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

机译:基于GPM IMERG产品对中国长江盆地GPM IMERG产品的极端降水估算

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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.
机译:精确估计极端降水对于水文预测和洪水风险管理是重要的。最近的研究表明,卫星衍生的降水产品可以提供衡量数据的替代品,使得评估这些产品的准确性是必不可少的。本研究旨在定量评估全球降水测量(GPM)特派团在长江盆地GPM数据(GPM IMERG)的综合多卫星检索的应用。已经比较了超过第90百分位数和年度总降水的极端降水事件,并在2014-2017中用仪表观察检查。我们在2014年7月评估了GPM IMERG产品在极端降水事件中的表现。一般而言,GPM衍生的估计在月度尺度时与仪表数据相加得很好(Pearson的相关系数为0.8637),很可能是因为每月调整在GPM数据集中仪表。 GPM衍生和仪表估计之间的协议在日常时间尺度上不太明显。 IMERM产品在长江流域的上游区域进行了月度尺度,概率检测0.7739,Heidke的技能得分为0.5116。这表明卫星降水数据在高空区域中表现良好。 GPM数据产生了具有短介质复发间隔的极端降水事件的良好估计,但低估了所有返回时期。在极端降水事件期间,GPM产品在整个盆地中检测到沉淀过程,屈服于0.9137-0.9979的Pearson的相关系数。本研究表明,基于GPM的估计对于长江流域的极端降水事件仿真是有用的,并为该地区提供了一种新的洪水预测资源。

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