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Uncertainty over the consequences of unprecedented global warming is central to environmental insecurity. Global warming threatens to exacerbate all other ecological stresses and menaces human populations and economies. Despite scientific efforts, great uncertainties still pervade crucial aspects of the climate change process and its consequences. Yet integrated assessment models widely used to analyze climate policy options, such as the Nordhaus DICE model, establish that model outputs are highly sensitive to plausible alternative parameter values. This paper further explores uncertainties by substituting probability distributions for pre-determined values of key parameters in the DICE model. It then draws randomly from these probability distributions to implement a Monte Carlo analysis of policy outcomes, generating hundreds of policy simulations. An important finding is that the sacrifice in world consumption entailed in keeping the rise in global temperatures below two degrees centigrade would likely be negligible if emitting countries cooperate in adopting efficient mitigation policies. In other words, the cost of insurance against dangerous climate change is close to zero. Thus, the result of this analysis suggests that science and economics agree on keeping climate change below a level threatening serious damage.