## 4 Summary and Conclusions  
This paper proposes an algorithm that directly estimates surface albedo from TOA observations acquired by HJ satellites by incorporating a MODIS-based surface BRDF database into the radiative transfer simulations to correct the angular effects. Validation against ground measurements shows that the proposed algorithm is capable of producing accurate surface albedo over both snow-free and snow-covered surfaces with an RMSE of 0.030, which suggests the feasibility of using HJ data for medium-resolution surface albedo monitoring and coarse-resolution data evaluation. Both validations against ground measurements and MODIS albedo products indicate that the accuracy of albedo estimation improves with an increase in view zenith angle as a result of the large field-of-view of HJ sensors, which further demonstrates the unique advantage of HJ data in the albedo estimation compared with other medium-resolution sensors.  
Figure 9: Relationship between HJ white-sky albedo estimation accuracy compared with MODIS product and view zenith angle for forest samples: bias and RRMSE. RRMSE is calculated as the ratio of absolute difference in HJ albedo and MODIS albedo to MODIS albedo.  
Apart from the potential of using this algorithm for albedo monitoring over snow-covered surfaces, the uncertainties of snow-free albedo estimation from HJ data are slightly larger than those results from the Landsat data [22,23,26]. The limited spectral coverage of HJ sensors, its calibration accuracy, striping noise, and low SNR are likely the main factors causing the increased uncertainty in albedo estimation. In addition, the band conversion from MODIS to HJ data can lead to an error of 0.003-0.007. More efforts are needed to understand the pixel level difference between HJ albedo and MODIS products. Nevertheless, the inter-comparison of HJ albedo with MODIS product suggests that the proposed algorithm can still achieve a good accuracy in albedo estimation with an RMSE of 0.011-0.014 over a variety of land cover types even with the reduced spectral coverage and low SNR of HJ data.  
In order to further improve the surface albedo estimation, refining the radiometric calibration is a possible solution. Alternatively, a usage of multi-angular observations, provided by the short revisiting periods (<4 days) of HJ data, would also significantly reduce the uncertainties through sampling the BRDF [35], which, however, was not implemented in this study due to lack of enough HJ data.  
Based on the results using the wide-swath HJ data, we are confident that this approach can be revised and applied to other similar data sets, such as Landsat satellite series and the forthcoming Sentinel-2 satellites.  
This work was supported by the NASA grant NNX09 AN36G through the University of Maryland, College Park. We would like to thank the MODIS and HJ teams for maintaining the satellite data. Many thanks to the AmeriFlux PIs and SURFRAD teams for providing the ground measurements. We also thank the anonymous reviewers for their comments in improving the manuscript. We are grateful for the financial support from the University of Maryland Libraries Open Access Publishing Fund.  
The authors reviewed and provided valuable comments for the manuscript.  
The authors declare no conflict of interest.