Motivated by critiques from Lenton (2011) and Weitzman (2009), this paper incorporates a series of uncertain catastrophic tipping points into the DICE integrated assessment model. Using the best available knowledge about climate tipping points and their economic impacts, ranges for probability of occurrence and magnitude of impact are inserted into DICE (Excel) and simulated using Monte Carlo methods (VBA). The results address two research questions: Does our existing knowledge of potential catastrophes generate a fat tailed distribution of economic output? Does incorporating these tipping points change the form of the general damage function under extreme scenarios? Evidence from these simulations, albeit computationally constrained, suggest “no” on both counts.