**5. Discussion**

#### *5.1. The Advantages and Disadvantages of FY-2E QPE, FY-2G QPE, and IMERG*

As mentioned above, we found that FY-2G QPE generally outperformed IMERG in terms of the statistical metrics over mainland China in summer, 2018. One of the possible reasons for this could be the di fferent correction strategies; for example, the fusion method of FY-2 QPE considers not only the intensity, but also the directionality, of precipitation in the estimate fields. The FY-2 QPE fusion methods assume that the error field of the satellite-based precipitation estimate is related to not only the distance to the ground stations, but also the directionality of precipitation.

The unsatisfying performances of FY-2E QPE are significant, and may be related to the service life designed for FY-2E. FY-2E was launched in 2008 and was discontinued in early 2019, with a running time of about 11 years [35]. Therefore, the summer of 2018 coincides with the late stage of its operation. This could also explain the fact that there are some striped textures of precipitation spatial distributions derived from FY-2E in southern China in Figure 2b, which shows the spatial discontinuity of the satellite-based precipitation products. With the inevitable degradation of the sensors aboard the satellite, performance degradation is understandable.

According to the results demonstrated above, we found that FY-2 series satellites QPE and IMERG have advantages and disadvantages across the study area (Table 5). In mainland China, FY-2G QPE is more suitable in operational applications than IMERG, not only in terms of data accuracy, but also for the latency of the products (1 h for FY, 4 h for IMERG Early-run, 14 h for IMERG Late-run, and 3.5 months for IMERG Final-run), although there is no data coverage in the northern part of Heilongjiang Province (>50◦N), while the time span of FY-2 series satellites is not long enough. In contrast, the IMERG Final-run precipitation product has been calculated back to 2000. Therefore, it is appropriate for IMERG to be used for long-term studies related to precipitation with fine spatiotemporal resolutions. Regarding the spatial coverage of these precipitation products, IMERG is more applicable for global-scale research due to the wide coverage of its products. Nonetheless, users should still pay grea<sup>t</sup> attention to the not so satisfying performance of IMERG at hourly and diurnal scales. Furthermore, some algorithms and methods, such as downscaling and retrospective studies, could be applied to yield long-term precipitation estimates with finer spatiotemporal resolutions in the future [36–39].


**Table 5.** Summary of advances and weaknesses of the three products over mainland China.

#### *5.2. Possible Error Source Analysis of the GPM IMERG Product*

For decades, numerous researchers have focused on the errors of satellite-based precipitation products at multiple scales all over the world, leading to the continuous improvement of these products to [40–45]. In this study, we have proposed some possible error sources of the GPM IMERG product, hoping to provide preliminary references for improving satellite-based QPE for the next generation. As can be seen from Figures 5 and 7, the large FAR (>0.7) of IMERG is mainly distributed in northwestern China, where the values of CC are relatively small compared with the other regions over mainland China. Additionally, the bias is generally greater than 50%. The dominant arid and semi-arid climate means that the area exhibits little precipitation over the entire year. The small amount of rainfall in summer makes it di fficult to obtain correct detections [46,47]. Moreover, the ground observations obtained from meteorological stations for calibrating the satellite-based precipitation estimates are limited. These two issues may lead to a high false alarm ratio and significant overestimates over northwestern China.

In spite of the good performance compared with ground observations at monthly scale, the hourly and daily performance of IMERG shown by various indicators is not so satisfying. The characteristics of IMERG algorithms, including calibration algorithms and retrieval algorithms, might be related to this phenomenon. We know from the Algorithm Theoretical Basis Document (V06) of IMERG that the calibration strategy of IMERG Final-run products still has much room to improve [12]. The half-hourly precipitation estimates are simply multiplied by the monthly calibration ratios against monthly ground observations to yield half-hourly Final-run products. Although this will result in monthly estimates matching the gauge values more closely, IMERG Final-run datasets show an unsatisfying performance at meteorological scales (e.g., hourly or daily scale). We could assume that by using gauge calibrations at finer temporal resolutions, such as a daily scale, IMERG would likely yield satisfying performances at meteorological scales in terms of diagnostic indicators, with decreasing proportions of false negatives and false alarms. As for the retrieval algorithms of IMERG, the databases, including the a-priori database of cloud and precipitation profiles for inverting the passive microwave-based satellite precipitation estimates and the cloud feature database for inverting the infrared-based satellite precipitation estimates, might not be robust enough in China, considering the complex terrains and climatic factors [12,48–51]. In Figure 9, the POD patterns of IMERG are similar to those of FY-2G QPE, while the performances of its FAR and CSI patterns are not good. The phenomenon is caused by the larger proportion of false alarms of IMERG than those of FY-2G QPE. The high probability of false alarm occurrence indicated that the ability of IMERG in detecting the precipitation clouds at meteorological scales is comparatively weak, which may be related to the not well-matched feature database for precipitation retrieval algorithms over mainland China. In addition, significant overestimates and false alarms of IMERG in some areas may also result in large surrounding values for IMERG products. Meanwhile, the inconsistency between IMERG and FY-2G QPE would be significantly aggravated, as shown in Figure 10b.
