This paper proposes an operationally simple and easily general- izable methodology to incorporate climate change damage uncertainty into Integrated Assessment Models (IAMs). Uncertainty is transformed into a risk-premium, damage-correction, region-specific factor by extracting dam- age distribution means and variances from an ensemble of socio economic and climate change scenarios. This risk premium quantifies what society would be willing to pay to insure against the uncertainty of the damages, and it can be considered an add-up to the standard “average damage”. Our computations show the addition to be significant, but highly sensitive to the coefficient of relative risk aversion. Once the climate change damage func- tion incorporates the risk premium into the model, results show a substantial increase in both mitigation and adaptation, reflecting a more conservative at- titude by the social planner. Interestingly, adaptation is stimulated more than mitigation in the first half of the century, while the situation reverses after- wards. Over the century, the risk premium correction fosters more mitigation, which doubles, than adaptation, which rises by about 80%.