A Synergic Retrieval Algorithm of Aerosol Optical and Composition Profiles from Dual-Channel Mie Lidar Observations

Mie lidar has been profoundly applied in the profiling of aerosol optical coefficients in atmosphere. However, few studies further explore quantitative strategies for the retrieval of aerosol mass profiles from lidar observation. To address the growing need for spatial and temporal aerosol mass data, a synergic retrieval algorithm for simultaneously profiling the aerosol extinction coefficient and mass composition from spaceborne dual-channel lidar data is proposed. By constructing the relationship between mixed aerosol mass profiles and extinction coefficients at different wavelengths by a forward model, additional constraints are induced to improve the accuracy of lidar ratio, which is a critical parameter for the retrieval of aerosol extinction coefficients by solving the lidar equation. Meanwhile, aerosol composition profiles can also be deduced based on the a priori estimation of aerosol compositions and intrinsic optical features of the aerosols. This method is first applied in simulated data with wavelengths at 532 nm and 1064 nm. The simulations are based on the reanalysis data of aerosol mass concentration profiles in Inner Mongolia, China. Compared with the classic Fernald method using empirically estimated lidar ratio, the proposed method improves the accuracy of column-integrated aerosol extinction coefficients (also known as aerosol optical depth, AOD) by 19.58% at 532 nm and 3.57% at 1064 nm. The accuracy for column dust and sulfate aerosols is enhanced by 12.46% and 17.58%, respectively. Further validation with CALIOP observations suggests that the proposed method produces improved extinction results and reliable aerosol composition information.