Direct estimation of land surface albedo from VIIRS data: Algorithm improvement and preliminary validation

Abstract

AbstractLand surface albedo (LSA), part of the Visible Infrared Imaging Radiometer Suite (VIIRS) surface albedo environmental data record (EDR), is an essential variable regulating shortwave energy exchange between the land surface and the atmosphere. Two sub‐algorithms, the dark pixel sub‐algorithm (DPSA) and the bright pixel sub‐algorithm (BPSA), were proposed for retrieving LSA from VIIRS data. The BPSA estimates LSA directly from VIIRS top‐of‐atmosphere (TOA) reflectance through simulation of atmospheric radiative transfer. Several changes have been made to improve the BPSA since the deployment of VIIRS. A database of the Moderate Resolution Imaging Spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF) is collected and converted to bidirectional reflectance at VIIRS bands. The converted reflectance is then used as input to the atmospheric radiative transfer model to generate a look‐up table (LUT) of regression coefficients with consideration of surface BRDF. Before its implementation in the operational system, the new BPSA is tested on the local infrastructure. The incorporation of the surface BRDF improves the accuracy of LSA estimation and reduces the temporal variation of LSA over stable surfaces. VIIRS LSA retrievals agree well with the MODIS albedo products. Comparison with field measurements at seven Surface Radiation (SURFRAD) Network sites shows that VIIRS LSA retrieved from the LUT with surface BRDF has an R2 value of 0.80 and root mean square error of 0.049, better than MODIS albedo products. The VIIRS results have a slight negative bias of 0.004, whereas the MODIS albedo is underestimated with a larger negative bias of 0.026.