1 

## Technical Support Document: - Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis -

Under Executive Order 12866 -

Interagency Working Group on Social Cost of Carbon, United States Government

With participation by

Council of Economic Advisers Council on Environmental Quality Department of Agriculture Department of Commerce Department of Energy Department of Transportation Domestic Policy Council Environmental Protection Agency National Economic Council Office of Management and Budget Office of Science and Technology Policy Department of the Treasury

May 2013

Revised November 2013 See Appendix B for Details on Revision2 Executive Summary

Under Executive Order 12866, agencies are required, to the extent permitted by law, “to assess both the costs and the benefits of the intended regulation and, recognizing that some costs and benefits are difficult to quantify, propose or adopt a regulation only upon a reasoned determination that the benefits of the intended regulation justify its costs.” The purpose of the “social cost of carbon” (SCC) estimates presented here is to allow agencies to incorporate the social benefits of reducing carbon dioxide (CO 2 ) emissions int o cost

- benefit analyses of regulatory actions that impact cumulative global emissions. The SCC is an estimate of the monetized damages associated with an incremental increase in carbon emissions in a given year. It is intended to include (but is not limite d to) changes in net agricultural productivity, human health, property damages from increased flood risk, and the value of ecosystem services due to climate change.

The interagency process that developed the original U.S. government’s SCC estimates is desc ribed in the 2010 interagency technical support document (TSD) ( Interagency Working Group on Social Cost of
Carbon 2010 )

. Th rough that process th e interagency group selected four SCC values for use in regulatory analyses. Three values are based on the ave rage SCC from three integrated assessment
models (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

- t han

- expected impacts from temperature change further out in the tails of the SCC distribution.

While acknowledging the continued limitations of the approach taken by the interagency group in 2010,
this document provides an update of the SCC estimates based on new versions of each IAM (DICE, PAGE, and FUND)

. It does not revisit other interagency modeling decisions (e.g., with regard to the discount rate, reference case socioeconomic and emission scenarios, or equilibrium climate sensitivity )

. Improvements in the way damages are modeled are confined to those that have been incorporated into
the latest versions of the models by the developers themselves in the peer

- reviewed literature.

The SCC estimates using the updated versions of the models are higher than those reported in the 2010
TSD

. By way of comparison, the four 2020 SCC estimates reported in the 2010 TSD were $7, $26, $42 and $81 (2007$). The co rresponding four updated SCC estimates for 2020 are $12, $43, $ 6 4 , and $12 8 (2007$). The model updates that are relevant to the SCC estimates include: an explicit representation of sea level rise damages in the DICE and PAGE models ; updated adaptation assumptions, revisions to

ensure damage s are constrained by GDP, updated regional scali ng of damages

, and a revised treatment of potentially abrupt shifts in climate damages in the PAGE model ; an updated carbon cycle in the DICE
model ; and updated damage functions for sea level rise impacts, the agricultur al sector , and reduced space heating requirements , as well as changes to the transient response of temperature to the buildup
of GHG concentrations and the inclusion of indirect effects of methane emissions in the FUND model

. The SCC estimates vary by year, and the following table summar izes the revised SCC estimates from 2010 through 2050.3 Revised Social Cost of CO 2 , 2010

– 2050 (in 2007 dollars per metric ton of CO 2 )

Discount Rate 5 .0 % 3 .0 % 2.5% 3 .0 % Year Avg Avg Avg 95th 2010 11 3 2 5 1 8 9 2015 1 1 3 7 5 7 109 2020 12 43 6 4 12 8 2025 14 4 7 69 14 3 2030 16 52 7 5 159 2035 19 5 6 8 0 17 5 2040 21 6 1 8 6 19 1 2045 24 66 92 206 2050 2 6 71 9 7 22 04

I. Purpose

The purpose of this document is to update the schedule of social cost of carbon (SCC) estimates from the 2010 interagency technical support document (TSD) ( Interagency Working Group on Social Cost of
Carbon 2010 )

. 1 E.O. 13563 commits the Administration to regulatory decision making “based on the best
available science

. ” 2 Additionally, t he interagency group recommended in 201 0 that the SCC estimates be revisited on a regular basis or as model updates that reflect the growing body of scientific and economic knowledge become available

. 3 New versions of the three integrated assessment models used by the U.S. government to estima te the SCC ( DICE, FUND, and PAGE ) , are now available and have been published in the peer reviewed literature

. While acknowledging the continued limitations of the approach taken by the interagency group in 2010 (documented in the original 2010 TSD) , this d ocument provides an update of the SCC estimates based on the latest peer

- reviewed version of the models

, replacing model version s that were developed up to ten years ago in a rapidly evolving field

. It does not revisit other assumptions with regard to the discount rate, reference case socioeconomic and emission scenarios, or equilibrium climate sensitivity

. Improvements in the way damages are modeled are confined to those that have been incorporated into the latest versions of the models by the developers
themselves in the peer

- reviewed literature

. The agencies participating in the interagency working group continue to investigate potential improvements to the way in which economic damages associated with changes in CO 2 emissions are quan tified.

Section II summarizes the major updates relevant to SCC estimation that are contained in the new
versions of the integrated assessment models released since the 2010 interagency report

. Section III presents the updated schedule of SCC estimates fo r 201 0

– 2050 based on these versions of the models

. Section IV provides a discus sion of other model limitations and research gaps

.

II. Summary of Model Updates

This section briefly summarizes changes to the most recent versions of the three integrated assessm ent models (IAMs) used by the interagency group in 2010

. We focus on describing those model updates that are relevant to estimating the social cost of carbon , as summarized in Table 1

. For example, both the DICE and PAGE models now include an explicit repr esentation of sea level rise damages. Other revisions to PAGE include: updated adaptation assumptions, revisions to ensure damage s are constrained by GDP, updated regional scaling of damages

, and a revised treatment of potentially abrupt shifts in climate damages. T he DICE model’s simple carbon cycle has been updated to be more consistent with a more complex climate model. The FUND model includes updated damage functions for sea level rise impacts,
the agricultur al sector , and redu ced space heating requirements , as well as changes to the transient response of temperature to the buildup of GHG concentrations and the inclusion of indirect effects of

1 In this document, we present all values of the SCC as the cost per metric ton of CO 2 emissions. Alternatively, one could report the SCC as the cost per metric ton of carbon emissions. The multiplier for translating between mass of CO 2 and the mass of carbon is 3.67 (the molecular weight of CO 2 divided by the molecular weight of carbon =
4 4/12 = 3.67).

2 http://www.whitehouse.gov/sites/default/files/omb/inforeg/eo12866/eo13563_01182011.pdf

3 See p. 1, 3, 4, 29, and 33 ( Interagency Working Group on Social Cost of Carbon 2010)

.5

methane emissions

. Changes made to parts of the models that are superseded by the inte ragency working group’s modeling assumptions

– regarding equilibrium climate sensitivity, discounting, and
socioeconomic variables

– are not discussed here but can be found in the references provided in each
section below

.
Table 1: Summary of Key Model Revisions Relevant to the Interagency SCC

IAM Version used in 2010 Interagency Analysis New

Version Key changes relevant to interagency SCC

DICE 2007 2010 Updated calibration of the carbon cycle model and explicit representation of sea level rise (SLR) and associated damages.
FUND 3.5

(2009) 3.8

(2012) Updated damage functions for space heating, SLR,

agricultural impacts, changes to transient response of temperature to buildup of GHG concentrations, and inclusion of indirect climate effects of methane.
PAGE 2002 2009 E xplicit representation of SLR damages, revisions to damage function to ensure damages do not exceed 100% of GDP

, change in regional scaling of damages,

r evised treatment of potential abrupt damages, and updated adaptation assumptions

.

A. DICE

DICE 2010 includes a number of changes over the previous 2007 version used in the 2010 interagency
report. The model changes that are relevant for the SCC estimates developed by the interagency working group include: 1) updated parameter values for the carbon cycle model, 2) an explicit representation of sea level dynamics, and 3) a re

- calibrated damage function that includes an expl icit representation of economic damages from sea level rise

. Changes were also made to other parts of the
DICE model

— including the equilibrium climate sensitivity parameter, the rate of change of total factor productivity, and the elasticity of the margina l utility of consumption

— but these components of DICE

are superseded by the interagency working group ’s assumptions and so will not be discussed here

. More details on DICE2007 can be found in Nordhaus (2008) and on DICE2010 in Nordhaus (201 0 ) . The
DICE201 0 model and documentation is also available for download from the homepage of William
Nordhaus

.
Carbon Cycle Parameters

DICE uses a three

- box model of carbon stocks and flows to represent the accumulation and transfer of carbon among the atmosphere, the sh allow ocean and terrestrial biosphere, and the deep ocean

. These parameters are “calibrated to match the carbon cycle in the Model for the Assessment of Greenhouse6

Gas Induced Climate Change (MAGICC)” (Nordhaus 2008 p 44)

. 4 Carbon cycle transfer coefficien t values
in DICE2010 are based on re

- calibration of the model to match the newer 2009 version of MAGICC (Nordhaus 2010 p 2)

. For example, in DICE2010

, in each decade

, 12 percent of the carbon in the atmosphere is transferred to the shallow ocean, 4.7 percent of the carbon in the shallow ocean is transferred to the atmosphere, 94.8 percent remains in the shallow ocean, and 0.5 percent is transferred to the deep ocean. For comparison, in DICE 2007
, 1 8.9 percent of the carbon in the atmosphere is tran sferred to the shallow ocean each decade

, 9.7 percent of the carbon in the shallow ocean is transferred to the atmosphere, 85.3 percent remains in the shallow ocean, and 5 percent is transferred to the deep ocean.

The implication of these changes for DICE 2010 is in general a weakening of the ocean as a carbon sink and therefore a higher concentration of carbon in the atmosphere than in DICE2007 , for a given path of
emissions . All else equal, these changes will generally increase the level of warming and th erefore the
SCC estimates in DICE2010 relative to those from DICE2007.

Sea Level Dynamics

A new feature of DICE2010 is an explicit representation of the dynamics of the global average sea level anomaly to be used in the updated damage function (discussed b elow)

. This section contains a brief description of the sea level rise (SLR) module; a more detailed description can be found on the model developer’s website. 5 The average global sea level anomaly is modeled as the sum of four terms that represent contri butions from: 1) thermal expansion of the oceans, 2) melting of glaciers and small ice caps, 3) melting of the Greenland ice sheet, and 4) melting of the Antarctic ice sheet

.
The parameters of the four components of the SLR module are calibrated to match consensus results from the IPCC’s Fourth Assessment Report (AR4)

. 6 The rise in sea level from thermal expansion in each time period (decade) is 2 percent of the difference between the sea level in the previous period and the long run equilibrium sea level, which is 0.5 meters per degree Celsius (°C) above the average global temperature in 1900

. The rise in sea level from the melting of glaciers and small ice caps occurs at a rate
of 0.008 meters per decade per °C above the average global temperature in 1900

.
The contribution to sea level rise from melting of the Greenland ice sheet is more complex

. The equilibrium contribution to SLR is 0 meters for temperature anomalies less than 1 o C and increases linearly from 0 meters to a maximum of 7.3 meters for temp erature anomalies between 1 o C and 3.5 °C

. The contribution to SLR in each period is proportional to the difference between the previous period’s sea level anomaly and the equilibrium sea level anomaly, where the constant of proportionality
increases with the temperature anomaly in the current period.

4 MAGICC is a simple climate model initially developed by the U.S . National Center for Atmospheric Research that has been used heavily by the Intergovernmental Panel on Climate Change (IPCC) to emulate projections from more sophisticated state of the art earth system simulation models ( Randall et al. 2007).

5 Documentat ion on the new sea level rise module of DICE is available on William Nordhaus’ website at: http://nordhaus.econ.yale.edu/documents/SLR_021910.pdf

. 6 For a review of post

- IPCC AR4 research on sea level rise, see Nicholls et al. (2011) and NAS (2011).7

The contribution to SLR from the melting of the Antarctic ice sheet is

- 0.001 meters per decade when the temperature anomaly is below 3 °C and increases linearly between 3 °C and 6 °C to a maximum rate
of 0.0 25 meters per decade at a temperature anomaly of 6 °C.

Re

- calibrated Damage Function

Economic damages from climate change in the DICE model are represented by a fractional loss of gross economic output in each period

. A portion of the remaining economic ou tput in each period (net of climate change damages) is consumed and the remainder is invested in the physical capital stock to support future economic production, so each period’s climate damages will reduce consumption in that period and in all future per iods due to the lost investment

. The fraction of output in each period that is lost due to climate change impacts is represented as one minus a fraction, which is one divided by a quadratic function of the temperature anomaly, producing a sigmoid (“S”

- shap ed) function

. 7 The loss function in DICE2010 has been expanded by adding a quadratic function of SLR to the quadratic function of temperature

. In DICE2010 the temperature anomaly coefficients have been recalibrated to avoid
double

- counting damages from sea level rise that were implicitly included in these parameters in
DICE2007

.
The aggregate damages in DICE2010 are illustrated by Nordhaus (2010 p 3), who notes that “...damages in the uncontrolled (baseline) [i

. e

. , reference] case ... in 2095 are $12 trillion, or 2.8 percent of global output, for a global temperature increase of 3.4 o C above 1900 levels.” This compares to a loss of 3.2 percent of global output at 3.4 o C in DICE2007

. However, in DICE2010
, annual damages are lower in
most of the early periods of the modeling horizon but higher in later periods than would be calculated using the DICE2007 damage function

. Specifically, the percent difference between damages in the base run of DICE2010 and those that would be calculated using the DICE2007 damage fun ction starts at +7 percent in 2005, decreases to a low of

- 14 percent in 20 6 5, then continuously increases to +20 percent by 2300 (the end of the interagency analysis time horizon), and to +1 6 0 percent by the end of the model
time horizon in 2595

. The large increases in the far future years of the time horizon are due to the permanence associated with damages from sea level rise, along with the assumption that the sea level is projected to continue to rise long after the global average temperature b egins to decrease. The changes to the loss function generally decrease the interagency working group SCC estimates slightly given that relative increases in damages in later periods are discounted more heavily , all else equal

.

B. FUND

FUND version 3.8 includes a number of changes over the previous version 3.5 (Narita et al. 2010) used in
the 2010 interagency report

. D ocumentation supporting FUND and the model’s source code for all
versions of the model is available from the model autho rs. 8 Notable changes, due to their impact on the

7 The model and documentation, including formulas, are available on the author’s webpage at http://www.econ.yale.edu/~nordhaus/homepage/RICEmodels.htm

. 8 http://www.fund

- model.org/ . This report uses version 3.8 of the FUND model, which represents a modest update to the most recent version of the model to appear in the literature (version 3.7) (Anthoff and Tol, 2013a ). For the purpose of computing the SCC, the relevant changes (between 3.7 to 3.8) are associated with improving8

SCC estimates, are adjustments to the space heating, agriculture, and sea level rise damage functions in addition to changes to the temperature response function and the inclusion of indirect effects from

me thane emissions

. 9 We discuss each of these in turn.

Space Heating

In FUND
, the damages associated with the change in energy needs for space heating are based on the
estimate d impact due to one degree of warming

. These baseline damages are scaled based on the forecasted temperature anomaly’s deviation from the one degree benchmark and adjusted for changes
in vulnerability due to economic and energy efficiency growth

. In FUND 3.5
, t he function that scales the base year damages adjusted for vulnerability allo ws for the possibility that in some simulations the
benefits associated with reduced heating needs may be an unbounded c onvex function of the temperature anomaly

. In FUND 3.8
, the form of the scaling has been modified to ensure that the function is everywh ere concave and that there will exist an upper bound on the benefits a region may receive from reduced space heating needs

. The new formulation approaches a value of two in the limit of large temperature anomal ies , or i n other words

, assuming no decrease i n vulnerability

, the reduced expenditures on space heating at any level of warming will not exceed two times the reductions experienced at one degree of warming

. Since the reduced need for space heating represents a benefit of climate change in the model, or a negative damage, this change will increase the estimated SCC

. This update accounts for a significant portion of the difference in the expected SCC estimates reported by
the two version s of the model when run probabilistically

.

Sea Level Rise and Land Loss

The FUND model explicitly includes damages associated with the inundation of dry land due to sea level
rise

. The amount of land lost within a region is dependent upon the proportion of the coastline being protected by adequate sea walls and the amount of sea level rise

. In FUND 3.5 the function defining the potential land lost in a given year due to sea level rise is linear in the rate of sea level rise for that year

. This assumption implicitly assumes that all regions are well represented by a homogen eous coastline in length and a constant uniform slope moving inland

. In FUND 3.8 the function defining the potential land
lost has been changed to be a convex function of sea level rise , thereby assuming that the slope of the
shore line increases moving in land

. The effect of this change is to typically reduce the vulnerability of some regions to sea level rise based land loss, thereby lowering the expected SCC estimate. 10

Agriculture

consistency with IPCC AR4 by adjusting the atmospheric lifetimes of CH4 and N2O and incorporating the indirect forcing effects of CH4, along w ith making minor stability improvements in the sea wall construction algorithm.

9 The other damage sectors (water resources, space cooling, land loss, migration, ecosystems, human health, and extreme weather) were not significantly updated.

10 For stability purposes this report also uses an update to the model which assumes that regional coastal protection measures will be built to protect the most valuable land first, such that the marginal benefits of coastal protection is decreasing in the l evel of protection following Fankhauser (1995).9

In FUND
, the damages associated with the agricultural sector are measure d as proportional to the
sector’s value

. The fraction is bounded from above by one and is made up of three additive c omponents that represent the effects from carbon fertilization, the rate of temperature change, and the level of the temperature anomaly

. I n both FUND 3.5 and FUND 3.8
, the fraction of the sector’s value lost due to the level of the temperature anomaly i s modeled as a quadratic function with an intercept of zero

. In FUND
3.5
, the coefficients of this loss function a re modeled as the ratio of two random normal variables

. T his specification had the potential for unintended extreme behavior as draws from the parameter in the denominator approached zero or went negative

. In FUND 3.8
, the coefficients are drawn directly f rom truncated normal distributions so that they remain in the range and , respectively, ensuring the correct sign and eliminating the potential for divide by zero errors. T he mean s for the new
distribut ion s are set equal to the ratio of the means from the normal distributions used in the previous
version

. In general the impact of this change has been to decrease the range of the distribution while spreading out the distributions’ mass over the remaining range relative to the previous version

. The net effect of this change on the SCC estimates is difficult to predict.

Transient Temperature Response

The temperature response model translates changes in global levels of radiative forcing into the current

ex pected temperature anomaly

. In FUND
, a given year ’ s increase in the temperature anomaly is based on a mean reverting function where the mean equals the equilibrium temperature anomaly that would eventually be reached if that year’s level of radiative forcing were sustained

. The rate of mean reversion
defi n es the rate at which the transient temperature approaches the equilibrium

. I n FUND 3.5
, the rate of temperature response i s defined as a decreasing linear function of equilibrium climate sensitivity to capture the fact that the progress ive heat uptake of the deep ocean causes the rate to slow at higher values of the equilibrium climate sensitivity

. In FUND 3.8
, the rate of temperature response h as been updated to a quadratic function of the equilibrium climate sensitivity

. This change reduces the sensitivi ty of the rate of temperature response to the level of the equilibrium climate sensitivity , a relationship first noted by Hansen et al. (1985) based on the heat uptake of the deep ocean

. Therefore in FUND 3.8
, the temperature response will typically be fas ter than in the previous version

. The overall effect of this change is likely to increase estimates of the SCC as higher temperatures are reached during the timeframe analyzed and as the same damages experienced in the previous version of the model are now experienced earlier and therefore discounted less.

Methane

The IPCC AR4 notes a series of indirect effects of methane emissions, and has developed methods for proxying such effects when computing the global warming potential of methane (Forster et al. 200 7)

. FUND 3.8 now includes the same methods for incorporating the indirect effects of methane emissions. Specifically, the average atmospheric lifetime of methane has been set to 12 years to account for the
feedback of methane emissions on its own lifetime. The radiative forcing associated with atmospheric
methane has also been increase d by 40% to account for its net impact on ozone production and stratospheric water vapor. All else equal, the effect of this increased radiative forcing will be to increase
th e estimated SCC values, due to greater projected temperature anomaly.10

C. PAGE

PAGE09 (Hope 201 3 ) includes a number of changes from PAGE2002, the version used in the 2010 SCC interagency report. The changes that most directly affect the SCC estimates include: explicitly modeling the impacts from sea level rise, revisions to the damage function to ensure damages are constrained by
GDP , a change in the regional scaling of da mages , a revised treatment for the probability of a discontinuity with in the damage function, and revised assumptions on adaptation. The model also includes revisions to the carbon cycle feedback and the calculation of regional temperature s

. 11 More
details on PAGE09 can be found in Hope ( 2011a, 2011b, 2011c). A description of PAGE2002 can be found in Hope (2006).

Sea Level Rise

While PAGE2002 aggregates all damages into two categories

– economic and non

- economic impacts

- , PAGE09 adds a third explicit cate gory : damages from sea level rise

. In the previous version of the model, damages from sea level rise were subsumed by the other damage categories. In PAGE09 sea level damages increase less than linearly with sea level under the assumption that land, people , and GDP are
more concentrated in low

- lying shoreline areas . Damages from the economic and non

- economic sector were adjusted to account for the introduction of this new category.

Revised Damage Function to Account for Saturation

In PAGE09, small initia l economic and non

- economic benefits (negative damages) are modeled for small temperature increases, but all regions eventually experience economic damages from climate change, where damages are the sum of additively separable polynomial functions of temperature and sea level rise. Damages transition from this polynomial function to a logistic path once they exceed a certain proportion of remaining Gross Domestic Product (GDP) to ensure that damages do not exceed 100 percent of GDP. This differs fr om PAGE2002, which allowed Eastern Europe to potentially experience large benefits from temperature increases, and which also did not bound the possible damages that could be experienced.

Regional Scaling Factors

As in the previous version of PAGE, the PAG E09 model calculates the damages for the European Union (EU) and then

, assumes that damages for other regions are proportional based on a given scaling factor

. The scaling factor in PAGE09 is based on the length of a region’s coastline relative to the EU ( Hope 2011b) . Because of the long coastline in the EU, other regions are, on average, less vulnerable than the EU for the same sea level and temperature increase

, but all regions have a positive scaling factor. PAGE2002 based its scaling factors on four stu dies reported in the IPCC’s third assessment report, and allowed for benefits from temperature increase in Eastern Europe, smaller impacts in develop ed countries, and higher damages in developing countries.

11 Because several changes in the PAGE model are structural (e.g., the addition of sea level rise and treatment of discontinuity), it is not possible to assess the direct impact of each change on the SCC in is olation as done for the other two models above

.11

Probability of a Discontinuity

In PAGE2002, the damages associated with a “discontinuity” (nonlinear extreme event) were modeled as an expected value. Specifically, a stochastic probability of a discontinuity was multiplied by the damages associated with a discontinuity to obtain an expected value, and this was added to the
economic and non

- economic impacts. That is

, additional damages from an extreme event, such as extreme melting of the Greenland ice sheet, were multiplied by the probability of the event occurring and added to the damage estimate

. In PAGE09, the probability of discontinuity is treated as a discrete event for each year in the model. The damages for each model run are estimated either with or without a discontinuity occurring, rather than as an expected value. A large

‐ scale discontinuity becomes possible when the temperature rises beyond some threshold value between 2 and 4°C. The probability that a discontinuity will occur beyond this threshold then increases by between 10 and 30 percent for every 1°C rise in temperature beyond the thres hold. If a discontinuity occurs, the EU loses an additional 5 to 25 percent of its GDP (drawn from a triangular distribution with a mean of 15 percent) in addition to other damages, and other regions lose an amount determined by the regional scaling factor . The threshold value for a possible discontinuity is lower than in PAGE2002, while the rate at which the probability of a discontinuity increases with the temperature anomaly and the damages that result from a discontinuity are both higher than in PAGE200 2. The model assumes that only one discontinuity can
occur and that the impact is phased in over a period of time, but once it occurs, its effect is permanent.

Adaptation

As in PAGE2002, adaptation is available to help mitigate any climate change impacts t hat occur. In PAGE this adaptation is the same regardless of the temperature change or sea level rise and is there for e akin

to what is more commonly considered a reduction in vulnerability . It is modeled by reducing the damages by some percentage

. PAGE09 assumes a smaller decrease in vulnerability than the previous
version of the model and assumes that it will take longer for this change in vulnerability to be realized. In the aggregated economic sector, at the time of full implementation

, this adap tation will mitigate all damages up to a temperature increase of 1°C, and for temperature anomalies between 1°C and 2 °C, it will reduce damages by 15

- 30 percent (depending on the region) . H owever , it takes 20 years to fully implement this adaptation

. In P AGE2002
, adaptation was assumed to reduce economic sector damages
up to 2 °C by 50

- 90 percent after 20 years. Beyond 2 °C
, no adaptation is assumed to be available to mitigate the impacts of climate change. For the non

- economic sector, in PAGE09 adapt at ion i s available to reduce 15 percent of the damages due to a temperature increase between 0°C and 2°C and is assumed to take 40 years to fully implement , instead of 25 percent of the damages over 20 years
assumed in PAGE2002 . Similarly, adaptation is assumed t o alleviate 25

- 50 percent of the damages from the first 0.20 to 0.25 meters of sea level rise but is assumed to be ineffective thereafter. Hope (2011c) estimates that the less optimistic assumptions regarding the ability to offset impacts of temperature an d sea level rise via adaptation increase the SCC by approximately 30 percent.

Other Noteworthy Changes12

Two other changes in the model are worth noting. The re is a change in the way the model accounts for
decreased CO 2 absorption on land and in the ocean as temperature rises. PAGE09 introduces a linear feedback from global mean temperature to the percentage gain in the excess concentration of CO 2 , capped at a maximum level. In PAGE2002, an additional amount was added to the CO 2 emissions each period to accou nt for a decrease in ocean absorption and a loss of soil carbon. Also updated is the method by which the average global and annual temperature anomaly is downscaled to determine annual average regional temperature anomalies to be used in the regional damag e functions. In
PAGE 2002
, the scaling was determined solely based on regional difference in emissions of sulfate
aerosols. In PAGE09

, this regional temperature anomaly is further adjusted using an additive factor that is based on the average absolute latitude of a region relative to the area weighted average absolute
la titude of the Earth’s landmass , to capture relatively greater change s in temperature forecast to be experienced at higher latitudes

.

III. Revised SCC Estimates

The updated versions of the three integrated assessment models were run using the same methodology
detailed in the 2010 TSD ( Interagency Working Group on Social Cost of Carbon 2010 )

. The approach along with the inputs for the socioeconomic emission s scenarios, equilibrium climate sensitivity distribution, and discount rate remain s the same

. This includes the five reference scenarios based on the

EMF

- 22 modeling exercis e, the Roe and Baker equilibrium climate sensitivity distribution calibrated to
the IPCC AR4 , and three constant discount rates of 2.5, 3, and 5 percent.

As was previously the case, the use of three models, three discount rates, and five scenarios produces 45 separate distributions for the global SCC

. The approach laid out in the 2010 TSD applied equal weight
to each model and socioeconomic scenario in orde r to reduce the dimensionality down to three
separate distributions representative of the three discount rates

. The interagency group selected four values from these distributions for use in regulatory analysis

. Three values are based on the average SCC

ac ross models and socio

- economic

- emissions scenarios at the 2.5, 3, and 5 percent discount rates

, respectively

. The fourth value wa s chosen to represent the higher

- than

- expected economic impacts from climate change further out in the tails of the SCC distrib ution

. For this purpose, the 95th percentile
of the SCC estimates at a 3 percent discount rate was chosen

. ( A detailed set of percentiles by model
and scenario combination and additional summary statistics for the 2020 values is available in the Appendix.) As noted in the 2010 TSD
, “ the 3 percent discount rate is the central value, and so the central value that emerges is the average SCC across models at the 3 percent discount rate ” ( Interagency Working Group on Social Cost of Carbon 2010 , p. 25)

. However, f or purposes of capturing the uncertainties involved in regulatory impact analysis, the interagency group emphasizes the importance and value of including all four SCC values

.

Table 2 shows the four selected SCC estimates in five year increments from 2010 to 2050

. Values for 2010, 2020, 2030, 2040, and 2050 are calculated by first combining all outputs (10,000 estimates per13

model run) from all scenarios and models for a given discount rate

. Values for the years in between are calculated using linear interpolation

. The full set of revised annual SCC estimates between 2010 and
2050 is reported in the Appendix

.

Table 2 : Revised Social Cost of CO 2 , 2010

– 2050 (in 2007 dollars per metric ton of CO 2 )

Discount Rate 5 .0 % 3 .0 % 2.5% 3 .0 % Year Avg Avg Avg 95th 2010 11 3 2 5 1 8 9 2015 1 1 3 7 5 7 109 2020 12 43 6 4 12 8 2025 14 4 7 69 14 3 2030 16 52 7 5 159 2035 19 5 6 8 0 17 5 2040 21 6 1 8 6 19 1 2045 2 4 6 6 92 206 2050 2 6 71 9 7 22 0

The SCC estimates using the updated versions of the models are higher than those reported in the 2010 TSD due to the changes to the models outlined in the previous section. By way of comparison, the 2020 SCC estimates reported in the original TSD were $7, $26, $42 and $81 (2007$) (Interagency Working Group on Social Cost of Carbon 2010). Figure 1 illustrates where the four SCC values for 20 2 0 fall within
the full distribution for each discount rate based on the combined set of runs for each model and

scena rio (150,000 estimates in total for each discount rate). In general, the distributions are skewed to the right and have long tails. The Figure also shows that the lower the discount rate, the longer the right
tail of the distribution.

Figure 1: Distributio n of SCC Estimates for 20 2 0 (in 2007$ per metric ton CO 2 )14

As was the case in the 2010 TSD, t he SCC increases over time because future emissions are expected to produce larger incremental damages as physical and economic systems become more stressed in response to greater climatic change

. The approach taken by the interagency group is to compute the cost of a marginal ton emitted in the future by running the models for a set of perturbation years out to
2050

. Table 3 illustrates how the growth rate for t hese four SCC estimates varies over time

.

Table 3 : Average Annual Growth Rates of SCC Estimates between 2010 and 2050

Average Annual Growth 5.0% 3.0% 2.5% 3.0% Rate (%) Avg Avg Avg 95th 2010

- 2020 1.2% 3. 3 % 2.4% 4. 4 % 2020

- 2030 3.4% 2.1% 1.7% 2.4% 2030

- 2040 3.0% 1. 9 % 1.5% 2. 1 % 2040

- 2050 2.6 % 1 .6% 1.3% 1.5 %

T he future monetized value of emission reductions in each year (the SCC in year t multiplied by the change in emissions in year t ) must be discounted to the present to determine its total net present value for use in regulatory analysis

. As previously discussed in the 2010 TSD, d amages from future emissions
should be discounted at the same rate as that used to calculate the SCC estimates themselves to ensure internal consistency

– i.e., future damages from climate change, whether they result from emissions today o r emissions in a later year, should be discounted using the same rate.

Under current OMB guidance contained in Circular A

- 4, analysis of economically significant proposed and final regulations from the domestic perspective is required, while analysis from the international perspective is optional. However, the climate change problem is highly unusual in at least two respects. First, it involves a global externality: emissions of most greenhouse gases contribute to damages around15

the world even when they are emitted in the United States. Consequently, to address the global natu re of the problem, the SCC must incorporate the full (global) damages caused by GHG emissions. Second, climate change presents a problem that the United States alone cannot solve. Even if the United States were to reduce its greenhouse gas emissions to zer o, that step would be far from enough to avoid substantial climate change. Other countries would also need to take action to reduce emissions if significant changes in the global climate are to be avoided. Emphasizing the need for a global solution to a gl obal problem, the United States has been actively involved in seeking international agreements to reduce emissions and in encouraging other nations, including emerging major economies, to take significant steps to reduce emissions. When these consideration s are taken as a whole, the interagency group concluded that a global measure of the benefits from reducing U.S. emissions is preferable. For additional discussion, see the 2010 TSD.

IV. Other Model Limitations and Research Gaps

The 2010 interagency SCC TSD discusse s a number of important limitations for which additional research
is needed

. In particular, the document highlight s the need to improve the quantification of both non

catastrophic and catastrophic damages, the treatment of adaptation and technologi cal change, and the way in which inter

- regional and inter

- sectoral linkages are modeled

. While the new version of the
models discussed above offer some improvements in these areas, further work remains warranted. The
2010 TSD also discusse s the need to mo re carefully assess the implications of risk aversion for SCC estimation as well as the inability to perfectly substitute between climate and non

- climate goods at higher temperature increases, both of which have implications for the discount rate used

. EPA , DOE, and other agencies continue to engage in research on modeling and valuation of climate impacts that can potentially improve SCC estimation in the future

.

References

Anthoff, D. and Tol, R.S.J. 2013 a

. The uncertainty about the social cost of carbo n: a decomposition analysis using FUND. Climatic Change 117: 515

– 530

.

Anthoff, D. and Tol, R.S.J. 2013 b . Erratum to: The uncertainty about the social cost of carbon: A decomposition analysis using FUND. Climatic Change . Advance online publication. doi: 10.1007/s10584

- 013

- 0959

- 1.

Fankhauser, S. 1995. Valuing climate change: The economics of the greenhouse. London, England: Earthscan.

Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, J. Lean, D.C. Lowe, G. Myhre, J. Nga nga, R. Prinn, G. Raga, M. Schulz and R. Van Dorland

. 2007

. Changes in Atmospheric Constituents and in Radiative Forcing. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergover nmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.16

Hope, Chris. 2006. “The Marginal Impact of CO 2 from PAGE2002: An Integrated Assessment Model Incorporating the IPCC’s Five Reasons for Concern.” The Integrated Assessment Journal

. 6 ( 1 ): 19

– 56

.
Hope, Chris. 2011a “ The PAGE09 Integrated Assessment Model: A Technical Description ” Cambridge Judg e Busines s School Working Paper No. 4/2011 (April). Accessed November 23, 2011: http://www.jbs.cam.ac.uk/research/working_papers/2011/wp1104.pdf

.
Hope, Chris. 2011b “ The Social Cost of CO 2 from the PAGE09 Model ” Cambridge Judg e Business School Working Paper No. 5/2011 (June). Accessed November 23, 2011: http://www.jbs.cam.ac.uk/research/working_papers/2011/ wp1105.pdf

.
Hope, Chris. 2011c “ New Insights from the PAGE09 Model: The Social Cost of CO 2 ” Cambridge Judg e Business School Working Paper No. 8/2011 (July). Accessed November 23, 2011: http://www.jbs.cam.ac.uk/research/working_papers/2011/wp1108.pdf

.
Hope, C. 201 3 . Critical issues for the calculation of the social cost of CO 2 : why the estimates from PAGE09 are higher than those from PAGE2002. Climatic Change 117: 531

– 543

.
Interagency Working Group on Social Cost of Carbon. 2010. Social Cost of Carbon for Regulatory Impact Analysis under Executive Order 12866

. February. United States Government. http://www.whitehouse.gov/sites/default/files/omb/inforeg/for

- agencies/Social

- Cost

- of

- Carbon

- for

RIA.pdf

.
Meehl, G.A., T.F. Stocker, W.D. Collins, P. Friedlingstein, A.T. Gaye, J.M. Gregory, A. Kitoh, R. Knutti, J.M. Murphy, A. Noda, S.C.B. Raper, I.G. Watterson, A.J. Weaver and Z.

- C. Zhao

. 2007

. Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Narita, D., R. S. J. Tol and D. Anthoff

. 2010. Economic costs of extratropical storms under climate change: an application of FUND. Journal of Environmental Planning and Management 53(3): 371

- 384.

National Academy of Sciences

. 2011. Climate Stabilization Targets: Emissions, Concentrations, and Impacts over Decades to Millennia

. Washington, DC: National Academies Press, Inc.

Nicholls, R.J., N. Marinova, J.A. Lowe, S. Brown, P. Vellinga, D. de Gusmão, J. Hinkel and R.S.J. Tol. 2011.
Sea

- level rise and its possible impacts given a ‘beyond 4°C wor ld’ in the twenty

- first century. Phil. Trans.
R. Soc. A 369(1934): 161

- 181.

Nordhaus, W. 201 0

. Economic aspects of global warming in a post

- Copenhagen environment.
P roceedings of the National Academy of Sciences 107 ( 26 ): 11721

- 11726.

Nordhaus, W. 2008. A Question of Balance: Weighing the Options on Global Warming Policies. New Haven, CT: Yale University Press.17

Randall, D.A., R.A. Wood, S. Bony, R. Colman, T. Fichefet, J. Fyfe, V. Kattsov, A. Pitman, J. Shukla, J. Srinivasan, R.J. Stouffer, A. Sumi and K.E. Taylor. 2007. Climate Models and Their Evaluation. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.18

Appendix A

Table A1: Annual SCC Values: 2010

- 2050 ( 2007$/ metric ton CO 2 )

Discount Rate 5.0% 3.0% 2.5% 3.0% Year Avg Avg Avg 95th
2010 11 32 51 89 2011 11 33 52 93 2012 11 34 54 97 2013 11 35 55 101 2014 11 36 56 105 2015 11 37 57 109 2016 12 38 59 112 2017 12 39 60 116 2018 12 40 61 120 2019 12 42 62 124 2020 12 43 64 128 2021 12 43 65 131 2022 13 44 66 134 2023 13 45 67 137 2024 14 46 68 140 2025 14 47 69 143 2026 15 48 70 146 2027 15 49 71 149 2028 15 50 72 152 2029 16 51 73 155 2030 16 52 75 159 2031 17 52 76 162 2032 17 53 77 165 2033 18 54 78 168 2034 18 55 79 172 2035 19 56 80 175 2036 19 57 81 178 2037 20 58 83 181 2038 20 59 84 185 2039 21 60 85 188 2040 21 61 86 191 2041 22 62 87 194 2042 22 63 88 197 2043 23 64 89 200 2044 23 65 90 203 2045 24 66 92 206 2046 24 67 93 209 2047 25 68 94 211 2048 25 69 95 214 2049 26 70 96 217 2050 26 71 97 22019

Table A 2 : 20 2 0 Global SCC Estimates at 2.5 Percent Discount Rate (2007$/ metric ton CO 2 )

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95 th 99th Scenario 12 PAGE IMAGE 6 11 15 27 58 129 139 327 515 991 MERGE Optimistic 4 6 9 16 34 78 82 196 317 649 MESSAGE 4 8 11 20 42 108 107 278 483 918 MiniCAM Base 5 9 12 22 47 107 113 266 431 872 5th Scenario 2 4 6 11 25 85 68 200 387 955

Scenario DICE IMAGE 25 31 37 47 64 72 92 123 139 161 MERGE Optimistic 14 18 20 26 36 40 50 65 74 85 MESSAGE 20 24 28 37 51 58 71 95 109 221 MiniCAM Base 20 25 29 38 53 61 76 102 117 135 5th Scenario 17 22 25 33 45 52 65 91 106 126

Scenario FUND IMAGE

- 14

- 2 4 15 31 39 55 86 107 157 MERGE Optimistic - 6 1 6 14 27 35 46 70 87 141 MESSAGE

- 16

- 5 1 11 24 31 43 67 83 126 MiniCAM Base

- 7 2 7 16 32 39 55 83 103 158 5th Scenario

- 29

- 13

- 6 4 16 21 32 53 69 103

Table A3 : 20 2 0 Global SCC Estimates at 3 Percent Discount Rate (2007$/ metric ton CO 2 )

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th Scenario PAGE IMAGE 4 7 10 18 38 91 95 238 385 727 MERGE Optimistic 2 4 6 11 23 56 58 142 232 481 MESSAGE 3 5 7 13 29 75 74 197 330 641 MiniCAM Base 3 5 8 14 30 73 75 184 300 623 5th Scenario 1 3 4 7 17 58 48 136 264 660

Scenario DICE IMAGE 16 21 24 32 43 48 60 79 90 102 MERGE Optimistic 10 13 15 19 25 28 35 44 50 58 MESSAGE 14 18 20 26 35 40 49 64 73 83 MiniCAM Base 13 17 20 26 35 39 49 65 73 85 5th Scenario 12 15 17 22 30 34 43 58 67 79

Scenario FUND IMAGE

- 13

- 4 0 8 18 23 33 51 65 99 MERGE Optimistic - 7

- 1 2 8 17 21 29 45 57 95 MESSAGE

- 14

- 6

- 2 5 14 18 26 41 52 82 MiniCAM Base

- 7

- 1 3 9 19 23 33 50 63 101 5th Scenario

- 22

- 11

- 6 1 8 11 18 31 40 62

12 See 2010 TSD for a description of these scenarios.20

Table A4 : 20 2 0 Global SCC Estimates at 5 Percent Discount Rate (2007$/ metric ton CO 2 )

Percentile 1st 5th 10th 25th 50th Avg 75th 90th 95th 99th Scenario PAGE IMAGE 1 2 2 5 10 28 27 71 123 244 MERGE Optimistic 1 1 2 3 7 17 17 45 75 153 MESSAGE 1 1 2 4 9 24 22 60 106 216 MiniCAM Base 1 1 2 3 8 21 21 54 94 190 5th Scenario 0 1 1 2 5 18 14 41 78 208

Scenario DICE IMAGE 6 8 9 11 14 15 18 22 25 27 MERGE Optimistic 4 5 6 7 9 10 12 15 16 18 MESSAGE 6 7 8 10 12 13 16 20 22 25 MiniCAM Base 5 6 7 8 11 12 14 18 20 22 5th Scenario 5 6 6 8 10 11 14 17 19 21

Scenario FUND IMAGE

- 9

- 5

- 4

- 1 2 3 6 10 14 24 MERGE Optimistic - 6

- 4

- 2 0 3 4 6 11 15 26 MESSAGE

- 10

- 6

- 4

- 1 1 2 5 9 12 21 MiniCAM Base

- 7

- 4

- 2 0 3 4 6 11 14 25 5th Scenario

- 11

- 7

- 5

- 3 0 0 3 5 7 1321 Table A5 : Additional Summary Statistics of 2020 Global SCC Estimates

Discount rate: 5.0% 3.0% 2.5% Statistic: Mean Variance Skewness Kurtosis Mean Variance Skewness Kurtosis Mean Variance Skewness Kurtosis DICE 12 26 2 15 38 409 3 24 57 1097 3 30 PAGE 22 1616 5 32 71 14953 4 22 101 29312 4 23 FUND 3 41 5 179 19 1452

- 42 8727 33 6154

- 73 1493122

Appendix B

The November 2013 revision of this technical support document is based on two corrections to the runs based on the FUND model. First, the potential dry land loss in the algorithm that estimates regional coastal protections was mis specified in the model’s computer code . This correction is covered in an erratum to Anthoff and Tol (2013 a ) published in the same journal ( Climatic Change ) in October 2013 (Anthoff and Tol (2013b)) . Second, the equilibrium climate sensitivity distribution was inadvertently specified as a trunc ated Gamma distribution (the default in FUND) as opposed to the truncated Roe and
Baker distribution as was intended. The truncated Gamma distribution used in the FUND runs had approximately the same mean and upper truncation point, but lower variance and faster decay of the upper tail, as compared to the intended specification based on the Roe and Baker distribution. The difference between the original estimates reported in the May 2013 version of this technical support
document and this revision are gener ally one dollar or less.