ArticlePDF Available

The Next Generation of Scenarios for Climate Change Research and Assessment


Abstract and Figures

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth's climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.
Content may be subject to copyright.
The next generation of scenarios for climate
change research and assessment
Richard H. Moss
, Jae A. Edmonds
, Kathy A. Hibbard
, Martin R. Manning
, Steven K. Rose
, Detlef P. van Vuuren
Timothy R. Carter
, Seita Emori
, Mikiko Kainuma
, Tom Kram
, Gerald A. Meehl
, John F. B. Mitchell
Nebojsa Nakicenovic
, Keywan Riahi
, Steven J. Smith
, Ronald J. Stouffer
, Allison M. Thomson
John P. Weyant
& Thomas J. Wilbanks
Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of
Earth’s climate system and its likely response to human and natural influences. The implications of climate change for the
environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on
how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in
future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential
consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such
as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information
among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate
some of the most challenging and important questions about climate change confronting the global community.
To improve understanding of the complex interactions of the
climate system, ecosystems, and human activities and condi-
tions, the research community develops and uses scenarios.
These scenarios provide plausible descriptions of how the
future might unfold in several key areas—socioeconomic, technological
and environmental conditions, emissions of greenhouse gases and
aerosols, and climate. When applied in climate change research,
scenarios help to evaluate uncertainty about human contributions to
climate change, the response of the Earth system to human activities, the
impacts of a range of future climates, and the implications of different
approaches to mitigation (measures to reduce net emissions) and
adaptation (actions that facilitate response to new climate conditions).
Traditionally, model-based scenarios used in climate change
research have been developed using a sequential process focused on a
step-by-step and time-consuming delivery of information between
separated scientific disciplines. Now, climate change researchers from
different disciplines have establisheda new coordinatedparallel process
for developing scenarios. This starts with four scenarios of future radi-
ative forcings (the change in the balance between incoming and out-
going radiation to the atmosphere caused by changes in atmospheric
constituents, such as carbon dioxide). Using this starting point, the
parallel process will encourage research that will characterize a broad
range of possible futureclimate conditions, taking into account recent
climate observations and new information about climate system pro-
cesses. Studies will give more attention to evaluating adaptation needs
and strategies, exploring mitigation options, and improving under-
standing of potentially large feedbacks (that is, impacts of climate
change such as melting of permafrost or dieback of forests that cause
further changes in climate).
Central to the new parallel process is the concept that the four
radiative forcing pathways can be achieved by a diverse range of socio-
economic and technological development scenarios. Among other
issues, the parallel process facilitates exploration of the question
‘What are the ways in which the world could develop in order to reach
a particular radiative forcing pathway?’ An immediate consequence of
this new approach will be heightened collaboration between impacts,
adaptation and vulnerability research, and climate and integrated
assessment modelling (Box 1). This will improve the analysis of com-
plex issues, such as the costs, benefits and risks of different policy
choices and climate and socioeconomic futures. The parallel process
will reduce the time lags between the creation of emissions scenarios,
their use in climate modelling, and the application of the resulting
climate scenarios in research on impacts, adaptation and vulnerability.
This Perspective provides an overview of how scenarios are used in
climate change research, and summarizes the new process initiated
with ‘representative concentration pathways’ (RCPs) that will pro-
vide a framework for modelling in the next stages of scenario-based
research. Additional information can be found in refs 1–4.
Alternative futures
The use of scenarios originated in military planning and gaming, and
in the early 1960s was extended into strategic planning in businesses
and other organizations where decision makers wanted to analyse, in
a systematic way, the implications of investment and other strategic
decisions with long-term consequences
. The goal of working with
scenarios is not to predict the future, but to better understand un-
certainties in order to reach decisions that are robust under a wide
range of possible futures
Joint Global Change Research Institute, Pacific Northwest National Laboratory/University of Maryland, 5825 University Research Court, Suite 3500, College Park, Maryland 20740,
National Center for Atmospheric Research, Climate and Global Dynamics Division, 1850 Table Mesa Drive, Boulder, Colorado 80305, USA.
New Zealand Climate Change
Research Institute, Victoria University of Wellington, PO Box 600, Wellington, New Zealand.
Electric Power Research Institute, 2000 L Street NW, Suite 805, Washington DC 20036,
Netherlands Environmental Assessment Agency, Postbus 303, 3720 AH Bilthoven, The Netherlands.
Finnish Environment Institute, Box 140, Mechelininkatu 34a, Helsinki
00251, Finland.
National Institute for Environmental Studies, 16-2, Onogawa, Tsukuba 305-8506, Japan.
Met Office, Fitzroy Road, Exeter, Devon EX1 3PB, UK.
International Institute
for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria.
Vienna University of Technology, Karlsplatz 13, A-1040 Vienna, Austria.
Geophysical Fluid Dynamics
Laboratory, National Oceanic and Atmospheric Administration, Princeton, New Jersey 08542, USA.
Stanford University, Stanford, California 94305, USA.
Environmental Sciences
Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
Vol 463j11 February 2010jdoi:10.1038/nature08823
Macmillan Publishers Limited. All rights reserved
In climate change research, scenarios describe plausible trajectories
of climate conditions and other aspects of the future. A variety of
techniques have been used, including temporal and spatial analogues
of future climates and model-based scenarios, which are the focus of
this Perspective
. The earliest model-based ‘scenarios’ were stylized
representations of increases in the atmospheric concentrations of
carbon dioxide (a greenhouse gas that retains energy radiating from
the Earth’s surface). Initially a doubling or quadrupling of carbon
dioxide was used as an input to ‘force’ early climate models. These
scenarios provided a coherent basis for using climate models to
address the question, ‘If carbon dioxide concentrations increased by
a specified amount or rate, how might the climate system respond?’
Over time, an increasingly broad array of scenarios has been
developed to address different components of the issue
; we show
in Fig. 1 an historical perspective on the development of scenarios,
some notable applications, and some context. Today, scenarios
represent major driving forces, processes, impacts (physical, eco-
logical and economic) and potential responses important for inform-
ing climate change policy (Fig. 2). Within the overall category of
scenarios, several types are prominent in climate change research.
Emissions scenarios. Emissions scenarios are descriptions of potential
future discharges to theatmosphere of substances that affect the Earth’s
radiation balance, such as greenhouse gases and aerosols. Along with
information on other related conditions such as land use and land
cover, emissions scenarios provide inputs to climate models. They
are produced with integrated assessment models (Box 1) based on
assumptions about driving forces, such as patterns of economic and
population growth, technology development, and other factors. Over
time, the information provided by integrated assessment models and
used in climate models has become increasingly comprehensive,
including time-dependent emissions of radiatively significant gases
and particles, precursor pollutant compounds, and land cover and use.
In addition to their use as inputs to climate models, emissions
scenarios are used to explore alternative energy and technology
futures. This allows exploration of what changes in technologies,
economic development, policy, or other factors would be required
to shift emissions from a baseline to a lower path—for example,
keeping greenhouse gas concentrations (or global average surface air
temperature increases) below a specified level. They can be used to
analyse the need for and the value of technology, and the implications
of choices to limit radiative forcing to prescribed limits. Although
scenario outputs include emissions and land use/cover, they also
include drivers of change, such as patterns and rates of economic
growth, demographic change, technology, policy and other factors
that are important for the assessment of the impacts of climate
Emissions scenarios for climate change research are not forecasts
or predictions, but reflect expert judgments regarding plausible
future emissions based on research into socioeconomic, environ-
mental, and technological trends represented in integrated assess-
ment models. Emissions scenarios for climate change research do
not track ‘short-term’ fluctuations, such as business cycles or oil
market price volatility. Instead, they focus on long-term (decades
to centuries) trends in energy and land-use patterns. The long-term
focus is necessary for evaluating the slow response of the climate
system (centuries) to changing concentrations of greenhouse gases.
The long-term focus also reflects the long time horizon for retiring
and replacing many components of energy and economic infrastruc-
ture. Uncertainty in emissions scenarios results from the inherent
uncertainty of future socioeconomic and technology conditions,
uncertainty in the policy environment, and differences in representa-
tions of processes and relationships across integrated assessment
models, among other factors. An underlying key issue is whether
probabilities can be usefully associated with scenarios or different
Notable applications
1896 Arrhenius’
estimates CO2-
warming 64
1960 Keeling
CO2 is
increasing 65
1967 Modelled
estimates of
sensitivity 62
1969 Coupled
GCM 63
1970s Scenarios
used to explore
natural resource
sustainability 23–26
1980s Scenarios
mainstream in
research 27–29
1980 World
1988 GCM
simulations using
(transient) scenarios
indicate the signal of
anthropogenic climate
warming would soon
emerge from natural
variability 66
1983 Villach
and ecosystem
impacts with
scenarios 67
1985 Second
Villach Conference
estimates mid 21st
century rise of
global mean
greater than any in
human history 68
1990 IPCC
scenarios 36
1990 IPCC First
Assessment Report
uses analogue and
equilibrium climate
scenarios for
impact assessment
1988 IPCC
1992 IPCC IS92
scenarios 30
1991 Impact
based on
scenarios 66, 69
1994 IPCC
guidelines 70
Scenario development
Figure 1
Timeline highlighting some notable developments in the creation and use of emissions and climate scenarios. The entries are illustrative of the
overall course of model-based scenario development (blue) and application (beige) described in this Perspective, and also give some context (green); they do
PERSPECTIVES NATUREjVol 463j11 February 2010
Macmillan Publishers Limited. All rights reserved
levels of radiative forcing; for example, the probability that concen-
trations will stabilize above or below a specified level
Climate scenarios. Climate scenarios are plausible representations
of future climate conditions (temperature, precipitation and other cli-
matological phenomena). They can be produced using a variety
of approaches including: incremental techniques where particular cli-
matic (or related) elements are increased by plausible amounts; spatial
and temporal analogues in which recorded climate regimes that may
resemble the future climate are used as example future conditions; other
techniques, such as extrapolation and expert judgment; and techniques
that use a variety of physical climate and Earth system models, including
regional climate models
. All of these techniques continue to play a
useful role in development of scenarios, with the appropriate choice of
method depending on the intended use of the scenario
major advances are expected with model-based approaches. There is
a notable increase in interest in regional-scale climate scenarios and
projection methods, especially for impact and adaptation assessment
Environmental scenarios. Analysis of the potential impact of a par-
ticular climate scenario requires environmental scenarios of eco-
logical and physical conditions at greater detail than is included in
climate models. These scenarios focus on changes in environmental
conditions other than climate that may occur regardless of climate
change. Such factors include water availability and quality at basin
levels (including human uses), sea level rise incorporating geological
and climate factors, characteristics of land cover and use, and local
atmospheric and other conditions affecting air quality. Climate
change merges with these factors, and in many cases, the potential
impact of climate change and effectiveness of adaptation options
cannot be understood without examining these interactions
Vulnerability scenarios. Finally, scenarios of factors affecting vul-
nerability, such as demographic, economic, policy, cultural and insti-
tutional characteristics are needed for different types of impact
modelling and research. This information is crucial for evaluating
the potential of humankind to be affected by changes in climate, as
well as for examining how different types of economic growth and
social change affect vulnerability and the capacity to adapt to potential
impacts. Although some of these factors can be modelled and applied
at regional or national scales
, for the most part data at finer spatial
resolution are required. An increasing body of literature, including
some using integrated assessment models, is exploring alternative
methods for the quantitative and qualitative ‘downscaling’ of these
vulnerability factors in a way that is consistent with the socioeconomic
assumptions underlying global emissions scenarios
Earlier scenario work. Antecedents of contemporary global scenarios
were developed in ‘futuresstudies’ that exploredthe long-term sustain-
ability of natural resources
and the implications of global energy
needs for future CO
emissions and concentrations
. The Inter-
governmental Panel on Climate Change (IPCC) has used emissions
and climate scenarios as a central component of its work of assessing
climate change research. It stimulated development of the field by
commissioning several sets of emissions scenarios for use in its reports.
In earlier emissions scenario exercises, the IPCC convened authors and
modellers, provided terms of reference, and approved the scenarios
through an intergovernmental process that took several years. The
1990 IPCC scenario A (SA90)
set explored four emissions pathways,
including a ‘business as usual’ future and three policy scenarios. They
were followed by the 1992 IPCC scenarios (IS92)
that played out the
implications of uncertainties in economic growth, population and tech-
nology in a number of business as usual energy and economic futures.
The latest set of scenarios from the IPCC, contained in the Special
Report on Emissions Scenarios (SRES)
, investigated the uncertainty
of future greenhouse gas and short-lived pollutant emissions given a
wide range of driving forces. Some of the cases explored the implica-
tions of economic convergence between developed and developing
generator for
non-specialists 71
Comparison of
global vegetation
model results
using equilibrium
GCM 2 × CO2 72
1995 IPCC
Report uses
scenarios in
impact report
1996 Country
studies of
impacts 73
published 74
1998 IPCC
regional impacts
(using IS92) 75
1999 SRES,
no climate policies
included 32
2000 Pattern
scaling of IS92-
based climate
projections to
emulate SRES 76 2001
assessment of
scenarios 77
2001 IPCC
Report impact
results using
IS92 scenarios
2001 Socio-
scenarios 78
2004 Regional
projections of
temperature and
precipitation based
on SRES 79
2005 Scenarios
and model
comparison of
options for non-
CO2 GHGs 80
2007 IPCC ‘new
scenarios’ expert
meeting 3 and model
comparison of
economic and
technological pathways
to stabilize radiative
forcing at several
levels 48
2007 IPCC Fourth
Report uses SRES
and IS92 scenarios
for impacts
2007 IAMC founded
2009 RCPs
released, starting
‘parallel phase’ of
new scenario
2009 UK
national climate
projections 81
and extension
of methodology
for probabilistic
projections 82
2009 World
Conference 3
of capacity to
respond to the
needs of users
of climate
not provide a comprehensive account of all major scenarios and significant studies or assessments that have used them. See Supplementary Information for
details. GCM, general circulation model; GHG, greenhouse gas; IAMC, Integrated Assessment Modelling Consortium.
NATUREjVol 463j11 February 2010 PERSPECTIVES
Macmillan Publishers Limited. All rights reserved
countries. Unlike previous emissions scenarios, the quantitative SRES
projections were complemented by ‘storylines’ or narratives of the
future, which facilitated the interpretation of the scenarios. Unlike
previous scenarios that were developed using only one or two models,
the SRES scenarios were produced through an ‘open process’ involving
many different modellingteams. The IS92 and SRES scenarios assumed
there were no policy actions to mitigate climate change.
Many other organizations have developed scenarios that include
greenhouse gas emissions and their interactions with other socio-
economic and environmental systems (for example, the International
Energy Agency
and the Millennium Ecosystem Assessment
played a substantial role in shaping the scenario development process
(the Energy Modelling Forum). Overviews of scenario development in
climate change research are available
(see also timeline in Fig. 1).
Motivations for new scenarios
Although the previous IPCC scenarios and process have been produc-
tive, new scenarios and a new process for selecting and using them are
needed. Nearly a decade of new economic data, information about emer-
ging technologies, and observations of environmental factors such as
land use and land cover change should be reflected in new scenarios
End users,including policymakers, have new information needsthat
require changes in scenario focus. For example, there is a high level of
interest in climate scenarios that explore different approaches to miti-
gation in addition to the traditional ‘no climate policy’ scenarios. As a
result, an increasing number of scenarios are being developed to
explore conditions consistent with managed long-run climate out-
comes, including a 2 uC maximum global average surface temperature
increase over pre-industrial levels, as well as ‘overshoot’ scenarios in
which radiative forcing peaks and then declines to a target level
addition, increasing attention to the impacts of climate change and the
need for adaptation has spawned an interest in climate scenarios that
focus on the next two to three decades with higher spatial and temporal
resolution and improved representation of extreme events. Analysis of
adaptation also requires development of socioeconomic scenarios suit-
able to support analysis of vulnerability.
Box 1 jModels and frameworks
Scenarios are generated and used by three broad types of models and
analytic frameworks in climate change research: integrated assessment
models, climate models, and models and other approaches used to help
assess impacts, adaptation and vulnerability.
(1) Integrated assessment models represent key features of human
systems, such as demography, energy use, technology, the economy,
agriculture, forestry and land use. They also incorporate simplified
representations ofthe climatesystem, ecosystems, andin some cases,climate
. These simplified representations are calibrated against more
complex climate and impact models. Because of their breadth, these models
integrate information needed to study the interactions of human systems
(including potential climate policies) and environmental processes that affect
climate change and its impacts. Integrated assessment models typically
disaggregate the world into a dozen or more regions with time steps of about a
decade. Integrated assessment models are used to develop emissions
scenarios, estimate the potential economic impacts of climate change and the
costs and benefits of mitigation, simulate feedbacks, and evaluate
uncertainties. Because they are increasingly comprehensive and include more
detail about air pollutant emissions and land use, these models are increasingly
important for research on the interaction of climate change with other policy
objectives (such as air-pollution control and biodiversity protection).
(2) Climate models
are numerical representationsof the Earth’s natural
systems used to study how climate responds to changes in natural and
human-induced perturbations. There are a wide variety and complexity of
climate models. Atmosphere
ocean general circulation models are the most
complex physical climate models, and include components that simulate
interactions of the atmosphere, ocean, land and sea ice. They divide the
atmosphere and oceans into thousands of grid cells, and include interactive
land-surface and biophysical processes. Regional climate models focus on
subcontinental scale geographies at finer resolution. Earth system models are
based on physical climate models, and include additional ecological and
chemical processes, such as the land and ocean carbon cycle, vegetation and
atmospheric chemistry,which respondto changes in climate simulated by the
model. Earth system models of intermediate complexity represent many of
the key systems and processes, but with simplified equations and reduced
spatial resolution. These models are useful for sensitivity experiments,
questions involving long timescales (hundreds to thousands of years), or when
a large number of simulations are required. Simple climate models incorporate
fewer detailed processes in the atmosphere
ocean system and at coarser
spatial scales. They are useful for exploring key uncertainties and have been
incorporated into many integrated assessment models.
(3) Assessing impacts, adaptation and vulnerability to climate change
depends on a widearray of methods and tools that includes both quantitative
and qualitative approaches. Prominent approaches include observations,
modelling, assessment techniques that engage stakeholders in participatory
processes, economic evaluation methods and decision analysis
models and frameworks span the range from biophysical to economic, and
explore the consequences of changes in climate for climate-sensitive
resources and activities, such as agriculture, water resources, human health,
ecosystems and coastal infrastructure. These frameworks inform decision
makers of the potential risks and opportunities presented by climate change,
and provide a means of evaluating the impacts associated with different
magnitudes of climate change and the comparative effectiveness of various
response strategies and management options. When impact models include
representations of changes in fluxes ofgreenhouse gases tothe atmosphere
from natural and managed systems, they are useful for studying climate
system ‘feedbacks’; for example, from forest dieback or permafrost melting.
The figure depicts the domains of the three sets of models and
, and illustrates that the models increasingly are covering
overlapping substantive domains, which underscores the importance of
coordination and consistency in using scenarios.
Energy The economy
Agriculture and
settlement and
Sea level rise
Integrated assessment
Imapacts, adaptation and
Climate models
PERSPECTIVES NATUREjVol 463j11 February 2010
Macmillan Publishers Limited. All rights reserved
Scientific advances also motivate interest in new scenarios within
the scientific community. Interest in modelling future climate condi-
tions nearer to a long-term equilibrium across components of the
climate system, such as the oceans and the ice sheets, has created a
demand for emissions scenarios to extend well beyond the conven-
tional 2100 end-point
. Simultaneously, climate models are becom-
ing more comprehensive and incorporating the oceanic and terrestrial
carbon cycle, aerosols, atmospheric chemistry, ice sheets and dynamic
. As more physical processes are simulated, more
detailed emissions scenarios are required, along with higher resolution
and more consistent land-use and land-cover data and projections.
Finally, increasing the overlap in the substantive domains of climate,
impact and integrated assessment models (Box 1) creates a demand for
harmonization of assumptions and data on some initial conditions,
within the limits posed by historical and observational uncertainties.
Apart from responding to new opportunities and information
needs, a new process for developing scenariosis needed in part because
the IPCC decided at its twenty-fifth session in 2006 not to commission
another set of emissions scenarios, leaving new scenario development
to the research community. IPCC instead limited its role to catalysing
and assessing the large and growing scenario literature. The research
community responded by, among other things, creating this new
process to provide cross-disciplinary coordination. Finally, a new
process that shortens development time and leads to greater coordi-
nation will facilitate additional scientific advances, including
increased understanding of different types of feedbacks and improved
synthesis of research on adaptation, mitigation and damages incurred
and avoided by different policy options.
Redesigned scenario process
The earlier sequential approach. Until now, scenarios were
developed and applied sequentially in a linear causal chain that
extended from the socioeconomic factors that influence greenhouse
gas emissions to atmosphericand climate processes to impacts (Fig. 3).
This sequential process involved developing emissions scenarios
based on different socioeconomic futures, estimating concentrations
and radiative forcing from emissions, projecting the ensuing climate,
and then using those scenarios in impact research. The process led to
inconsistency because of delays between the development of the
emissions scenarios, their use in climate modelling, and the availabil-
ity of the resulting climate scenarios for impact research and assess-
ment. For example, work on the SRES scenarios
started in 1997 and
took approximately three years to complete (Fig. 1). The first climate
model results using these scenarios as inputs were assessed in the 2001
IPCC Third Assessment Report, but not until 2007, when the IPCC
published its Fourth Assessment Report, was a more complete set of
SRES-driven climate scenarios available and impact, adaptation and
vulnerability research using these scenarios assessed by IPCC. By this
time, results from a new generation of climate models were being
assessed in the same report, thus creating inconsistencies between the
new climate scenarios and the older ones used in the impact studies.
This complicated the synthesis of results on issues such as costs and
benefits, and created challenges when comparing feedbacks from
different models.
The parallel approach. To shorten the time between the development
of emissions scenarios and the use of the resulting climate scenarios in
impact research, as well as to address the key information needs of
users more effectively, the integrated assessment, climate and impact
research communities have cooperated to devise an alternative ‘par-
allel’ approach for creating and using scenarios (Fig. 4). Rather than
starting with detailed socioeconomic storylines to generate emissions
and then climate scenarios, the parallel process begins with the iden-
tification of important characteristics for scenarios of radiative
forcings for climate modelling, the most prominent of which is the
level of radiative forcing in the year 2100. These radiative forcing
trajectories are not associated with unique socioeconomic or emissions
scenarios, and instead can result from different combinations of eco-
nomic, technological, demographic, policy and institutional futures
Climate variability
and change
H2O, CO2, CH4, N2O, O3, etc.
ice interaction
cycle Carbon
and responses
Land surface
Sea ice
Ocean circulation, sea levels,
Land-use/land-cover change
Figure 2
Major natural and anthropogenic processes and influences on
the climate system addressed in scenarios. The climate system consists of
five interacting components: the atmosphere, the hydrosphere, the
cryosphere, the land surface and the biosphere. Scenarios of emissions and
other drivers are used to assess the impact of a range of human activities on
these components. Changes in climate described in climate scenarios are
major drivers of changes in both natural and human systems. Impacts on
ecosystems, natural resources, economic activities and infrastructure, and
human well-being, depend not only on climate change, but also on other
changes in the environment (depicted in environmental scenarios) and the
capacity of societies and economies to buffer and adapt to impacts
(addressed in scenarios of vulnerability and adaptive capacity). Closer
integration of scenarios is required to address feedback loops and other
issues, such as the ecological and economic implications of different sets of
adaptation and mitigation policies. Figure from ref. 83.
NATUREjVol 463j11 February 2010 PERSPECTIVES
Macmillan Publishers Limited. All rights reserved
(for comparisons of how different emissions scenarios generated with
different integrated assessment models stabilize at specified target
levels, see refs 47, 48).
Climate models require data on the time-evolving emissions or
concentrations of radiatively active constituents, and some have
additional requirements for information about the time-evolving
paths for land use and land cover. The research community identified
a specific emission scenario (including data on land use and land
cover) from the peer-reviewed literature as a plausible pathway
towards reaching each target radiative forcing trajectory (Table 1;
the selection process and criteria are described more fully below).
These were given the label ‘representative concentration pathways’
(RCPs). The word ‘representative’ signifies that each RCP provides
only one of many possible scenarios that would lead to the specific
radiative forcing characteristics. The term ‘pathway’ emphasizes that
not only the long-term concentration levels are of interest, but also
the trajectory taken over time to reach that outcome. In summary, the
new parallel process starts with the selection of four RCPs, each of
which corresponds to a specific radiative forcing pathway.
In the ‘parallel phase’ of the process, climate and integrated assess-
ment modellers will work simultaneously rather than sequentially.
The climate modellers will conduct new climate model experiments
and produce new climate scenarios using the time series of emissions
and concentrations from the four RCPs. The focus on a few, well-
spaced RCPs will produce discernible climate change outcomes from
one RCP to another, save computational resources, and thus make it
possible to conduct additional new types of experiments.
At the same time as the climate modellers are preparing simula-
tions with the RCPs, the integrated assessment modellers will develop
an ensemble of new socioeconomic and emissions scenarios. Because
this work is done in parallel rather than sequentially, the process is
shortened by the time previously devoted to up-front development of
emissions scenarios. The new ensemble of integrated assessment
model scenarios will constitute an important complement to the
RCPs, because they will help to identify the range of different tech-
nological, socioeconomic and policy futures that could lead to a
particular concentration pathway and magnitude of climate change.
This will encourage new research into novel approaches to meet
Integration of climate
and socio-economic
• Integrated
• Pattern scaling
• Downscaling of
climate and
• …
Radiative forcing
New research
and assessments
• Impact,
• Climate
• Model
• …
Broad range
forcing in 2100
Shape of radiative
forcing over time
pathways (RCPs)
(four pathways from
existing literature)
• Greenhouse gases
• Short-lived gases
and aerosols
• Land cover/use
New socio-economic and
emissions scenarios;
vulnerability storylines
• Adaptation
• Mitigation
• Stabilization
• Overshoots
• …
Climate scenarios
• Near-term (2035)
• Long-term (2100+)
• Regional climate
• Pattern scaling methods
2008 2009 2010 2011 2012 2013
with RCPs
of the RCPs
Figure 4
The parallel process. This figure depicts the process of
developing new scenarios that will be used in future climate change research
and impacts assessments. The process began with identification of radiative
forcing characteristics that support modelling of a wide range of possible
future climates. Representative concentration pathways (RCPs) were
selected from the published literature to provide needed inputs of emissions,
concentrations and land use/cover for climate models. In parallel with
development of climate scenarios based on the RCPs, new socio-economic
scenarios (some consistent with the radiative forcing characteristics used to
identify the RCPs and some developed to explore completely different
futures and issues) will be developed to explore important socio-economic
uncertainties affecting both adaptation and mitigation. Using a variety of
tools and methods, such as pattern scaling, the new socio-economic
scenarios will be integrated with the new climate scenarios. New research
using the integrated scenarios will explore adaptation, mitigation and other
issues such as feedbacks, using consistent assumptions. This research will
provide insights into the costs, benefits and risks of different climate futures,
policies and socio-economic development pathways.
• Population
• Energy
• Industry
• Agriculture
• …
• Greenhouse
gases (CO2,
CH4, N2O, …
• Aerosols and
active gases
(SO2, BC, OC,
CO, NOx,
• Land use and
land cover
• Atmospheric
Carbon cycle –
including ocean
and terrestrial
• Atmospheric
• Temperature
• Precipitation
• Humidity
• Soil moisture
• Extreme
• …
Coastal zones
Hydrology and
water resources
• Ecosystems
• Food security
• Infrastructure
• Human health
• …
Figure 3
Sequential approach. This figure depicts the simple linear chain
of causes and consequences of anthropogenic climate change. Scenarios were
developed on the basis of this sequence, and handed from one research
community to the next in a lengthy process that led to inconsistencies. GDP,
gross domestic product; BC, black carbon; OC, organic carbon; VOCs,
volatile organic compounds. Figure adapted from ref. 11.
PERSPECTIVES NATUREjVol 463j11 February 2010
Macmillan Publishers Limited. All rights reserved
targets identified by policy makers. In addition, the integrated assess-
ment modellers will develop entirely new scenarios with different
radiative forcing pathways to explore additional issues and un-
certainties. For example, new reference scenarios will be developed
to explore alternative demographic, socioeconomic, land use, and
technology scenario backgrounds. Scenarios will becreated to explore
alternativestabilization levels, including higher overshoot pathways, as
well as the technology, institutional, policy and economic conditions
associated with these pathways. Other scenarios will be developed to
explore uncertainties in processes such as the terrestrial carbon cycle,
the ocean carbon cycle and the atmospheric chemistry of aerosols. A
variety of new regionally based scenarios will be developed using
regional models by research teams in developing and transition-
economy countries. The process by which new scenarios will be pro-
duced and the nature of coordination across research teams is not
specified here and remains to be determined.
The socioeconomic assumptions underlying the new emissions
scenarios (along with information about the spatial distribution of
these characteristics, when possible) will be used to develop scenarios
of factors affecting vulnerability, and will then be paired with climate
model results to provide consistent inputs for impact, adaptation and
vulnerability research. It is an open research question how wide a
range of socioeconomic conditions could be consistent with a given
forcing pathway, including its ultimate level, pathway over time and
spatial pattern; however, the range of underlying socioeconomic
scenarios that are consistent is potentially very wide (carbon cycle
uncertainties are among the major unknowns affecting scenario
A significant portion of the new research anticipated to result from
the RCPs and the subsequent process will be assessed in the IPCC’s
Fifth Assessment Report, now under way and scheduled for release
during 2013 and 2014.
Selection process for the RCPs
A careful selection process was used to identify the RCPs, using
criteria that reflected the needs of both climate scenario developers
and users
. As a user of the RCPs and the ensuing research, the IPCC
requested the development of new scenarios compatible with the
literature of reference and mitigation scenarios and helped catalyse
the selection process. The criteria established by the research com-
munity included compatibility ‘with the full range of stabilization,
mitigation, and reference emissions scenarios available in the current
scientific literature’
; a manageable and even number of scenarios (to
avoid the inclination with an odd number of cases to select the central
case as the ‘best estimate’); an adequate separation of the radiative
forcing pathways in the long term in order to provide distinguishable
forcing pathways for the climate models; and the availability of model
outputs for all relevant forcing agents and land use. The scientific
community used these criteria to identify four radiative forcing path-
ways, and a new Integrated Assessment Modelling Consortium
(IAMC), comprising 45 participating organizations (http://www., then assembled a list of candidate scenarios
for each radiative forcing level from the peer-reviewed literature.
The selection process relied on previous assessment of the literature
conducted by IPCC Working Group III during development of the
Fourth Assessment Report
. Of the 324 scenarios considered, 32 met
the selection criteria and were able to provide data in the required
format. An individual scenario was then selected for each RCP
(Table 1). The final RCP selections (RCP2.6, RCP4.5, RCP6.0 and
RCP8.5) were made on the basis of discussions at an IPCC expert
Table 1
The four RCPs
Name Radiative forcing Concentration
Pathway Model providing RCP*Reference
in 2100 .1,370 CO
-equiv. in 2100 Rising MESSAGE
at stabilization after 2100 ,850 CO
-equiv. (at stabilization after 2100) Stabilization without
at stabilization after 2100 ,650 CO
-equiv. (at stabilization after 2100) Stabilization without
RCP2.6Peak at ,3Wm
before 2100 and
then declines
Peak at ,490 CO
-equiv. before 2100 and
then declines
Peak and decline IMAGE
*MESSAGE, Model for Energy Supply Strategy Alternatives and their General Environmental Impact, International Institute for Applied Systems Analysis, Austria; AIM, Asia-Pacific Integrated
Model, National Institute for Environmental Studies, Japan; GCAM, Global Change Assessment Model, Pacific Northwest National Laboratory, USA (previously referred to as MiniCAM); IMAGE,
Integrated Model to Assess the Global Environment, Netherlands Environmental Assessment Agency, The Netherlands.
Radiative forcing (W m–2)
GCAM 4.5
AIM 6.0
Emissions (Gt CO2)
GCAM 4.5
AIM 6.0
Figure 5
Representative concentration pathways. a, Changes in radiative
forcing relative to pre-industrial conditions. Bold coloured lines show the
four RCPs; thin lines show individual scenarios from approximately 30
candidate RCP scenarios that provide information on all key factors
affecting radiative forcing from ref. 47 and the larger set analysed by IPCC
Working Group III during development of the Fourth Assessment Report
b, Energy and industry CO
emissions for the RCP candidates. The range of
emissions in the post-SRES literature is presented for the maximum and
minimum (thick dashed curve) and 10th to 90th percentile (shaded area).
Blue shaded area corresponds to mitigation scenarios; grey shaded area
corresponds to reference scenarios; pink area represents the overlap between
reference and mitigation scenarios.
NATUREjVol 463j11 February 2010 PERSPECTIVES
Macmillan Publishers Limited. All rights reserved
meeting in September 2007, a subsequent open review of proposed
selections involving many modelling teams and users, and the re-
commendation of an ad hoc committee convened to review alterna-
tives for the lowest RCP
The IAMC coordinated preparation of the RCP data in consultation
with the climate modelling and impact research communities
regional and spatial RCP data for the climate simulations is publicly
available through the IAMC-RCP database (
Figure 5 illustrates how the selected RCPs represent the literature in
terms of radiative forcing (Fig. 5a) and energy and industry CO
emissions (Fig. 5b). The selected set of RCPs spans the range of radi-
ative forcing scenarios in the published literature at September 2007.
For energy and industry CO
emissions, RCP8.5 represents the 90th
percentile of the reference emissions range, while RCP2.6 represents
pathways below the 10th percentile of mitigation scenarios. They are
also similarly representative of emissions of greenhouse gases and
particles other than CO
(refs 3, 47, 49 and 51).
The RCPs provide a starting point for new and wide-ranging
research. However, it is important to recognize their uses and limits.
They are neither forecasts nor policy recommendations, but were
chosen to map a broad range of climate outcomes. The RCPs cannot
be treated as a set with consistent internal logic. For example, RCP8.5
cannot be used as a no-climate-policy reference scenario for the other
RCPs because RCP8.5’s socioeconomic, technology and biophysical
assumptions differ from those of the other RCPs.
New products and collaborations
Two sets of climate projections will be developed using the RCPs, one
focusing on the near term (to 2035) and the other extending to 2100
and beyond (the Coupled Model Intercomparison Project, Phase 5
(CMIP5) was used to coordinate the experimental design for climate
modelling leading to the Fifth Assessment Report
). The near-term
climate projections (mainly comprising ‘decadal predictions’
) will
use the single mid-range RCP4.5, because the radiative forcing in the
different RCPs does not diverge appreciably until after this time
period (Fig. 5a). Because multiple scenarios do not need to be run
to span radiative forcing uncertainties, it is possible to run the models
at higher resolution and to prepare larger ensembles (a group of
model experiments used to analyse uncertainty) to improve under-
standing of likely extremes, thereby aiding evaluation of impacts and
adaptation needs for the coming decades. Another set of runs will
provide long-term climate projections to the year 2100, with some
pathways extended to 2300. These extended pathways will be used
for comparative analysis of the long-term climate and environmental
implications of different mitigation scenarios or pathways. ‘Pattern-
scaling’ methods, which use the outcomes of simple climate models
to scale the patterns of climate change produced by complex climate
models to correspond to different emissions scenarios, will be further
evaluated and developed
The new process will increase collaboration among researchers
working on impacts, adaptation and vulnerability with climate and
integrated assessment modellers. One area of collaboration is prepara-
tion of narrative storylines and quantitative vulnerability scenarios
that are coordinated with emissions scenarios, thus encouraging
more impact research that is coordinated explicitly with emissions
and climate scenarios. This will extend the use of socioeconomic
scenarios, which previously have been used more to project green-
house gas emissions than to assess adaptive capacity and vulnerability.
The narratives will provide an interpretative tool for relating the
scenarios to conditions that affect vulnerability at the local and
regional scales at which many impact studies are undertaken. In addi-
tion, downscaled socioeconomic data for consistent, comparable
research on impacts, adaptation and vulnerability will be developed
and evaluated. Results from impact studies using the RCPs will feed
back into climate and integrated assessment modelling.
New climate-policy-intervention scenarios will provide insights
on reducing or stabilizing concentrations of greenhouse gases. For
example, it is anticipated that scenarios will consider land-use and
land-cover choices that include bioenergy production in a world that
is also adapting to climate change. Much work is expected to focus on
low stabilization levels and overshoot scenarios in response to grow-
ing policy interest (Table 1 and Fig. 5a).
Another anticipated advance is the development of integrated
Earth system models that incorporate integrated assessment models,
climate models and impact models. Whereas integrated Earth system
models will not replace the three existing classes of models, they will
bring them closer together than ever before and enable new insights
into the challenge of integrating adaptation and mitigation in climate
change risk management.
Concluding comments
This new generation of scenarios will improve society’s understand-
ing of plausible climate and socio-economic futures. The importance
of the new scenarios is matched by the importance of the increased
level of communication and collaboration across different groups of
The new process is only a first step toward the goal of integrating
the now separate tasks of developing scenarios, making projections
and evaluating the impact of the projections. Next steps for further
strengthening the process include establishing mechanisms for
ongoing coordination and information exchange, integrating data
and information systems, and improving support for users. Institu-
tions for coordination and knowledge management across groups
working on impacts, adaptation and vulnerability need to be
strengthened. In addition, the scenario process will need to continue
to evolve to increase the involvement of researchers and users from
developing countries to focus additional attention on crucial inter-
actions among development strategies, adaptation and mitigation.
These steps will improve the climate change impact and response
knowledge base, contribute to the development of socioeconomic
scenarios as a tool for assessing climate change risks and vulner-
abilities, and increase the use of climate scenarios as one starting
point for impact and response analysis.
Realizing the potential benefits of the new process also depends on
a number of scientific advances. Improvement in the representation
of the terrestrial carbon cycle in climate and integrated assessment
models is necessary to reconcile how human use of land resources
interacts with potential climate change impacts on, for instance,
vegetation and carbon cycling. If decadal prediction is to become
skilful, progress in understanding the physical climate system and
new approaches for data assimilation and initialization of models are
needed. Communicating decadal predictions in a way that is useful to
society at large is also a great challenge. Developing new approaches
for making socioeconomic scenarios more useful for research on
adaptive capacity and vulnerability is essential to improving our
ability to compare the consequences of adaptation and mitigation
strategies. Managing the cascade of uncertainties that span different
types of scenarios and improving characterization of uncertainties
and probabilities for ranges of future forcing and climate change is
necessary to make scenarios more useful to decision makers.
Although scenarios do not offer a crystal ball for the future, the new
coordinated approach for developing and applying them in climate
change research will yield valuable insights into the interaction of
natural and human-induced climate processes, and the potential costs
and benefits of different mixes of adaptation and mitigation policy.
1. Meehl, G. A. & Hibbard, K. A. A Strategy for Climate Change Stabilization
Experiments with AOGCMs and ESMs (WCRP Informal Report No. 3/2007, ICPO
Publication No. 112, IGBP Report No. 57, World Climate Research Programme,
Geneva, 2007).
2. Hibbard, K. A., Meehl, G. A., Cox, P. & Friedlingstein, P. A strategy for climate
change stabilization experiments. Eos 88,217, 219, 221 (2007).
PERSPECTIVES NATUREjVol 463j11 February 2010
Macmillan Publishers Limited. All rights reserved
3. Moss, R. H. et al. Towards New Scenarios for Analysis of Emissions, Climate Change,
Impacts,and ResponseStrategies (IPCC Expert M eeting Report, IP CC, Geneva, 200 8).
4. van Vuuren, D. P. et al. Work plan for data exchange between the integrated
assessment and climate modeling community in support of phase-0 of scenario
analysis for climate change assessment (representative community pathways).
Ææ(6 October 2008).
5. Bradfield, R., Wright, G., Burta, G., Carnish, G. & Van Der Heijden, K. The origins
and evolution of scenario techniques in long range business planning. Futures 37,
812 (2005).
6. Jefferson, M. in Beyond Positive Economics? (ed. Wiseman, J.) 122
(Macmillan, 1983).
7. Kahn, H. & Weiner, A. The Year 2000: A Framework for Speculation on the Next
Thirty-three Years (Macmillan, 1967).
8. World Energy Council. Energy for Tomorrow’s World (Kogan Page, London, 1993).
9. Schwartz, P. The Art of the Long View: Planning for the Future in an Uncertain World
(Doubleday, 1996).
10. Mearns, L. O. et al. in Climate Change 2001: The Physical Science Basis (eds
Houghton, J. T., Ding, Y. & Griggs, D. J.) 739
768 (Cambridge Univ. Press, 2001).
11. Parson, E. A. et al. Global Change Scenarios: Their Development and Use (Sub-report
2.1B of Synthesis and Assessment Product 2.1, US Climate Change Science
Program and the Subcommittee on Global Change Research, Department of
Energy, Office of Biological & Environmental Research, Washington DC (2007).
12. Weyant, J. et al. in Climate Change 1995: Economic and Social Dimensions of Climate
Change (eds Bruce, J. P., Lee, H. & Haites, E. F.) 367
398 (Cambridge Univ. Press,
13. Schneider, S. H. What is ‘‘dangerou s’’ climate change? Nature 411, 17
19 (2001).
14. Grubler, A. & Nakicenovic, N. Identifying dangers in an uncertain climate. Nature
412, 15 (2001).
15. Pittock, A. B., Jones, R. N. & Mitchell, C. D. Probabilities will help us plan for
climate change. Nature 413, 249 (2001).
16. Carter, T. R. et al. General Guidelines on the Use of Scenario Data for Climate Impact
and Adaptation Assessment (Task Group on Data and Scenario Support for Impact
and Climate Assessment (TGICA), IPCC, Geneva, 2007).
17. Christensen, J. H. et al. in Climate Change 2007: The Physical Science Basis (eds
Solomon, S., Qin, D. & Manning, M.) 847
940 (Cambridge Univ. Press, 2007).
18. Carter, T. R. et al. in Climate Change 2001: Impacts, Adaptation and Vulnerability
(eds McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J. & White, K. S.)
190 (Cambridge Univ. Press, 2001).
19. Malone, E. L. & Brenkert, A. L. in The Distributional Effects of Climate Change: Social
and Economic Implications (eds Ruth, M. & Ibarraran, M.) 8
45 (Elsevier Science,
20. Gaffin, S. R., Rosenzweig, C., Xing, X. & Yetman, G. Downscaling and geo-spatial
gridding of socio-economic projections from the IPCC Special Report on
Emissions Scenarios (SRES). Glob. Environ. Change 14, 105
123 (2004).
21. Grubler, A. et al. Regional, national, and spatially explicit scenarios of
demographic and economic change based on SRES. Technol. Forecast. Soc. Change
74, 980
1029 (2006).
22. Van Vuuren, D. P., Lucas, P. & Hilderink, H. Downscaling drivers of global
environmental change. Enabling use of global SRES scenarios at the national and
grid levels. Glob. Environ. Change 17, 114
130 (2007).
23. Meadows, D. et al. The Limits to Growth (Universe Books, 1972).
24. Leontief, W. The Future of the World Economy: A Study on the Impact of Prospective
Economic Issues and Policies on the International Development Strategy (United
Nations, New York, 1976).
25. Herrera, A. et al. Catastrophe or New Society? A Latin American World Model (IDRC,
Ottawa, 1976).
26. Mesarovic, M. & Pestel, E. Mankind at the Turning Point (Dutton, 1974).
27. Ha
¨fele, W., Anderer, J., McDonald, A. & Nakicenovic, N. Energy in a Finite World:
Paths to a Sustainable Future (Ballinger, 1981).
28. Robertson, J. The Sane Alternative
A Choice of Futures (River Basin, 1983).
29. Svedin, U. & Aniansson, B. Surprising Futures: Notes From an International Workshop
on Long-term World Development (Swedish Council for Planning and Coordination
of Research, Stockholm, 1987).
30. Response Strategies Working Group. in Climate Change: The IPCC Scientific
Assessment (eds Houghton, J. T., Jenkins, G. J. & Ephraums J. J.) 329
(Cambridge Univ. Press, 1990).
31. Leggett, J., Pepper, W. J. & Swart, R. J. in Climate Change 1992: The Supplementary
Report to the IPCC Scientific Assessment (eds Houghton, J. T., Callander, B. A. &
Varney, S. K.) 69
95 (Cambridge Univ. Press, 1992).
32. Nakic
´,N.,et al. Special Report on Emissions Scenarios: A Special Report of
Working Group III of the Intergovernmental Panel on Climate Change (Cambridge
Univ. Press, 2000).
33. World Energy Outlook (International Energy Agency, Paris, 2009).
34. Millennium Ecosystem Assessment. Ecosystems and Human Well-being: Scenarios,
Vol. 2 (eds Carpenter, S. R. et al.) xix
551 (Island Press, 2005).
35. Alcamo, J. et al. in Climate Change 1994: Radiative Forcing of Climate Change and an
Evaluation of the IPCC IS92 Emission Scenarios (eds Houghton, J. T. et al.) 247
(Cambridge Univ. Press, 1995).
36. Carter, T. R. et al. in Climate Change 2007: Impacts, Adaptation and Vulnerability
(eds Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. & Hanson, C.
E.) 133
171 (Cambridge Univ. Press, 2007).
37. Hurtt, G. C. et al. Harmonization of global land-use scenarios for the period1500-
2100 for IPCC-AR5. iLEAPS Newsl. 7, 6
8 (2009).
38. Clarke, L. & Weyant, J. Introduction to the EMF Special Issue on climate change
control scenarios. Energy Econ. 31, S63
S81 (2009).
39. Huntingford, C. & Lowe, J. Overshoot scenarios and climate change. Science 316,
829 (2007).
40. Wigley, T. M. L., Richels, R. & Edmonds, J. in Human-Induced Climate Change: An
Interdisciplinary Perspective (eds Schlesinger, M. et al.)84
92 (Cambridge Univ.
Press, 2007).
41. Calvin, K. et al. Limiting climate change to 450 ppm CO
equivalent in the 21st
century. Energy Econ. 31, S107
S120 (2009).
42. Rao, S. et al. IMAGE and MESSAGE Scenarios Limiting GHG Concentration to Low
Levels (IIASA Interim Report IR-08-020, International Institute for Applied
Systems Analysis, Laxenburg, Austria, 2008).
43. Taylor, K. E., Stouffer, R. J. & Meehl, G. A. A summary of the CMIP5 experimental
design. Æ
submenuheader51æ(18 December 2009).
44. Randall, D. A. et al. in Climate Change 2007: The Physical Science Basis (eds
Solomon, S., Qin, D. & Manning, M.) 589
662 (Cambridge Univ. Press, 2007).
45. Cox, P. M. et al. Acceleration of global warming due to carbon-cycle feedbacks in a
coupled climate model. Nature 408, 184
187 (2000).
46. Friedlingstein, P. et al. Climate-carbon cycle feedback analysis: results from the
(CMIP)-M-4 model intercomparison. J. Clim. 19, 3337
3353 (2006).
47. van Vuuren, D. P. et al. Temperature increase of 21st century mitigation scenarios.
Proc. Natl Acad. Sci. USA 105, 15258
15262 (2008).
48. Clarke, L. et al. Scenarios of Greenhouse Gas Emissions and Atmospheric
Concentrations (Sub-report 2.1A of Synthesis and Assessment Product 2.1, US
Climate Change Science Program and the Subcommittee on Global Change
Research, Department of Energy, Office of Biological & Environmental Research,
Washington DC, 2007).
49. Fisher, B. S. et al. in Climate Change 2007: Mitigation (eds Metz, B., Davidson, O. R.,
Bosch, P. R., Dave, R. & Meyer, L. A.) 169
250 (Cambridge Univ. Press, 2007).
50. Weyant, J. et al. Report of 2.6 versus 2.9 Watts/m
RCP evaluation panel Æhttp://æ(31 March 2009).
51. Lamarque, J.-F. et al. Gridded emissions in support of IPCC AR5. IGAC Newsl. 41,
18 (2009).
52. Meehl, G. A. et al. Decadal prediction: can it be skillful? Bull. Am. Meteorol. Soc. 90,
1485 (2009).
53. Mitchell, T. D. Pattern scaling
an examination of the accuracy of the technique
for describing future climates. Clim. Change 60, 217
242 (2003).
54. Huntingford, C. & Cox, P. M. An analogue model to derive additional climate
change scenarios from existing GCM simulations. Clim. Dyn. 16, 575
586 (2000).
55. Rao, S. & Riahi, K. The role of non-CO
greenhouse gases in climate change
mitigation: Long-term scenarios for the 21st century. Multigas mitigation and
climate policy. Energy J. 3(Special Issue), 177
200 (2006).
56. Riahi, K., Gruebler, A. & Nakicenovic, N. Scenarios of long-term socio-economic
and environmental development under climate stabilization. Technol. Forecast.
Soc. Change 74, 887
935 (2007).
57. Fujino, J. et al. Multigas mitigation analysis on stabilization scenarios using AIM
global model. Multigas mitigation and climate policy. Energy J. 3(Special Issue),
354 (2006).
58. Hijioka, Y., Matsuoka, Y., Nishimoto, H., Masui, M. & Kainuma, M. Global GHG
emissions scenarios under GHG concentration stabilization targets. J. Glob.
Environ. Eng. 13, 97
108 (2008).
59. Smith, S. J. & Wigley, T. M. L. Multi-gas forcing stabilization with the MiniCAM.
Multigas mitigation and climate policy. Energy J. 3(Special Issue), 373
60. van Vuuren, D. P., Eickhout, B., Lucas, P. L. & den Elzen, M. G. J. Long-term multi-
gas scenarios to stabilise radiative forcing — Exploring costs and benefits within
an integrated assessment framework. Multigas mitigation and climate policy.
Energy J. 3(Special Issue), 201
234 (2006).
61. van Vuuren, D. P. et al. Stabilizing greenhouse gas concentrations at low levels: an
assessment of reduction strategies and costs. Clim. Change 81, 119
159 (2007).
62. Manabe, S. & Wetherald, R. T. Thermal equilibrium of the atmosphere with a
given distribution of relative humidity. J. Atmos. Sci. 24, 241
259 (1967).
63. Manabe, S. et al. A global ocean-atmosphere climate model: Part I. The
atmospheric circulation. J. Phys. Oceanogr. 5, 3
29 (1975).
64. Arrhenius, S. On the influence of carbonic acid in the air upon the temperature of
the ground. Lond. Edinb. Dublin Phil. Mag. J. Sci. (5th ser.) 41, 237
275 (1896).
65. Keeling, C. D. The concentration and isotopic abundance of carbon dioxide in the
atmosphere. Tellus 12, 200
203 (1960).
66. Hansen, J. et al. Global climate changes as forecast by Goddard Institute for Space
Studies three-dimensional model. J. Geophys. Res. 93, 9341
9364 (1988).
67. WMO/UNEP/ICSU. Report of the Study Conference on Sensitivity of Ecosystems and
Society to Climate Change (WCP-83, UNESCO, Geneva, 1984).
68. WMO/UNEP/ICSU. Report of the International Conference on the Assessment of the
Role of Carbon Dioxide and of other Greenhouse Gases in Climate Variations and
Associated Impacts (WMO No. 661, UNESCO, Geneva, 1986).
69. Carter, T. R., Parry, M. L. & Porter, J. H. Climatic change and future agroclimatic
potential in Europe. Int. J. Climatol. 11, 251
269 (1991).
70. Carter, T. R., Parry, M. L., Harasawa, H. & Nishioka, S. (eds) IPCC Technical
Guidelines for Assessing Climate Change Impacts and Adaptations (Dept of
Geography, University College London, UK, and Center for Global Environmental
Research, National Institute for Environmental Studies, Tsukuba, Japan, 1994).
NATUREjVol 463j11 February 2010 PERSPECTIVES
Macmillan Publishers Limited. All rights reserved
71. Hulme, M., Raper, S. C. B. & Wigley, T. M. L. An integrated framework to address
climate change (ESCAPE) and further developments of the global and regional
climate modules (MAGICC). Energy Policy 23, 347
355 (1995).
72. Melillo, J. M. et al. Vegetation/Ecosystem Modeling and Analysis Project
(VEMAP): comparing biogeography and biogeochemistry models in a
continental-scale study of terrestrial ecosystem responses to climate change and
doubling. Glob. Biogeochem. Cycles 9, 407
437 (1995).
73. Smith, J. B., et al. Vulnerability and Adaptation to Climate Change. Interim Results
from the U.S. Country Studies Program (Kluwer Academic, 1996).
74. Nakic
´, N., Victor, N. & Morita, T. Emissions scenarios database and review
of scenarios. Mitig. Adapt. Strategies Glob. Change 3, 95
120 (1998).
75. Watson, R. T., Zinyowera, M. C. & Moss, R. H. (eds) The Regional Impacts of
Climate Change: An Assessment of Vulnerability (Cambridge Univ. Press, 1998).
76. Carter, T. R. et al. Climate Change in the 21st Century
Interim Characterizations
Based on the New IPCC Emissions Scenarios (The Finnish Environment 433, Finnish
Environment Institute, Helsinki, 2000).
77. Morita, T. et al. in Climate Change 2001: Mitigation (eds Metz, B., Davidson, O.,
Swart, R. & Pan J.) 115
166 (Cambridge Univ. Press, 2007).
78. United Kingdom Climate Impacts Programme. Socio-economic Scenarios for
Climate Change Impact Assessment: A Guide to Their Use in the UK Climate Impacts
Programme (United Kingdom Climate Impacts Programme, Oxford, 2001).
79. Ruosteenoja, K., Carter, T. R., Jylha
¨, K. & Tuomenvirta, H. Future Climate in World
Regions: An Intercomparison of Model-based Projections for the New IPCC Emissions
Scenarios (The Finnish Environment 644, Finnish Environment Institute, Helsinki,
80. Weyant, J. P., De La Chesnaye, C. F. & Blenford, J. Overview of EMF21: multi-
greenhouse gas mitigation and climate policy. Energy J. 27 (Special Issue), 1
81. Murphy, J. M. et al. UK Climate Projections Science Report: Climate Change
Projections (Met Office Hadley Centre, Exeter, UK, 2009).
82. van der Linden, P. & Mitchell, J. F. B. (eds) ENSEMBLES: Climate Change and its
Impacts: Summary of research and results from the ENSEMBLES project (Met Office
Hadley Centre, Exeter, UK, 2009).
83. U.S. Climate Change Science Program. Strategic Plan for the Climate Change
Science Program, Final Report (eds Subcommittee on Global Change Research)
Figure 2.5 19 (US Climate Change Science Program, Washington DC, 2003).
84. Le Treut, H. et al. in Climate Change 2007: The Physical Science Basis (eds Solomon,
S. et al.) 93
127 (Cambridge Univ. Press, 2007).
85. Ahmad, Q. K. et al. in Climate Change 2001: Impacts, Adaptation and Vulnerability
(eds McCarthy, J. J., Canziani, O. F., Leary, N. A., Dokken, D. J. & White, K. S.)
143 (Cambridge Univ. Press, 2001).
86. US Department of Energy. Science Challenges and Future Directions: Climate Change
Integrated Assessment Research (Report of the Workshop on Integrated
Assessment, November 2008, US Department of Energy, Office of Science,
Washington DC, 2009).
87. van Vuuren, D. P. & Riahi, K. Do recent emission trends imply higher emissions
forever? Clim. Change 91, 237
248 (2008).
Supplementary Information is linked to the online version of the paper at
Acknowledgements The authors acknowledge the following individuals for their
contributions: L. Arris, M. Babiker, F. Birol, P. Bosch, O. Boucher, S. Brinkman,
E. Calvo, I. Elgizouli, L. Erda, J. Feddema, A. Garg, A. Gaye, M. Ibarraran, E. La
Rovere, B. Metz, R. Jones, J. Kelleher, J. F. Lamarque, B. Matthews, L. Meyer, B.
O’Neill, S. Nishioka, R. Pichs, H. Pitcher, P. Runci, D. Shindell, P. R. Shukla,
A. Snidvongs, P. Thornton, J. P. van Ypersele, V. Vilarin
˜o and M. Zurek.
Author Contributions R.H.M. is coordinating lead author of the paper. J.A.E.,
K.A.H., M.R.M., S.K.R. and D.P.v.V. are principal co-authors of the paper. All others
are co-authors. Authors are drawn from the integrated assessment modelling and
climate modelling communities, and from the impacts, adaptation and vulnerability
research communities; all contributed important inputs to the process.
Author Information Reprints and permissions information is available at The authors declare no competing financial interests.
Correspondence and requests for materials should be addressed to R.H.M.
PERSPECTIVES NATUREjVol 463j11 February 2010
Macmillan Publishers Limited. All rights reserved
... The human-Earth system is fundamentally integrated with impacts and feedbacks tightly 42 interconnecting outcomes across human decisions and the broader environment. Human 43 decisions regarding land use, water use, and energy consumption affect the broader Earth 44 system, which can subsequently drive future human decisions [1,2]. Multisectoral models are 45 those that include representations of energy, water, land, socioeconomic, and climate sectors 46 ...
... Concentration Pathways (RCPs), for example, provide scenarios that reach varying magnitudes 50 of radiative forcing by the end of the century based on changing GHG emissions and land use 51 [1][2][3]. Shared Socio-economic Pathways (SSPs) provide scenarios driven by plausible changes in 52 global developments including population and economic growth, fossil fuel dependency, and 53 ...
Full-text available
A primary advantage to using reduced complexity climate models (RCMs) has been their ability to quickly conduct probabilistic climate projections, a key component of uncertainty quantification in many impact studies and multisector systems. Providing frameworks for such analyses has been a target of several RCMs used in studies of the future co-evolution of the human and Earth systems. In this paper, we present Matilda, an open-science R software package that facilitates probabilistic climate projection analysis, implemented here using the Hector simple climate model in a seamless and easily applied framework. The primary goal of Matilda is to provide the user with a turn-key method to build parameter sets from literature-based prior distributions, run Hector iteratively to produce perturbed parameter ensembles (PPEs), weight ensembles for realism against observed historical climate data, and compute probabilistic projections for different climate variables. This workflow gives the user the ability to explore viable parameter space and propagate uncertainty to model ensembles with just a few lines of code. The package provides significant freedom to select different scoring criteria and algorithms to weight ensemble members, as well as the flexibility to implement custom criteria. Additionally, the architecture of the package simplifies the process of building and analyzing PPEs without requiring significant programming expertise, to accommodate diverse use cases. We present a case study that provides illustrative results of a probabilistic analysis of mean global surface temperature as an example of the software application.
... In order to increase the sensitivity of the model besides forest inventory data, drought resistance parameter was introduced using Ellenberg's indices. Regarding this, EIVs is significant in defining the ecological niche of a plant species, especially if you consider modeling under different climate change scenario analyses, improving conducted research to include climate change risks and vulnerabilities and contribute to the development of socio-economic futures (Moss et al., 2010). If we take into account that beech indeed is a species sensitive to drought (Fotelli et al., 2009;Geßler et al., 2007;Leuschner, 2020;Scherrer et al., 2011), these results indicate that Ellenberg's indicators represent a new approach to determining areas prone to desertification using MEDALUS model. ...
Full-text available
This paper aims to improve the methodology and results accuracy of MEDALUS model for assessing land degradation sensitivity through the application of different data detail levels and by introducing the application of Ellenberg indices in metrics related to vegetation drought sensitivity assessment. For that purpose, the MEDALUS model was applied at 2 levels of detail. Level I (municipality level) implied the use of available large-scale databases and level II (watershed) contains more detailed information about vegetation used in the calculation of the VQI and MQI factors (Fig. S6). The comparison was made using data based on CORINE Land Cover (2012) and forest inventory data, complemented with object-based classification. Results showed that data based on forest inventory data with the application of Ellenberg’s indices and object-based classification have one class more, critical (C1 and C2) and that the percentage distribution of classes is different in both quantitative (area size of class sensitivity) and qualitative (aggregation and dispersion of sensitivity classes). The use of data from Forest Management Plans and the application of Ellenberg’s indices affect the quality of the results and find its application in the model, especially if these results are used for monitoring and land area management on fine scales. Remote sensed data images (Sentinel-2B) were introduced into the methodology as a very important environmental monitoring tool and model results validation.
... If rapid selection of resistant genotypes to increases in OA does not evolve before a high-emissions, worst-case scenario occurs (RCP8.5, IPCC based projection; Moss et al., 2010;Meinshausen et al., 2011) by the turn of the century, ocean pCO 2 could have a detrimental effect on recruitment (e.g., Lehodey et al., 2017;Stiasny et al., 2016)through adverse biological responses of early life stages to increases in acidification that directly or indirectly may affect subsequent survival-of one of the world's most economically important pelagic fish stocks in the Pacific Ocean. ...
Increasing ocean acidification is a concern due to its potential effects on the growth, development, and survival of early life stages of tuna in oceanic habitats and on the spatial extent of their suitable nursery habitat. To investigate the potential effects of increasing CO 2 on otolith calcification of 9-day old pre-flexion stage yellowfin tuna (Thunnus albacares), an experiment was conducted at the Inter-American Tropical Tuna Commission's Achotines Laboratory in Panama during 2011. Fertilized eggs and larvae were exposed to mean pCO 2 levels that ranged from present day (355 μatm) to two levels predicted to occur in some areas of the Pacific in the near future (2013 and 3321 μatm), and to an extreme value equivalent to long-term projections for 300 years in the future (9624 μatm). The results indicated significantly larger otoliths (in area and perimeter) with significant, and increasing, fluctuating asymmetry at acidification levels similar to those projected for the near future and long-term. Otoliths increased significantly in size despite a significant decrease in somatic length with increasing pCO 2. A consistent correlation between otolith and somatic growth of yellowfin tuna larvae among treatments was evident (i.e., larger otoliths were still associated with larger larvae within a treatment). The observed changes in otolith morphology with increasing ocean acidification have the potential to indirectly affect larval survival through dysfunction of the mechanosensory organs, but this remains to be verified in yellowfin tuna larvae.
... To facilitate future assessments of climate change, representative concentration pathways (RCPs) were developed for the climate modeling community as a basis for long-term and near-term modeling experiments. In contrast to the IPCC's Special Report on Emissions (SRES) scenarios, the radiative forcing trajectories of RCPs are not associated with predefined storylines and can reflect various possible combinations of economic, technological, demographic, and policy developments [37]. ...
Full-text available
As a semi-arid to semi-humid transitional zone, the Loess Plateau is sensitive to climate change due to its fragile ecological environment and geographic features. This study assesses the performance of six historical experiments from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in this region during 1980–2005. In addition, projected future changes in surface air temperature and precipitation are investigated under the representative concentration pathways (RCP) 2.6 and 8.5 during three periods in the 21st century: the early future (2011–2040), middle future (2041–2070), and late future (2071–2099). Results show that experiments reasonably reproduce the spatial pattern of 2m temperature and precipitation for all seasons, yet with a slight warm bias and prominent wet bias. In the future, the area-averaged magnitude of change will be 1.1 °C, 1.4 °C, and 1.4 °C under RCP2.6 and 1.3 °C, 2.7 °C, and 4.5 °C under RCP8.5 for the early, middle, and late periods, respectively. The warming effect is greater in elevated areas. Precipitation change in future periods is more complex, with both increasing and decreasing trends, depending on the season, location, and scenario. The results are expected to provide regional climate information for decision makers and benefit applications such as agriculture, ecological environment protection, and water resource management.
... "√" indicated that the variable was retained to build the model, and "×" indicated that the variable was dropped due to its high correlation with other variables. levels) to high (pessimistic emission levels) (Moss et al. 2010). Here, we used RCP 26 and RCP 85 to predict the future distribution in the 2050s (2040~2050) and 2100s (2090~2100). ...
Full-text available
Climate change and species invasions are among the most serious threats to global biodiversity, and climate change will further greatly alter the distribution of invasive species. The red drum Sciaenops ocellatus (Linnaeus, 1766) has established non-native populations in many parts of the world, leading to negative effects on local ecosystems. In this study, based on 455 global occurrence records (38 of which were in Chinese waters) and 5 biologically relevant variables (average ocean bottom temperature, ocean bottom average salinity, ocean bottom average flow rate, depth, and distance from shore), a weighted ensemble model was developed to predict the current potential distribution of red drum in Chinese waters and the future distribution under two climate change scenarios (RCP 26 and RCP 85). Based on the True Skill Statistics (TSS) and the Area Under Curve (AUC), the ensemble model showed more accurate predictive performance than any single model. Among the five environmental variables, the average temperature was the most important environmental variable influencing the distribution of red drum. Ensemble model prediction showed that the current suitable habitat of red drum was mainly concentrated on the coast of Chinese mainland, around Hainan Island, and the western coastal waters of Taiwan Province (17~41°N). Projections in the 2050s and 2100s suggested that red drum would expand northwards under both future climate scenarios (RCP 26 and RCP 85), especially in the western part of the Yellow Sea and along the Bohai Sea coast, which should be involved in the management strategies to maintain ecosystem structure and function.
... The contributions of bioclimatic variables were significant in both the historical and futuristic potential distribution model of A. assamica. Although it is evident that bio4 which is temperature seasonality has minimal effect on the current distribution of the species, the same has a greater impact on CN, CC, and BC climate scenario respectively (Kanwal and Lodhi 2018;Moss et al. 2010;Myers 2000). Thus, it depicted the role of seasonal pattern in temperature could have a direct effect on determining the distribution of the species which is significant in view of changing climate. ...
Full-text available
Climate change has signifcantly afected the potential distribution and altitudinal shift of several plant species. Amentotaxus assamicus being one of the critically endangered gymnosperms under the family Taxaceac is restricted only to a few pockets of Arunachal Pradesh with low population size. The current study aims to analyze the current distribution of A. assamica in the state using key environmental parameters and to predict the potential suitable habitat in accordance with two IPCC representative concentration pathway (RCP) scenarios. The future potential distribution was projected for two possible climate scenarios (RCP 4.5 and RCP 8.5) given by three various global climate models (GCMs), viz., BC_CSM 1.1 (BC), CCSM4 (CC), and CNRM-CM5 (CN). A total of 36 independent localities of A. assamica were used to model the current species distribution along with 23 environmental variables, including bioclimatic parameters, elevation, global land cover, and soil data. To run the future simulations, IPCC AR5 scenarios were used for 19 bioclimatic variables. Maxent modeling was used for the current distribution of A. assamica in Arunachal Pradesh, India, through 10 duplicate runs which showed the test AUC average of 0.905 as well as a standard deviation of 0.057. Soil available nitrogen at 15 cm depth was found to contribute the maximum in the model accounting for 38.2% followed by soil nitrogen at 5 cm depth (21.8%). Bio 4, Bio 6, Bio 7, and Bio 19 were the key variables that contributed to varying extent in all the three GCMs consisting of two scenarios each. Under the high suitability zone, the optimistic scenario (RCP 4.5; 3618.25 km2 ) represented the maximum area followed by RCP 8.5 (3269.89 km2 ) whereas the lowest in the current distribution model revealed as 2909.64 km2 . Furthermore, the high suitability distribution range in terms of altitudinal regime shifted from 270 msl of lowest elevation in the current distribution to the 966 msl in the RCP 4.5 scenario and 894 msl in the RCP 8.5 scenario. The altitudinal shift of the distribution found in the futuristic model is signifcant, and the species’ lower range of altitudinal distribution has clearly shifted upward. The fndings of this study would be useful in determining quantifed future climate space for the species and allow the conservation managers to formulate appropriate conservation strategies.
This study examines the currently available literature on infrastructure assessment tools and the impact of climate change on its maintenance costs. Critical infrastructure (CI) performance and protection is a global priority. Many countries struggle to ensure the functioning of their infrastructure during or after extreme events. Furthermore, climate change (CC) projections suggest that future events might be of higher magnitudes. When considering the life-cycle of infrastructure, one of the most important aspects to consider is risk. Risk is first identified and then addressed during CI design, construction, and subsequent maintenance. Many studies have taken the approach of applying cost–benefit analysis (CBA) to their research in order to estimate the impact of future climate. The objective of CBA is to find, from an economic standpoint, the best strategy to mitigate climate change by reducing the costs of preparedness and mitigation actions for CC. In conclusion, the framework aims for better decision making in both the short-term and the long-term.
Climate projections simulated by the Brazilian Earth System Model (BESM2.5) under RCP4.5 and RCP8.5 climate scenarios are analyzed based on future changes of surface air temperature (SAT) and precipitation with respect to the historical reference period 1971–2000. Since BESM2.5 is the only climate model developed in a South American country, this study gives a particular emphasis to South American future climate projections. Regarding the surface air temperature, BESM2.5 projects a steady warming throughout the 21st century, with the highest warming over eastern Amazonia, northern Chile and central South America for both scenarios. The SAT changes range between 2 °C and 3–4 °C for RCP4.5 and RCP8.5, respectively. On the other hand, projected precipitation varies over different regions of South America, with decreasing and increasing trends over the Amazon and southern South America, respectively. Interestingly, this study shows contrasting results with respect to extreme precipitation indicators, projecting enhanced extreme events with higher numbers of both consecutive dry days and days in which the precipitation exceeds 20 mm over the southeastern region. The model projects a meridional dipole pattern in the precipitation, with decreasing precipitation and longer dry spells over Northeast Brazil and the East Amazon region and increasing precipitation and shorter dry spells over Northwest South America and West Amazon, that is driven by future changes in the SLP that imposes a meridional gradient over these regions, causing the increase of westerlies that are likely to increase the moisture transport from the Pacific Ocean into western South America and the weakening of the easterlies that transport moisture over eastern South America and East Amazon.
Full-text available
Integrated modeling systems are used to identify the effects of climate variability on future sediment production, assisting in watershed management. In this study, an integrated modeling system composed of erosion and climatological models was used to evaluate the effects of climate variability on sediment production in the Itaqueri river basin, state of São Paulo (Brazil). For this, we used climate data generated by the ETA-MIROC5 and ETA-HadGEM2-ES models for future estimation of sediment production using the Erosion Potential Method (EPM) model under RCPs 4.5 and 8.5. The Itaqueri river basin presented an average annual production of sediments equivalent to 9.41 Mg. ha-¹. year-¹, which considering the total area of the basin is equivalent to 208,467 Mg. year-¹. Considering the sediment retention rate, the actual sediment loss in the current scenario (2019) was 22,306 Mg. year-¹. Regarding the effects of the variability of climatic elements, in the medium term (2070) the average annual production of sediments in the basin may increase by up to 61.8% (RCP 4.5) and 30.5% (RCP 8.5). In this same period, the actual loss of sediments could reach 36,076 Mg. year-¹ and contribute to the silting and reduction of the useful life of the Lobo reservoir. The EPM model proved to be effective in identifying areas with the highest production of sediments and, in an integrated manner with climate models, it can help in a preliminary and preventive way in identifying the effects of climate variability. However, uncertainties related to the adoption of climate elements are regularly included as part of the risk in water resources management.
In recent years, Asia and the Pacific have been ravaged by strong typhoons that caused widespread destruction. The powerful winds from these typhoons ripped off roofs, windows, doors and walls from houses, and destroyed trees and other vegetation, leaving a vast amount of wooden, metallic, plastic, and glass debris and waste scattered across a wide area. Proper management of disaster waste is a critical task during the initial phase of disaster recovery. It is essential for coastal cities that are frequently affected by typhoons to have adequate capacity for post-disaster waste management. This capacity development project aimed to contribute to this end by providing appropriate knowledge and training to government and non-government stakeholders. The project was implemented in Lautoka City, Fiji and Makati City, Philippines, with the support of four prominent universities. In total, six training sessions were conducted under the project. The primary outputs of this project are the disaster waste management contingency plans of the two participating cities. The project team disseminated information about the capacity development project through the project website and through presentations in academic conferences, webinars, workshops, training, non-academic conferences, and radio guest appearances.
Martin Parry University College, London, UK The 13 country studies collected in this re­ Adaptations Assessment published by the port represent the first of what is likely to Intergovernmental Panel on Climate Change become a worldwide, country-by-country (Carter et al., 1994) as an agreed technical estimate of the likely impacts of, and appro­ set of scientific methods for climate impact priate adaptations to, greenhouse-gas-in­ assessment and has written its own guidance duced global climate change. document, Guidance for Vulnerability and Adaptation Assessment (U.S. CSP, 1994). Under the U.N. Framework Convention on The u.S. Country Studies Program devel­ Climate Change (UNFCCC), signatories oped the Guidance and other reviews of agreed to two near-term actions and one ma­ methodology into a nonspecialist set of jor subsequent one. The two near-term ac­ workbooks for use at the country level, tions are to make annual estimates of the which, backed up by advice from experi­ emissions and sinks of greenhouse gases, enced scientists from the United States and which are now being reported as part of a other countries, enabled local scientists to country-by-country inventory developed by conduct their own vulnerability and adapta­ the U.N. Environment Programme, the Or­ tion assessments.
A systematic variation with season and latitude in the concentration and isotopic abundance of atmospheric carbon dioxide has been found in the northern hemisphere. In Antarctica, however, a small but persistent increase in concentration has been found. Possible causes for these variations are discussed. DOI: 10.1111/j.2153-3490.1960.tb01300.x
Stabilization of the climate system requires stabilization of greenhouse-gas concentrations. Most work to date has considered only stabilization of CO2, where there are choices regarding both the concentration stabilization target and the pathway towards that target. Here we consider the effects of accounting for non-CO2 gases (CH4 and N2O), for different CO2 targets and different pathways. As primary cases for CO2 we use the standard “WRE” pathways to stabilization at 450 ppm or 550 ppm. We also consider a new “overshoot” concentration profile for CO2 in which concentrations initially exceed and then decline towards a final stabilization level of 450 ppm, as might occur if an initial target choice were later found to be too high. Emissions reductions for CH4 and N2O are optimized for the different pathways using an energy-economics model (MERGE). The optimization procedure minimizes the total cost of emissions reductions. The CH4 and N2O emissions reductions lead to substantially reduced future warming and future sea-level rise relative to stabilization cases where likely emissions reductions for these gases are ignored. For central climate and sea level model parameter values the reductions are 0.3–0.4 °C and 2–3 cm in 2100 and 0.9–1.0 °C and about 14 cm in 2400. Reduced CH4 and N2O emissions also allow larger CO2 emissions by reducing the magnitude of climate feedbacks on the carbon cycle. © Cambridge University Press 2007, Cambridge University Press, 2010.