A New Method for Retrieving Daily Land Surface Albedo from VIIRS Data

Abstract

Unlike instantaneous albedo, daily albedo of land surfaces is currently not routinely generated from satellite data, although it is a key input parameter for calculating daily shortwave radiation budget. This paper presents a novel approach to directly retrieve daily mean values of land surface broadband blue-sky albedo from Visible Infrared Imaging Radiometer Suite clear-sky data of apparent reflectance, with the assumption that the atmospheric conditions of the satellite overpass time can represent their daily values. Training data were simulated by atmospheric radiative transfer models, with surface spectra and bidirectional reflectance distribution function data as inputs for four aerosol types and a range of aerosol loadings. Sensitivity analysis was conducted to study the effects of cloud coverage, aerosol, and surface types on retrieval accuracy. Two years of measurements at six Surface Radiation Budget Network and eight Greenland Climate Network stations were used for algorithm validation. Daily albedo of snow-free surfaces can be retrieved with very high accuracy. By excluding far off-nadir observations of snow surfaces, the overall accuracy of retrieving daily albedo has a bias of 0.003 and a root-mean-square error of 0.055.