3 October 2006 A numerical model to improve the derivation of aerosols optical parameters from elastic backscatter lidar data
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Abstract
LIDAR systems have demonstrated their ability to map aerosol variations throughout the atmospheric column and therefore they have has become a central technology in current strategies for tropospheric aerosol research. Its use is complicated, however, by the fact that the lidar signal contains a convolution of two basic optical properties of the aerosol particles: the backscatter coefficient and the extinction coefficient. A quantitative retrieval of either property requires knowledge of their relationship along the laser path which is referred as lidar ratio. If the lidar ratio can not be measured by high spectral resolution lidar, or Raman lidar, then either an assumed value of LRa must be used in the lidar retrieval, leading to very large uncertainties in light extinction, or models can be used for determination of LRa profile. Our research refers to the development of an iterative hybrid regularization technique for elastic backscatter lidar data processing and retrieval of the aerosols optical parameters using the atmospheric model, Mie model and Fernald-Klett, but also Ackermann algorithm for lidar ratio calculation based on relative humidity profile. This study focuses on a numerical investigation about the lidar ratio of tropospheric aerosols characterizing Romanian atmosphere. The model can be also used for other type of atmosphere in order to improve the derivation of aerosols optical parameters from elastic backscatter lidar data when no other information than meteorological data are available.
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Doina Nicolae, Camelia Talianu, Anca Nemuc, Emil Carstea, Jeni Ciuciu, Constantin Cristescu, "A numerical model to improve the derivation of aerosols optical parameters from elastic backscatter lidar data", Proc. SPIE 6367, Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II, 636706 (3 October 2006); doi: 10.1117/12.714436; https://doi.org/10.1117/12.714436
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