The primary focus of this study is to simulate, characterize and validate diurnal patterns of global solar radiation (GSR), temperature, relative humidity and wind speed from daily ground observations from 2017 to 2020 at Obafemi Awolowo University, Ile-Ife, Nigeria. The study also estimates diurnal variations of the meteorological parameters from three daily reanalyses (NASA, NCEP/NCAR and ERA5) and compares the results with hourly station observations (using performance evaluation indices such as mean bias, BIAS; percentage mean bias, PBIAS; root-mean-square-error, RMSE; Nash-Sutcliffe coefficient, NSE; normalised standard deviation, NSD and correlation coefficient, r). Results showed that the empirical models adequately captured the observed diurnal characteristics of the meteorological variables. Good estimates of diurnal patterns of GSR (BIAS = 6.77 Wm⁻²; RMSE =9.20 Wm⁻²; PBIAS = 5.68%; NSE =0.52; NSD = 0.62; r = 0.86), temperature (BIAS = -0.79°C; RMSE = 1.90°C; PBIAS = -2.43%; NSE =0.60; NSD =1.09; r = 0.86), and humidity (BIAS = 2.81%; RMSE =6.10%; PBIAS = 2.51%; NSE =0.43; NSD =0.83; r = 0.73) were obtained. Statistics suggested very strong model fits and close agreements with observations. Large and significant discrepancies (at p ≤ 0.05), however, were obtained for diurnal simulations of wind speed (BIAS = 0.28 ms⁻¹; RMSE =0.40 ms⁻¹; PBIAS = 9.79%; NSE = -0.10; NSD =1.36; r = 0.65). Furthermore, the model performances for hourly disaggregation of the parameters varied amongst the reanalyses. The findings provide good basis for generating sub-daily meteorological data resources with wide range of applications in hydrology, climate modelling, and plant growth simulation.

本研究的主要重点是模拟、表征和验证尼日利亚伊莱伊夫奥巴费米阿沃洛沃大学 2017 年至 2020 年每日地面观测的全球太阳辐射 (GSR)、温度、相对湿度和风速的昼夜模式。该研究还估计了三个每日再分析（NASA、NCEP/NCAR 和 ERA5）的气象参数的日变化，并将结果与​​每小时站观测值进行比较（使用性能评估指数，如平均偏差，BIAS；百分比平均偏差，PBIAS；根-均方误差，RMSE；Nash-Sutcliffe 系数，NSE；归一化标准差，NSD 和相关系数，r）。结果表明，经验模型充分捕捉了观测到的气象变量的日特征。对 GSR 昼夜模式的良好估计（BIAS = 6.77 Wm ^-2；RMSE =9.20 Wm ^-2；PBIAS = 5.68%；NSE =0.52；NSD = 0.62；r  = 0.86），温度（BIAS = -0.79°C；RMSE = 1.90°C；PBIAS = -2.43%；NSE =0.60；NSD =1.09；r  = 0.86）和湿度（BIAS = 2.81%；RMSE =6.10%；PBIAS = 2.51%；NSE =0.43；NSD =0.83；r  = 0.73)。统计数据表明模型非常适合并且与观察结果密切一致。 然而，对于风速的昼夜模拟（BIAS = 0.28 ms ^-1; RMSE =0.40 毫秒^-1；PBIAS = 9.79%；NSE = -0.10；NSD = 1.36；r  = 0.65)。此外，在重新分析中，每小时分解参数的模型性能各不相同。研究结果为生成次日气象数据资源提供了良好的基础，在水文、气候建模和植物生长模拟等领域具有广泛的应用。