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Information about clouds, in particular the accurateidentification of cloud free pixels, is crucial for the retrievalof tropospheric vertical column densities from space. TheHeidelberg Iterative Cloud Retrieval Utilities (HICRU) retrieveeffective cloud fraction using spectra of two instruments designedfor trace gas retrievals from space: The Global Ozone MonitoringExperiment (GOME) on the European Remote Sensing Satellite (ERS-2)and the SCanning Imaging Absorption SpectroMeter for AtmosphericCHartographY (SCIAMACHY) on ENVISAT.<P>HICRU applies the widely used threshold method to the so-calledPolarization Monitoring Devices (PMDs) with higher spatialresolution compared to the channels used for trace gas retrievals.Cloud retrieval and in particular the identification of cloud freepixels is improved by HICRU through a sophisticated, iterativeretrieval of the thresholds which takes their dependency ondifferent instrumental and geometrical parameters into account.The lower thresholds, which represent the surface albedo andstrongly affect the results of the algorithm, are retrievedaccurately through a four stage classification scheme using imagesequence analysis.<P>The design and the results of the algorithm applied to GOME dataare described and compared to several other cloud algorithms forGOME. The differences to other cloud algorithms are discussed withrespect to the particular characteristics of the algorithms

The Heidelberg iterative cloud retrieval utilities (HICRU) and its application to GOME data