风云卫星微波双氧吸收通道降雪反演方法研究

目前被动微波降雪反演算法中存在两个问题。一是地表积雪的发射与降雪粒子散射具有相似的辐射特征，影响反演精度；二是雪云中过冷却水层的微波发射削弱雪粒子散射降温信号，造成反演误差。如何利用新型卫星资料解决以上两个问题成为改进降雪反演方法的关键。2017年风云三号D星的发射使我国成为国际上唯一拥有118GHz探测能力的国家。本项目将立足于风云卫星特有的118GHz探测通道，在发展包含过冷却水粒子、冰雪粒子吸收散射的快速矢量辐射传输模型基础上，通过亮温敏感性模拟，从理论上分析目前主流算法中因地表发射率不确定性和忽略过冷却水存在造成的降雪反演误差；在此基础上，采用贝叶斯方法利用传统通道完成水成物廓线初估；再利用风云卫星双氧通道同步物理迭代，对过冷却水以及雪水含量廓线进行限定，实现降雪的统计物理反演。最后进行新算法效果检验。项目成果将有望改善过冷却水出现时以及积雪覆盖条件下的卫星降雪反演精度。

At present, almost all the passive microwave snowfall retrieval algorithms employ the 89, 150 GHz window channel, and 183 GHz water vapor channels radiation. However, it is difficulty for the window channels to identify the snowfall signal under surface snow cover conditions. Besides, the increase in brightness temperature caused by supercooled water emission is neglected in these algorithms, which may lead to a significant snowfall inversion error. This study will develop a snowfall profile retrieval method by combining the unique 118 GHz and the traditional 50-57 GHz temperature-sounding channels on the FengYun satellite. Although 118 and 50-57 GHz channels are both oxygen absorption channels and are not sensitive to the surface emissions, they have apparent different absorption and scattering characteristics for supercooled droplets and snow particles. Therefore, the observations of these channels can be used to simultaneously retrieval the supercooled water and snow water content profiles and thereby improving the accuracy of snow inversion in the presence of supercooled droplets layer and land snow cover scenarios. In this research, we will develop a fast vector radiation transfer model that can simulate the absorption and scattering of supercooled droplets, ice cloud particles, and snow particles. Based on this model, the snowfall inversion error caused by surface emissivity uncertainty and ignoring the existence of supercooled droplets layer are simulated and analyzed and then theoretically reveal the influence of these factors on snowfall inversion. Furthermore, the Bayesian method will be used to estimate the prior hydrometeor profiles using traditional snowfall retrieval channels such as 89, 150, and 183 GHz channels. After that, the physical iterative inversion technology will be used to fit the observation of dual oxygen channels to improve snowfall retrieval accuracy. Finally, the new retrieval algorithm is validated by comparing it with the snowfall products from spaceborne radar.