联合星载毫米波雷达和中分辨率光谱成像仪的云底高度反演

云底高度是云重要的宏观物理参数。本文基于MODIS和CPR探测得到的可见光、红外和毫米波数据,提出了用主成分分析(Principal Component Analysis,PCA)和BP神经网络反演云底高度的新方法,并以相对湿度阈值法处理探空资料所获取的云底高度为基准,对PCA-BP法和CloudSat产品获取的云底高度进行了对比分析。结果表明:对绝大部分类型的云,PCA-BP法的反演偏差小于CloudSat产品。PCA-BP法和CloudSat产品反演的云底高度在夏季偏低,在其他季节偏高,且PCA-BP法与探空仪的均方根误差在所有季节均小于CloudSat产品,两者反演的云底高度具有一致的季节特征,即夏高冬低。PCA-BP法和CloudSat产品所获取的云底高度随纬度升高有减小趋势,在不同地区,两者具有不同的反演效果,反演误差随纬度升高而逐渐减小,对比结果说明了PCA-BP法反演云底高度具有一定的可行性。

Research on retrieval of cloud base height based on CPR and MODIS

The cloud base height is an important macrophysical parameter. Based on the data of visible, infrared and millimeter waves detected by MODIS and CPR, this paper proposes a new method to retrieve cloud base height by using Principal Component Analysis (PCA) and BP neural network. The cloud base heights retrieved by PCA-BP method and CloudSat products are compared with the cloud base height obtained from the sounding data processed by the relative humidity threshold method. The results show that the value of deviation of PCA-BP method is lower than that of CloudSat products for most types of clouds. The cloud base heights retrieved by PCA-BP method and CloudSat products have lower values in summer and higher values in other seasons, and the root mean square errors occurred by using the PCA-BP method and the radiosonde have lower values than those occurred by using the CloudSat products in all seasons, the cloud base heights retrieved by the two have a consistent seasonal characteristic, that is, the values are the highest in summer and the lowest in winter. The cloud base heights retrieved by PCA-BP method and CloudSat products decrease with increasing latitude. The two method have different retrieving results in different regions, the biases of both two methods decrease with increasing latitude. The comparison results show that it is to some extent feasible to use the PCA-BP method to retrieve the cloud base height.