Ultraviolet Erythemal Irradiance (UVER) under Different Sky Conditions in Burgos, Spain: Multilinear Regression and Artificial Neural Network Models

Abstract

Different strategies for modeling Global Horizontal UltraViolet Erythemal irradiance (G⁡H⁡U⁢V⁢E) based on meteorological parameters measured in Burgos (Spain) have been developed. The experimental campaign ran from September 2020 to June 2022. The selection of relevant variables for modeling was based on Pearson’s correlation coefficient. Multilinear Regression Model (M⁢L⁢R) and artificial neural network (A⁢N⁢N) techniques were employed to model G⁡H⁡U⁢V⁢E under different sky conditions (all skies, overcast, intermediate, and clear skies), classified according to the C⁢I⁢E standard on a 10 min basis. A⁢N⁢N models of G⁡H⁡U⁢V⁢E outperform those based on MLR according to the traditional statistical indices used in this study (R2, M⁢B⁢E, and n⁢R⁢M⁢S⁢E). Moreover, the work proposes a simple all-sky A⁢N⁢N model of G⁡H⁡U⁢V⁢E based on usually recorded variables at ground meteorological stations.