Characterizing the features of precipitation for the Tibetan Plateau among four gridded datasets: Detection accuracy and spatio-temporal variabilities

Abstract

Evaluation of the gridded products in the detection accuracy and spatio-temporal variabilities of precipitation over the Tibetan Plateau (TP) is crucial to the research of climate change and extreme events. Previous evaluation works mainly focus on the amount of precipitation and the capability in event detection. This study presents a multi-scale evaluation of four gridded precipitation datasets with relatively high resolutions against stations data in the variabilities of precipitation over the TP from 2004 to 2017. The four gridded products are the fifth-generation ECMWF atmospheric reanalysis of the global climate (ERA5), the Global Land Data Assimilation Systems (GLDAS), the High Asian Refined Analysis version 2 (HAR v2), and the Tropical Rainfall Measuring Mission (TRMM). Results show that TRMM and GLDAS have good performances in the occurrence frequency of daily precipitation over the TP but cannot precisely detect the daily precipitation events. In contrast, ERA5 can well detect the daily precipitation events although it overestimates the frequency of daily precipitation. Regarding the longer time scales, ERA5 outperforms the other three gridded products. It succeeds in reproducing the interannual and decadal variabilities of precipitation and reflecting the spatio-temporal patterns of precipitation over the whole TP. Thus, this study highlights that there are different optimal choices of precipitation products for different study purposes, and demonstrates the potential capability of ERA5 for being used in the studies of climate and hydrological change over the TP.