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This study validates a method for discriminating between daytime clouds and dust aerosol layers over the Sahara Desert that uses a combination of active CALIOP(Cloud-Aerosol Lidar with Orthogonal Polarization) and passive IIR(Infrared Imaging Radiometer) measurements;hereafter,the CLIM method.The CLIM method reduces misclassification of dense dust aerosol layers in the Sahara region relative to other techniques.When evaluated against a suite of simultaneous measurements from CALIPSO(Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations),CloudSat,and the MODIS(Moderate-resolution Imaging Spectroradiometer),the misclassification rate for dust using the CLIM technique is 1.16%during boreal spring 2007.This rate is lower than the misclassification rates for dust using the cloud aerosol discriminations performed for version 2(V2-CAD;16.39%) or version 3(V3-CAD;2.01%) of the CALIPSO data processing algorithm.The total identification errors for data from in spring 2007 are 13.46%for V2-CAD,3.39%for V3-CAD,and 1.99%for CLIM.These results indicate that CLIM and V3-CAD are both significantly better than V2-CAD for discriminating between clouds and dust aerosol layers.Misclassifications by CLIM in this region are mainly limited to mixed cloud-dust aerosol layers.V3-CAD sometimes misidentifies low-level aerosol layers adjacent to the surface as thin clouds,and sometimes fails to detect thin clouds entirely.The CLIM method is both simple and fast,and may be useful as a reference for testing or validating other discrimination techniques and methods.  相似文献   
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