Aerosol microphysical properties retrievals from high spectral resolution lidar data

Abstract

An Optimal Estimation (OE) inversion method has been developed to retrieve aerosol effective size, volume concentration, and complex refractive indices using three wavelengths backscattering (3β) and two wavelengths of extinction (2α) lidar measurements. The algorithm is capable of retrieving multiple aerosol modes and can retrieve vertical profiles simultaneously using altitude resolved HSRL data. The algorithm is designed in such as way that it can include additional measurements (e.g., polarimeter or Sun photometer) for improved aerosol microphysical property retrievals. In a traditional aerosol retrieval algorithm, one solves for aerosol size distributions under various parameter space (rmin, rmax, real and imaginary refractive index) using Tikhonov (or other) regularization and then selects physically and mathematically meaningful solutions from hundreds of thousand retrievals. In an attempt to speed up the retrieval and to provide retrieval error estimates, the OE method solves for all related aerosol microphysical parameters (e.g., number concentrations, particle size distribution, real and imaginary part of refractive indices) simultaneously in a maximum-likelihood sense by fitting the observed data. Other quantities such as effective particle radius, surface area concentration, volume concentration, and single scattering albedo are also derived from the retrieved size distribution and the number concentrations. Preliminary results using both simulated data and airborne measurements from HSRL-2. Coincident airborne in-situ and surface remote sensing datasets will be used to evaluate the performance of the new OE algorithm.