Abstract

The global solar radiation is an important meteorological parameter for understanding the biochemical processes in the environment. Their measurement is complex and requires a high cost of installation, operation and maintenance, but this can be estimated by empirical equations based primarily on their geolocation. However, the accuracy of the results obtained is not suitable for understanding the processes evaluated. The aim of this study was to establish a statistical correlation model for estimating global solar radiation from alternative meteorological parameter. The meteorological information was provided by the Institute of Hydrology, Meteorology and Environmental Studies of Colombia, which provided the measurement of solar radiation, temperature, relative humidity and sunshine of the day for a year. Simple regressions between variables and solar radiation were raised; and multiple regressions between the possible combinations of each variables and solar radiation. The results show a good statistical correlation between variables solar radiation, temperature and relative humidity and little relation to the hours of sunshine, where relative humidity has the higher correlation and therefore is the parameter that more influence has on the model. The multivariate models (R2 average 11.91%) have better fit than simple models (R2 average 5.66%). The best model is multivariate regression in which all variables were included (R2 of 13.75%) although not the simplest model estimation.