Abstract
Abstract. 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 mmh−1) of rainfall intensity values (where the sampling errors prevail), while its role vanishes with increasing RI in the range where the mechanical errors prevail.
Highlights
In an effort to homogenize the dataset, we considered the standardized value of the generic rainfall intensity value (RIn) obtained as follows: RIn
We first evaluated the accuracy of the investigated RI algorithms using tipping-bucket rain gauges (TBRGs) measurements by comparing their performance with the working reference
The raw data recorded during a dedicated monitoring campaign have been analysed using two different post-processing algorithms to calculate 1 min RI series
Summary
Sound metrological procedures for the assessment of the uncertainty of meteorological measurements have recently been introduced within the framework of Europe-wide collaborative projects (Merlone et al, 2015) and therein extended to the measurement of liquid precipitation (see Santana et al, 2015). In this context, we use the term uncertainty in accordance with the International Vocabulary of Metrology (VIM) as the non-negative parameter characterizing the dispersion of the quantity values being attributed to a measurand (JCGM, 2012). In the case of tipping-bucket rain gauges (TBRGs), dedicated post-processing algorithms must be employed to achieve sufficient accuracy and to minimize the impact of sampling errors and the discrete nature of the measurement
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