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Eight rainfall events recorded from May to September 2013 at HongKong International Airport (HKIA) have been selected to investigate theperformance of post-processing algorithms used to calculate the rainfallintensity (RI) from tipping-bucket rain gauges (TBRGs). We assumed adrop-counter catching-type gauge as a working reference and compared rainfallintensity measurements with two calibrated TBRGs operated at a timeresolution of 1 min. The two TBRGs differ in their internal mechanics, onebeing a traditional single-layer dual-bucket assembly, while the other hastwo layers of buckets. The drop-counter gauge operates at a time resolutionof 10 s, while the time of tipping is recorded for the two TBRGs. Thepost-processing algorithms employed for the two TBRGs are based on theassumption that the tip volume is uniformly distributed over the inter-tipperiod. A series of data of an ideal TBRG is reconstructed using the virtualtime of tipping derived from the drop-counter data. From the comparisonbetween the ideal gauge and the measurements from the two real TBRGs, theperformances of different post-processing and correction algorithms arestatistically evaluated over the set of recorded rain events. The improvementobtained by adopting the inter-tip time algorithm in the calculation of theRI is confirmed. However, by comparing the performance of the real and idealTBRGs, the beneficial effect of the inter-tip algorithm is shown to berelevant for the mid–low range (6–50 mm<mspace width="0.125em" linebreak="nobreak"/>h<sup>−1</sup>) of rainfallintensity values (where the sampling errors prevail), while its role vanisheswith increasing RI in the range where the mechanical errors prevail

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