In regional studies, reanalysis datasets can extend precipitation time series with insufficient observations. In the present study, the ERA5 precipitation dataset was compared to observational datasets from meteorological stations in nine different precipitation zones of Iran (0.125° × 0.125° grid box) for the period 2000–2018, and measurement criteria and skill detection criteria were applied to analyze the datasets. The results of the daily analysis revealed that the correlation between ERA5 and observed precipitation were larger than 0.5 at 90% of stations. Also, The daily standard relative bias indicated that precipitation was overestimated in zone 6. As detection criteria, the frequency bias index (FBI) and proportion correct (PC) showed that the ERA5 data could capture daily precipitation events. Correlation confidence comparisons between the ERA5 and observational time series at daily, monthly, and seasonal scales revealed that the correlation confidence was higher at monthly and seasonal scales. The standard relative bias results at monthly and seasonal scales followed the daily relative bias results, and most of the ERA5 underestimations during the summer belonged to zone 1 in the coastal area of the Caspian Sea with convective precipitation. In addition, some complex mountainous regions were associated with overestimated precipitation, especially in northwest Iran (zone 6) in different time scales.

中文翻译：

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2000-2018年伊朗基于不同时间尺度的ERA5降水精度评估

在区域研究中，再分析数据集可以在观测不足的情况下扩展降水时间序列。在本研究中，将 ERA5 降水数据集与伊朗 9 个不同降水区（0.125°×0.125° 网格框）2000-2018 年期间气象站的观测数据集进行比较，并将测量标准和技能检测标准应用于分析数据集。日分析结果表明，ERA5与观测降水的相关性在90%的站点上均大于0.5。此外，日标准相对偏差表明6区降水被高估。作为检测标准，频率偏差指数（FBI）和比例校正（PC）表明ERA5数据可以捕捉每日降水事件。ERA5 和观测时间序列在日、月和季节尺度上的相关置信度比较显示，在月度和季节尺度上的相关置信度更高。月和季节尺度的标准相对偏差结果遵循日相对偏差结果，夏季的ERA5低估大部分属于对流降水的里海沿岸地区1区。此外，一些复杂的山区与高估的降水有关，特别是在不同时间尺度的伊朗西北部（6区）。月和季节尺度的标准相对偏差结果遵循日相对偏差结果，夏季的ERA5低估大部分属于对流降水的里海沿岸地区1区。此外，一些复杂的山区与高估的降水有关，特别是在不同时间尺度的伊朗西北部（6区）。月和季节尺度的标准相对偏差结果遵循日相对偏差结果，夏季的ERA5低估大部分属于对流降水的里海沿岸地区1区。此外，一些复杂的山区与高估的降水有关，特别是在不同时间尺度的伊朗西北部（6区）。