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Downward longwave radiation flux is an important variable for estimating net radiation, in order to investigate the surface energy budget and carry out climatic studies. The flux is usually estimated using empirical models based on the information of meteorological parameters such as relative humidity, surface and air temperature, and water vapor pressure. This paper presents the assessment of 11 widely used empirical models for estimating downward longwave radiation using a ground-based dataset acquired from January 2016 to December 2017 at Ile-Ife, a tropical city in Nigeria. The original Idso and Niemela et al. models performed better than other models with errors less than 5.0% when compared to measured values. The performances of all the models improved greatly after calibration. The Guest model, which gave low errors (MBE = 0.65 Wm–2, RMBE = 0.15%, RMSE = 9.38 Wm–2, RRMSE = 2.14%, MAE = 7.84 Wm–2, RMAE = 1.79%), performed best followed by the Dilley and O’Brien, Idso, Prata, Brutsaert, Garratt, Niemela et al., and Ångström models. The calibrated models presented in this study can be used to estimate the flux under cloudless sky conditions at Ile-Ife and at other places with similar meteorological conditions, where this flux is not measured due to technological problems and the high cost of purchasing and maintaining the needed sensors. The proposed model for estimating the flux showed better performance with lower statistical errors than all the existing empirical models tested, and conform greatly (R2 = 0.88) to the measured data.
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