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Application of the Doppler weather radar in real-time quality control of hourly gauge precipitation in eastern China

机译:多普勒天气雷达在中国东部小时降水量实时质量控制中的应用

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The current real-time operational quality control method for hourly rain gauge records at meteorological stations of China is primarily based on a comparison with historical extreme records, and the spatial and temporal consistencies of rain records. However, this method might make erroneous judgments for heavy precipitation because of its remarkable inhomogeneous features. In this study, we develop a Radar Supported Operational Real-time Quality Control (RS_ORQC) method to improve hourly gauge precipitation records in eastern China by using Doppler weather radar data and national automatic rain-gauge network in JJA (i.e., June, July and August) between 2010 and 2011. According to the probability density function (PDF) and cumulative probability density function (CDF), we establish the statistic relationships between NSN precipitation records under 7 radar coverage and radar quantitative precipitation estimation (QPE). The other NSN records under 5 radar coverage are used for the verification. The results show that the correct rate of this radar-supported new method in judging gauge precipitation is close to 99.95% when the hourly rainfall rate is below 10 mm h(-1) and is 96.21% when the rainfall intensity is above 10 mm h(-1). Moreover, the improved quality control method is also applied to evaluate the quality of provincial station network (PSN) precipitation records over eastern China. The correct rate of PSN precipitation records is 99.92% when the hourly rainfall rate is below 10 mm h(-1), and it is 93.33% when the hourly rainfall rate is above 10 mm h(-1). Case studies also exhibit that the radar-supported method can make correct judgments for extreme heavy rainfall. (C) 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.
机译:当前中国气象站小时雨量计记录的实时运行质量控制方法主要是基于与历史极端记录的比较以及雨记录的时空一致性。但是,这种方法由于其明显的非均一特征而可能对强降水做出错误的判断。在这项研究中,我们开发了雷达支持的操作实时质量控制(RS_ORQC)方法,通过使用多普勒天气雷达数据和JJA的国家自动雨量计网络(即6月,7月和根据2010年至2011年8月的数据。根据概率密度函数(PDF)和累积概率密度函数(CDF),我们建立了7雷达覆盖下的NSN降水记录与雷达定量降水估计(QPE)之间的统计关系。在5个雷达覆盖范围内的其他NSN记录用于验证。结果表明,当小时降水率低于10 mm h(-1)时,该雷达支持的新方法判断降水量的正确率接近99.95%,而当降雨强度高于10 mm h时正确率达到96.21%。 (-1)。此外,改进的质量控制方法还被用于评估中国东部省级站网(PSN)降水记录的质量。当小时降雨量低于10 mm h(-1)时,PSN降水记录的正确率为99.92%,而当小时降雨量高于10 mm h(-1)时为93.33%。案例研究还表明,雷达支持的方法可以对极端暴雨做出正确的判断。 (C)2016作者。由Elsevier B.V.发布。这是CC BY-NC-ND许可下的开放获取文章。

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