Estimation of solar radiation using two-step method in Yangtze River basin in China

Solar radiation is the principal and fundamental energy for many physical, chemical and biological processes. Estimation of solar radiation from other measured meteorological variables offers an important alternative in the absence of availability of measured solar radiation data. In this paper, we validate and assess four commonly used air temperature-based models including the Hargreaves and Samani, Hargreaves, Bristow & Campbell and Chen model and a local regression model, developed using long-term data from 14 sites in Yangtze River basin in China. We present the two-step method to estimate solar radiation from the commonly measured air temperature. The model performance is evaluated using root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute bias error (MABE) and mean absolute percentage error (MAPE). Results show that the two-step method gives good performance and significantly outperforms the temperature-based models. The parameters determination equations of the two-step method are proposed to solve the difficult problem in parameter calibration at the site where no long-term observations of solar radiation and sunshine duration are available. It is found that the two-step method using the parameters determined by the proposed equations gives good performance, with the averaged R-2 of 0.881, RRMSE of 15.04% and MAPE of 12.67%. Therefore, the two-step method with the parameters determined by the proposed equations could be used to estimate solar radiation in Yangtze River basin. It is believed to be useful for the site where no measured solar radiation and sunshine duration data is available, whereas the air temperatures are common measured.