Vol. 29, issue 05, article # 7

Lysenko S. A., Kugeiko M. M., Khomich V. V. Multifrequency lidar sensing of atmospheric aerosol under conditions of information uncertainty. // Optika Atmosfery i Okeana. 2016. V. 29. No. 05. P. 404–413. DOI: 10.15372/AOO20160507 [in Russian].
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Abstract:

We have proposed a method for solving the inverse problem of multifrequency lidar sensing of the atmospheric aerosol, which enables to retrieve the spatial distribution of volume concentrations of aerosol components, aerosol particle size distribution integrated along the sensing path, and the complex refractive index of the particles, without any additional data for calibration of the lidar and for supplementary definition of the inverse problem. The method is based on the assumption that the average sizes, the variance of sizes and the complex refractive index of the particles of each aerosol components do not change along the sensing path, and the number of lidar spectral channels is greater than the number of aerosol components. In this case the system of equations for the spectral-temporal readings of lidar signal becomes overdetermined, and its numerical solution allows determining not only the microphysical parameters of aerosol but also lidar calibration constants at operating wavelengths. Examples of processing of elastic and Raman scattering lidar signals of model aerodispersive medium at wavelengths λ0 = 0.355, 0.532, 1.064 μm and λR = 0.387, 0.607 μm, respectively, were presented.
It is shown that microphysical parameters of fine components (with particles size less than 1–2 μm) are retrieved from the signals with an error less than 10%. The error of microphysical parameters of coarse particles retrieval is strongly dependent on the significance of their contribution to the total transmission of the medium. The difference between aerosol extinction and backscatter coefficients calculated on the base of retrieved microphysical aerosol parameters and their actual values are within a few percents.

Keywords:

aerosol, optical parameters, microphysical parameters, multifrequency sensing, inverse problem, calibration-free method

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