Evaluating extreme precipitation estimations based on the GPM IMERG products over the Yangtze River Basin, China

Abstract

Accurate estimation of extreme precipitation is important for hydrological prediction and flood risk management. Recent research suggests that satellite-derived precipitation products can provide an alternative to gauged data, making it essential to evaluate the accuracy of these products. This study aimed to quantitatively evaluate the application of the Global Precipitation Measurement (GPM) mission’s Integrated Multi-satellite Retrievals of GPM data (GPM IMERG) over the Yangtze River Basin. Both extreme precipitation events exceeding the 90th percentile and annual total precipitation have been compared and examined with gauge observations for 2014–2017. We evaluated the performance of the GPM IMERG product during an extreme precipitation event in July 2014. In general, the GPM-derived estimates agreed well with the gauge data at monthly time scales (Pearson’s correlation coefficient of 0.8637), most likely because of monthly adjustment to gauges within the GPM dataset. The agreement between GPM-derived and gauge estimates was less pronounced at daily time scales. The IMERG product performed best in upstream areas of the Yangtze River Basin over monthly time scales, giving a probability of detection of 0.7739 and a Heidke’s Skill Score of 0.5116. This indicates that satellite precipitation data performed well in high-altitude regions. The GPM data produced a good estimation of extreme precipitation events with short–medium recurrence intervals but underestimated all return periods. During extreme precipitation events, the GPM product detected the precipitation process over the whole basin, yielding Pearson’s correlation coefficients of 0.9137–0.9979. This study shows that the GPM-based estimates are useful for extreme precipitation event simulation over the Yangtze River Basin and provide a new resource for flood forecasting in this region.