5
Discussions, Conclusions, and Recommendations
The first part of this chapter summarizes the committee’s conclusions and presents its recommendation on the first two questions covered in this first phase of the study. The second part of this chapter introduces concepts relevant to the committee’s third question and provides conclusions and recommendations on that question.
NEAR-TERM UPDATES TO CLIMATE SYSTEM MODELING IN SCC ESTIMATION
The first two charge questions direct the committee to consider near-term updates to the social cost of carbon (SCC). Specifically, the committee considered whether a near-term update is warranted on the basis of recent evidence regarding the sensitivity of temperature change to carbon emissions. The basic issues are the technical merits and challenges of a narrowly focused update to the SCC estimates and whether the Interagency Working Group on the Social Cost of Carbon (IWG) should conduct a near-term update of the SCC prior to receiving recommendations related to a more comprehensive update (Phase 2 of the committee’s study).
In its analysis, the committee considered the criteria outlined in Chapter 1, including
- the accuracy and characterization of uncertainty of climate system modeling (e.g., assessing whether a near-term update would necessarily improve the representation of the response of temperature change to emissions relative to more complete, state-of-the-art models of the climate system);
- overall SCC reliability;
- alternative options for climate system representation; and
- whether there is sufficient benefit to warrant investing limited available resources in conducting a near-term update to the SCC estimates, relative to investing those resources in lasting improvements to the methods and science underlying the SCC.
CONCLUSION 1 The equilibrium climate sensitivity (ECS) is only one parameter affecting the social cost of carbon (SCC). Each of the three SCC integrated assessment models also embodies a different representation of the climate system and its underlying uncertainties, including relationships and parameters beyond the ECS. Therefore, updating the ECS alone within the current SCC framework may not significantly improve the estimates.
CONCLUSION 2 The relationship between CO2 emissions and global mean surface temperature can be summarized by four metrics: equilibrium climate sensitivity (ECS), transient climate response, transient climate response to emissions, and the initial pulse-adjustment timescale. ECS is less relevant than the other three metrics in characterizing the climate system response on timescales of less than a century. As a long-term, equilibrium metric, ECS alone does not provide an adequate summary of the relationship between CO2 emissions and global mean surface temperature for calculating the social cost of carbon (SCC). Therefore, simply
updating the distribution of ECS without assessing the impact on these other metrics may not result in an improved estimate of the SCC.
RECOMMENDATION 1 The committee recommends against a near-term update to the social cost of carbon based simply on a recalibration of the probability distribution of the equilibrium climate sensitivity (ECS) to reflect the recent consensus statement in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Consequently, the committee also recommends against a near-term change in the distributional form of the ECS.
Rather than updating the ECS in the current framework, the IWG could undertake efforts to adopt or develop a common “module” that represents the relationship between CO2 emissions and global mean surface temperature change, its uncertainty, and its profile over time. If the IWG pursues such an effort, the following criteria would provide a more robust alternative to assessing the link between CO2 emissions to temperature change than ECS alone:
- The module’s behavior should be consistent with the best available scientific understanding of the relationship between emissions and temperature change, its pattern over time, and its uncertainty. Specifically, the module should be assessed on the basis of both its response to a pulse of emissions and its response to long-term forcing trajectories (specifically, trajectories designed to assess transient climate response and transient climate response to emissions, as well as high- and low-emissions baseline trajectories). Given the degree of assessment they face, including consistency with observational data, the IPCC-class Earth system models provide a reference for evaluating the central projections of a climate module.
- The proposed module should strive for simplicity and transparency so that the central tendency and range of uncertainty in its behavior are readily understood, are reproducible, and are amenable to continuous improvement over time through the incorporation of evolving scientific evidence.
- The possible implications of the choice of a common climate module for the assessment of impacts of other, non-CO2 greenhouse gases should also be considered.
NEAR-TERM ENHANCEMENT OF THE QUALITATIVE CHARACTERIZATION OF SCC UNCERTAINTY TO INCREASE TRANSPARENCY
The third charge question directs the committee to consider ways to enhance the qualitative characterization of uncertainties associated with the current SCC estimates in the near term to increase the transparency associated with using these estimates in regulatory impact analyses.
To be well defined, the SCC must be conditioned on certain variables, for example, the year in which the change in emissions is assumed to occur. Parameters that may require policy or value judgments must also be specified: these may concern how effects across people are aggregated, including across time, across different income levels, and over political jurisdictions. The SCC may be presented on the basis of different assumed values for such parameters, but it is generally inappropriate to take averages across such values because the variation does not reflect—or does not only reflect—uncertainty. For practical regulatory purposes, for example, it is necessary to present SCC estimates conditional on alternative discount rates in order to allow
those SCC estimates to be combined with other cost and benefit estimates that use different discount rates.
The SCC depends on a number of inputs that are uncertain. Some are aspects of the natural world, such as the sensitivity of temperature change to emissions and how it evolves over time. Others are consequences of current and future human behavior, such as population growth, economic growth, and the trajectory of global greenhouse gas emissions. For regulatory decision making, it is at least conceptually possible to describe the uncertainty of these inputs in SCC calculations using probability distributions. Ideally, joint probability distributions could be defined for all of the uncertain inputs to an SCC-IAM, and the impact of uncertainty on the SCC could be evaluated using Monte Carlo analysis or a related approach.
One reason for modeling uncertainty is related to nonlinearities. If the SCC calculation involves nonlinearities over the range of uncertain parameters, the average value of the SCC computed from random draws of these uncertain inputs may not be the same as the single SCC computed from the average parameter values. The implications of such nonlinearities may be difficult to know a priori, suggesting it is best to compute the SCC from random draws of uncertain inputs.
It is also important to model uncertainty in order to provide a range of plausible estimates for cost-benefit analysis. The U.S. Office of Budget and Management (OMB) Circular A-4 requests a formal quantitative analysis of uncertain costs and benefits for major rules with effects of $1 billion or more. Given the consequences of the presence of CO2 emissions across many government rulemakings, it is important to address this need.
Handling of Uncertainty in IWG Analysis
In constructing the SCC, the IWG treated some parameters of the climate system and damage functions as uncertain and random and represented these parameters using probability distributions. A common distribution, using a distributional form developed by Roe and Baker (2007), was used to represent the ECS in each of the three SCC-IAMs: the Dynamic Integrated Climate-Economy Model (DICE), the Policy Analysis of the Greenhouse Effect (PAGE), and the Climate Framework for Uncertainty, Negotiation and Distribution (FUND). In addition, 11 climate system parameters in FUND and 10 in PAGE were also represented by probability distributions, as were 50 parameters in FUND’s damage model and 46 in PAGE’s damage model (see Chapter 2 for an overview of these models). Socioeconomic and emissions uncertainty was also considered through five alternative scenarios. In calculating the SCC, each SCC-IAM was run by taking 10,000 draws from the relevant probability distributions and calculating the SCC for each draw, conditional on a socioeconomic and emissions scenario and discount rate.
CONCLUSION 3 The Interagency Working Group on the Social Cost of Carbon (SCC) technical support document explicitly describes the factors on which the SCC is conditioned, such as the year emissions occur and the discount rate and also makes explicit the sources of distributions for various inputs. However, it does not detail all sources of model-specific uncertainty in the social cost of carbon integrated assessment models.
RECOMMENDATION 2 When presenting the social cost of carbon (SCC) estimates, the Interagency Working Group (IWG) on the SCC should continue to make explicit the sources of uncertainty. The IWG should also enhance its efforts to describe uncertainty by adding an appendix to the technical support document that
describes the uncertain parameters in the Climate Framework for Uncertainty, Negotiation and Distribution and Policy Analysis of the Greenhouse Effect models.
CONCLUSION 4 Multiple runs from three models provide a frequency distribution of the social cost of carbon (SCC) estimates based on five socioeconomic-emissions scenarios, three discount rates, draws from the equilibrium climate sensitivity distribution, and other model-specific uncertain parameters. This set of estimates does not yield a probability distribution that fully characterizes uncertainty about the SCC.
Sources of Uncertainty Omitted from the IWG Analysis
The committee notes that none of the three SCC-IAMs (nor any others of which the committee is aware) are sufficiently comprehensive to include all of the uncertainties in the inputs that are likely to be important in calculating the SCC. Moreover, explicit distributions for some important inputs (e.g., emission scenarios, economic growth, and population) have not been developed by the IWG for use in estimating the SCC. Factors omitted or not adequately captured by the analysis need to be better characterized. In addition, a single unifying discussion of captured and omitted uncertainty is needed. There is, however, no section of the IWG’s technical support documents that contain a unified discussion of this topic.
RECOMMENDATION 3 The Interagency Working Group on the Social Cost of Carbon (IWG) should expand its discussion of the sources of uncertainty in inputs used to estimate the social cost of carbon (SCC), when presenting uncertainty in the SCC estimates. The IWG should include a section entitled “Treatment of Uncertainty” in each technical support document updating the SCC. This section should discuss various types of uncertainty and how they were handled in estimating the SCC, as well as sources of uncertainty that are not captured in current SCC estimates.
The uncertainties discussed in this section would include the uncertain parameters unique to each of the models, uncertainty about climate change impacts and their valuation, and the risk of potential catastrophic outcomes. The section would also discuss the implicit, equal weight placed on the three IAMs and five socioeconomic scenarios in computing an average SCC, the possible alternatives of unequal weights or alternative models and scenarios, and the motivation for the chosen approach. The executive summary of the technical support document and individual regulatory impact analyses that use the SCC might usefully provide a summary of this discussion.
Reporting of Results
In the executive summaries of the IWG’s technical support documents, the presentation of SCC estimates and the description of the uncertainty underlying them are brief. For each year of interest, four summary estimates of the SCC are shown (see Table 2-3, in Chapter 2): the average SCC for 2.5, 3, and 5 percent discount rates, as well as the 95th percentile for a 3 percent
discount rate.27 Thus, the only range of SCC estimates presented in the executive summary of the technical support documents is the range based on discount rates, together with the 95th percentile of the SCC based on a 3 percent discount rate. A more complete characterization of uncertainty would include other sources of variability in the SCC, for each discount rate, and would include both high and low values. These values could be used in sensitivity analyses in regulatory impact analyses.
CONCLUSION 5 It is important to continue to separate the impact of the discount rate on the social cost of carbon from the impact of other sources of variability. A balanced presentation of uncertainty includes both low and high values conditioned on each discount rate.
RECOMMENDATION 4 The executive summary of each technical support document should provide guidance concerning interpretation of reported social cost of carbon (SCC) estimates for cost-benefit analysis. In particular, the guidance should indicate that SCC estimates conditioned on a particular discount rate should be combined with other cost and benefit estimates conditioned on consistent discount rates, when they are used together in a particular analysis.
The guidance should also indicate that when uncertainty ranges are presented in an analysis, those ranges should include uncertainty derived from the frequency distribution of SCC estimates. To facilitate such inclusion, the executive summary of the technical support document should present symmetric high and low values from the frequency distribution of SCC estimates with equal prominence, conditional on each assumed discount rate.
One approach to the implementation of this recommendation would be to present in the executive summary a table similar to Table 5-1 below which would show high and low estimates of the SCC, as well as the average estimate, for each discount rate. The executive summary could also display the frequency distribution of SCC estimates as in Figure 5-1, with separate graphs for each discount rate. Separating the presentation of frequency distributions will encourage careful attention to the special role of discount rates on the basis of the regulatory context and the need to combine the SCC with other cost and benefit estimates. Also, the IWG could identify a high percentile (e.g., 90th, 95th) and corresponding low percentile (e.g., 10th, 5th) of the SCC frequency distributions on each graph. This approach would define a usable uncertainty range for the regulatory impact analysis for each discount rate.
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27The most recent IWG technical support document states (Interagency Working Group on the Social Cost of Carbon, 2015, p. 2): “Three values are based on the average SCC from three integrated assessment models (SCC-IAMs), at discount rates of 2.5, 3, and 5 percent. The fourth value, which represents the 95th percentile SCC estimate across all three models at a 3 percent discount rate, is included to represent higher-than-expected impacts from temperature change further out in the tails of the SCC distribution.”
TABLE 5-1: An Example of a Table of SCC Estimates
Discount Rate | |||||||||
Year | 5.00% | 3.00% | 2.50% | ||||||
Low | Avg. | High | Low | Avg. | High | Low | Avg. | High | |
2020 | -- | -- | -- | -- | -- | -- | -- | -- | -- |
2025 | -- | -- | -- | -- | -- | -- | -- | ||
… | -- | -- | |||||||
2050 | -- | -- | -- | -- | -- | -- | -- | -- | -- |