Previous research has shown that land cover change can have a large effect on local climate through biogeophysical effects like albedo. These effects, however, are typically ignored by Integrated Assessment Models (IAMs), which hold albedo forcing constant in the future. As a result, estimates of radiative forcing and temperature rise in IAMs will stray far from estimates by Earth System Models (ESMs) in scenarios with large land cover changes. We rectify this issue by using an ESM (the Community Earth System Model) to parameterize the albedo feedback in an IAM (the Global Change Assessment Model). Using the newly modified IAM, we examine the effect of including albedo in the forcing calculation on energy, agriculture, emissions, and the cost of mitigation. This work represents a collaboration between researchers working with high-resolution biogeophysical models and IAM researchers, who typically need to represent biophysical phenomena using scientifically accurate, yet computationally efficient methods. This parsimony permits the resulting coupled behavior to be assessed in the context of large ensemble calculations and uncertainty analysis.