大气温湿廓线是数值预报中最基本的气象参数, 高光谱红外卫星可以观测到较高垂直分辨率的大气信息, 为了准确获取廓线信息, 利用搭载于美国对地观测卫星Suomi NPP(national polar-orbiting partnership)平台上的CrIS(cross-track infrared sounder)红外高光谱观测资料, 讨论了通道选取方法, 采用特征向量统计法反演法得到初始大气廓线, 利用非线性牛顿迭代法进一步提高反演精度。 将反演结果和全球数据同化系统GDAS(global data assimilation system)模式分析数据以及配对的无线探空值进行比较, 发现反演结果与真值趋势一致, 较之初始廓线有显著提高, 在100～700 hPa之间, 温度廓线反演精度最高, 均方差小于1 K, 在300～900 hPa之间, 湿度廓线反演精度最高, 均方差小于20%, 与所选取通道的雅各比峰值区间一致。

In order to get higher vertical resolution atmosphere profile information, the present paper retrieves atmospheric temperature and moisture profiles from the Cross-track Infrared Sounder (CrIS) on the newly-launched Suomi National Polar-orbiting Partnership (Suomi NPP) and future Joint Polar Satellite System (JPSS) with a nonlinear Newton iteration method by using the profiles retrieved via statical regression method as the first guess, and the issue of channel selection is discussed. The retrieved profiles are compared with radiosonde observations, and National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) analyses show that the physical retrievals of temperature and moisture are in good agreement with the distributions from GDAS analysis fields and radiosonde observations, and have a notable improvements of the atmospheric profile retrieval accuracy as compared with the eigenvector regression algorithm. For pressures between 200 and 700 hPa the accuracy is of the order of 1 K for the temperature profile, and 20% for the relative humidity profile is consistent with the jacobian peaks of the selected channels.