# Evaluation of Grid-Based Rainfall Products and Water Balances over the Mekong River Basin
## 4 Results and Discussion
### Statistical Evaluation of GPPs
#### 4.1.3 Daily Comparison
The rainfall of all of the GPPs in  
Figure 4: Correlation coefficients of the GPPs and the observed rainfall with latitude. Figure 5: The occurrence frequencies (bars) of CPC, TRMM 3B42, GSMaP, CMORPH, and the daily gauge observations, as well as their relative contributions (lines) to the total rainfall during the period 1998–2006. this class provides an insignificant contribution. At the light rain intensity (1,20) mm, the occurrence frequency of GSMaP is 36.3% compared to 20.7% for the observations, and the contribution is 62.5% and 35% for GSMaP and the observations, respectively, which is nearly a 30% difference. The CPC and CMORPH products illustrate the same variation, but with a narrower spread compared to GSMaP--the occurrence frequency of 27% and 20% with little rain, and 35.5% and 28.7% with moderate rain, respectively. TRMM 3B42 deviates the least compared to the observations regarding the occurrence frequencies and contributions of all rainfall intensities, as shown in Figure 5. TRMM 3B42 estimates the occurrence frequency of little rain events to be approximately 11.7%, which is approximately 7% lower than the actual occurrence frequency. TRMM 3B42 estimates the occurrence frequency of light rainfall events to be approximately 29.14%, which is approximately 8% higher than the actual occurrence frequency, and the contribution to be 45%, which is 15% higher than the observations. With moderate rain class (20,50) mm, the contribution of TRMM 3B42 even matches that of the observations--38% and 39%, respectively. At heavy intensity (>50 mm), the difference between TRMM and the observations, both in occurrence frequency and contribution, is also lowest--0.62% and 10%, respectively. In other words, quantitatively analyzing the discrepancies between the GPPs and the rain gauge data in terms of the rain class first shows that all of the GPPs feature similar error characteristics, i.e., they tend to overestimate little and light rainfall events, but underestimate moderate and heavy ones. Significant discrepancies can be found in the GSMaP product in contrast to the narrowest spread presented in TRMM 3B42. Second, all of the GPPs perform poorly in capturing heavy rainfall (>50 mm/day) events, which suggests that local calibration with rain gauge or ground radar data should be carried out to further improve the daily precipitation estimates for further studies. The analysis of statistical indicators proves that the TRMM 3B42 product illustrates the best ability to capture precipitation for the whole MRB at different time scales: Monthly, seasonal, and annual comparisons. It can be found that at the daily time scale, the GSMaP and CPC products show better performance than the other GPPs in the upstream region of the basin. Evaluation of the different GPPs at different variability scales (i.e., spatial and temporal scales) using statistical indicators provides an overall picture of the GPPs' performance. To enable the guiding of users to more precisely select the appropriate product for hydrological applications, multiple GPPs should be tested in hydrological simulations [48; 49]. Therefore, in this study, further simulations of the daily hydrological process in the MRB using the SWAT model were conducted.