Automatic rain gauges measure precipitation directly and are important in areal rainfall calculation, climate research, and meteorological services. However, a system for quality control is required when using automatic rain gauge data quantitatively due to various types of systematic and random errors caused by wind, evaporation, splashing, calibration, funnel blockage, mechanical failure, finite sampling, signal transmission interference, power failure, and other factors. Doppler radar has become an important method for monitoring precipitation in recent decades due to its high spatial and temporal resolution. In this study, a two-step calibration method was used to improve radar quantitative precipitation estimation. Then, the differences between radar-gauge pairs were statistically analysed to determine an effective criterion for rain gauge quality control. Finally, two heavy rain events were studied to assess the proposed quality control procedure. The results showed that the two-step calibration method can improve radar quantitative precipitation estimations by removing systematic bias and eliminating relative errors in space. Thus, radar quantitative precipitation estimation can be applied in real-time automatic rain gauge quality control. With respect to the entire set of gauge data, the percentage of false quality control results was as suspected, approximately 0.1%, with the wrongly rejected gauges located mainly on the edges of rain bands. The real-time rain gauge data quality control method, however, causes the incorrect rejection of gauges not only in regions where rain gauges are located on the edges of rain bands but also in regions where radar data are unavailable or are not under quality control.