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Accurate spatial precipitation data are of prime importance for hydrological simulations and flood forecasts. Interpolation methods and satellite-based precipitation products (SPPs) are often applied to obtain spatially distributed precipitation over basins. The objective of this study is to investigate whether satellite precipitation data can yield better estimates than the precipitation information (gauge observations) already available in the basin. In this study, we assessed the performance of three Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) products against two calculated interpolation data and the ground precipitation observations at a daily scale in the middle reaches of the Yellow River Basin (MRYRB). This research includes two interpolation methods, namely, inverse distance weighting (IDW) and ordinary kriging (OK), and three latest IMERG SPPs, namely, IMERG “Early”, “Late”, and “Final” run SPPs (IMERG-E, IMERG-L, and IMERG-F). The results show that the two interpolation methods (IDW and OK) obtain the best overall performance, followed by IMERG-F, whereas IMERG-E and IMERG-L have inferior performance. Compared with the two interpolation methods, IMERG-F obtains higher CC values and lower FAR scores during the rainy season and presents better correlation with the gauge-based precipitation at the basin boundary. Furthermore, IMERG-F possesses a better capability over IDW and OK in detecting heavy precipitation events (over 20 mm). Nevertheless, the three IMERG SPPs generally provide similarly poor performance in terms of detection metrics and failed to accurately detect winter precipitation. The findings of this study are expected to provide SPP researchers and users with useful feedback on the net utility of satellite products and remind researchers of the importance of interpolated precipitation data in the assessment of satellite precipitation.
Shi et al. (2022) studied this question.
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