Estimation of daily global solar irradiance from the air temperature in the state of Paraná, Brazil

Global solar irradiance (GSI) is a fundamental source of energy on Earth. Despite its importance, sunshine or solar irradiance data are rarely available from weather stations. In the absence of available data, there are empirical methods that can be used to estimate solar irradiance. The objective of this study is to calibrate the parameters and to evaluate the performance of four empirical models of solar irradiance estimation (those of Chen, Hargreaves, Hunt, and Richardson) from air temperature data for eight localities in the state of Paraná, Brazil. Data were obtained from the Meteorological Database for Teaching and Research (BDMEP). For the comparison of means among the models, the Kruskal-Wallis non-parametric test was used. Dunn’s multiple comparison tests were used to analyze which models presented different means from the others. The performance of each model was assessed using the indices Pearson correlation coefficient (r), mean bias error (MBE), root mean square error (RMSE), Wilmott concordance index (d), performance index (c) and the Nash-Sutcliffe efficiency (NSE) coefficient. It was observed that the models proposed by Chen and Hunt presented the best performances in the estimation of GSI for the studied Paraná state localities, given that they yielded results which are closer to the observed historical data.