在模拟星载红外高光谱辐射观测值对云高和有效云量的敏感性基础上展开了有云时大气温湿廓线反演的模拟研究,用特征向量统计反演法反演大气温湿廓线时进行云顶高度分类在一定程度上可提高反演精度,但在云顶以下高度反演误差仍然较大.在AIRS像元中加入匹配的晴空MODIS红外观测值,可以提高云顶以下高度的反演精度,云顶所在高度越高大气参数反演精度提高越大,尤其足温度反演精度,有云时模拟的均方根误差在整层大气中几乎小于2K.

Clouds play an mi portant role in the radiation budget of the earth. The satellite observations under cloudy condition provide notonly information of cloud absorption butalso abundant information of cloud properties. Although the infrared sounderwith high spectral resolution resolves the ill-posed problem in atmospheric retrieva,l there are stillmany challenges in cloudy atmospheric retrieva.l How to get soundings temperature andmoisture vertical profiles under cloudy skies becomes very mi portant.Until now our research ismainly focus on the statistical and physical algorithm of at mospheric temperature and humidity retrieval in the clear sky,less advancement in the cloudy atmospheric retrieva.l AIRS (Atmospheric InfraRed Sounder)onboard the NationalAeronautics and Space Administration s Earth Observing System s (EOS)Aqua spacecraft is selected as the representative instrumentto smi ulate and validate the discussed algorithm.AIRS is a high spectral resolution infrared sounderwith 2378 channels over the range from 650 cm-1(15μm)to 2700cm-1(3.7μm).Ityields vertical profiles of atmospheric temperature andwater from earth s surface to an altitude of 40 km with a horizontal resolution of13.5 km atnadir, with the property of high measurement precision and high spectral resolution.In this paper the smi ulated space-based high spectral resolution AIRS radiances with different cloud top heights and effective cloud fractions are used to demonstrate the measurement sensitivity and atmospheric profile retrievalperformance.The smi ulated cloudy retrieval of atmospheric temperature andmoisture derived from the statistical eigenvector regression algorithm are analyzed with and without the cloud top height classification. Collocated cloudy AIRS and the associated clear MODIS (the Moderate Resolution Imaging Spectroradiomete) infrared observations with in the AIRS field of view are also used to demonstrate the profile retrieval mi provementbelow the cloud layer. In addition this paper has demonstrated that the use of collocated clear MODISmulti-spectral mi agerdata alongwith theAIRS high spectral resolution infrared ra- diances can greatly mi prove the single FOV cloudy retrieval even under opaque cloudy condition.The results are listed as following.1.The root-mean-square error of retrieved temperature and themixed ratio ofwater vapor below the cloud top increasewith effective cloud fraction.2.The knowledge of cloud height is critical to sounding retrieval performance. The temperature retrieval around the cloud layer can be significantly mi proved if the cloud heightknown perfectly for themid-and high-level clouds, while to the low level clouds the retrievalhas less sensitivity to the cloud height error. The retrieval accuracy of the cloud height with 50 hPa error decrease comparingwith the cloud height known perfectly. The temperature retrieval seems to bemore sensitive to cloud height error than humidity retrieva.l 3. The cloud classified statistical or physical regression can be an alternative approach for obtaining efficient cloudy sounding retrieval given that the initial cloud height information is available.4. The use ofcollocated clear MODIS multi-spectral mi agerdata alongwith theAIRS high spectral resolution infrared radiances can greatly mi prove the single FOV cloudy retrieval especially undermore overcast condition.