Evaluation of the latest satellite–gauge precipitation products and their hydrologic applications over the Huaihe River basin

• Published in: Journal of hydrology (Amsterdam) 2016-05, Vol.536, p.302-319
• Main Authors: Sun, Ruochen, Yuan, Huiling, Liu, Xiaoli, Jiang, Xiaoman
• Format: Article
• Language: English
• Subjects: Brackish; China; CMORPH; Computer simulation; Floods; Gages; Gauge adjustment; Gauges; Hydrologic simulation; Hydrology; Quantitative precipitation estimate (QPE); River basins; Satellite–gauge; TRMM; Water runoff
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2016.02.054

•Four latest satellite–gauge QPEs and their hydrologic applications are evaluated.•Gauge adjustment procedures and the gauge density greatly affect the QPE quality.•The error characteristics of rainfall are propagated into hydrologic simulations.•CMORPH CMA can serve as an alternative high quality QPE in China. Satellite–gauge quantitative precipitation estimate (QPE) products may reduce the errors in near real-time satellite precipitation estimates by combining rain gauge data, which provides great potential to hydrometeorological applications. This study aims to comprehensively evaluate four of the latest satellite–gauge QPEs, including NASA’s Tropical Rainfall Measuring Mission (TRMM) 3B42V7 product, NOAA’s Climate Prediction Center (CPC) MORPHing technique (CMORPH) bias-corrected product (CMORPH CRT), CMORPH satellite–gauge merged product (CMORPH BLD) and CMORPH satellite–gauge merged product developed at the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA) (CMORPH CMA). These four satellite–gauge QPEs are statistically evaluated over the Huaihe River basin during 2003–2012 and applied into the distributed Variable Infiltration Capacity (VIC) model to assess hydrologic utilities. Compared to the China Gauge-based Daily Precipitation Analysis (CGDPA) newly developed at CMA/NMIC, the four satellite–gauge QPEs generally depict the spatial distribution well, with the underestimation in the southern mountains and overestimation in the northern plain of the Huaihe River basin. Specifically, both TRMM and CMORPH CRT adopt simple gauge adjustment algorithms and exhibit relatively poor performance, with evidently deteriorated quality in winter. In contrast, the probability density function-optimal interpolation (PDF-OI) gauge adjustment procedure has been applied in CMORPH BLD and CMORPH CMA, resulting in higher quality and more stable performance. CMORPH CMA further benefits from a merged dense gauge observation network and outperforms the other QPEs with significant improvements in rainfall amount and spatial/temporal distributions. Due to the insufficient gauge observations in the merging process, CMORPH BLD features the similar error characteristics of CMORPH CRT with a positive bias of light precipitation and a negative bias of heavy precipitation, in contrast to the overall large overestimation by TRMM. The quality of QPEs directly impacts streamflow simulations, as the precipitation biases are propagated