Solar radiation estimated from empirical models for the north of Minas Gerais, Brazil
DOI:
https://doi.org/10.14393/BJ-v32n1a2016-26169Keywords:
agrometeorology, solar radiationAbstract
Estimating daily solar radiation (Rs) provides an important alternative in situations where it cannot be measured by conventional pyranometers. This study used meteorological data from nine cities in the north of the Minas Gerais state, Brazil, for the period from 2008 to 2010 with the aim of evaluate the accuracy and applicability of some simple models to help regions where Rs is impossible to be measured. Five models were evaluated for their estimates of Rs based on simple available data. For each city studied, the equations were previously calibrated. Meteorologically based empirical models to estimate daily global solar radiation are an appropriate tool if the parameters can be calibrated for different locations. These models have the advantage of using meteorological data, which are commonly available. Based on the overall results, we conclude that the accuracy of estimation by available meteorological data is acceptable and comparable with the accuracy of classical models. Considering the greater availability of air temperature data and application in studies that do not require great accuracy in estimating Rs, all models were adequate for use. The accuracy of Rs was only slightly improved by adding rainfall records as input variable. Therefore, in the region studied, the choice of simpler models, having as input the daily maximum and minimum air temperature would not imply large error in the estimates. For most sites, Bristow and Campbell model had the best estimate of Rs with a RMSE of 2.69 MJ m-2 and R2= 0.69, with the possibility to calibrate with available temperature data, becoming a practical and reliable model. Hargraves model should be avoided due to its lower performance compared to the other models applied.
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Copyright (c) 2016 Valdiney José da Silva, Fábio Janoni Carvalho, Claúdio Ricardo da Silva, Roberto Terumi Atarassi, Javier Almorox
This work is licensed under a Creative Commons Attribution 4.0 International License.