High quality of long-term daily weather data is essential for simulating crop production and its variability. However, daily weather data with adequate duration and required quality are not available in many regions. This study has evaluated the suitability of AgMERRA (The Modern-Era Retrospective Analysis for Research and Applications) weather data for simulating rainfed wheat evapotranspiration (ETc) and yield. Daily AgMERRA were compared with corresponding observed weather data of 11 land stations across the northeast Iran, considering the different periods from 1980 to 2010. Cropwat and CSM-CERES-Wheat models were used to simulate ETc and yield of rainfed wheat, respectively. The comparison of daily AgMERRA with observations resulted in the highest correlation (r2 > 70%) and good agreement (d > 0.77 and NRMSE < 30%) between climate variables, except for daily wind speed and precipitation at all locations. However, when daily precipitation data were aggregated into 15-day periods, agreement and correlation improved. According to the monthly comparison, the largest bias between AgMERRA temperature and radiation with land observations was obtained from June to August (summer season). Results also indicated that the distribution of simulated ETc and yield using AgMERRA was within 10% of the simulated yield using observations at 73% and 100% of locations, respectively. The degree of variation of AgMERRA-simulated ETc and yield was very similar to the calculated coefficient of variation in simulated ETc and yield based on observations at 73% of locations. However, simulation of ETc and yield using AgMERRA for single years was more uncertain when compared with simulated ETc and yield based on observations for the same year. It is concluded that AgMERRA can provide a robust estimate of long-term average ETc and yield of wheat than the ETc and yield of a single year in regions that there is no long-term weather data available.

中文翻译：

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使用网格 AgMERRA 天气数据预测伊朗东北部雨养小麦蒸散量和产量的性能

高质量的长期每日天气数据对于模拟作物生产及其变异性至关重要。然而，在许多地区无法获得具有足够持续时间和所需质量的每日天气数据。本研究评估了 AgMERRA（研究和应用的现代时代回顾性分析）天气数据在模拟雨养小麦蒸散量 (ETc) 和产量方面的适用性。考虑到 1980 年至 2010 年的不同时期，每日 AgMERRA 与伊朗东北部 11 个陆地站的相应观测天气数据进行了比较。 Cropwat 和 CSM-CERES-Wheat 模型分别用于模拟 ETc 和雨育小麦的产量。每日 AgMERRA 与观察结果的比较导致最高的相关性 (r2 > 70%) 和良好的一致性 (d > 0.77 和 NRMSE < 30%) 之间的气候变量，除了所有地点的每日风速和降水。然而，当将每日降水数据汇总到 15 天期间时，一致性和相关性得到改善。根据月度比较，AgMERRA 温度和辐射与陆地观测的最大偏差是在 6 月至 8 月（夏季）。结果还表明，使用 AgMERRA 模拟的 ETc 分布和使用分别在 73% 和 100% 位置观察的模拟产量的 10% 以内。AgMERRA 模拟的 ETc 和产量的变化程度与基于 73% 位置的观察结果计算出的模拟 ETc 和产量的变异系数非常相似。然而，与基于同年观测的模拟 ETc 和产量相比，使用 AgMERRA 模拟单一年份的 ETc 和产量更不确定。结论是，在没有长期天气数据可用的地区，AgMERRA 可以提供对小麦长期平均 ETc 和产量的可靠估计，而不是单年的 ETc 和产量。