  There is great uncertainty about future climate conditions and the
appropriate policies for managing interactions between the climate and the
economy. We develop a multidimensional computational model to examine how
uncertainties and risks in the economic and climate systems affect the social
cost of carbon (SCC)---that is, the present value of the marginal damage to
economic output caused by carbon emissions. The SCC is substantially increased
by economic and climate risks at both current and future times. Furthermore,
the SCC is itself a stochastic process with significant variation; for example,
the basic elements of risk incorporated into our model cause the SCC in 2100 to
be, with significant probability, ten times what it would be without those
risks. We have only imprecise information about what parameter values are best
for approximating reality. To deal with this parametric uncertainty we perform
extensive uncertainty quantification and show that these findings are robust
for a wide range of alternative specifications. More generally, this work shows
that large-scale computing can enable economists to examine substantially more
complex and realistic models for the purposes of policy analysis.
