高光谱大气红外探测器通道选择方法及试验研究

Study on Method and Experiment of Hyper-spectral Atmospheric Infrared Sounder Channel Selection

考虑到高光谱大气红外探测器通道之间的相关性、变分同化的时效性等,需要进行通道选择。利用主成分—逐步回归法进行AIRS通道选择研究。由于短波CO2通道易受太阳光影响,分白天和夜晚进行。具体执行过程中,首先进行通道预处理,然后分别对温度和湿度雅可比矩阵进行主成分分析,并采用逐步回归法找出对前几个主成分影响较大的通道得到入选的通道子集。进而根据经验和实际观测资料,为了达到全局最优并兼顾局部,基于分区的思想,采用主成分—双区逐步回归法进行通道选择。结果表明:1利用AIRS进行反演时,合理选择通道是非常必要的;2主成分—双区逐步回归法得到的通道组合进行温度、湿度反演的误差整体比基于信息熵分步迭代小。

Considering the correlation between channels of hyper-spectral atmospheric infrared sounder,as well as the timeliness of variational assimilation,channel selection is necessary.The principal componentstepwise regression method is adopted for AIRS channel selection in this paper.Due to the fact that CO2 short wave channel easily affected by sunlight during the day,this study consider the channel combination during daytime and nighttime respectively.In the process of specific implementation:First,the channels are pre-processed.Then,the principal components of Jacobi matrix about the temperature and humidity are analyzed respectively and some principal components with great effects are selected.By using the stepwise regression method,the channels with great affect on principal components are selected to form a channel subset.Further,according to the experience and actual observation data,principal components dual-zone regression method is adopted for channel selection,in order to make an achievement of optimizing the global and take the local into account,with the idea of partition.Research results indicate that:①it is very necessary to rationally choose the channels when retrieves atmospheric temperature and humidity with AIRS data;② The channel combination obtains from principal components dual-zone regression,and retrieving atmospheric temperature and humidity error are smaller than iterative method based on information entropy as a whole.