Particle Size Distributions Based on a Multipopulation Genetic Algorithm Used in Multiwavelength Lidar

Abstract

Aerosols influence the radiation budget of the Earth’s atmospheric system. Aerosol particle size distribution is one of the major parameters used for characterizing aerosol influence on radiative forcing. The optical and microphysical properties of aerosol particles over Yinchuan, China, were measured with a multiwavelength lidar developed at Beifang University of Nationalities using backscatter and extinction coefficients at wavelengths of 1064, 532, and 355 nm. These data were used to retrieve particle size distributions. Given the disadvantages of the traditional regularization method, the innovative multipopulation genetic algorithm (MPGA) was used to retrieve the particle size distribution from the lidar data. To verify the feasibility of using the MPGA on multiwavelength lidar data, experiments were carried out under different atmospheric conditions, including a background sunny day, a cloudy day, and a foggy day. The particle size distributions obtained from the multiwavelength lidar data were compared with results retrieved from direct irradiance data from a sun photometer. Results showed that the MPGA is suitable for retrieving particle size distributions from multiwavelength lidar data.