Abstract
Parameterization schemes (bulk formulae) are widely used to estimate all-sky surface downward longwave radiation (SDLR) due to the simple, readily available inputs and acceptable accuracy from local to regional scales. Seven widely used bulk formulae are evaluated using the ground measurements collected from 44 globally distributed flux measurement sites of five networks. The Bayesian model averaging (BMA) method is introduced to integrate multiple bulk formulae to obtain an estimate of cloudy-sky SDLR for the first time. The second multiple linear regression model of Carmona et al. (2014) performs the best, with BIAS, RMSE, and R2 of zero, 20.13 W·m−2 and 0.87, respectively. The BMA method can achieve balanced results that are close to the accuracy of the second multiple linear regression model of Carmona et al. (2014) and better than the average accuracy of seven bulk formulae, with BIAS, RMSE, and R2 of −1.08 W·m−2, 21.99 W·m−2 and 0.87, respectively. In addition, the bulk formula of Crawford and Duchon (1999) is preferred if there is insufficient data to calibrate the bulk formulae because it does not need local calibration and has an acceptable accuracy, with BIAS, RMSE, and R2 of 0.96 W·m−2, 26.58 W·m−2 and 0.82, respectively. The effects of climate type, land cover type, and surface elevation are also investigated to fully assess the applicability of each bulk formula and BMA. In general, there is no cloudy-sky bulk parametrization scheme that can be successfully applied everywhere.
Highlights
The radiation budget at the Earth’s surface is an important factor that determines land surface processes such as evapotranspiration, oceanic and atmospheric circulations [1,2]
Wang and Liang [20] applied the bulk formulae of Brunt [21] and Brutsaert [22] to estimate all-sky surface downward longwave radiation (SDLR) from global available meteorological observations to calculate the decadal variation in SDLR
The results showed that the best all-sky parameterization scheme for the five sites was Dilley and O’Brien’s A model [35] for clear-sky conditions combined with Sicart et al.’s A cloud correction [38], with a mean root mean square errors (RMSEs) of 26.3 W·m−2 and a mean MBE of zero
Summary
The radiation budget at the Earth’s surface is an important factor that determines land surface processes such as evapotranspiration, oceanic and atmospheric circulations [1,2]. SDLR can be accurately measured using ground-based instruments (e.g., pyrgeometer) This method is relatively expensive and sensitive and has spatially sparse coverage at the global scale [10]. Many researchers have used remote sensing and meteorological data to estimate high spatial-temporal SDLR [11,12,13,14], and many SDLR retrieval algorithms have been proposed. These algorithms can be classified into three categories: physical, parameterized, and statistical methods [15,16].
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