Global Science Report is a feature from the Center for the Study of Science, where we highlight one or two important new items in the scientific literature or the popular media. For broader and more technical perspectives, consult our monthly “Current Wisdom.”

As we mentioned in our last post, the federal Office of Management and Budget (OMB) is in the process of reviewing how the Obama administration calculates and uses the social cost of carbon (SCC). The SCC is a loosey-goosey computer model result that attempts to determine the present value of future damages that result from climate change caused by pernicious economic activity. Basically, it can be gamed to give any result you want.

We have filed a series of comments with the OMB outlining what is wrong with the current federal determination of the SCC used as the excuse for more carbon dioxide restrictions. There is so much wrong with the feds’ SCC, that we concluded that rather than just update it, the OMB ought to just chuck the whole concept of the social cost of carbon out the window and quickly close and lock it.

We have discussed many of the problems with the SCC before, and in our last post we described how the feds have turned the idea of a “social cost” on its head. In this installment, we describe a particularly egregious fault that exists in at least one of the prominent models used by the federal government to determine the SCC: The projections of future sea-level rise (a leading driver of future climate change-related damages) from the model are much higher than even the worst-case mainstream scientific thinking on the matter. This necessarily results in an SCC determination that is higher than the best science could possibly allow.

The text below, describing our finding, is adapted from our most recent set of comments to the OMB.

The Dynamic Integrated Climate-Economy (DICE) model, developed by Yale economist William Nordhaus (2010a), is what is termed an “integrated assessment model” or, IAM. An IAM is computer model which combines economics, climate change and feedbacks between the two to project how future societies are impacted by projected climate change and ultimately to determine the social cost of carbon (i.e., how much future damage, in today’s monetary terms, occurs for each unit emission of carbon (dioxide)).

In examining the climate change output from the DICE model, we found that it projects a degree of future sea level rise that far exceeds mainstream projections and are unsupported by the best available science. The sea level rise projections from more than half of the future scenarios examined exceed even the highest end of the projected sea level rise by the year 2300 as reported in the Fifth Assessment Report (AR5) of the UN’s Intergovernmental Panel on Climate Change (see Figure 1).

Figure 1. Projections of sea level rise from the DICE model (the arithmetic average of the 10,000 Monte Carlo runs from each scenario) for the five scenarios examined by the federal interagency working group (colored lines) compared with the range of sea level rise projections for the year 2300 given in the IPCC AR5 (represented by the vertical blue bar). (DICE data provided by Kevin Dayaratna and David Kreutzer of the Heritage Foundation)

Interestingly, Nordhaus (2010b) recognizes that the DICE sea level rise projections are outside the mainstream climate view as expressed by the IPCC:

“The RICE [DICE] model projection is in the middle of the pack of alternative specifications of the different Rahmstorf specifications. Table 1 shows the RICE, base Rahmstorf, and average Rahmstorf. Note that in all cases, these are significantly above the IPCC projections in AR4.” [emphasis added]

The justification given for the high sea-level rise projections in the DICE model (Nordhaus, 2010) is that they well-match the results of a “semi-empirical” methodology employed by Rahmstorf (2007) and Vermeer and Rahmstorf (2009).

However, as we have pointed out, recent science has proven the “semi-empirical” approach to projecting future sea level rise unreliable. For example, Gregory et al. (2012) examined the assumption used in the “semi-empirical” methods and found them to be unsubstantiated. Gregory et al (2012) specifically refer to the results of Rahmstorf (2007) and Vermeer and Rahmstorf (2009):

The implication of our closure of the [global mean sea level rise, GMSLR] budget is that a relationship between global climate change and the rate of GMSLR is weak or absent in the past. The lack of a strong relationship is consistent with the evidence from the tide-gauge datasets, whose authors find acceleration of GMSLR during the 20th century to be either insignificant or small. It also calls into question the basis of the semi-empirical methods for projecting GMSLR, which depend on calibrating a relationship between global climate change or radiative forcing and the rate of GMSLR from observational data (Rahmstorf, 2007; Vermeer and Rahmstorf, 2009; Jevrejeva et al., 2010).

In light of these findings, the justification for the very high sea-level rise projections produced by the DICE model is not acceptable.

Given the strong relationship between sea-level rise and future damage built into the DICE model, there can be no doubt that the SCC estimates from the DICE model are higher than the best science can allow and consequently, should not be accepted by the OMB as a reliable estimate of the social cost of carbon.

We did not investigate the sea-level rise projections from the other two IAMs employed in the federal SCC determination, but such an analysis must be carried out prior to extending any confidence in the values of the SCC resulting from those models—confidence that we demonstrate cannot be assigned to the DICE determinations of the social cost of carbon.

References:

Gregory, J., et al., 2012. Twentieth-century global-mean sea-level rise: is the whole greater than the sum of the parts? Journal of Climate, 26, 4476–4499, doi:10.1175/JCLI-D-12–00319

Nordhaus, W. 2010a. Economic aspects of global warming in a post-Copenhagen environment. Proceedings of the National Academy of Sciences 107(26): 11721–11726.

Nordhaus, W., 2010b. Projections of Sea Level Rise (SLR), http://www.econ.yale.edu/~nordhaus/homepage/documents/SLR_021910.pdf