Evaluating Constrained Retrievals of Smoke Aerosol Lidar Ratio using Space-based Lidar Data

Smoke aerosols originate from various regional sources and fuel types which are dependent on the properties of the fire. Thus, spatial variability in smoke composition and optical properties exists. Spaceborne backscatter lidar observations from instruments such as the Cloud-Aerosol Transport System (CATS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) have been extensively used for monitoring of spatial-temporal variations of atmospheric aerosol optical properties. CATS, an elastic backscatter lidar located on the International Space Station (ISS), was operational from February 2015-October 2017 providing near real-time backscatter measurements at multiple wavelengths and depolarization ratio from regular transects of the biomass burning regions of Africa and South America. Additionally, CALIOP operated for 17 years (2006-2023) providing multiwavelength daily global coverage of clouds and aerosols. Despite the undoubted usefulness of these sensors, large uncertainties still exist in aerosol lidar ratio retrievals, which can vary significantly as a function of observing conditions and aerosol types. Therefore, careful atmospheric aerosol layer typing and lidar ratio assignment is needed for accurate aerosol extinction retrievals.

Due to the nature of backscatter lidar retrievals, a direct calculation of the layer lidar ratio is not always possible. However, a method has been established in the past to determine the lidar ratio of a transparent aerosol layer over an opaque water cloud. Utilizing a combined dataset from both CATS and CALIOP, this constraint technique is applied to smoke aerosol layers produced in biomass burning practices. The dependence of smoke lidar ratio on meteorological variables is explored and the complexities of smoke aerosol lidar ratio are highlighted, including a dependence of spherical smoke lidar ratios on relative humidity. This analysis presents the possibility of more accurate lidar ratio assignments, and thus more accurate extinction retrievals, than what is currently implemented in CATS or CALIPSO data such as a look up table based on layer relative humidity.