Research Of Cloud Geometrical Height Based On Space-based Active And Passive Remote Sensing

Cloud is an important modulator of the hydrologic cycling and energy balance of the Earth-atmosphere system.Knowledge of the cloud vertical structures is crucial in the climate modeling and aviation flight.This research is based on data products of A-Train satellites.Taking advantage of active(CloudSat/CALIPSO)and passive(MODIS)remote sensing data,the retrieval of cloud geometrical height and related application are studied.The spatio-temporal variation and frequency of CTH of the topmost cloud layer over China and the North Atlantic have been analysed based on CloudSat 2B-GEOPROF and 2B-CLDCLASS products from 2011 to 2013.In addition,the CTH differences between the CloudSat and MODIS are quantificationally described with different cloud types,using CloudSat and MODIS collocation datas in 2010.CBH is estimated by combining measurements from CloudSat/CALIPSO and MODIS based on the International Satellite Cloud Climatology Project(ISCCP)cloud-type classification and a weighted distance algorithm.The proposed method is validated by A-Train data.The difference between the real and estimated CBHs is mainly within 1 km when distance ranges from 0 km to 200 km,and the root mean square error is smaller than 2.2 km.The CBH estimation method was applied to the 3D cloud structure of Tropical Cyclone Bill.For stratocumulus,a new CBH estimation algorithm is established,which is a combination of the cloud type and the statistical characteristics.The validated results indicate that the mean deviation(MD)of stratocumulus CBH on land is not more than 0.4 km,and the Root Mean Square Error(RMSE)is not more than 0.5 km.The stratocumulus CBH estimation error is smaller on sea,and the MD and RMSE are less than 0.2 km and 0.3 km respectively.