We build a novel stochastic dynamic regional integrated assessment model (IAM) of the climate and economic system including a number of important climate science elements that are missing in most IAMs. These elements are spatial heat transport from the Equator to the Poles, sea level rise, permafrost thaw and tipping points. We study optimal policies under cooperation and various degrees of competition between regions. We solve the problems over a 500-year horizon, and can do this because we employ efficient parallel dynamic programming methods with the support of Blue Waters. Our results suggest that when the elements of climate science which are accounted for in this paper are ignored, important policy variables such as the social cost of carbon and adaptation could be seriously biased.
