Conventional methods for Aerosol Optical Depth (AOD) retrieval are limited to areas with low reflectance such as water or vegetated areas because the satellite signals from the aerosols in these areas are more obvious than those in areas with higher reflectance such as urban and sandy areas. Land Surface Reflectance (LSR) is the key parameter that must be estimated accurately. Most current methods used to estimate AOD are applicable only in areas with low reflectance. It has historically been difficult to estimate the LSR for bright surfaces because of their complex structure and high reflectance. This paper provides a method for estimating LSR for AOD retrieval in bright areas, and the method is applied to AOD retrieval for Landsat 8 Operational Land Imager (OLI) images at 500 m spatial resolution. A LSR database was constructed with the MODerate-resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09A1), and this database was also used to estimate the LSR of Landsat 8 OLI images. The AOD retrieved from the Landsat 8 OLI images was validated using the AOD measurements from four AErosol RObotic NETwork (AERONET) stations located in areas with bright surfaces. The MODIS AOD product (MOD04) was also compared with the retrieved AOD. The results demonstrate that the AOD retrieved with the new algorithm is highly consistent with the AOD derived from ground measurements, and its precision is better than that of MOD04 AOD products over bright areas.

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.

Surface longwave net radiation (LWNR) is a vital component in the surface radiation budget. Major progress has been made in the estimations of clear-sky LWNR. However, the estimation of cloudy-sky LWNR remains a significant challenge. In this paper, a linear model (LM) and a multivariate adaptive regression spline (MARS) model were developed to estimate the cloudy-sky LWNR from a satellite-derived surface shortwave net radiation product. Spatially and temporally matched satellite data and ground-measured LWNR, which was collected at 24 sites from four networks, were used to build and validate the linear and MARS models. The effects of land cover, climate type, and surface elevation on the estimate of LWNR were also analyzed. The MARS model, incorporating the normalized difference vegetation index (NDVI) and surface elevation (H) as the inputs, had the best performance. The determination coefficient, BIAS, and root mean square error (RMSE) were 0.51, 0.01 W/m², and 26.10 W/m², respectively. The developed model, when combined with freely distributed Global LAnd Surface Satellite (GLASS) products, showed promise for producing surface LWNR and all-sky surface net radiation.