This study evaluates the reliability of gridded rainfall products with fine spatial resolution using 29 gauges of a dense observation network in Niger. Four gridded datasets were considered, viz. the African Rainfall Climatology version 2.0 (ARC2), Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), Climate Prediction Center morphing technique (CMORPH) and Tropical Applications of Meteorology using Satellite data and ground-based observations (TAMSAT). The datasets were quantitatively compared to the gauge rainfall at different timescales and their rainfall detection skills were assessed using four validation metrics and three contingency indices, respectively. Furthermore, their potentials for trend analysis was assessed using a modified Mann-Kendall test; and finally, their capability of capturing damaging rainfalls was evaluated using data of five historical damaging rainfall amounts on a daily basis. The CMORPH product showed a good performance in detecting rainfall events and exhibited the best linear relationship with the gauge rainfall; however, it displayed high errors and relative bias (RB > 100%)—showing its inaccuracy in rainfall quantification. At daily, dekadal and monthly timescale, CHIRPS showed the lowest errors, followed by the ARC2 and TAMSAT, whereas ARC2 exhibited the lowest RB—between −12% and 22%. All of the four datasets were unable to unveil the significant trends found in ground observations and were inaccurate in sensing the depths of damaging rainfall amounts. The overall results revealed that the 3-hourly CMORPH dataset is a good sub-daily rainfall product—whereas daily, dekadal and monthly CHIRPS and ARC2 rainfalls have good potentials for hydro-climatological applications in Niger.

这项研究使用尼日尔的29个密集观测网络测量了具有精细空间分辨率的栅格化降雨产品的可靠性。考虑了四个网格化数据集，即。非洲降水气候学2.0版（ARC2），气候危害小组带站的红外降水（CHIRPS），气候预测中心变型技术（CMORPH）和使用卫星数据和地面观测的热带气象学应用（TAMSAT）。将数据集与不同时间尺度上的标准降雨量进行定量比较，并分别使用四个验证指标和三个应变指标评估了它们的降雨量检测技能。此外，使用改进的Mann-Kendall检验评估了它们进行趋势分析的潜力。最后，每天使用五个历史破坏性降雨量的数据评估其捕获破坏性降雨的能力。CMORPH产品在检测降雨事件方面表现出良好的性能，并且与雨量计的降雨量表现出最佳的线性关系；但是，它显示出很高的误差和相对偏差（RB> 100％），表明其在降雨量化中不准确。在每日，十进制和每月的时间尺度上，CHIRPS的误差最低，其次是ARC2和TAMSAT，而ARC2的RB最低，介于-12％和22％之间。这四个数据集都无法揭示地面观测中发现的重要趋势，并且无法准确检测出破坏性降雨量的深度。总体结果表明，每小时3小时的CMORPH数据集是次日降雨的良好产品，而每天，