4.1.1. Temporal Analysis

Figure 2 compares the mean of the observed monthly precipitation in the SRB with that of the five SPPs from January 2009 to December 2017. Figure A3 compares the scatterplots between observed and estimated monthly rainfall among the SPPs. In general, all five SPPs are capable of capturing the overall trend of monthly precipitation variations. The annual CCs of the five SPPs are all above 0.85, while those of IMERG\_F and 3B42 even exceed 0.95. The IMERG products all exhibit a tendency of underestimating rainfall, especially in wet months. In particular, for June, 2011 whose monthly rainfall reached as high as 1109 mm, IMERG\_E, IMERG\_L, and IMERG\_F give a low estimate of 608, 608, and 710 mm, respectively.

**Figure 2.** Comparison of mean monthly precipitation observations with the estimates of five SPPs from 2009 to 2017: (**a**) IMERG products; (**b**) TRMM products.

Table 2 compares the mean values of the four continuous evaluation metrics over the 13 rainfall stations among the five SPPs both annually and seasonally. With the highest RMSE of 101.42 mm and MAD of 65.72 mm, the 3B42RT product deviates the most from historical rainfall observations annually. A closer examination of the seasonal changes in RMSE and MAD, however, have shown that its considerably larger deviation in summer is the main cause. In the three seasons other than summer, 3B42RT actually deviates less than the two near-real-time IMERG products (Table 2).


**Table 2.** Mean evaluation metrics of the SPPs at monthly scale.

<sup>a</sup> Spring extends from March to May; Summer extends from June to August; Fall extends from September to November; Winter extends from December to the following February.

Annually, the three IMERG products tend to underestimate monthly precipitation, while the two TMPA products behave the opposite. Seasonally, IMERG\_F tend to underestimate monthly precipitation throughout the year, while the other two IMERG products act the same except that they tend to slightly overestimate in winter. In contrast, the RB of 3B42 remains close to zero all over the year except it approaches 10% in winter. Meanwhile, the RB of 3B42RT fluctuates much more ranging from -4.9% in spring to 25.8% in summer (Table 2). In terms of the other three continuous metrics, the five SPPs have exhibited somewhat similar seasonal patterns of change. For example, the CCs of the SPPs all reach or approach their peak values in summer, while decreasing to the bottom in fall. Meanwhile, both the RMSEs and MADs of the SPPs all rise to the top in summer, drop to medium in spring, and down to the lowest in fall and winter (Table 2). The seasonal changes in RMSEs and MADs correspond closely to the changes in the magnitude of seasonal rainfall.

Except for RB, the two post-time products (IMERG\_F and 3B42) perform significantly better than the rest real-time or near real-time products both annually and seasonally, with a noticeably higher value of CC (e.g., 0.97 and 0.95 annually) as well as considerably lower values of RMSE (e.g., 53.82 and 54.13 mm annually), and MAD (e.g., 35.79 and 37.07 mm annually) (Table 2). The findings of the overall better performance of the two post-time SPPs products compared to the real-time or near real-time products at the monthly time scale are not surprising, since both are generated after the adjustment of real-time products based on monthly measurements of ground rain gauges [42], although which may not include the 13 rain gauges covered in our study. With their annual CC and RB values exceeding the good performance thresholds, both IMERG\_F and 3B42 can be regarded as reliable sources of monthly precipitation in the SRB. Similar to our study, previous studies have also observed satisfactory performance of IMERG\_F and 3B42 in monthly rainfall estimation [43,44].
