Cloud amount and aerosol characteristic research in the atmosphere over Hubei province, China

Although the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) has been widely used in aerosol research, the classification of aerosol and cloud still presents some problems. The traditional classification method used by NASA is probability distribution functions (PDFs), but in reality, when we want to realize this algorithm, we find it is difficult to describe the multi-modal distribution of cloud backscatter coefficients. Further, because ice cloud and dust aerosol have some similar properties, it is not easy to identify them. In this paper, we introduce a classification method which is based on a support vector machine (SVM), and we add another characteristic. Then according to the result of classification inversion of the aerosol characteristic, the height of cloud top, at the same time, is combined with CloudSat data to calculate other cloud characters. These data will be helpful for further climate research.