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Robust abatement pathways to tolerable climate futures require immediate global action

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Disentangling the relative importance of climate change abatement policies from the human–Earth system (HES) uncertainties that determine their performance is challenging because the two are inexorably linked, and the nature of this linkage is dynamic, interactive and metric specific ¹ . Here, we demonstrate an approach to quantify the individual and joint roles that diverse HES uncertainties and our choices in abatement policy play in determining future climate and economic conditions, as simulated by an improved version of the Dynamic Integrated model of Climate and the Economy 2,3 . Despite wide-ranging HES uncertainties, the growth rate of global abatement (a societal choice) is the primary driver of long-term warming. It is not a question of whether we can limit warming but whether we choose to do so. Our results elucidate important long-term HES dynamics that are often masked by common time-aggregated metrics. Aggressive near-term abatement will be very costly and do little to impact near-term warming. Conversely, the warming that will be experienced by future generations will mostly be driven by earlier abatement actions. We quantify probabilistic abatement pathways to tolerable climate/economic outcomes 4,5 , conditional on the climate sensitivity to the atmospheric CO 2 concentration. Even under optimistic assumptions about the climate sensitivity, pathways to a tolerable climate/economic future are rapidly narrowing. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.
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Letters
https://doi.org/10.1038/s41558-019-0426-8
1Department of Civil and Environmental Engineering, Tufts University, Medford, MA, USA. 2School of Civil and Environmental Engineering, Cornell
University, Ithaca, NY, USA. 3Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, USA. 4Department of
Geosciences, The Pennsylvania State University, University Park, PA, USA. 5Department of Earth and Planetary Sciences, Rutgers University, Piscataway,
NJ, USA. 6Present address: Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy.
*e-mail: jonathan.lamontagne@tufts.edu
Disentangling the relative importance of climate change
abatement policies from the human–Earth system (HES)
uncertainties that determine their performance is challeng-
ing because the two are inexorably linked, and the nature of
this linkage is dynamic, interactive and metric specific1. Here,
we demonstrate an approach to quantify the individual and
joint roles that diverse HES uncertainties and our choices in
abatement policy play in determining future climate and eco-
nomic conditions, as simulated by an improved version of the
Dynamic Integrated model of Climate and the Economy2,3.
Despite wide-ranging HES uncertainties, the growth rate of
global abatement (a societal choice) is the primary driver of
long-term warming. It is not a question of whether we can
limit warming but whether we choose to do so. Our results
elucidate important long-term HES dynamics that are often
masked by common time-aggregated metrics. Aggressive
near-term abatement will be very costly and do little to
impact near-term warming. Conversely, the warming that will
be experienced by future generations will mostly be driven by
earlier abatement actions. We quantify probabilistic abate-
ment pathways to tolerable climate/economic outcomes4,5,
conditional on the climate sensitivity to the atmospheric CO2
concentration. Even under optimistic assumptions about the
climate sensitivity, pathways to a tolerable climate/economic
future are rapidly narrowing.
Policy discussions of climate change mitigation and adaptation
benefit from estimates of the potential extent and timing of future
climate change, and the potential damages and costs this change
might induce. Providing decision-makers with these estimates is
exceedingly difficult because the scientific community lacks a com-
plete understanding of the complex interactions between human
systems and the climate6. Integrated assessment models (IAMs)
approximate these interactions in a computational framework7.
IAMs have been used to create successive generations of global
change scenarios that are ubiquitous in planning and evaluation
applications across many disciplines, including the representa-
tive concentration pathways8 and shared socioeconomc pathways9.
Recent work has considered the sensitivity of IAM results to HES
uncertainties1 and structural model uncertainty across IAMs10,
but little attention has been paid to the interaction between HES
uncertainties and abatement policy11. Here we contribute a unified
framework to evaluate the joint impact of HES uncertainties and
abatement actions on climate–economic outcomes. By considering
the evolution of sensitivities and impacts over century-scale peri-
ods, our framework elucidates important long-term HES dynamics,
and identifies robust abatement pathways to achieve tolerable
climate/economic futures12 (that is, a tolerable policy window).
We utilize an improved version of the Dynamic Integrated
model of Climate and the Economy (DICE)3. DICE is a simple,
though widely used13, IAM that links a global representation of the
economy with a simplified climate emulator. We adopt DICE as a
parsimonious and archetypal surrogate for more complex IAMs
that represent multi-sector and regional dynamics, and are used to
generate shared scenarios such as the representative concentration
pathways and shared socioeconomic pathways (see Weyant14 for a
review). Following previous work2,15 we improve the climate module
in DICE by replacing it with the DOEClim model16. DOEClim is an
energy-balance model that has representation of land, the tropo-
sphere and ocean dynamics, with shallow mixing and deep diffu-
sivity layers. We convert the DICE–DOEClim model from a policy
optimization to a policy simulation model to enable simultaneous
exploration of the full abatement strategy space and parametric
uncertainties2 (see Methods for details). Of course, our findings are
subject to the ability of the DICE–DOEClim model to capture the
key dynamics of the integrated HES and will inevitably be subject
to the limitations of that model. Despite recent advances17, exten-
sive sensitivity and uncertainty analyses of more complex IAMs that
give a better representation of regional and multi-sector dynamics
can pose intractable computational challenges. Thus, we adopt the
parsimonious, globally aggregated DICE model.
As an illustrative example, we assume the global CO2 emissions
abatement level grows exponentially over time, until full abate-
ment is achieved. This is a special case of a more flexible functional
form used in earlier work11. We sample the exponential growth
rate to generate abatement trajectories that achieve full abatement
uniformly between 2030 and 2150 (Fig. 1a and see Methods). We
assume that the year 2030 is the earliest opportunity for the energy
system to become fully carbon neutral11 with a maximum relative
abatement growth rate of 26.3% per year, whereas 2150 is assumed
to be the first year of negative emissions3. The resulting emissions
trajectories are broadly consistent with the representative concen-
tration pathway and shared socioeconomic pathway trajectories
(see Supplementary Figs 2–6).
We sampled 24 different sources of HES uncertainty, as repre-
sented in DICE–DOEClim, along with the growth rate of global
abatement to generate 5,200,000 alternative states of the world
(see Methods for details). The 24 HES uncertainties cover most
of the parameters of the DICE–DOEClim model, including those
that define population growth, total factor productivity, economic
impacts of climate change, the cost of carbon-free technologies, the
Robust abatement pathways to tolerable climate
futures require immediate global action
J.R.Lamontagne 1*, P.M.Reed2, G.Marangoni 3,6, K.Keller 3,4 and G.G.Garner 5
Corrected: Publisher Correction
NATURE CLIMATE CHANGE | VOL 9 | APRIL 2019 | 290–294 | www.nature.com/natureclimatechange
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