Cloud Retrieval for Sciamachy

The ENVISAT Satellite Payload includes the SCIAMACHY instrument designed to measure a number of chemically important atmospheric trace constituents on a global basis. Accurate determination of cloud information out of SCIAMACHY nadir measurements is needed for the retrieval of ozone and other trace gases and it is crucial for more demanding applications like aerosol retrieval and the retrieval of trace gas concentrations in the troposphere. Determination of cloud coverage is done traditionally using threshold tests to distinguish between cloud–free and cloud–contaminated pixels. The probably most notable work using this approach is the one presented in [6], where different test are applied to examine variations in brightness temperatures or albedos measured by NOAA’s Advanced Very High Resolution Radiometer (AVHRR). The major problem with the threshold techniques is that the threshold settings, even dynamical thresholding or threshold functions, and the generation of global threshold maps are tedious and complicated tasks that are usually done with theoretical models or are performed empirically with the help of human experts [2]. The Optical Cloud Recognition Algorithm (OCRA presented in this paper is a novel algorithm for cloud recognition which uses the information provided by the SCIAMACHY polarization measurement devices. OCRA overcomes the problems of the traditional threshold testing and it is based on the fusion of multitemporal images to determine a so called ”cloud–free composite”. The paper is divided in two parts. The first section describes the cloud recognition algorithm OCRA, the second part presents the application of OCRA to the GOME/ERS–2 and SCIAMACHY/ENVISAT sensors.