Atmospheric simulation‐based precipitation datasets outperform satellite‐based products in closing basin‐wide water budget in the eastern Tibetan Plateau

Abstract

AbstractSatellite‐based precipitation products (SBPs) have been widely used in hydrological applications in recent decades but may contain large uncertainties in mountainous regions. Atmospheric simulation‐based datasets (ABDs) have been greatly improved in recent years, but their applications in mountainous hydrology are rare and need further validation. This study compares the performance of three SBPs and two ABDs in the mountainous Minjiang River basin, focusing on their potential for closing the basin‐wide water budget. The three SBPs include the China Merged Precipitation Analysis (CMPA), the Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement (IMERG) and the Global Satellite Mapping of Precipitation (GSMaP); the two ABDs are the fifth generation Reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5) and the High Asia Refined Analysis Version 2 (HAR V2). The five products are validated with rain gauge data and results show that all the five products except IMERG can generally reproduce the spatial pattern and elevation dependence of observed precipitation. Particularly, precipitation amount in the two ABDs is close to gauge observations in the low elevations, but much more than the gauge observations in areas with a sharp rise in elevations. Assessment of water budget shows that all SBPs yield severe negative water imbalance (greater than 50.0% of corresponding runoff) at most sub‐basins, while the ABDs can better close the water budget with water imbalance values between ±30.0% in most sub‐basins, respectively. Further analyses show that large relative differences between SBPs and ABDs mainly occur in areas with large topographical relief and in winter, which is likely because the ABDs outperform the SBPs in capturing orographic precipitation in complex terrain and solid precipitation in winter.