Impacts of Gauge Data Bias on the Performance Evaluation of Satellite-Based Precipitation Products in the Arid Region of Northwestern China

Abstract

It has been reported that systematic bias exists in gauge measurements, which are usually used as the evaluation benchmark, so it is crucial to investigate the impacts of gauge data bias on the evaluation of satellite precipitation products. Six satellite precipitation products (IMERG, CMORPH, GSMaP, PERSIANN, PERSIANN−CCS, and PDIR−Now) and gauge data are collected from 2003 to 2015 in the arid region of Northwestern China. A daily correction for precipitation biases from wind-induced undercatch, wetting loss, and trace error is made for gauge measurements. The changes in metrics, including four continuous and four categorical metrics, are calculated to illustrate how the gauge data bias impacts the evaluation of six satellite precipitation products. The results show the following: The overall performances of six satellite precipitation products are undervalued by the gauge bias. Compared to other satellite products, the performance of IMERG is the best, whether before or after bias correction. However, the performances of all six satellite products are still not good enough even after bias correction and need to be improved. The impacts of gauge bias on the evaluation of the satellite precipitation products also differ by subregion, season, satellite precipitation product, precipitation intensity, and precipitation phase. In conclusion, the impacts of the gauge bias on the performance assessment of satellite products are obvious over the study region, implying that bias correction for gauge measurements is needed to obtain an accurate understanding of the performance of satellite precipitation products if choosing the gauge data as the evaluation benchmark.