Systematic Relationships Between Lidar Observables And Sizes And Mineral Composition Of Dust Aerosols

Abstract:

The physical and chemical properties of soil dust aerosol particles fundamentally affect their interaction with climate, including shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, heterogeneous formation of sulfates and nitrates on the surface of dust particles, and atmospheric processing of iron into bioavailable forms that increase the productivity of marine phytoplankton. Lidar measurements, such as extinction-to-backscatter, color and depolarization ratios, are frequently used to distinguish between aerosol types with different physical and chemical properties. The chemical composition of aerosol particles determines their complex refractive index, hence affecting their backscattering properties. Here we present a study on how dust aerosol backscattering and depolarization properties at wavelengths of 355, 532 and 1064 nm are related to size and complex refractive index, which varies with the mineral composition of the dust. Dust aerosols are represented by collections of spheroids with a range of prolate and oblate aspect ratios and their optical properties are obtained using T-matrix calculations. We find simple, systematic relationships between lidar observables and the dust size and complex refractive index that may aid the use of space-based or airborne lidars for direct retrieval of dust properties or for the evaluation of chemical transport models using forward simulated lidar variables. In addition, we present first results on the spatial variation of forward-simulated lidar variables based on a dust model that accounts for the atmospheric cycle of eight different mineral types plus internal mixtures of seven mineral types with iron oxides, which was recently implemented in the NASA GISS Earth System ModelE2.