Impacts of Topography on Daily Mean Albedo Estimation Over Snow-Free Rugged Terrain

Abstract

Daily mean albedo is a critical variable in surface energy budget and climate change studies. Currently, satellite-based daily mean albedo is typically estimated from the diurnal variation of albedo, derived from multiangle reflectance observations using a bidirectional reflectance distribution function (BRDF) kernel-driven model. However, this model assumes flat terrain and neglects topographic effects. This study evaluates the estimation errors of daily mean albedo derived from the BRDF kernel-driven model over rugged terrain. Experiments were conducted for rugged terrains with different mean slopes (10°, 20°, and 30°) and aspects (north and west) at spatial scales of 500 m and 1 km, using the large-scale remote sensing data and the image simulation framework (LESS) model. The results demonstrate that topography significantly influences the daily mean albedo derived from the BRDF kernel-driven model, with the largest relative error exceeding 50%. The estimation error increases as the slope of the terrain becomes steeper and is also strongly influenced by the aspect of the terrain. When the solar azimuth angle aligns with the aspect of the rugged terrain, the estimation error becomes particularly pronounced. These findings highlight the necessity of accounting for topographic effects when estimating daily mean albedo.