosol hygroscopicity, is introduced to retrieve the sigma(ext) profile from elastic-backscatter lidar signals. Conventionally, a constant column-integrated LR that is estimated from aerosol optical depth is used by the retrieving algorithms. In this paper, the influences of aerosol PNSD, aerosol hygroscopic growth and relative humidity (RH) profiles on the variation in LR are investigated based on the datasets from field measurements in the North China Plain (NCP). Results show that LR has an enhancement factor of 2.2 when RH reaches 92 %. Simulation results indicate that both the magnitude and vertical structures of the sigma(ext) profiles by using the column-related LR method are significantly biased from the original sigma(ext) profile. The relative bias, which is mainly influenced by RH and PNSD, can reach up to 40 % when RH at the top of the mixed layer is above 90 %. A new algorithm for retrieving sigma(ext) profiles and a new scheme of LR enhancement factor by RH in the NCP are proposed in this study. The relative bias between the sigma(ext) profile retrieved with this new algorithm and the ideal true value is reduced to below 13 %.