Aerosol composition retrieval from a combination of three different spaceborne 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 utilise an optimal estimation retrieval algorithm with data from three satellite-based instruments: the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and Sentinel-3B and the Infrared Atmospheric Sounding Interferometer (IASI) and the Global Ozone Monitoring Experiment-2 (GOME-2) on MetOp-A, MetOp-B and MetOp-C. Data are averaged to a common 40×80 km2 grid, temporally aligned within a 60 min window and cloud masked. A simulation study has been 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 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.