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Time-dependent Z-R relationships for estimating rainfall fields from radar measurements

机译:雷达测量估算降雨场的时间依赖性Z-R关系

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The operational use of weather radars has become a widespread and useful tool for estimating rainfall fields. The radar-gauge adjustment is a commonly adopted technique which allows one to reduce bias and dispersion between radar rainfall estimates and the corresponding ground measurements provided by rain gauges. This paper investigates a new methodology for estimating radar-based rainfall fields by recalibrating at each time step the reflectivity-rainfall rate (Z-R) relationship on the basis of ground measurements provided by a rain gauge network. The power-law equation for converting reflectivity measurements into rainfall rates is readjusted at each time step, by calibrating its parameters using hourly Z-R pairs collected in the proximity of the considered time step. Calibration windows with duration between 1 and 24 h are used for estimating the parameters of the Z-R relationship. A case study pertaining to 19 rainfall events occurred in the north-western Italy is considered, in an area located within 25 km from the radar site, with available measurements of rainfall rate at the ground and radar reflectivity aloft. Results obtained with the proposed method are compared to those of three other literature methods. Applications are described for a posteriori evaluation of rainfall fields and for real-time estimation. Results suggest that the use of a calibration window of 2–5 h yields the best performances, with improvements that reach the 28% of the standard error obtained by using the most accurate fixed (climatological) Z-R relationship.
机译:天气雷达的操作使用已成为估算降雨场的广泛和有用的工具。雷达仪调整是一种常用的技术,它允许一个人减少雷达降雨估计和雨量仪提供的相应地测量之间的偏差和分散。本文研究了通过在每次雨量仪网络提供的地面测量的基础上重新校准来验证基于雷达的降雨场的新方法。通过使用在所考虑的时间步骤的邻近收集的每小时Z-R对中校准其参数,重新调整将反射率测量转换为降雨速率的电力规律方程。校准窗口在1到24小时之间的校准窗口用于估计Z-R关系的参数。在意大利西北部发生的案例研究发生在距离雷达网站不到25公里的地区,距离南北西北有关的19南部的降雨事件,可在地面的降雨率和雷达反射率。用该方法获得的结果与三种其他文献方法的结果进行比较。用于对降雨场的后验评估和实时估计的应用。结果表明,使用2-5小时的校准窗口产生了最佳性能,提高了通过使用最准确的固定(气候)Z-R关系获得的标准误差的28%。

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