# Publications by Year: 2018

Potentially Large Equilibrium Climate Sensitivity Tail Uncertainty. Economics Letters [Internet]. 2018;168 :144-146. Publisher's VersionAbstract wagner_weitzman_econletters_2018.pdf

. 2018

Wagner G, Weitzman ML. Potentially Large Equilibrium Climate Sensitivity Tail Uncertainty. Economics Letters [Internet]. 2018;168 :144-146. Publisher's VersionAbstract

Equilibrium climate sensitivity (ECS), the link between concentrations of greenhouse gases in the atmosphere and eventual global average tempera- tures, has been persistently and perhaps deeply uncertain. Its ‘likely’ range has been approximately between 1.5 and 4.5 degrees Centigrade for almost 40 years (Wagner and Weitzman, 2015). Moreover, Roe and Baker (2007), Weitzman (2009), and others have argued that its right-hand tail may be long, ‘fat’ even. Enter Cox et al. (2018), who use an ‘emergent constraint’ approach to characterize the probability distribution of ECS as having a cen- tral or best estimate of 2.8◦C with a 66% confidence interval of 2.2-3.4 ◦C. This implies, by their calculations, that the probability of ECS exceeding 4.5◦C is less than 1%. They characterize such kind of result as “renewing hope that we may yet be able to avoid global warming exceeding 2[◦C]”. We share the desire for less uncertainty around ECS (Weitzman, 2011; Wagner and Weitzman, 2015). However, we are afraid that the upper-tail emergent constraint on ECS islargely a function of the assumed normal error terms in the regression analysis. We do not attemptto evaluate Cox et al. (2018)’s physical modeling (aside from the normality assumption), leaving that task to physical scientists. We take Cox et al. (2018)’s 66% confidence interval as given and explore the implications of applying alternative probability distri- butions. We find, for example, that moving from a normal to a log-normal distribution, while giving identical probabilities for being in the 2.2-3.4◦C range, increases the probability of exceeding 4.5◦C by over five times. Using instead a fat-tailed Pareto distribution, an admittedly extreme case, increases the probability by over forty times.

**Keywords:** climate change, climate sensitivity, fat tails

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