## 3 Results and Discussion  
### Validation against Ground Measurements  
Validations at AmeriFlux (Figure 5) and SURFRAD (Figure 6) sites were made using all available clear-sky HJ data and ground measurements. Results from both networks show negligible bias (within 0.003) and high determination coefficients (R\({}^{2}\): 0.88-0.98). The RMSEs are well constrained within 0.024-0.033 considering that this approach can also estimate snow-covered albedos. Combining results from the two networks the RMSE and R\({}^{2}\) are 0.030 and 0.947, respectively, for all the cases; while the RMSE and R\({}^{2}\) drop to 0.029 and 0.618, respectively, for snow-free cases. We also found that reducing the resolution of solar zenith angle in the look-up tables (Table 2) to 20\({}^{\circ}\) would only cause slightly worse results, with an increase in RMSEs of less than 0.002.  
The effects of surface BRDF on the remotely sensed signals were corrected through the incorporation of the BRDF database into the radiative transfer simulations. In Figure 7, the relative estimation errors seem to be randomly distributed with solar zenith angle and view zenith angle, which indicates that the estimation biases do not have any significant relationship with the geometries over various types of land covers. Figure 7 also shows that the absolute errors tend to decrease with the increase in view zenith angle, which demonstrates the potential of improving the albedo estimation from the wide swath HJ data; however, more data are needed before any solid conclusions can be made.  
Figure 4: RMSEs of using simulated HJ TOA reflectance (view zenith angle = 25\({}^{\circ}\)) to estimate surface broadband shortwave albedos: (**a**) black-sky albedo; and (**b**) white-sky albedo.  
Because surface albedo is strongly correlated with land cover type, it is therefore useful to further examine the results by breaking down the validation samples into different land covers, namely forest, grassland/cropland, and open shrub/woody savanna (Table 3). The forest sites observed low surface albedo and often high landscape homogeneity. Thus, surface albedo estimation achieved the lowest bias and RMSE at the forest sites among the three land cover classes. As the vegetation canopy fraction decreases, surface albedo gradually increases. Validation uncertainty of surface albedo can be affected by the increased surface heterogeneity as a result of different combinations of vegetation and background soil fractions. Albedo estimates at the grassland and cropland sites were found to have a slight negative bias of 0.018 compared with the ground measurements. At the same time, an overestimation of 0.022 in albedo is associated with the sparsely-vegetated sites. The validation results shown here agree well with the results of the 0.024 and 0.025 cases.  
Figure 5: Comparison of HJ shortwave albedo and ground measurements at 26 AmeriFlux sites (\(n=74\)). Different colors and shapes represent different sites.  
Figure 6: Comparison of HJ shortwave albedo and ground measurements at six SURFAD sites (\(n=49\)).  
the finding in an earlier study that focused on MODIS albedo products, which demonstrated the albedo overestimation at woody savanna sites and underestimation at grassland and cropland sites [37].