Quantifying the effects of the microphysical hygroscopic restructuring of soot on ensemble optical properties and...

Black carbon, or soot, significantly contributes to atmospheric light absorption due to its low single scattering albedo (SSA). This study investigates the impact of soot's hygroscopic restructuring on satellite remote sensing, focusing on radiative forcing, top-of-atmosphere (TOA) reflectance, and aerosol optical depth (AOD) retrievals. We characterized soot aging using relative humidity (RH) growth factor functions and modeled fresh and aging soot aggregates using a cluster-cluster aggregation algorithm. Bulk optical properties for each RH level were simulated using core-mantle generalized multi-sphere Mie-solution, weighted by the probability density function of soot monomer numbers. We incorporated soot aging models into the 6S radiative transfer model by adjusting the geometric mean radius of the soot component to match bulk SSA values at each aging degree. Extensive radiative transfer simulations were conducted, complemented by an analysis of 16 actual soot-containing cases in China from 2016 to 2019. Results showed that identical soot loads correspond to lower reflectance in dry environments and higher reflectance in humid environments. MODIS AOD retrieval errors approached zero when RH was close to 70 %, likely due to the similarity between the 6S default soot and the aging model at this humidity. Neglecting RH led to overestimations in AOD for cases with RH < 65 % and underestimations in high humidity cases (RH > 75 %). The average MODIS AOD retrieval errors for RH < 65 %, RH between 65 % and 75 %, and RH > 75 % were -33.15 %, -1.80 %, and +42.42 %, respectively. This study underscores the necessity of incorporating RH into satellite AOD retrieval algorithms to enhance accuracy and reduce uncertainties.