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Ground observation of precipitation over complex terrain is subject to large uncertainties due to inadequate sampling. This study explores a method that combines limited gauge data and a high‐resolution numerical simulation to quantify the precipitation uncertainties in central Himalaya. Specifically, the Coefficient of spatial Variability (CV) of precipitation and the minimum Number of Required Stations (NRS) to obtain areal‐mean precipitation ground truth values within a 0.25° area are investigated using fine‐scale meteorological simulation at 1.5 km grid spacing. Evaluation over a densely‐gauged area demonstrates comparable CV and NRS values between station observations and simulations. The simulated CV and NRS values in a larger area show a strong and positive dependence on each other and an expected positive (negative) correlation with topographic complexity (temporal scale). The proposed method sheds lights on evaluating precipitation products and holds promise for informing the layout of rain gauge networks in complex terrain. Plain Language Summary: A challenging issue in evaluating gridded precipitation products for regions of complex terrain is to understand the uncertainties in the ground "truth," which usually requires a dense observing network. In this study we show that data from a high‐resolution numerical simulation can be used to quantify the uncertainties in the ground "truth" even though precipitation amount at individual rain gauge stations may not be accurately simulated. This method is validated in a valley of central Himalaya with high terrain complexity, in terms of the spatial variability of precipitation and the minimum number of stations needed to estimate the area‐averaged precipitation. We further show that uncertainties in the ground "truth" can be considerable even in flat areas. Key Points: A high‐resolution numerical simulation can be used to quantify the uncertainties in precipitation ground truth over complex terrainThe minimum number of stations to represent the area‐averaged precipitation highly depends on the spatial variability of precipitationAlthough topography strongly influences precipitation, it does not fully determine precipitation spatial variation even at monthly scale [ABSTRACT FROM AUTHOR]