Error features of the hourly GSMaP multi-satellite precipitation estimates over nine major basins of China

As one of the current mainstream satellite precipitation estimates, the Global Satellite Mapping of Precipitation (GSMaP) system of Japan has been developed to produce high-precision and high-resolution global rainfall products by integrating almost all of the available precipitation-related satellite sensors. To quantify the error features of GSMaP estimates and understand their hydrological potentials at short temporal scale, three widely used GSMaP products (GSMaP_NRT, GSMaP_MVK, and GSMaP_Gauge) were comprehensively investigated at 1 hourly and 0.1° × 0.1° resolutions over nine major basins of China. Assessment results show that GSMaP_NRT apparently underestimates the rainfall amounts, while GSMaP_MVK with both forward and backward propagation processes algorithm can effectively capture the most rainfall events and has the lower error and bias. GSMaP_Gauge displays the best error stability and error structure over most basins of China and also exhibits stronger rain-rate dependencies. However, its unexpected positive biases in southeastern basins, which mainly come from the overestimation at lower rain rates, still need to improve further in future developments. We expected the results documented here can both provide the retrieval developers with some valuable references and offer hydrologic users of GSMaP data a better understanding of their error features and potential utilizations for various hydrological applications.