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Use of Specific Attenuation for Rainfall Measurement at X-Band Radar Wavelengths. Part I: Radar Calibration and Partial Beam Blockage Estimation

机译:使用特定衰减在X波段雷达波长处进行降雨测量。第一部分:雷达校准和部分波束阻塞估计

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摘要

In a two-part paper, radar rain-rate retrievals using specific attenuation A suggested by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two twin polarimetric X-band weather radars in Germany during the summers of 2011-13 are used to analyze various aspects of rain-rate retrieval, including miscalibration correction, mitigation of ground clutter contamination and partial beam blockage (PBB), sensitivity to precipitation characteristics, and the temperature assumptions of the R(A) technique. In this paper, the relations inherent to the R(A) method are used to estimate radar reflectivity Z from A and compare it to the measured Z in order to estimate PBB and calibration offsets for both radars. The fields of Z estimated from A for both radars are consistent, and the differences between Z(A) and measured Z are in good agreement with the ones calculated using either consistency relations between reflectivity at horizontal polarization Z(H), differential reflectivity Z(DR), and specific differential phase K-DP in rain or a digital elevation model in the presence of PBB. In the analysis, the dependence of A on temperature appears to have minimal effects on the overall performance of the method. As expected, the difference between Z(A) and attenuation-corrected measured Z observations varies with rain type and exhibits a weak systematic dependency on rainfall intensity; thus, averaging over several rain events is required to obtain reliable estimates of the Z biases caused by radar miscalibration and PBB.
机译:在由两部分组成的论文中,Ryzhkov等人建议使用特定衰减A进行雷达降雨率反演。经过彻底调查。在2011-13年夏季,德国的两个双极化X波段天气雷达连续测量重叠的时间序列,以分析降雨率的各个方面,包括失准校正,减轻地面杂波污染和部分光束阻塞( PBB),对降水特征的敏感性以及R(A)技术的温度假设。在本文中,R(A)方法固有的关系用于从A估算雷达反射率Z并将其与测得的Z进行比较,以便估算两个雷达的PBB和校准偏移。从A估计的两个雷达的Z场是一致的,并且Z(A)和测得的Z之差与使用水平偏振Z(H)的反射率,差分反射率Z( DR)和特定的微分相位K-DP(在雨中或存在PBB的数字高程模型中)。在分析中,A对温度的依赖性似乎对方法的整体性能影响最小。正如预期的那样,Z(A)和经衰减校正的Z观测值之间的差异随降雨类型而变化,并且对降雨强度表现出较弱的系统依赖性;因此,需要对几个降雨事件进行平均,才能获得由雷达失调和PBB引起的Z偏差的可靠估计。

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