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首页> 外文期刊>Water resources research >High-Resolution Simulation Study Exploring the Potential of Radars, Crowdsourced Personal Weather Stations, and Commercial Microwave Links to Monitor Small-Scale Urban Rainfall
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High-Resolution Simulation Study Exploring the Potential of Radars, Crowdsourced Personal Weather Stations, and Commercial Microwave Links to Monitor Small-Scale Urban Rainfall

机译:高分辨率模拟研究探索雷达,人群资源丰富的个人气象站和商用微波链路以监测小规模城市降雨的潜力

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Many applications in urban areas require high-resolution rainfall measurements. Typical operational weather radars can provide rainfall intensities at 1-km(2) grid cells every 5min. Opportunistic sensing with commercial microwave links yields path-averaged rainfall intensities (typically 0.1-10km) within urban areas. Additionally, large amounts of urban in situ rainfall measurements from amateur weather observers are obtainable in real-time. The accuracy of these three techniques is evaluated for an urban study area of 20x20km, taking into account their respective network layouts and sampling characteristics. We use two simulated rainfall events described in terms of drop size distributions on a 100-m grid and with a temporal resolution of 30s. Accurate radar rainfall estimation with the Z-R relationship relies heavily on an appropriate choice of parameters, and a dual-polarization strategy is more suitable for higher intensities. Under ideal measurement conditions, the weather station network is the most promising, with a Pearson correlation coefficient above 0.86 and a relative bias below 4% for 100-m rainfall estimates at 5-min resolution. Microwave link rainfall observations contain the largest error, shown by a consistently larger coefficient of variation. The accuracy of all techniques improves when considering rainfall at larger scales, especially by increasing time intervals, with the strongest improvements found for microwave links for which errors are largely caused by their temporal sampling. Sparser networks are examined, showing that the decline in measurement accuracy only becomes significant when the link and station network density are reduced to less than half their levels in Amsterdam.
机译:城市地区的许多应用都需要高分辨率的降雨测量。典型的操作性天气雷达每5分钟可以提供1 km(2)网格单元的降雨强度。商业微波链路的机会感应可在城市区域内产生平均路径降雨强度(通常为0.1-10 km)。另外,业余天气观察者可以实时获得大量的城市现场降雨测量值。考虑到它们各自的网络布局和采样特性,针对20x20km的城市研究区域评估了这三种技术的准确性。我们使用两个模拟的降雨事件,这些降雨事件以100米网格上的液滴大小分布和30s的时间分辨率来描述。具有Z-R关系的准确雷达降雨量估计在很大程度上取决于适当选择的参数,而双极化策略更适合于更高的强度。在理想的测量条件下,气象站网络是最有前途的,Pearson相关系数高于0.86,且对5分钟分辨率下100 m降雨量的估计的相对偏差低于4%。微波链路降雨观测值包含最大的误差,以一贯更大的变化系数表示。当考虑更大范围的降雨时,所有技术的准确性都会提高,尤其是通过增加时间间隔,这是微波链路发现的最强改进,微波链路的误差主要是由它们的时间采样引起的。对稀疏网络进行了检查,结果表明,只有当链路和站点的网络密度降低到其阿姆斯特丹水平的一半以下时,测量精度的下降才变得明显。

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