LAUSR

Abstract Accurate global solar radiation (Rs) information is pivotal to the design and management of solar energy systems. Nevertheless, the expensive devices for Rs measurements make Rs data always unavailable in many regions around the world. The empirical models that predict Rs using other widely available climatic variables are feasible alternatives when Rs measurements are unavailable. However, the parameters of empirical models are site-specific and always need local calibration. In this context, the present study firstly developed a novel empirical model for accurately predicting Rs at the national scale in China, and then compared the new model with nineteen locally calibrated empirical models that have been largely reported in prior studies, including seven sunshine-based, nine temperature-based, and three complex empirical models. Daily Rs and other meteorological data during 1994–2016 from 96 weather stations in China were used to calibrate/develop and assess the models. The results showed that the newly proposed C4 model generally offered the best prediction accuracy among the models, with average MAE of 1.69 MJ m−2 d−1, RRMSE of 16.2% and NS of 0.895, which can be recommended as the optimal model for predicting Rs in China. The models reviewed and developed in this study improved the prediction accuracy of Rs, which can provide crucial information for the design and implementation of solar photovoltaic and thermal systems.