Multifrequency lidar sensing of atmospheric aerosol under conditions of information uncertainty

Abstract

A method is proposed for solving the inverse problem in multifrequency lidar sensing of the atmospheric aerosol. The method allows retrieving the spatial distribution of volume concentrations of aerosol components, the aerosol particle size distribution integral over the sensing path, and the complex refractive index of the particles, without any additional data for the lidar calibration and supplement of the inverse problem definition. The method is based on the assumption that the average sizes, their variances, and the complex refractive indices for the particles of each aerosol component do not change along the sensing path, and the number of the lidar spectral channels is greater than the number of aerosol components. In this case, the system of equations for the spectral-spatial readings of the lidar signal becomes overdetermined, and its numerical solution allows deriving not only the microphysical parameters of the aerosol, but also the lidar calibration constants at operational wavelengths. Examples of processing the elastic and Raman scattering lidar signals in a model aerodispersive medium at the wavelengths λ0 = 0.355, 0.532, and 1.064 μm and λR = 0.387 and 0.607 μm, respectively, are presented. It is shown that microphysical parameters of the fine aerosol component (with particle sizes less than 1–2 μm) can be retrieved from the signals with an error less than 10%, and the error in retrieving the microphysical parameters of coarse particles depends strongly on their contribution to the total medium transmission. The aerosol extinction and backscattering coefficients calculated on the basis of the aerosol microphysical parameters retrieved differ from their actual values by a few percent.