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

摘要

In this paper the simulated space-based high spectral resolution infrared 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 (the Atmospheric InfraRed Sounder) and the associated clear MODIS (the Moderate Resolution Imaging Spectroradiomete) infrared observations within the AIRS field of view (FOV) are also used to demonstrate the profile retrieval improvement below the cloud layer. The results show that the knowledge of cloud height is critical to sounding retrieval performance. 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.