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 onlyof systematic biases caused by random noises but also spatially nonuniformbiases in radar rainfall at individual rain-gauge stations. In this study, areal-time adjustment to the radar reflectivity--rainfall rates (Z--R)relationship scheme and the gauge-corrected, radar-based, estimation schemewith inverse distance weighting interpolation was developed. Based on thecharacteristics of the two schemes, the two-step correction technique ofradar quantitative precipitation estimation is proposed. To minimize theerrors between radar quantitative precipitation estimations and rain gaugeobservations, a real-time adjustment to the Z--R relationshipscheme is used to remove systematic bias on the time-domain. Thegauge-corrected, radar-based, estimation scheme is then used to eliminatenon-uniform errors in space. Based on radar data and rain gauge observationsnear the Huaihe River, the two-step correction technique was evaluated usingtwo heavy-precipitation events. The results show that the proposed schemeimproved not only in the underestimation of rainfall but also reduced theroot-mean-square error and the mean relative error of radar--rain gaugepairs.