Evaluating Biases in Simulated Land Surface Albedo from CMIP5 Earth System Models

Abstract:

Land surface albedo is a critical parameter affecting the energy balance and near-surface climate. Here we use satellite data to evaluate simulated surface albedo in 37 models participating in the Coupled Model Intercomparison Project Phase 5. There is a systematic overestimation in simulated seasonal cycle of albedo with the highest bias over the Northern Hemisphere winter season. We partition the bias in surface albedo during snow-covered season into that in snow cover fraction (SCF) and albedo contrast (β₁). There is a widespread overestimation of β₁ due to simulated snow-covered albedo brighter than observed and negative biases in SCF are not always related to negative albedo biases, highlighting the need for a realistic representation of snow-covered albedo in models. Insolation weighting shows that spring albedo biases are of greater importance for climate and the removal of albedo biases is supposed to improve temperature simulations particularly over the regions with high elevation.