This paper focuses on the uncertainty of summer precipitation estimations produced by Global Satellite Mapping of Precipitation (GSMaP) over Mongolia, a region with complex terrain and sparse weather observation networks. We first compared the average summer precipitation over Mongolian territory as reported by several precipitation products. Although the interannual variability of the product was comparable, the amount of recorded precipitation differed among various products. The rain gauge-based analysis reported the lowest amount of precipitation, whereas the satellite-based GSMaP_MVK (Moving Vector algorithm with Kalman filter) reported the highest amount. Our results represent the first estimate of the characteristic differences among various precipitation-monitoring products, including Global Precipitation Measurement (GPM)-based products, as they relate to climatic and hydrometeorological assessments in Mongolia. We then performed a detailed comparison using a case study, in which a heavy rainfall event was captured by the GPM mission's core observatory near Ulaanbaatar in July 2016. In this case, gauged and ungauged GSMaP estimates of the precipitation over the mountain area significantly differed between algorithm versions 6 and 7. An intercomparison of atmospheric numerical modeling, the GPM core observatory, and rain gauge observation revealed that the rain gauge calibration of GSMaP effectively moderates the large error of the ungauged GSMaP data. The source of the significant ungauged GSMaP error is likely to be the rain rate estimates in algorithm version 7. However, the GSMaP gauge-calibrated estimates of the precipitation over mountainous areas may be affected by a potential underestimation of gauge analysis due to the missing localized precipitation occurring in the large gaps of the routine observation network. We expect that these findings will be helpful for developers aiming to further improve the GSMaP algorithm.