## 1 Introduction  
Reliable precipitation data and information are essential for understanding the water and energy cycles at both regional and global scales. However, accurate observation of precipitation is challenging in many remote regions of the world, such as the Tibetan Plateau (TP), due to sparse gauge networks and high spatial variability in precipitation [1, 2]. Satellite remote sensing has provided unprecedented precipitation information at a broader range of time and space scales, representing a significant contribution toward mapping global rainfall [3, 4, 5]. The Global Precipitation Measurement (GPM) mission is an important new program designed for global satellite precipitation estimation based on an international satellite constellation, which provides precipitation measurements from space at a spatial resolution of 0.1\({}^{\circ}\) x 0.1\({}^{\circ}\) and a half-hourly temporal resolution [6]. As the successor of the highly successful TRMM, the GPM mission provides four levels of products based on various algorithms. Level 1 data consist of geolocated, calibrated Dual-frequency Precipitation Radar (DPR) power, GPM Microwave Imager (GMI) brightness temperatures and intercalibrated brightness temperatures from partner radiometers at the Instantaneous Field Of View (IFOV); Level 2 products include geolocated, geophysical data and DPR reflectivity at the IFOV; Level 3 products consist of gridded time-space sampled geophysical data (e.g., precipitation rates) from the GPM Core sensors and partner radiometers; and Level 4 products include merged remotely-sensed and model information [6]. The Integrated Multi-satellite Retrievals for GPM mission (IMERG) was designed to create Level 3 products, a consistently calibrated global precipitation product with appropriate error and metadata information. The intercomparison of GPM with current satellite precipitation products and corresponding analysis across the TP is urgently needed. Efforts have been made to assess the suitability of satellite precipitation products over the TP [1; 7; 8; 9; 10; 11]. Previous studies found that the TMPA precipitation products outperform other satellite products (e.g., PERSIANN and CMORPH) across the plateau with lower errors and biases [9; 11]. The work in [9] showed that Global Precipitation Climatology Center (GPCC) gauges employed in the post-real-time TMPA system significantly improve the data accuracy. The work in [11] also confirmed that due to the monthly gauge adjustments, the research products of TMPA exhibit great hydrological potential at both monthly and daily scales over the TP. The work in [12] showed that the latest 3B42 Version 7 (3B42V7) clearly improves upon 3B42V6 over China in terms of daily mean precipitation. Here, the TMPA 3B42V7 product of the best performance is selected to compare to the GPM IMERG product. Despite the aforementioned studies, the newly-launched GPM satellite-based precipitation estimates warrant evaluation over the TP urgently because: (1) the similarity and differences of GPM Day-1 IMERG and TMPA 3B42V7 rainfall products should be investigated; (2) error analysis at the sub-daily scale is seldom performed; and (3) impacts of elevation and latitude on satellite rainfall estimates should be thoroughly explored. In the cold season (i.e., October to the next March), snowfall occurs frequently across the TP [13; 14]. Figures S1 and S2 also show snowfall regimes (including snowfall occurrence and amounts) retrieved from the IMERG product for the period October 2014-March 2015. Moreover, the automatic gauge network is generally switched off from October to the next March on the TP [15]. Thus, this study focuses on the error analysis and comprehensive assessments of GPM-era Day-1 IMERG and TRMM-era 3B42V7 products only in the warm season of 2014 over the TP. In order to understand solid precipitation regimes from IMERG on the TP, we perform an initial comparison with the field snowfall experiment at a site in the northeastern TP.