Calibration and evaluation of estimation models of global solar radiation for the state of Goiás, Brazil

Abstract

Despite the importance of global solar radiation (Rs), data of this variable are not available for many regions of Brazil due to low density of surface weather stations, mainly in the North and Central-West regions. The estimation of this variable for regions with no Rs data are based on mathematical models, which has shown to be a viable alternative. The objective of this work was to contribute to these studies through the calibration and evaluation of three traditional models: Angstrom-Prescott (AP), Hargreaves (HAR), and Bristow-Campbell (BC), and, in addition, propose a new model (PMo) for estimation of Rs from multiple regression. The models were adjusted and evaluated for six locations in the state of Goiás (Central-West of Brazil), using meteorological data from 2008 to 2016. The local adjustment process improved the predictive capacity of the models AP (r2 = 0.74 and MAE = 1.68), BC (r2 = 0.62 and MAE = 2.34) and HAR (r2 = 0.55 and MAE = 2.32). However, according to the Nash index, unsatisfactory performances were found for the HAR model for the municipalities of Mineiros and Rio Verde, and for the BC model for Rio Verde. Despite requiring more meteorological variables, the PMo model estimated Rs adequately for the evaluated regions (r2 = 0.70 and MAE = 1.98), with superior performance to BC and HAR methods.