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Abstract

Solar radiation is one of the most important meteorological variables, as it is directly related to evaporation. Based on this variable, it is possible to develop models for estimating meteorological elements. However, when there is lack of data, estimates can be made using mathematical models. The objective of this paper was to perform the calibration and statistical performance evaluation of fifteen simplified models of global solar radiation estimation based on air temperature for 51 cities in the state of Minas Gerais, Brazil. The data were provided by the National Meteorological Institute using Automatic Meteorological Stations (EMA’s) located in the cities studied. The performance indexes used were the Coefficient of Determination for Linear Regression (R2), Root-Mean-Square Error and Mean Relative Error, and the Willmott d Index. Through the results obtained, it is possible to observe that the model with the best performance for the state of Minas Gerais was that of Donatelli and Campbell, because, based on the statistical analysis and ordering of the indexes, that is, the use of the position values (Vp) of the indicatives statistics to classify and define the best method for estimating global radiation, this model was the one that obtained the lowest Vp value.

Details

Title
Performance and estimation of solar radiation models in state of Minas Gerais, Brazil
Author
Cunha, Angélica Carvalho 1 ; Filho Luís Roberto Almeida Gabriel 2 ; Tanaka, Adriana Aki 3 ; Putti, Fernando Ferrari 2 

 José Rosário Vellano University (Unifenas), School of Agronomy, Alfenas, Brazil 
 São Paulo State University (UNESP), School of Sciences and Engineering, Tupã, Brazil (GRID:grid.410543.7) (ISNI:0000 0001 2188 478X) 
 Rural Federal University of Pernambuco (UFRPE), School of Agronomy, Recife, Brazil (GRID:grid.411227.3) (ISNI:0000 0001 0670 7996) 
Pages
603-622
Publication year
2021
Publication date
Mar 2021
Publisher
Springer Nature B.V.
ISSN
23636203
e-ISSN
23636211
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2488040658
Copyright
© Springer Nature Switzerland AG 2020.