Satellite Aerosol Composition Retrieval from a combination of three different Instruments: Information content analysis

Abstract. This study focuses on the information content for retrieving Aerosol Optical Depth (AOD) and its components from satellite measurements. We utilize an optimal estimation retrieval algorithm with data from three satellite-based instruments: SLSTR on Sentinel 3A/3B, IASI and GOME-2 on Metop A/B/C. Data are averaged to a common 40x80 km² grid, temporally aligned within a 60-minute window and cloud masked. A simulation study will be carried out to analyse the information content of the instrument combination, identify retrievable parameters and initiate the development of a uniform retrieval algorithm for the AOD and aerosol components. The simulation study for the information content analysis is implemented using the radiative transfer model SCIATRAN and uses MERRA-2 reanalysis data for AOD and mass mixing ratios of different aerosol components. The study shows 6 to 15 degrees of freedom for the determination of aerosol components dependent on AOD and the underlying surface. The results will be used for the development of a synergistic multi-sensor retrieval algorithm for AOD and its components in cloud-free atmospheres across various surface types.