近实时卫星降水的误差解析、数据融合和水文集合模拟研究

In recent, various developed real-time satellite rainfall datasets and their sustaining improved quality provides new opptrunities both for hydrology research and practice, especially in those areas with scare gauge mesurements. Hence, how to anlyze the accuracy of these datesets and fully tap into their potentiality has become a siginificant and open problem for hydrology communicty. Motivated by this, choosing three important areas in China, the Hanjing River Basin, Mingjiang River Basin and Qinghai Lake Basin, this project plans to conduct a deep research for the error characteristics analysis, data merging and hydrologic esemble simualtions using the four representative real-time satellite rainfall datasets, namely TRMM 3B42RTV7, CMORPH, GSMAP_NT and PETSIANN. Main proposals include the following items: (1) Using improved assesing indices, to compresneivey illustrated the error distrutions rules for various real-time satellite rainfall estimates and their related influencing factors; (2) For various surface rainfall gauge density and configuration, to propsed new rainfall merging alogrithms capable of combining various satellite rainfall information with gauge measurements and elucidate their gain for improve the rainfall estimation. (3) Based on the Baysian model averaging framework, runoff and drought emsemble simualtion will be conducted both using purely near real-time satelllite rainfall and their merged rainfall. The uncertainty of simulated runoff and drought process caused by rainfall error will be anlyzed. Also, measurements to reduce the uncertainty will be considered. The expected achievements of the project are significant for rational utlization of real-time satellite rainfall datasets to improved our capability for rainfall flood and drought hazard monitoring&mitigation. At the same time ,new findings will be fed back into the development of satellite rainfall retrieving alogrithms.

近实时卫星降水数据的不断涌现为地面降水资料稀缺地区的水文研究与实践提供了新机遇。科学认识这些数据的误差特征，充分发挥其水文应用潜力是一个开放性的科学问题。鉴于此，本项目拟在汉江、岷江和青海湖流域，开展TRMM 3B42RTV7、CMORPH、GSMAP_NT和PETSIANN四种代表性近实时卫星降水资料的误差综合解析、数据融合和水文集合模拟研究。主要内容：（1）完善综合评价指标，在多种时空尺度上阐明卫星降水的误差特征与影响因素；（2）针对不同地面雨量资料条件，发展集成多种信息的卫星降水融合新方法，辨识其对提高降水估计精度的增益；（3）基于Bayesian模型平均，采用卫星降水及其融合数据，开展径流、干旱集合模拟，揭示降水误差导致的不确定性并提出有效的削减方法。项目成果对于合理使用近实时卫星降水数据，提高资料稀缺流域的水旱监测预报能力具有重要意义，还将为卫星降水反演算法的改进提供反馈信息。

气象卫星采用星载传感器探测的云层波谱信息反演降水，是一种具有良好应用前景的全球性或准全球性降水获取技术，但卫星降水数据具有复杂误差特征。深入认识卫星降水数据误差特征，发展卫星降水误差削减方法具有重要科学价值。本项目比较了代表性近实时卫星降水数据误差的时空分布特征，研发了多源降水融合新算法并辨识了其对提高降水估计精度的作用，开展了相关数据在水文模拟与干旱评价中的试验分析。主要成果如下：.（1）综合解析了代表性近实时卫星降水误差分布规律及影响因素。在淮河流域、赣江流域、太湖流域等多个地区，以考虑地理地形因素影响的空间插值方法得到的基准降水量为参照，采用体积分类指标等评价了TMMM、CMORPH、GPM等近实时卫星降水数据误差特征，揭示不同条件下卫星降水误差变化规律，对各类数据的误差特征进行了解析。.（2）开发了卫星降水融合模型并辨识了多源降水融合的增益特征。采用地理时空加权回归（GTWR），构建了可同时集成雷达、卫星、再分析和雨量计等降水信息，并考虑地理地形因素影响和同时利用降水时空相关信息的降水融合新算法。基于独立的雨量观测数据辨识了降水融合算法相对传统空间插值的增益，分析了多源降水融合的有效范围。.（3）开展了卫星降水及其融合数据的水文模拟试验和气象干旱分析。构建了分布式水文模型，以近实时卫星~雨量计降水融合数据作为降水输入，开展了水文模拟试验。通过不同对照组综合比较，阐明了降水融合的水文模拟增益。采用近时卫星降水数据计算标准化降水指数，通过与地面基准降水计算结果比较，阐明了近实时卫星降水对气象干旱事件的捕捉和跟踪能力。.上述成果深化了对近实时卫星降水数据误差特征的认知，为卫星降水数据研制提供了反馈信息，促进卫星降水及其融合数据在地面雨量观测资料稀缺地区暴雨、洪水、干旱监测与预报预警中的应用。