资源环境科技发展态势分析平台

Ice particle morphology and microphysical properties of cirrus clouds are essential for assessing radiative forcing associated with these clouds. We develop an optimal estimation-based algorithm to infer cirrus cloud optical thickness (COT), cloud effective radius (CER), plate fraction including quasi-horizontally oriented plates (HOPs), and the degree of surface roughness from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Infrared Imaging Radiometer (IIR) on the Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) platform. A simple but realistic ice particle model is used, and the relevant bulk optical properties are computed using state-of-the-art light-scattering computational capabilities. Rigorous estimation of uncertainties related to surface properties, atmospheric gases, and cloud heterogeneity is performed. The results based on the present method show that COTs are quite consistent with other satellite products and CERs essentially agree with the other counterparts. A 1month global analysis for April 2007, in which CALIPSO off-nadir angle is 0.3 degrees, shows that the HOP has significant temperature-dependence and is critical to the lidar ratio when cloud temperature is warmer than -40 degrees C. The lidar ratio is calculated from the bulk optical properties based on the inferred parameters, showing robust temperature dependence. The median lidar ratio of cirrus clouds is 27-31sr over the globe.