## 4 Summary and Conclusions  
This study evaluates the performance of TMPA QPE products 3B42 RT and 3B42V7 for an extreme precipitation event in Beijing and adjacent areas. The evaluation has used a dense gauge network to provide the ground truth. The evaluation metrics, including RB, RMSE, and CC, are applied for grid-based accumulated rainfall and time series rainfall with further analysis of probability distributions and contingency. Findings are summarized as follows:  
Figure 5: **(a)** Occurrence probability distribution of rain rate; and **(b)** volume probability distribution of rain rate with bin interval of 0.5 mm/h.  
Figure 6: Contingency statistics for **(a)** probability of detection (POD); **(b)** false alarm ratio (FAR); and **(c)** critical success index (CSI) with bin interval of 1 mm/h.  
* Spatially, 3B42 RT and 3B42V7 can generally capture the rainfall spatial patterns with moderate CC (0.59) in the entire HBT region for the daily accumulated precipitation;
* Temporally, as to the region-averaged rainfall, 3B42 RT and 3B42V7 matched well with gauge temporal variation with high CCs (0.87 and 0.88, respectively) for the entire HBT region but a low CC (\(-\)0.17) for the Beijing area(Figure 4);
* Overall, 3B42 RT (3B42V7) overestimated the daily-accumulated rainfall by 21.95% (11.92%) in HBT and by 56.04% (38.08%) in Beijing. However, at the storm center, the two TMPA products underestimated rainfall by 29.02% and 36.07%;
* 3B42V7 and 3B42 RT have low probabilities of detecting intensive rainfall (e.g., \(>\)23 mm/h) and also misidentified the storm center.  
This study implies that satellite-based QPE products 3B42 RT and 3B42V7 might not perform well during heavy rainfall events because of their limitations in resolution. Therefore, the users should be cautious when applying 3B42 RT and 3B42V7 for hydrological modeling and natural hazards (e.g., landslide) monitoring in extreme precipitation events. However, as the Global Precipitation Measuring (GPM) mission, with more advanced dual-frequency radar onboard, will be launched in 2014, we can anticipate that future satellite-based QPE algorithms can be further improved for hydrological and meteorological applications. The TMPA algorithm developer may develop a better orographic precipitation estimation scheme for extreme precipitation events for the Day-1 algorithm of the GPM mission, which the V7 TMPA algorithm will evolve to, in 2014. GPM will advance the state of the art and there is still a lot of hard, practical work to be done to improve the satellite-based QPE algorithm.  
Thanks are given to [PERSON] of National Weather Service for their careful proofreading this paper. We are very grateful to the scientists in the NASA science team, who are responsible for the development of TMPA algorithm and for providing the history MTSAT-2 satellite brightness temperature images and helpful advice to conduct this study. This work was partially supported by the National Natural Science Foundation of China under Grant No. 41105098, 41275030, 40905019 and the R & D Special Foundation for Public Welfare Industry (meteorology) of China under Grant No. GYHY201306040 as well as by NOAA Multi-function Phased-Array Radar Project administrated by Atmospheric Radar Research Center at the University of Oklahoma.