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Classification is a critical step in the backscatter lidar data processing to accurately retrieve extinction and backscatter profiles of atmospheric aerosols and clouds. Different schemes, such as the probability distribution functions (PDFs) method, have been used in the cloud and aerosol classification. In this paper, we attempt to use the support vector machine (SVM) to discriminate aerosols from clouds, with a focus on dust aerosol classification in China. To demonstrate the feasibility of the SVM classifier, we chose dust storms that occurred in the Gobi and Taklimakan deserts and observed by the CALIPSO lidar in spring time 2007. The results show that the SVM can correctly identify the dust storms. (C) 2010 Elsevier Ltd. All rights reserved.