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CLOUD AMOUNT AND AEROSOL CHARACTERISTIC RESEARCH IN THE ATMOSPHERE OVER HUBEI PROVINCE, CHINA

机译:中国湖北省大气中的云量和气溶胶特征研究

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Although the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO) has been widely used in aerosol research, the classification of aerosol and cloud still exist some problems. Tradition classification method used by NASA is probability distribution functions (PDFs), but in reality, when we want to realize this algorithm, we fund it is difficult to describe the multi-modal distribution of cloud backscatter coefficients. Further, because ice cloud and dust aerosol have some similar properties, so it is not easy to identify them. In this paper, we introduce a classification method which based on Support vector machine (SVM), and add another characteristic. Then according to the result of classification inverse the aerosol characteristic, the height of cloud top, at the same time, combine with the CloudSat calculate the other cloud character, these data will be helpful for further climate research.
机译:虽然具有正交偏振(CALIPSO)的云气溶胶激光乐队已广泛用于气溶胶研究,但气溶胶和云的分类仍存在一些问题。 NASA使用的传统分类方法是概率分布函数(PDF),但实际上,当我们想要实现这一算法时,我们基于云背散系数的多模态分布很难描述。此外,因为冰云和灰尘气溶胶具有一些类似的性质,所以它不容易识别它们。在本文中,我们介绍了一种基于支持向量机(SVM)的分类方法,并添加另一个特征。然后根据分类的结果,逆气溶胶特性,云顶的高度,同时,与CloudSat结合计算了其他云特征,这些数据将有助于进一步的气候研究。

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