Abstract: A total of eight clearsky and eight cloudysky parameterized models for estimating daytime downward longwave radiation were evaluated by using the meteorological data measured in the Changbai Mountains region, Northeast China. The results indicated that the Satterlund model performed better in estimating clearsky downward longwave radiation, and the bias (BIAS) and root mean square error (RMSE) were -23.34 and 28.55 W·m^-2, respectively. Although the coefficients were not significantly changed, the performance of Satterlund model was significantly improved after the locally calibrated, and the BIAS and RMSE decreased to -6.33 and 18.08 W·m^-2, respectively. Jacobs model was found to be best for modeling cloudysky downward longwave radiation and the BIAS and RMSE were 0.38 and 29.29 W·m^-2, respectively. Sensitivity analysis showed that the vapor pressure  was the most sensitive variable to the atmospheric emissivity and the temperature was not sensitive to it. The predicted results of the optimal model (clear and cloudysky) were consistent with the measured data, while the performance of these models was
affected by a sudden change of cloudy cover.