Accurate estimates of extreme precipitation events play an important role in climate change studies and natural disaster risk assessments. This study aimed to evaluate the capability of the China Meteorological Forcing Dataset (CMFD), Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), and Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) to detect the spatiotemporal patterns of extreme precipitation events over the Qinghai-Tibet Plateau (QTP) in China, from 1981 to 2014. Compared to the gauge-based precipitation dataset obtained from 101 stations across the region, 12 indices of extreme precipitation were employed and classified into three categories: fixed threshold, station-related threshold, and non-threshold indices. Correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), and Kling-Gupta efficiency (KGE), were used to assess the accuracy of extreme precipitation estimation; indices including probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) were adopted to evaluate the ability of gridded products' to detect rain occurrences. The results indicated that all three gridded datasets showed acceptable representation of the extreme precipitation events over the QTP. CMFD and APHRODITE tended to slightly underestimate extreme precipitation indices (except for consecutive wet days), whereas CHIRPS overestimated most indices. Overall, CMFD outperformed the other datasets for capturing the spatiotemporal pattern of most extreme precipitation indices over the QTP. Although CHIRPS had lower levels of accuracy, the generated data had a higher spatial resolution, and with correction, it may be considered for small-scale studies in future research.

积雪融水是高海拔地区河流的重要补给水源,但高海拔地区资料稀缺,水文模拟面临极大的挑战.本文基于中国区域地面气象要素驱动数据集提供的降水、气温资料,结合MODIS雪盖数据,以2004-2009年为率定期,2010-2015年为验证期,在年楚河流域构建SRM模型,并以气象站点的实测资料为参照,对比分析了中国区域高时空分辨率地面气象要素驱动数据集在年楚河流域的融雪径流模拟效果.结果表明:基于气象站点实测降水和温度的融雪径流模拟纳什效率系数在率定期和验证期分别为0.75和0.68;基于中国区域高时空分辨率地面气象要素驱动数据集的融雪径流模拟纳什效率系数在率定期和验证期分别为0.77和0.78,径流模拟效果有所提高. CMFD再分析数据集可为缺资料地区的水文模拟提供数据来源,对高寒地区的融雪径流模拟具有一定的参考价值.

积雪融水是高海拔地区河流的重要补给水源,但高海拔地区资料稀缺,水文模拟面临极大的挑战.本文基于中国区域地面气象要素驱动数据集提供的降水、气温资料,结合MODIS雪盖数据,以2004-2009年为率定期,2010-2015年为验证期,在年楚河流域构建SRM模型,并以气象站点的实测资料为参照,对比分析了中国区域高时空分辨率地面气象要素驱动数据集在年楚河流域的融雪径流模拟效果.结果表明:基于气象站点实测降水和温度的融雪径流模拟纳什效率系数在率定期和验证期分别为0.75和0.68;基于中国区域高时空分辨率地面气象要素驱动数据集的融雪径流模拟纳什效率系数在率定期和验证期分别为0.77和0.78,径流模拟效果有所提高. CMFD再分析数据集可为缺资料地区的水文模拟提供数据来源,对高寒地区的融雪径流模拟具有一定的参考价值.

积雪融水是高海拔地区河流的重要补给水源,但高海拔地区资料稀缺,水文模拟面临极大的挑战.本文基于中国区域地面气象要素驱动数据集提供的降水、气温资料,结合MODIS雪盖数据,以2004-2009年为率定期,2010-2015年为验证期,在年楚河流域构建SRM模型,并以气象站点的实测资料为参照,对比分析了中国区域高时空分辨率地面气象要素驱动数据集在年楚河流域的融雪径流模拟效果.结果表明:基于气象站点实测降水和温度的融雪径流模拟纳什效率系数在率定期和验证期分别为0.75和0.68;基于中国区域高时空分辨率地面气象要素驱动数据集的融雪径流模拟纳什效率系数在率定期和验证期分别为0.77和0.78,径流模拟效果有所提高. CMFD再分析数据集可为缺资料地区的水文模拟提供数据来源,对高寒地区的融雪径流模拟具有一定的参考价值.