Development and application of a new algorithm of satellite remote sensing using multi-pixel and multi-parameter information for aerosol properties by GOSAT/CAI and other satellite-borne imagers

We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-pixel and multi-wavelength information of satellite imagers. In this algorithm, the inversion method is a combination of the MAP method (Maximum a posteriori method, Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine mode and coarse mode (sea salt or dust) particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area. We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode (dust), soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.