Global Land Surface Albedo Climatologies Derived from Eight Satellite Products and Three Decadal Albedo Trend Analysis

Surface albedo is one of the climate essential variables, which characterize the surface reflectivity of downward shortwave radiation. For several decades, long-term time series datasets of multiple global land surface albedo products have been generated from satellite observations. These datasets have been used as one of the key variables in climate change studies. This study aims to assess the surface albedo climatology and to analyze long-term albedo changes, from eight satellite-based datasets for the past three decades on a global basis. Our results show that climatological surface albedo datasets derived from satellite observations can reach a good agreement in general and thus can be used to validate, calibrate, and further improve surface albedo simulations and parameterizations in current climate models. However, the albedo products derived from the some coarse resolution datasets have large seasonal biases. Difference in winter zonal albedo at high latitudes can reach 0.4 among the eight satellite datasets. Satellite-based albedo datasets agree relatively well during the summer at high latitudes in both hemispheres. The fine-resolution datasets agree well with each other for all the land cover types in mid- to low latitudes; however, large spread was identified for their albedos at mid- to high latitudes over land covers with mixed snow and sparse vegetation. By analyzing the time series of satellite-based albedo products over the past three decades, albedo of the Northern Hemisphere was found to be decreasing in July, likely due to the shrinking snow cover. Meanwhile, albedo in January was found to be increasing, likely because of the expansion of snow cover in northern winter. However, to improve the albedo estimation at high latitudes, and ultimately the climate models used for long-term climate change studies, a still better understanding of differences between satellite-based albedo datasets is required.