Product-Error-Driven Uncertainty Model for Probabilistic Quantitative Precipitation Estimation with NEXRAD Data
Product-Error-Driven Uncertainty Model for Probabilistic Quantitative Precipitation Estimation with NEXRAD Data
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DOI：
10.1175/2007jhm814.1
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发表时间：
2007-12
影响因子：
3.8
通讯作者：
G. Ciach;W. Krajewski;G. Villarini
中科院分区：
文献类型：
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作者：
G. Ciach;W. Krajewski;G. Villarini
虽然人们普遍认为，基于美国国家气象监测雷达-1988多普勒（WSR-88D）站的雷达降雨（RR）估计包含高度的不确定性，但目前还没有方法可以告知用户其定量特征。通过以概率形式而不是传统的确定性形式交付产品，可以实现对这种不确定性的最全面的描述。作者正在开发一种基于气象雷达数据的概率定量降水估计（PQPE）方法。在本研究中，他们提出了该方法的核心要素：基于经验的RR产品误差结构模型。作者采用产品误差驱动（PED）的方法得到了一个真实的不确定性模型。它是基于对俄克拉何马州俄克拉何马市WSR-88D雷达（KTLX） 6年数据的分析，使用NEXRAD系统的降水处理系统算法进行处理。
Abstract Although it is broadly acknowledged that the radar-rainfall (RR) estimates based on the U.S. national network of Weather Surveillance Radar-1988 Doppler (WSR-88D) stations contain a high degree of uncertainty, no methods currently exist to inform users about its quantitative characteristics. The most comprehensive characterization of this uncertainty can be achieved by delivering the products in a probabilistic rather than the traditional deterministic form. The authors are developing a methodology for probabilistic quantitative precipitation estimation (PQPE) based on weather radar data. In this study, they present the central element of this methodology: an empirically based error structure model for the RR products. The authors apply a product-error-driven (PED) approach to obtain a realistic uncertainty model. It is based on the analyses of six years of data from the Oklahoma City, Oklahoma, WSR-88D radar (KTLX) processed with the Precipitation Processing System algorithm of the NEXRAD system...