Remote sensing of trace gases, aerosols, and clouds from measurements of up-welling radiation by GOME (Global Ozone Monitoring Experiment) aboard ERS-2 and SCIAMACHY (Scanning Imaging Absorption spectroMeter for Atmospheric CHartograhY) aboard ENVISAT under inhomogeneous cloud conditions

• Applicant: Professor Dr. Bernhard Mayer
• Subject Area: Atmospheric Science
• Term: from 2003 to 2007
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 5400767

Remote Sensing and Inhomogeneous Clouds, RESINC, aims to improve our understanding of the influence of cloud inhomogeneity on the retrieval of trace gases, aerosols, and clouds from GOME and SCIAMACHY. These instruments were conceived to yield, throughout the next two decades, global distributions of atmospheric constituents and thereby improve our knowledge of a variety of regional and global issues of importance for the chemistry and physics of the Earth´s atmosphere. Current remote sensing methods generally assume either a cloudless sky or horizontal homogeneity of the cloud within the instantaneous field of view (IFOV) of the instrument while in reality, clouds are highly inhomogeneous at all spatial scales. The IFOV of GOME and SCIAMACHY is relatively large due to the high signal-to-noise ratio required for trace gas measurements. Hence, a correct treatment of cloud inhomogeneity is essential to exploit their full potential. The main aim of this project is to quantify the uncertainty associated with this instrinsic inhomogeneity and thereby to improve the accuracy of the retrieval of trace gases, aerosols, and clouds from GOME and SCIAMACHY. A well-characterised three-dimensional radiative transfer model will be used to simulate satellite observations for a variety of typical cloud scenarios. These data will serve as a test for the existing retrievals, which assume homogeneous clouds. Based on the findings of this study, a parameterisation will be developed, tested, and applied, which enables cloud inhomogeneity to be explicitly accounted for in the retrieval.

• DFG Programme: Research Grants
• Participating Person: Professor Dr.-Ing. Ulrich Schumann