Evaluation of CLDAS and GPM Precipitation Products over the Tibetan Plateau in Summer 2005–2021 Based on Hourly Rain Gauge Observations

Accurate, reliable, and high spatiotemporal resolution precipitation products are essential for precipitation research, hydrological simulation, disaster warning, and many other applications over the Tibetan Plateau (TP). The Global Precipitation Measurement (GPM) data are widely recognized as the most reliable satellite precipitation product for the TP. The China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) precipitation fusion dataset (CLDAS-Prcp), hereafter referred to as CLDAS, is a high-resolution, self-developed precipitation product in China with regional characteristics. Focusing on the TP, this study provides a long-term evaluation of CLDAS and GPM from various aspects, including characteristics on different timescales, diurnal variation, and elevation impacts, based on hourly rain gauge data in summer from 2005 to 2021. The results show that CLDAS and GPM are highly effective alternatives to the rain gauge records over the TP. They both perform well for precipitation amount and frequency on multiple timescales. CLDAS tends to overestimate precipitation amount and underestimate precipitation frequency over the TP. However, GPM tends to overestimate both precipitation amount and frequency. The difference between them mainly lies in the trace precipitation. CLDAS and GPM effectively capture rainfall events, but their performance decreases significantly as intensity increases. They both show better accuracy in diurnal variation of precipitation amount than frequency, and their performance tends to be superior during nighttime compared to the daytime. Nevertheless, there are some differences of the two against rain gauge observations in diurnal variation, especially in the phase of the diurnal variation. The performance of CLDAS and GPM varies at different elevations. They both have the best performance over 3000–3500 m. The elevation dependence of CLDAS is relatively minor, while GPM shows a stronger elevation dependence in terms of precipitation amount. GPM tends to overestimate the precipitation amount at lower elevations and underestimate it at higher elevations. CLDAS and GPM exhibit unique strengths and weaknesses; hence, the choice should be made according to the specific situation of application.