Articles | Volume 9, issue 12
Atmos. Meas. Tech., 9, 5699–5706, 2016
Atmos. Meas. Tech., 9, 5699–5706, 2016

Research article 29 Nov 2016

Research article | 29 Nov 2016

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

Mattia Stagnaro1,2, Matteo Colli1,2, Luca Giovanni Lanza1,2, and Pak Wai Chan3 Mattia Stagnaro et al.
  • 1University of Genoa, Department of Civil, Chemical and Environmental Engineering, Via Montallegro 1, 16145 Genoa, Italy
  • 2WMO/CIMO Lead Centre “Benedetto Castelli” on Precipitation Intensity, Genoa, Italy
  • 3Hong Kong Observatory, 134A Nathan Road, Hong Kong, China

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.

Short summary
The research presented in this work involves field data analysis, numerical modelling techniques and approaches to a long-standing problem of liquid precipitation measurements: the sampling and the interpretation of the tipping-bucket sensor signal. The present study shows relevant implications of the adopted data processing methods for the accuracy of the rainfall intensity measurements provided by traditional tipping-bucket gauges.