Retrievals of vertically resolved aerosol microphysical particle parameters with regularization from spaceborne Aerosol and Carbon dioxide Detection Lidar (ACDL)

Abstract. Using an improved regularization method, we attempt to derive microphysical parameters (effective radius 𝑟_𝑒𝑓𝑓, surface area concentration 𝑆_𝑡, volume concentration 𝑉_𝑡) 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 3α+3β optical data combination. For monomodal aerosols, the retrieval errors are constrained within 15 % for 𝑟_𝑒𝑓𝑓, 30 % for 𝑆_𝑡, and 35 % for 𝑉_𝑡. In bimodal cases, errors increase to 18–35 % for 𝑟_𝑒𝑓𝑓, 35 % for 𝑆_𝑡, and up to 60 % for 𝑉_𝑡. Sensitivity analysis confirms that systematic errors of ±20 % in input optical data induce parameter uncertainties below 60 %. Case studies reveal four typical aerosols profiles: urban (𝑟_𝑒𝑓𝑓~0.5 μm), smoke (𝑟_𝑒𝑓𝑓~0.6 μm), dust (𝑟_𝑒𝑓𝑓~0.65 μm), and marine (𝑟_𝑒𝑓𝑓~0.85 μm). The inversion 𝑟_𝑒𝑓𝑓 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.