基于贝叶斯融合方法的高分辨率地面-卫星-雷达三源降水融合试验

An experiment of high-resolution gauge-radar-satellite combined precipitation retrieval based on the Bayesian merging method

  • 摘要: 为了探讨一种适用于区域性的地面、雷达、卫星等多源降水资料融合的方法,一种曾用于高分辨雷达、卫星土壤湿度产品反演的贝叶斯融合(Bayesian Merging)方法被尝试应用于江淮地区1 h-0.05°×0.05°经纬度高分辨率的雷达估测降水、卫星反演降水与地面站点观测降水3种资料的融合。在应用该方法时,通过2009年8月样本统计分别估计卫星和雷达反演降水的误差关系,通过曲线拟合建立误差方程,并以卫星资料作为背景场,但在融合时将雷达估测降水作为新的观测信息与地面观测降水同时引入。融合试验检验结果表明:贝叶斯融合方法能够有效实现雷达、地面、卫星3种不同来源资料的融合,该方法生成的多源融合产品的精度均优于任何单一来源的降水产品。

     

    Abstract: In order to develop a method for combining different precipitation sources such as gauge, radar and satellite with high resolution, the Bayesian merging method, which has been used to retrieve high-resolution surface moisture from radar and satellite sensors, was adopted to combine gauge, radar and satellite precipitation data at hourly and 0.05°×0.05° lat/lon resolutions over the Jiang-huai region. The errors statistics of the three sources of precipitation was performed via the samples in August of 2009. The CMORPH was set to the first guess, and the radar and gauge precipitations were merged as the observations together. The verification at the independent stations showed that the Bayesian merging method can be effectively applied to the combination of gauge-radar-satellite precipitations, and the accuracy of the combined precipitation was higher than any of the three sources of precipitation.

     

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