Abstract
Remote sensing can be used to estimate meteorological data. Images of atmospheric variables obtained by the AIRS (Atmospheric Infrared Sounder) sensor aboard Aqua satellite, were used to estimate maximum, minimum and average daily air temperature in Federal District region – Brazil. Simple and multiple linear regression models were used with explanatory variables derived of diurnal and nocturnal AIRS data of surface temperature, relative air humidity and atmospheric water vapor over the period 2012-2016. The dependent variables were the maximum, minimum and daily average air temperature obtained by two meteorological stations located in the study region. The AIRS fittings showed R² = 0.62 and RMSE = 1.64 °C for the daily maximum air temperature, R² = 0.59 and RMSE = 1.50 °C for the minimum daily air temperature, and R² = 0.76 and RMSE = 1.45 °C for the daily average air temperature. Our results suggest that the AIRS data can yield accurate daily air temperature estimates for Distrito Federal – Brazil region.
Keywords:
Surface temperature; remote sensing; linear regression
