基于云类型匹配和距离误差权重的单层云云底高度估计

Single-Layer Cloud Base Height Estimation Based on ISCCP Cloud-Type Classification and Weighted Distance

云底高度(cloud base height,CBH)的观测对地气系统的辐射模拟和保障飞行安全有重要意义。本文结合CloudSat/CPR、CALIPSO/CALIOP和Aqua/MODIS的主被动观测资料,建立了基于云类型和距离的CBH估计算法。本文云分类方法采取国际卫星云气候计划(International Satellite Cloud Climatology Project,ISCCP)的云分类法,并利用A-Train数据对估计结果进行验证。结果表明,CBH的平均误差小于3 km,而低云CBH的平均误差小于1 km。在0~500 km的估计范围内,CBH估计的绝对误差主要在1 km以内,均方根误差不超过3 km。最后,基于此方法,本文重建了一个锋面云系的三维结构。

Observation of cloud base height （CBH） is crucial in modeling earth-atmosphere radiation budget and for the aviation safety. CBH is estimated by combining measurements from CloudSat/CAI.IPSO 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 result indicates that the mean error of CBH is always less than 3 km, while the average error of CBH of low clouds is smaller than 1 kin. The difference between the real and estimated CBHs is mainly within 1 km when dis- tance ranges from 0 km to 500 km, and the root mean square error is smaller than 3 km. Application to the 3D cloud structure of a frontal Cloud is also demonstrated.