A Single-Scattering Optical Property Database for the Improvement of Downstream Lidar Calculations

Ice clouds play an essential role in Earths climate, but are one of the least understood atmospheric factors in the climate system, due to uncertainties in their microphysical and optical properties. Ice cloud single-scattering databases have been developed and improved to accurately represent the properties of ice clouds for radiative transfer and remote sensing applications. For the shortwave spectral regime (0.2 3.0 microns), specifically the 355, 532, and 1064 nanometer (nm) wavelengths commonly used in lidar applications, current databases provide inconsistent calculations due to a technical challenge in the simulation of nonspherical particle backscattering properties. For example, the accuracy of lidar-based cloud optical thickness retrievals is dependent on the accuracy of the extinction-to-backscatter ratio, also known as the lidar ratio, which is dependent on the particle backscattering intensity. An empirically predetermined lidar ratio has long been used for lidar-based ice cloud retrievals as a physics-based model is unavailable. As a result, shortwave- (active sensor) and infrared-based (passive sensor) radiative transfer models using previously-developed databases output inconsistent retrievals. In this study, we improve the backscattering properties of an optical property database a varying mixture of a 60-particle ensemble of single distorted hexagonal columns and a 20-particle ensemble of aggregates of 20 distorted hexagonal columns, for the lidar wavelengths of 355, 532 and 1064 nm. In addition to the computationally efficient Improved Geometric Optics Method (IGOM), this database also uses the Physical Geometric Optics Method (PGOM) to provide accurate backscattering calculations for moderate and large size parameters. Results show that the lidar ratio derived from the new database is now more consistent with lidar ratios derived from observational data. In the presentation, we will demonstrate the performance of the new ice optical property model and its application to CALIOP-based ice cloud property retrievals.