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Performance of post-processing algorithms for rainfall intensity using measurements from tipping-bucket rain gauges

机译：使用自卸式雨量计的测量结果进行降雨强度后处理算法的性能

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Eight rainfall events recorded from May to September?2013 at Hong Kong International Airport (HKIA) have been selected to investigate the performance of post-processing algorithms used to calculate the rainfall intensity (RI) from tipping-bucket rain gauges (TBRGs). We assumed a drop-counter catching-type gauge as a working reference and compared rainfall intensity measurements with two calibrated TBRGs operated at a time resolution of 1?min. The two TBRGs differ in their internal mechanics, one being a traditional single-layer dual-bucket assembly, while the other has two layers of buckets. The drop-counter gauge operates at a time resolution of 10?s, while the time of tipping is recorded for the two TBRGs. The post-processing algorithms employed for the two TBRGs are based on the assumption that the tip volume is uniformly distributed over the inter-tip period. A series of data of an ideal TBRG is reconstructed using the virtual time of tipping derived from the drop-counter data. From the comparison between the ideal gauge and the measurements from the two real TBRGs, the performances of different post-processing and correction algorithms are statistically evaluated over the set of recorded rain events. The improvement obtained by adopting the inter-tip time algorithm in the calculation of the RI is confirmed. However, by comparing the performance of the real and ideal TBRGs, the beneficial effect of the inter-tip algorithm is shown to be relevant for the mid–low range (6–50?mmmspace width="0.125em" linebreak="nobreak"/hsup?1/sup) of rainfall intensity values (where the sampling errors prevail), while its role vanishes with increasing RI in the range where the mechanical errors prevail.
机译：选择了2013年5月至2013年9月在香港国际机场（HKIA）记录的八次降雨事件，以研究用于计算自卸式雨量计（TBRG）的降雨强度（RI）的后处理算法的性能。我们以落差计数器式量规为工作参考，并将降雨强度测量结果与两个以1？min的时间分辨率运行的校准TBRG进行了比较。两种TBRG的内部机制不同，一种是传统的单层双桶组件，另一种是两层桶。液滴计数器的时间分辨率为10？s，同时记录了两个TBRG的倾翻时间。用于两个TBRG的后处理算法是基于这样的假设，即尖端体积在尖端间周期内均匀分布。理想的TBRG的一系列数据是使用从液滴计数器数据得出的虚拟小费时间重建的。通过比较理想的雨量器和两个实际TBRG的测量值，可以对记录的降雨事件集进行统计评估，以评估不同的后处理和校正算法的性能。确认了在RI计算中采用尖端间时间算法所获得的改进。但是，通过比较实际和理想TBRG的性能，针尖间算法的有益效果与中低范围（6–50？mm h ？1 ）（在采样误差占优势的位置），而在机械误差占优势的范围内，其作用随着RI的增加而消失。

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