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Abstract This study evaluated 24-, 6-, and 1-h radar precipitation estimated from the National Mosaic and Multisensor Quantitative Precipitation Estimation System (NMQ) and the Weather Surveillance Radar-1988 Doppler (WSR-88D) Precipitation Processing System (PPS) over the conterminous United States (CONUS) for the warm season April–September 2009 and the cool season October 2009–March 2010. Precipitation gauge observations from the Automated Surface Observing System (ASOS) were used as the ground truth. Gridded StageIV multisensor precipitation estimates were applied for supplementary verification. The comparison of the two systems consisted of a series of analyses including the linear correlation coefficient (CC) and the root-mean-square error (RMSE) between the radar precipitation estimates and the gauge observations, large precipitation amount detection categorical scores, and the reliability of precipitation amount distribution. Data stratified for the 12 CONUS River Forecast Centers (RFCs) and for the cold rains events with bright-band effects were analyzed additionally. Major results are 1) the linear CC of NMQ versus ASOS are generally higher than that of PPS versus ASOS over CONUS, while the spatial variations stratified by the RFCs may switch with seasons; 2) compared to the precipitation distribution of ASOS, NMQ shows less deviation than PPS; 3) for the cold rains verified against ASOS, NMQ has higher CC and PPS has lower RMSE for 6-h and higher RMSE for 1-h cold rains; and 4) for the precipitation detection categorical scores, either NMQ or PPS can be superior, depending on the time interval and season. The verification against StageIV gridded precipitation estimates showed that NMQ consistently had higher correlations and lower biases than did PPS.
Wu et al. (Thu,) studied this question.