中文摘要：

针对液态云微物理特性精确反演的迫切需求,综合主被动传感器的探测优势,联合CloudSat雷达反射率和Aqua光学厚度资料,提出基于最优估计理论的液态云微物理参数反演算法.通过假设粒子谱服从对数正态分布,基于前向物理模式建立测量变量与反演变量的函数关系,借助谱分布参数的先验信息、通过算法迭代得到谱参数的最优解,进而利用前向物理模式反演液态云微物理参数,并根据误差传递理论计算反演不确定度.通过设计反演方案,基于实测个例数据并与CloudSat官方发布产品和经验算法反演结果对比验证.结果表明：基于最优估计理论、联合主被动传感器资料的液态云微物理参数反演结果与官方发布产品一致性较好,弥补了经验算法误差大、扩展性差的不足,对于开展国内星载和机载W波段毫米波雷达液态云微物理参数反演研究具有重要的借鉴意义.

英文摘要：

In order to meet the urgent requirement for accurate retrieval of liquid cloud microphysical properties, integrating the detecting advantages of active and passive sensors and combining radar reflectivity and optical depth information from CloudSat and Aqua, a new retrieval algorithm of liquid cloud microphysical parameters is proposed according to the optimal estimation theory. By assuming the lognormal size distribution of cloud droplets and establishing functional relationships between measurement and retrieval variables based on forward physical model, with the prior information about spectral distribution parameters, the optimal solutions of spectral parameters are obtained after iteratively calculating, then the microphysical parameters of liquid cloud could be retrieved based on forward physical model, and the uncertainty can be calculated according to error propagation theory. By designing retrieval scheme and using measured case data, the retrieval results are compared with the data published by CloudSat official institutions and those retrieved using empirical algorithms, showing that retrievals of liqiud cloud microphysical parameters based on optimal estimation theory by using combined active and passive sensor data are well consistent with official released data, which makes up for the disadvantages of empirical algorithms that have large error and poor expansibility and gives some important references for retrieval research of liquid cloud microphysical parameters based on domestic spaceborne and airborne W-band millimeter-wave radar data.