Mathematical model for estimating daily average air temperature in Goiás, Brazil

• Autor(a) principal: Antonini, Jorge Cesar dos Anjos
• Data de Publicação: 2010
• Outros Autores: Silva, Euzebio Medrado da, Oliveira, Luiz Fernando Coutinho de, Sano, Edson Eyji
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Pesquisa Agropecuária Brasileira (Online)
• Texto Completo: https://seer.sct.embrapa.br/index.php/pab/article/view/1703
• topic: climatic modeling; multiple linear regression; Fourier series; modelagem climática; regressão linear múltipla; série de Fourier

The objective of this work was to develop a mathematical model to predict the daily average of air temperature in Goiás, Brazil. The model was developed through a linear combination of altitude, latitude, longitude, and the incomplete trigonometric Fourier series using the first three harmonic coefficients. The parameters of the model were adjusted with data from 21 weather stations, using multiple linear regression. The resulting correlation coefficient of the model was 0.91, and the Willmott's index of agreement was close to 1. The model was tested with data from three additional weather stations at different altitudes: high (1,100 m), medium (554 m), and low (431 m). The performance of the model was reasonable for both high and low altitude stations, and very good for the medium altitude station.