Climate stabilization efforts must integrate the actions of many socio-economic sectors to be successful in meeting climate stabilization goals, such as limiting atmospheric carbon dioxide (CO2) concentration to be less than double the pre-industrial levels. Estimates of the costs and benefits of stabilization policies are often informed by Integrated Assessment Models (IAMs) of the climate and the economy. These IAMs are highly non-linear with many parameters that abstract globally integrated characteristics of environmental and socio-economic systems. Diagnostic analyses of IAMs can aid in identifying the interdependencies and parametric controls of modeled stabilization policies. Here we report a comprehensive variance-based sensitivity analysis of a doubled-CO2 stabilization policy scenario generated by the globally-aggregated Dynamic Integrated model of Climate and the Economy (DICE). We find that neglecting uncertainties considerably underestimates damage and mitigation costs associated with a doubled-CO2 stabilization goal. More than ninety percent of the states-of-the-world (SOWs) sampled in our analysis exceed the damages and abatement costs calculated for the reference case neglecting uncertainties (1.2 trillion 2005 USD, with worst case costs exceeding $60 trillion). We attribute the variance in these costs to uncertainties in the model parameters relating to climate sensitivity, global participation in abatement, and the cost of lower emission energy sources.