Abstract

The Global Ozone Monitoring Experiment (GOME) flies on-board the ERS2 satellite since 1995 and its main mission is the retrieval of total ozone at the nominal ground resolution of 320×40 km 2. Cloud detection and characterization, an interesting result in itself, are needed to analyse spectral data prior to the retrieval of columnar ozone as well as other atmospheric constituents. The Cloud Clearing Algorithm (CCA) available in literature was developed based on a simple thresholding method: cloud detection is obtained within the Polarisation Measurements Devices (PMDs) ground pixel (20×40 km 2, one-sixteenth of the GOME spatial resolution) using thresholds that depend primarily on surface type and reflection, and solar zenith angles. A refinement of the CCA is presented. Thresholds over the ocean have been computed by comparing PMD detection results with the ERS2 Along Track Scanning Radiometer 2 (ATSR2) cloud masks, being ATSR2 measurements coincident in time and space with GOME ones. Refined CCA performances have been compared with a totally independent cloud classification algorithm that uses visible-infrared, high resolution full disk METEOSAT images. Case studies are presented, and differences between the two methods are discussed on the PMD and spectral GOME ground pixel sizes.

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