Open AccessModelling parametrization to estimate atmospheric long wave radiation in the Northern Mato Grosso, Brazil
Author(s) -
Carlos Alexandre Santos Querino,
Marcelo Sacardi Biudes,
Nadja Gomes Machado,
Juliane Kayse Albuquerque da Silva Querino,
Marcos Antônio Lima Moura,
Péricles Vale Alves
Publication year - 2020
Publication title -
ciência e natura
Language(s) - English
Resource type - Journals
eISSN - 2179-460X
pISSN - 0100-8307
DOI - 10.5902/2179460x41205
Subject(s) - parametrization (atmospheric modeling) , mean squared error , mathematics , coefficient of determination , mean absolute error , statistics , environmental science , atmospheric sciences , meteorology , climatology , geography , geology , physics , quantum mechanics , radiative transfer
The measures of Atmospheric Long Wave radiation are onerous, which brings the necessity to use alternative methods. Thus, the main aim of this paper was to test and parameterize some models that exist in the literature to estimate atmospheric long wave. The data were collected at Fazenda São Nicolau (2002 - 2003), located in Northwestern of Mato Grosso State. Data were processed hourly, monthly, and seasonal (dry and wet) besides clear and partly cloudy days on the average. The models of Swinbank, Idso Jackson, Idso, Prata and Duarte. were applied. The performance of the models was based on the mean error, square root of mean square error, absolute mean error, Pearson's coefficient and Willmott's coefficient. All models had presented high errors and low Peason’s and Willmott coefficients. After parameterizing, all models reduced their errors and increased Pearson and Willmott’s coefficient. The models of Idso and Swinbank had presented better and worse performance, respectively. It was not observed an increment on the performance of the model when classified according to cloudiness and seasonality. The Idso’s model had presented the lowest errors among the models. The model that had presented worst performance for any tested situation was Swinbank.