Operational Monitoring of Rainfall over the Arno River Basin Using Dual-Polarized Radar and Rain Gauges

Operational Monitoring of Rainfall over the Arno River Basin Using Dual-Polarized Radar and Rain Gauges
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使用双偏振雷达和雨量计对阿诺河流域的降雨量进行业务监测

DOI:
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发表时间:
2000
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通讯作者:
E. GoRouccr
E. GoRouccr
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文献类型:
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作者:
E. GoRouccr

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介绍了Polar 55 C在意大利Amo河流域上空收集的反射率(ZH)和微分反射率(ZoR)测量结果。结合雨量计网络,研究了基于双极化(ZoR)的降雨算法在C波段的适用性。传统的逐点比较雷达和雨量计估计的降雨量,以及统计比较的双极化雷达和雨量计数据通过概率匹配程序,提出。误差结构的反射率降雨Z-R关系,以及Z 0 R为基础的算法,作为一个功能的空间和时间的平均进行评估。逐点比较,以及基于累积分布函数(CDF)匹配的统计评估,被用来表明,在过多的地面杂波污染和衰减问题的业务环境中,基于双极化的降雨算法比任何任意的Z-R关系表现得更好。此外,它表明,一个双极化(ZoR)算法获得的匹配的CDF执行比最好的可能的Z-R关系。
Reflectivity (ZH) and differential reflectivity (ZoR) measurements collected by Polar 55C over the Amo River basin in Italy are presented. The applicability of dual-polarization (ZoR )-based rainfall algorithms at C band in an operational setting is studied in conjunction with a network of rain gauges. Conventional pointwise comparison of radar and rain gauge estimates of rainfall, as well as statistical comparison of dual-polarization radar and rain gauge data via probability matching procedure, are presented. Error structure of reflectivity rainfall Z-R relation, as well as Z0 R-based algorithms, is evaluated as a function of spatial and temporal averaging. Pointwise comparison, as well as statistical evaluation based on cumulative distribution function (CDF) matching, are used to show that in an operational environment with excessive ground-clutter contamination and attenuation problems the dual-polarization-based rainfall algorithm performs better than any arbitrary Z-R relation. In addition, it is shown that a dual-polarization (ZoR) algorithm obtained matching the CDFs performs better than the best possible Z-R relation.