Scientific workflow applied to cartographic modeling to spatializing global solar irradiation in the state of Rio de Janeiro through the Hargreaves-Samani method - Lima, Marciano da Costa (2022)
The availability of consistent global solar irradiance (Hg) data is restricted due to the low spatial density of stations that perform Hg measurements and/or degradation of meteorological observation networks. An alternative to this problem is the estimation of Hg, through empirical methods based on other meteorological elements obtained more frequently. Among these methods, the Hargreaves-Samani (1985) (HS) stands out for its simplicity and satisfactory performance in different climate conditions. This study aimed to evaluate the HS method for Hg spatialization in the State of Rio de Janeiro (Estado do Rio de Janeiro - ERJ), using data from air temperature extremes and monthly Hg from 17 automatic weather stations (EMA) of the Instituto Nacional de Meteorologia (INMET). For this, a workflow was developed based on regression models and cartographic modeling to spatialize Hg using the Hargreaves-Samani method. Spatialized Hg values were compared with data observed in the EMAs used, based on the coefficient of determination (r²), Willmott's concordance index (d), confidence index (c), and the root means square error (RQME). It was observed that the application of the method presented estimates with high precision (r² > 0.61) and accuracy (d > 0.78 and RQME > 1.02 MJ m-2 d-1) when seasonality was analyzed, but in its spatial analysis, the method showed lower precision (r² > 0.03) and accuracy (d > 0.53 and RQME > 0.55 MJ m-2 d-1). The proposed workflow presents satisfactory performance to represent the monthly Hg pattern in the ERJ.