## 4 Results
### Statistical Assessment of Multiple SPPs
#### 4.1.1 Precipitation at Gauge-Located Grid Cells
For the post-real-time products, the highest averaged POD values are found in GSMaP-MVK (0.233) in daytime and GSMaP-GAUGE (0.532) in nighttime, and 3B42V7 provides the lowest detection probabilities (0.192 and 0.336) in both time slots. Figure 4i,j denote that GSMaP-GAUGE has the highest false alarm ratios among all SPPs, with mean FAR values of 0.743 and 0.597 in daytime and nighttime, respectively. By contrast, the averaged FARs found in 3B42 RT and 3B42V7 are the lowest, reaching, on average, 0.596 and 0.595 in daytime and 0.406 and 0.406 in the nighttime. In addition, GSMaP-MVK obtains the highest CSIs in both time slots (0.162 and 0.335 on average) among all eight SPPs, whereas GSMaP-GAUGE and GSMaP-NRT provide the lowest values for the daytime precipitation estimates (0.127) and nighttime precipitation (0.256), respectively (Figure 4k,i). Figure 5 compares the histograms of the eight SPPs at the locations of the seven stations in the Chindwin River basin according to the ground observations for daytime and nighttime slots. Figure 5a shows that approximately 91.1% of the observed 3-hourly daytime precipitation data samples are under 0.1 mm, and all SPPs underestimate this frequency by 6.5-10.4%. All SPPs present an overestimation for 3-hourly daytime precipitation ranging from 0.1 mm to 10 mm. In particular, GSMaP-NRT and GSMaP-GAUGE provide evident overestimations of 11.3% and 9.8%, respectively, and 3B42 RT and 3B42V7 are in slight overestimations of 1.0% and 2.1%, respectively. Nearly all products underestimate the occurrence frequency of daytime precipitation between 10 and 20 mm, except for 3B42 RT with a mild overestimation of 0.2%. In addition, Figure 5a illustrates that an underestimation of 3-hourly daytime precipitation that exceeds 20 mm is found in all SPPs. All these observations indicate that the eight SPPs in this study tend to underestimate the occurrence frequencies of non-rain and heavy rain events and overestimate light and moderate rain events. A similar finding is also indicated in the 12-hourly satellite nighttime precipitation estimates (Figure 5b). Figure 5: Histograms of the eight satellite precipitation estimates at seven stations in the Chindwin River basin in contrast with the observations (1 April 2014–31 December 2016): **(a)** 3-hourly daytime precipitation and **(b)** 12-hourly nighttime precipitation. Taylor diagrams were likewise plotted to visualize the concise statistical summary on how well each SPP agrees with the ground precipitation observations in the Chindwin River basin (Figure 6). Figure 6 indicates that among all the near-real-time products, GSMaP-NRT is most inferior in capturing daytime precipitation dynamics, whereas 3B42 RT presents the best overall performance, followed by IMERG-L and IMERG-E. Concerning the accuracy of the four post-real-time products in retrieving daytime precipitation, IMERG-F demonstrates the best performance, which is slightly superior to 3B42V7. GSMaP-MVK is ranked third, and GSMaP-GAUGE is inferior due to its low relative mean squared deviation and CC (Figure 6a). The overall performance of the eight SPPs in retrieving nighttime precipitation is similar to the situation of the daytime precipitation estimates (Figure 6b).