Improvement of Radar Quantitative Precipitation Estimation Based on Real-Time Adjustments to Z--R Relationships and Inverse Distance Weighting Correction Schemes

The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations. In this study, a real-time adjustment to the radar reflectivity--rainfall rates (Z--R) relationship scheme and the gauge-corrected, radar-based, estimation scheme with inverse distance weighting interpolation was developed. Based on the characteristics of the two schemes, the two-step correction technique of radar quantitative precipitation estimation is proposed. To minimize the errors between radar quantitative precipitation estimations and rain gauge observations, a real-time adjustment to the Z--R relationship scheme is used to remove systematic bias on the time-domain. The gauge-corrected, radar-based, estimation scheme is then used to eliminate non-uniform errors in space. Based on radar data and rain gauge observations near the Huaihe River, the two-step correction technique was evaluated using two heavy-precipitation events. The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar--rain gauge pairs.