Tropospheric aerosol characterization: from GOME towards an ENVISAT perspective

The interest in aerosol observations from satellite passive instrument is steadily increasing as a result of the better understanding of the key role played by aerosols within the climate system. Satellite instruments supply global observations for establishing the aerosol climatology and characterizing single aerosol events. Since the 1980s data from geostationary meteorological satellites, such as the Geostationary Operational Environmental Satellite (GOES) and METEOSAT, and the Advanced Very High Resolution Radiometer (AVHRR) polar orbiting instruments have allowed for monitoring the aerosol optical thickness (AOT) over the oceans. More recently, it has been shown that the knowledge of the aerosol spectral optical properties is equally needed to understand the interaction of solar and terrestrial radiation with aerosols, together with a better appreciation of the role of clouds and surface reflection. Satellite observation have thus been directed towards the retrieval of AOT together with absorption potential, scattering efficiency and angular dependence, that is the identification of the predominant aerosol type over the scene. The Global Ozone Monitoring Experiment (GOME), in particular, has proved instrumental for the detection and characterization of the aerosol load, by exploiting its spectral coverage and resolution. An algorithm to determine the aerosol size distribution, spectral refractive index and AOT from GOME spectral reflectance is presented. The method is based on a non-linear fitting model. In addition, AOT values and aerosol type parameters derived from the GOME operational aerosol product can provide information for the algorithm initialization. Some examples are shown. The combination of the aerosol properties retrieved from high spectral resolution measurements with higher temporal frequency data from METEOSAT geostationary satellites is also included as an effective strategy for monitoring large atmospheric aerosol events. The algorithm is planned to be used with ENVISAT-1 data from the SCanning Imaging Absorption SpectroMeter for Atmospheric ChartographY (SCIAMACHY), the MEdium Resolution Imaging Specrometer (MERIS), and the Advanced Along Track Scanning Radiometer (AATSR). An overall improvement of the results is expected given the wider spectral coverage and higher spatial resolution of the new instruments with respect to GOME leading to a likely reduction in the uncertainties associated to the retrieval method.