依据云粒子对偏振激光的消偏原理,基于星载激光雷达CALIPSO的数据,利用其层积分衰减的后向散射β与 层积分的退偏振比δ之间的二维阈值关系及其空间相关性提出了一种云相态识别的新算法。应用该算法对 2010年3月3日中国区域内的一轨CALIPSO数据进行了云相态的反演实例实验,并对实验反演结果与CALIPSO相态 产品进行了对比分析。结果表明该算法具有更高的云相态识别精度。

According to cloud particle depolarization theory of polarization lidar, and based on the relationships between layer-integrated attenuated backscatter(β) and layer-integrated depolarization ratio (δ) of a two dimensional threshold and their spatial coherence analysis technique, a cloud phase discrimination algorithm using CALIPSO data was established. The testing retrieval sample of CALIPSO data of China region on March 3, 2010 used for the new algorithm were mainly derived from CALIPSO cloud phase product. The results show the new cloud phase discrimination algorithm based on CALIIPSO data has superior accuracy.