Refined Evaluation of Satellite Precipitation Products against Rain Gauge Observations along the Sichuan–Tibet Railway

Being constructed in southwestern China, the Sichuan–Tibet Railway (STR) travels across the eastern Tibetan Plateau where there is the most complex terrain and changeable weather in the world. Due to sparse ground-based observations over the Tibetan Plateau, precipitation products retrieved by remote sensing are more widely used; however, satellite-based precipitation products (SPPs) have not yet been strictly and systematically evaluated along the STR. This study aims to evaluate the performance of six SPPs by a series of metrics with available ground observations along the STR during 1998–2020. The six SPPs include the datasets derived from the Tropical Rainfall Measuring Mission (TRMM), Climate Prediction Center morphing technique (CMORPH), Global Precipitation Measurement (GPM), Global Satellite Mapping of Precipitation (GSMaP), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Fengyun-2 satellites precipitation estimate (FY2PRE). The results indicate that most of the SPPs can capture the precipitation characteristics on multiple timescales (monthly, daily, hourly, and diurnal cycle) as shown by the evaluated metrics. The probability density functions of the daily and hourly precipitation are also well represented by the SPPs, and 30 mm day⁻¹ and 16 mm h⁻¹ are identified as the daily and hourly thresholds of extreme precipitation events along the STR. The best SPP varies at different timescales: GPM and GSMaP are suitable for the monthly and daily scale, and FY2PRE and GPM are suited to the hourly scale. In general, GPM is relatively optimum on multiple timescales, and PERSIANN gives the worst performance. In addition, the SPPs perform worse at higher altitudes and for more intense precipitation. Overall, the results from this study are expected to provide essential reference for using the SPPs in meteorological services and disaster prevention in the STR construction and its future operation.