红外高光谱资料反演有云时大气温湿廓线的模拟研究

Simulation of Atmospheric Profile Retrieval from Hyperspectral Infrared Data under Cloudy Condition

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MOD IS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,尤其是温度反演精度,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 important role in the radiation budget of the earth.The satellite observations under cloudy condition provide not only information of cloud absorption but also abundant information of cloud properties.Although the infrared sounder with high spectral resolution resolves the ill-posed problem in atmospheric retrieval,there are still many challenges in cloudy atmospheric retrieval.How to get soundings temperature and moisture vertical profiles under cloudy skies becomes very important.Until now our research is mainly focus on the statistical and physical algorithm of atmospheric temperature and humidity retrieval in the clear sky,less advancement in the cloudy atmospheric retrieval.AIRS(Atmospheric InfraRed Sounder)onboard the National Aeronautics and Space Administration's Earth Observing System's(EOS)Aqua spacecraft is selected as the representative instrument to simulate and validate the discussed algorithm.AIRS is a high spectral resolution infrared sounder with 2378 channels over the range from 650 cm-1(15 μm)to 2700 cm-1(3.7 μm).It yields vertical profiles of atmospheric temperature and water from earth's surface to an altitude of 40 km with a horizontal resolution of 13.5 km at nadir,with the property of high measurement precision and high spectral resolution.In this paper the simulated 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 retrieval performance.The simulated cloudy retrieval of atmospheric temperature and moisture 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 within the AIRS field of view are also used to demonstrate the profile retrieval improvement below the cloud layer.In addition this paper has demonstrated that the use of collocated clear MODIS multi-spectral imager data along with the AIRS high spectral resolution infrared radiances can greatly improve 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 the mixed ratio of water vapor below the cloud top increase with 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 improved if the cloud height known perfectly for the mid-and high-level clouds,while to the low level clouds the retrieval has less sensitivity to the cloud height error.The retrieval accuracy of the cloud height with 50 hPa error decrease comparing with the cloud height known perfectly.The temperature retrieval seems to be more sensitive to cloud height error than humidity retrieval.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 of collocated clear MODIS multi-spectral imager data along with the AIRS high spectral resolution infrared radiances can greatly improve the single FOV cloudy retrieval especially under more overcast condition.