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As the Japanese Global Precipitation Measurement (GPM) product, the Global Satellite Mapping of Precipitation (GSMaP) has been provided by the Japan Aerospace Exploration Agency (JAXA) to distribute hourly global precipitation map with 0.1° × 0.1° lat/lon grid. Since JAXA started near-real-time processing of the GSMaP on November 2007, there have been various significant improvements to the GSMaP. This paper summarizes GSMaP products and related algorithms in the GPM era and shows validation results in Japan and the United States.

The estimation of precipitation (rainfall and snowfall) across the Earth’s surface is important for both science and user applications, ranging from understanding and improving our knowledge of the global energy and water cycle, to water resources and hydrological modelling, and to societal applications such as water availability and monitoring of waterborne diseases (see Kirschbaum DB, Huffman GJ, Adler RF, Braun S, Garrett K, Jones E, McNally A, Skofronick-Jackson G, Stocker E, Wu H, Zaitchik BF, Bull Am Meteorol Soc 98:1169–1194, 2017). The global mapping of precipitation through conventional means is essentially limited to land areas due to the reliance upon rain (and snow) gauges and/or radar (see Kidd C, Becker A, Huffman GJ, Muller CL, Joe P, Skofronick-Jackson G, Kirschbaum DB, Bull Am Meteorol Soc 98:69–78, 2017a). For truly global precipitation mapping satellite observations must be used. A range of techniques, algorithms and schemes have been developed to exploit these satellite observations and generate quantitative precipitation products, many with (quasi-) global coverage. Alongside these techniques, there is a need for the inter-comparison, verification, and validation of such products in order to quantify their accuracy and performance (and consistency) for both developers and users. The International Precipitation Working Group (IPWG) has supported a long-term effort to inter-compare and validate precipitation products through the exploitation of large-scale regional surface reference data sets. Here, we present the current and future validation efforts of the IPWG together with examples of satellite-surface inter-comparisons.