Satellite Aerosol Composition Retrieval from a Combination of three different Instruments

The influence of aerosols on climate is determined not only by their global distribution but also by their specific composition. Knowledge of the aerosol component distribution on a global scale is important (among other factors) for the radiation balance and the hydrological cycle due to the different influence of different components on the direct and indirect aerosol effect. Ideally, the component distribution should be known globally. For this reason, we propose a novel approach to derive the components using satellite observations.  Since no single instrument can provide a comprehensive analysis, we integrate data from three satellite-based instruments with complementary information content to achieve a synergistic aerosol retrieval. Our approach utilizes measurements with varying observational characteristics, including different spectral ranges (UV, VIS, thermal IR) and viewing geometries (nadir and oblique). The instruments involved are the dual-view SLSTR (Sea and Land Surface Temperature Radiometer) aboard Sentinel 3A and 3B, the Infrared Atmospheric Sounding Interferometer (IASI), and the Global Ozone Monitoring Experiment-2 (GOME-2), both on METOP A/B/C. The data are averaged onto a common grid of 40x80 km², temporally aligned within a 60-minute window, and subjected to cloud masking.

This study aims to extract the total Aerosol Optical Depth (AOD) as well as the AOD of major aerosol components from the satellite data using an optimal estimation framework. An information content analysis showed that an upper limit of up to 22 parameters (surface albedo at different wavelengths, surface temperature, Aerosol Optical Depth (AOD) and the AOD for up to 15 different aerosol components) with their uncertainties can be retrieved out of the combined dataset depending on the aerosol amount and the surface properties. For the a priori values of the retrieval parameters, we utilize climatological data: the GOME-2 surface LER database for albedo values, which contains Lambertian-equivalent reflectivity (LER), and climatological MERRA-2 reanalysis data for AOD and aerosol composition.

This combination of instruments thus has the potential to accurately ascertain aerosol composition and with this additional information to refine our understanding of their climate impact. In this study we show first promising results of the retrieval in different scenarios.