The study demonstrates a novel method to retrieve aerosol microphysical parameters using lidar data, indicating improved accuracy for various aerosol types.
Using an improved regularization method, we attempt to derive microphysical parameters (effective radius ๐๐๐๐, surface area concentration ๐๐ก, volume concentration ๐๐ก) of aerosol particle size distribution directly from the detection results of Aerosol and Carbon dioxide Detection Lidar (ACDL), which is the first spaceborne high spectral resolution lidar. The backscatter and extinction coefficients at 532 nm, 1064 nm, 1572 nm are adopted for regularization algorithm. Preliminary simulations for different aerosol types demonstrate the algorithm performance of the 3ฮฑ+3ฮฒ optical data combination. For monomodal aerosols, the retrieval errors are constrained within 15 % for ๐๐๐๐, 30 % for ๐๐ก, and 35 % for ๐๐ก. In bimodal cases, errors increase to 18โ35 % for ๐๐๐๐, 35 % for ๐๐ก, and up to 60 % for ๐๐ก. Sensitivity analysis confirms that systematic errors of ยฑ20 % in input optical data induce parameter uncertainties below 60 %. Case studies reveal four typical aerosols profiles: urban (๐๐๐๐~0.5 ฮผm), smoke (๐๐๐๐~0.6 ฮผm), dust (๐๐๐๐~0.65 ฮผm), and marine (๐๐๐๐~0.85 ฮผm). The inversion ๐๐๐๐ is compared with CALIPSO and LIVAS, which confirms high consistency for marine and dust, while urban and smoke retrievals show slightly larger. The inclusion of 1572 nm significantly enhances coarse-mode retrieval accuracy. The error statistics of the simulations and the actual comparison results show that the proposed inversion algorithm can reliably derive the particle size distribution parameters from the spaceborne multi-wavelength lidar ACDL. This work provides preliminary validation of ACDL's capability to retrieve vertically resolved global aerosol microphysical characterization.
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Bi et al. (2025) studied this question.
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