Information content analysis for aerosol type from a combination of three satellite instruments

Aerosols affect climate in several ways. Their effect depends not only on the aerosol abundance and geospatial distribution but also on the aerosol types present. Therefore, there is an important need for the retrieval of aerosol types from satellite measurements.

By combining data from different satellite instruments, information on the composition of aerosols in the atmosphere shall be determined with an optimal estimation retrieval algorithm. We make use of data from three different instruments measuring with different observation characteristics, different spectral ranges (UV, VIS, thermal IR), different viewing geometries (nadir, oblique). The included instruments are dual-view instrument SLSTR (Sea and Land Surface Temperature Radiometer) onboard Sentinel 3A and 3B; and the Infrared Atmospheric Sounding Interferometer (IASI) and the Global Ozone Monitoring Experiment-2 (GOME-2), both onboard Metop A/B/C.

In preparation for the information content analysis and future aerosol retrieval, the data from the different instruments are homogenized to a common grid of 40x80 km², the coarsest instrument resolution (GOME-2), within a temporal matching window of 60 minutes.  A cloud masking algorithm (APOLLO_NG) is then applied to the highest resolution radiometer data (1x1 km²) from SLSTR and in addition to the Advanced Very High Resolution Radiometer (AVHRR) onboard Metop A/B/C to take into account the temporal variation of the clouds.

For the information content analysis, a set of those observations is simulated with the SCIATRAN radiative transfer model for different observing conditions / geometries, surface types, aerosol types and aerosol amounts. With these data an analysis of the combined information content is then conducted which focuses on capabilities for the determination of aerosol abundance (total Aerosol Optical Depth - AOD) and aerosol types (as contributions to total AOD of fine / coarse mode, mineral dust, absorbing aerosols) in a cloud-free atmosphere over different ground surface types. The information content analysis will help to identify those instrument channels / spectral windows that carry most of the information which is then used to develop a retrieval algorithm for AOD and aerosol types.