The Width of Aerosol Size Distribution: A Nonnegligible Factor in the Hyperspectral Infrared Radiative Transfer Simulations and Aerosol Remote Sensing

Remote sensing of aerosols by infrared hyperspectral radiation has become an emerging research frontier in recent years. In current infrared hyperspectral remote sensing of aerosol, only the aerosol type and effective radius (Reff) are considered, while the width of the aerosol size distribution (Geometric Standard Deviation, GSD) is simplified as a constant, neglecting its impact on infrared radiative transfer. Is this simplification physically justified? To clarify this issue, an infrared hyperspectral radiative transfer model considering the variation of GSD of aerosol particles was established, and the impacts of GSD on both upwelling and downwelling radiances are investigated. It can be found that radiance discrepancies attributed to variations of GSD exceed those caused by effective radius up to 70%. The downwelling radiance demonstrates far greater sensitivity to GSD compared to its upwelling counterpart. Furthermore, the sensitivity of infrared radiance to GSD will be amplified with the increase of Aerosol Optical Depth (AOD). Finally, to further validate the necessity of considering GSD in aerosol remote sensing, both triple-parameter (AOD,Reff, and GSD) and dual-parameter inversions (AOD andReff) were performed by using machine learning methods respectively. The results indicate that incorporating GSD into the inversion process can help improve the accuracy of effective radius inversions.