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Retrieval methods of effective cloud cover for the GOME instrument: an intercomparison
1Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University, Utrecht, The Netherlands
2TNO MEP, Apeldoorn, The Netherlands
Abstract. The radiative scattering by clouds leads to errors in the retrieval of column densities and concentration profiles of atmospheric trace gas species from satellites. Moreover, the presence of clouds changes the UV actinic flux and the photo-dissociation rates of various species significantly. The Global Ozone Monitoring Experiment (GOME) instrument on the ERS-2 satellite, principally designed to retrieve trace gases in the atmosphere is also capable of detecting clouds. Four cloud fraction retrieval methods for GOME data that have been developed are discussed in this paper (the Initial Cloud Fitting Algorithm, the PMD Cloud Retrieval Algorithm, the Optical Cloud Recognition Algorithm and the Fast Retrieval Scheme for Cloud Observables). Their results of cloud fraction retrieval are compared to each-other and also to synoptic surface observations. It is shown that all studied retrieval methods calculate an effective cloud fraction that is related to a cloud with a high optical thickness. Generally, we found ICFA to produce the lowest cloud fractions, followed by OCRA, then FRESCO and PC2K along four processed tracks (+2%, +10% and +15% compared to ICFA respectively). Synoptical surface observations gave the highest absolute cloud fraction when compared with individual PMD sub-pixels of roughly the same size.
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Citation: Tuinder, O. N. E., de Winter-Sorkina, R., and Builtjes, P. J. H.: Retrieval methods of effective cloud cover for the GOME instrument: an intercomparison, Atmos. Chem. Phys. Discuss., 2, 623-668, 2002. Bibtex EndNote Reference Manager
