Reliable values of relative humidity are basic inputs for modelling in many disciplines and in the most disparate scientific fields. Unfortunately, humidity variables remain less focused than other meteorological parameters and generally suffer from considerable uncertainty mainly due to the fact that their observations are not widely available, fostering the use of the observations of other meteorological quantities to estimate them. The aim of this work is to assess the loss in daily maximum and minimum relative humidity accuracy when sampling interval becomes coarser than one hour. For this purpose, meteorological data from the ERA5 dataset, the most advanced reanalysis product released by the European Centre for Medium-Range Weather Forecasts (ECMWF), are used. Among the many advantages of ERA5 over the previous release ERA-Interim are the finer temporal resolution and data archived at the hourly time step. Near-surface relative humidity is derived using 1- and 3-hourly reanalysis data of 2-m temperature, 2-m dew-point temperature and surface pressure. Deviations from the actual values, as obtained from reference measures acquired at 15 minute intervals, are evaluated. Results show that the biases of the ERA5-based values are consistently reduced compared to its predecessor and that the performance of the calculated 1-hourly time resolution relative humidity data is almost equivalent to using observations. Reducing the sampling interval from three to one hour provides a significant improvement in data quality. The results indicate significant increases in errors in the estimates when the temporal resolution of the meteorological inputs becomes coarser than one hour, exceeding also the numerical and approximation errors due to simplifying assumptions in the theoretical and empirical formulas used. The positive impact of improving temporal resolution from ERA-Interim to ERA5 reanalysis is also quantified by the number of the correct relative humidity extremes increasing by 50%.

相对湿度的可靠值是许多学科和最不同的科学领域建模的基本输入。不幸的是，湿度变量仍然不如其他气象参数集中，并且通常受到相当大的不确定性的影响，这主要是因为它们的观测数据并不广泛可用，这促进了使用其他气象量的观测来估计它们。这项工作的目的是评估当采样间隔变得粗于一小时时每日最大和最小相对湿度精度的损失。为此，使用了来自欧洲中期天气预报中心 (ECMWF) 发布的最先进的再分析产品 ERA5 数据集的气象数据。ERA5 与​​之前版本 ERA-Interim 相比的众多优势包括更精细的时间分辨率和以每小时时间步长存档的数据。近地表相对湿度是使用 2 米温度、2 米露点温度和地表压力的 1 小时和 3 小时再分析数据得出的。评估与从以 15 分钟间隔获取的参考测量值获得的实际值的偏差。结果表明，与之前的版本相比，基于 ERA5 的值的偏差持续减少，并且计算出的 1 小时时间分辨率相对湿度数据的性能几乎等同于使用观测值。将采样间隔从三小时减少到一小时可显着提高数据质量。结果表明，当气象输入的时间分辨率变得粗于 1 小时时，估计误差显着增加，由于简化了所使用的理论和经验公式中的假设，也超过了数值和近似误差。将时间分辨率从 ERA-Interim 提高到 ERA5 再分析的积极影响也可以通过增加 50% 的正确相对湿度极端值的数量来量化。