Global-Change Scenarios

Their Development and Use

U.S. Climate Change Science Program

Synthesis and Assessment Product 2.1b

July 2007
FEDERAL EXECUTIVE TEAM

Acting Director, Climate Change Science Program ......................................................William J. Brennan

Acting Director, Climate Change Science Program Office ...........................................Peter A. Schultz

Lead Agency Principal Representative to CCSP;

Division Director, Department of Energy, Office of Biological 

and Environmental Research .........................................................................................Jerry W. Elwood

Product Lead; Department of Energy,

Office of Biological and Environmental Research ........................................................John C. Houghton

Synthesis and Assessment Product Advisory Group Chair,

Associate Director, EPA National Center for Environmental

Assessment.....................................................................................................................Michael W. Slimak

Synthesis and Assessment Product Coordinator,

Climate Change Science Program Office ......................................................................Fabien J.G. Laurier

OTHER AGENCY REPRESENTATIVES

Department of Agriculture .............................................................................................Jan Lewandrowski

Environmental Protection Agency .................................................................................Francisco de la Chesnaye

National Aeronautics and Space Administration ...........................................................Phil DeCola

National Oceanic and Atmospheric Administration ......................................................Hiram Levy

National Oceanic and Atmospheric Administration ......................................................Larry W. Horowitz 

This document does not express any regulatory policies of the United States or any of its agencies, or provide recommendations for 

regulatory action. Further information on the process for preparing Synthesis and Assessment products and the CCSP itself can be found

at www.climatescience.gov.
Global-Change Scenarios

Their Development and Use

Synthesis and Assessment Product 2.1b

Report by the U.S. Climate Change Science Program

and the Subcommittee on Global Change Research

AUTHORS:

Edward A. Parson, University of Michigan

Virginia R. Burkett, U.S. Geological Survey

Karen Fisher-Vanden, Dartmouth College

David W. Keith, University of Calgary

Linda O. Mearns, National Center for Atmospheric Research

Hugh M. Pitcher, Pacific Northwest National Laboratory

Cynthia E. Rosenzweig, National Aeronautics and Space Administration

Mort D. Webster, Massachusetts Institute of Technology
CLIMATE CHANGE SCIENCE PROGRAM PRODUCT DEVELOPMENT

ADVISORY COMMITTEE

Eight members of the Climate Change Science Program Product Development Advisory Committee (CPDAC) wrote

this Climate Change Science Program Synthesis and Assessment Product at the request of the Department of Energy.

The entire CPDAC has accepted the contents of the product. Recommendations made in this report regarding programmatic and organizational changes, and the adequacy of current budgets, reflect the judgment of the report’s authors

and the CPDAC and are not necessarily the views of the U.S. Government.

David C. Bader

Lawrence Livermore National

Laboratory

*Virginia R. Burkett

U.S. Geological Survey

Antonio J. Busalacchi

University of Maryland

Leon E. Clarke

Pacific Northwest National

Laboratory

Curtis C. Covey

Lawrence Livermore National

Laboratory

James A. Edmonds

Pacific Northwest National

Laboratory

*Karen Fisher-Vanden

Dartmouth College

Brian P. Flannery

Exxon-Mobil Corporation

William J. Gutowski

Iowa State University

David G. Hawkins

Natural Resources Defense Council

Isaac M. Held

Geophysical Fluid Dynamics

Laboratory

Henry D. Jacoby

Massachusetts Institute of

Technology

*David W. Keith

University of Calgary

Kenneth E. Kunkel

Illinois State Water Survey

Richard S. Lindzen

Massachusetts Institute of

Technology

*Linda O. Mearns

National Center for Atmospheric

Research

Ronald L. Miller

National Aeronautics and Space

Administration

*Edward A. Parson

University of Michigan

*Hugh M. Pitcher

Pacific Northwest National

Laboratory

William A. Pizer

Resources for the Future

John M. Reilly

Massachusetts Institute of

Technology

Richard G. Richels

Electric Power Research Institute

*Cynthia E. Rosenzweig

National Aeronautics and Space

Administration

Robin T. Tokmakian

Naval Postgraduate School

*Mort D. Webster

Massachusetts Institute of

Technology

Julie A. Winkler

Michigan State University

Gary W. Yohe

Wesleyan University

Minghua H. Zhang

Stony Brook University

*Authors for Global Change Scenarios:

Their Development and Use

Chair

Robert M. White, The Washington Advisory Group

Vice Chair

Soroosh Sorooshian, University of California-Irvine

Designated Federal Officer

Anjuli S. Bamzai, Department of Energy

Office of Biological and Environmental Research

Members
July 2007

Members of Congress:

On behalf of the National Science and Technology Council, the U.S. Climate Change Science Program (CCSP) is pleased to transmit to the President and the Congress this report, Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations and Review of Integrated Scenario Development and

Application. This is the second in a series of Synthesis and Assessment Products produced by the

CCSP. This series of 21 reports is aimed at providing current evaluations of climate change science to

inform public debate, policy, and operational decisions. These reports are also intended to help inform

CCSP’s consideration of future program priorities. This second Synthesis and Assessment Product

issued pursuant to Section 106 of the Global Change Research Act of 1990 and has two components:

“Development of New Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations”

(Part A) and a “Review of Integrated Scenario Development and Application” (Part B). Here we

transmit to you Part B.

CCSP’s guiding vision is to provide the Nation and the global community with the science-based

knowledge to manage the risks and opportunities of change in the climate and related environmental

systems. The Synthesis and Assessment Products are important steps toward that vision, helping

translate CCSP’s extensive observational and research base into informational tools directly addressing key questions that are being asked of the research community.

This product will contribute to and enhance the ongoing and iterative international process of producing and refining climate-related scenarios and scenario tools. It was developed with broad scientific

input and in accordance with the Guidelines for Producing CCSP Synthesis and Assessment Products,

Section 515 of the Treasury and General Government Appropriations Act for Fiscal Year 2001 (Public

Law 106-554), and the Information Quality Act guidelines issued by the Department of Energy pursuant to Section 515. The CCSP Interagency Committee relies on Department of Energy certifications regarding compliance with Section 515 and the Guidelines for Producing CCSP Synthesis and

Assessment Products. 

We commend the report’s authors for both the thorough nature of their work and their adherence to an

inclusive review process.

Carlos M. Gutierrez

Secretary of Commerce

Vice-Chair, Committee on 

Climate Change 

Science and Technology Integration

Samuel W. Bodman

Secretary of Energy

Chair, Committee on 

Climate Change

Science and Technology Integration

John H. Marburger III, Ph.D.

Director, Office of 

Science and Technology Policy 

Executive Director, Committee on 

Climate Change 

Science and Technology Integration
ACKNOWLEDGEMENT

This report has been peer reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The expert review and selection of reviewers followed the OMB’s Information Quality Bulletin for Peer Review.

The purpose of this independent review is to provide candid and critical comments that will assist the Climate Change

Science Program in making this published report as sound as possible and to ensure that the report meets institutional

standards. The peer review comments, draft manuscript, and response to the peer review comments are publicly available at: www.climatescience.gov/Library/sap/sap2-1/default.php.

We wish to thank the following individuals for their peer review of this report:

Frans Berkhout, Free University of Amsterdam

Garry Brewer, Yale University

Ged Davis, World Economic Forum

Nebojsa Nakicenovic, International Institute for Applied Systems Analysis

Robert Lempert, RAND Corporation

M. Granger Morgan, Carnegie-Mellon University

John Robinson, University of British Columbia

Thomas J. Wilbanks, Oak Ridge National Laboratory

We would also like to thank the numerous individuals who provided their comments during the public comment period. The public review comments, draft manuscript, and response to the public comments are publicly available at:

www.climatescience.gov/Library/sap/sap2-1/default.php.

The writing team is grateful for research assistance by Kristen Cleary, Emily Kelly, Paul Porter, Gautam Rao, and Nora

Van Horssen.

Editor ..........................................................................................................................Elizabeth L. Malone

Technical Advisor ..........................................................................................................David Dokken

Graphic Production ........................................................................................................DesignConcept

Recommended Citations

The Entire Volume - CCSP Synthesis and Assessment Product 2.1

CCSP, 2007: Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations (Part A) and Review of Integrated Scenario Development and Application (Part B). A Report by the U.S. Climate Change Science Program and the

Subcommittee on Global Change Research [Clarke, L., J. Edmonds, J. Jacoby, H. Pitcher, J. Reilly, R. Richels, E. Parson, V. Burkett, K. Fisher-Vanden, D. Keith, L. Mearns, C. Rosenzweig, M. Webster (Authors)]. Department of Energy,

Office of Biological & Environmental Research, Washington, DC., USA, 260 pp. 

This Sub-Report (2.1B)

Parson, E., V. Burkett, K. Fisher-Vanden, D. Keith, L. Mearns, H. Pitcher, C. Rosenzweig, M. Webster, 2007. Global

Change Scenarios: Their Development and Use. Sub-report 2.1B of Synthesis and Assessment Product 2.1 by the U.S.

Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office

of Biological & Environmental Research, Washington, DC., USA, 106 pp.

The Companion Sub-Report (2.1A)

Clarke, L., J. Edmonds, H. Jacoby, H. Pitcher, J. Reilly, R. Richels, 2007. Scenarios of Greenhouse Gas Emissions and

Atmospheric Concentrations. Sub-report 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change

Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological &

Environmental Research, Washington, DC., USA, 154 pp.
TABLE OF CONTENTS

Executive Summary ..........................................................................................1

Introduction ........................................................................................................9

SECTIONS

1 .................................................................................................. 13

Scenarios, their Characteristics and Uses

2 .................................................................................................. 21

Scenarios in Global-Change Analysis and Decision Support

3 .................................................................................................. 31

Review of Major Climate-Change Scenario Exercises

4 .................................................................................................. 51

Challenges and Controversies in Scenarios for Climate Change

5 .................................................................................................. 83

Conclusions and Recommendations

Acronyms ........................................................................................................ 95

References........................................................................................................ 97

Global-Change Scenarios - Their Development and Use
The U.S. Climate Change Science Program
1

Global-Change Scenarios - Their Development and Use

SCENARIOS FOR CLIMATE CHANGE: FIVE TYPES

Developing a scenario exercise involves many design choices, of which the most important involve choosing the few key uncertainties to represent in alternative scenarios. Five types of scenarios have been developed to address different aspects of

the climate-change issue; these are distinguished by where they fall along a simple linear causal chain extending from the 

socio-economic determinants of greenhouse-gas emissions through the impacts of climate change as shown in Figure ES-1.

(This figure does not represent the complete causal structure of the climate issue, which has many linkages and feedbacks.

Rather, this simple structure only illustrates how scenarios have been used to fit within the simplest and most prominent

causal pathway of the issue.)

Figure ES-1.

Scenarios of

anthropogenic

climate change:

simple linear causal

chain

EXECUTIVE SUMMARY

A scenario is a description of potential future conditions produced to inform decision-making under uncertainty. Scenarios can help inform decisions that involve high stakes and poorly characterized uncertainty, which

may thwart other, conventional forms of analysis or decision support. Originally developed to study military and security problems, scenarios are now

widely used for strategic planning and assessment in businesses and other

organizations, and increasingly to inform planning, analysis, and decisionmaking for environmental issues, including climate change. 

Scenarios can serve many purposes. They can help inform specific decisions, or can provide inputs to assessments, models,

or other decision-support activities when these activities need specification of potential future conditions. They can also provide various forms of indirect decision support, such as clarifying an issue’s importance, framing a decision agenda, shaking

up habitual thinking, stimulating creativity, clarifying points of agreement and disagreement, identifying and engaging needed

participants, or providing a structure for analysis of potential future decisions.

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

• fresh water

• ecosystems

• agriculture

• human health

• property,

 infrastructure

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

IMPACTS
2

The U.S. Climate Change Science Program Executive Summary

Emissions Scenarios for Climate Simulations:

Emissions scenarios present future paths of

greenhouse-gas emissions or other climate

perturbations. A major use of these is to

provide needed inputs to climate models.

Such scenarios may specify simple arbitrary

perturbations of emissions or concentrations

(e.g., doubling atmospheric CO2), or timepaths reflecting specified assumptions for

evolution of socio-economic drivers such as

population, economic growth, and technological change. 

Emissions Scenarios for Exploring Alternative

Energy/Technology Futures: Another use

of emissions scenarios involves specifying

an environmental or emissions target, arbitrarily or based on normative or political

goals, to examine what patterns of socioeconomic change, energy resources, and

technology development are consistent with

the target and/or what interventions might

be needed to meet it. Such scenarios have

examined conditions for stabilizing atmospheric CO2 concentration at various levels

and the implications of stabilizing radiative

forcing for multi-gas reduction strategies.

Climate-Change Scenarios: Climate scenarios

specify potential future climate conditions

to inform assessments of impacts, vulnerabilities, and adaptation options, and inform

decision-making for adaptation or mitigation.

They can be produced by arbitrary perturbation of present conditions, by using climates

from elsewhere or the past as a proxy for potential future climate in a given location, or

by climate-model simulations driven by some

specified scenario of future emissions. 

Scenarios of Direct Biophysical Impacts, e.g.,

Sea Level Rise: Scenarios can specify alternative trajectories for some important

form of climate impact that influences many

other impacts. For example, scenarios of sea

level rise can capture the most important impact pathways in many coastal regions, including the large uncertainties associated

with potential loss of continental ice sheets

in Greenland and Antarctica. 

Multivariate Scenarios for Impact Assessment:

Assessing climate-change impacts requires

not just considering climate in isolation, but

other linked changes and stresses, including

both environmental and socio-economic

trends. The factors that influence particular

impacts and vulnerabilities are likely to 

be widely variable, and may include

demographic, economic, technological, 

institutional, and cultural characteristics.

Consequently, scenarios may have to be generated in an exploratory manner in the context of attempting to assess specific local

and regional impacts.

SCENARIOS 

FOR CLIMATE CHANGE: 

MAJOR EXAMPLES

The report reviews four major exercises producing or using scenarios for climate-change

applications. The examples include national

and international activities, produced by different sets of actors for different purposes. 

The Intergovernmental Panel on Climate Change

(IPCC) has produced three sets of scenarios of

21st-century greenhouse-gas emissions, of which

the most ambitious and important were produced for the Special Report on Emissions Scenarios (SRES) between 1997 and 1999. SRES

produced four qualitative storylines on which

six “marker” scenarios were based – one model

quantification of each storyline plus two technological variants of one storyline that stressed

fossil-intensive and low-carbon energy supply

technologies – each produced by a different 

energy-economic model. Other models’ replications of each other’s marker scenarios plus a

few additional explorations yielded 40 scenarios

in total. These scenarios highlighted several insights, including the ability of alternative paths

with similar emissions in 2100 to differ widely

in their interim pathways and thus in atmospheric concentrations; the ability of alternative

technological assumptions alone to generate as

wide a range of emissions futures as substantially divergent socio-economic pathways; and

the fact that similar emissions paths can come

from widely different combinations of underlying socio-economic factors and so pose distinct

mitigation problems. A widely publicized critique of the SRES scenarios alleged over-estimation of future emissions growth due to the

metric used to compare incomes in rich and

poor nations, but the overestimation was later

found to be insignificant. More serious and illuminating challenges associated with these
3

Global-Change Scenarios - Their Development and Use

scenarios concerned how to balance and integrate qualitative and quantitative scenarios; how

to use and how much to coordinate multiple

models to generate the most useful insights; and

whether, when, and how it is appropriate to assign explicit probability judgments to alternative scenarios or associated ranges of

quantitative variables. 

The US National Assessment was a comprehensive assessment of potential impacts of climate change and variability on the United

States, focusing on major regions and sectors

(agriculture, water, human health, coastal areas

and marine resources, and forests). The National Assessment needed scenarios of 21st-century US climate and socio-economic changes.

For climate scenarios, it relied principally on

climate-model scenarios produced by the UK

Hadley Centre and the Canadian Centre for Climate Modeling and Analysis, each driven by a

single emissions scenario, with statistical downscaling based on detailed local conditions and

present patterns of fine-scale climate variation.

Other proposed types of climate scenario, including historical scenarios and inverse methods to probe for key vulnerabilities, were less

used. For socio-economic scenarios, a novel approach was proposed that combined specified

scenarios for a few key national-level variables

such as population and economic growth, and a

common process to elaborate and document additional socio-economic assumptions as needed

for specific regional and sector analyses. The

National Assessment was criticized for relying

on just two climate-model runs and one emissions scenario, although these choices were dictated by time limits and availability of

climate-model runs. Limited use was made of

the socio-economic approach, principally due

to time limits and communication problems.

The UK Climate Impacts Programme (UKCIP)

provides common datasets, tools, and support,

including scenarios, for climate-impact assessments for UK regions and sectors by researchers and stakeholders. The program

produced climate scenarios in 1998 and 2002,

all based on the Hadley Centre climate models,

and socio-economic scenarios in 2001. The

program stresses building a sustained assessment capability by acting as a motivator, resource, and light coordinator with little central

authority over separate assessments. The reliance on climate scenarios from just one family of climate models may pose risks of

incomplete representation of key uncertainties. 

The Millennium Ecosystem Assessment (MEA)

examined the status, present trends, and longerterm challenges to the world’s ecosystems, including climate change and other stresses. One

of the assessment’s four working groups constructed scenarios of global ecosystems to 2050

and beyond, largely independently of the group

examining current status and trends. All assessment components used a common conceptual framework, which distinguished indirect

drivers of ecosystem change (e.g., population

and economic growth, technological change,

policies and lifestyles), direct drivers (e.g., climate change, air pollution, and land-use and

land-cover change), ecosystem indicators,

ecosystem services, measures of human wellbeing, and response options. The Scenarios

group applied this framework to characterizing

potential ecosystem stresses in 2050, with more

limited projections to 2100. The four scenarios

were based on two dimensions of uncertainty:

degree of globalization, and predominance of

proactive vs. reactive response to ecosystem

stresses. The qualitative storylines underlying

these scenarios were more richly developed than

in other climate-change scenario exercises.

Concerns with these scenarios pertained to the

degree of integration and consistency among

qualitative and quantitative scenario components; risks of logical circularity within scenarios; and unexplained similarity of projected

ecosystem effects among scenarios.

SCENARIOS 

FOR CLIMATE CHANGE:

CHALLENGES AND

CONTROVERSIES 

Scenarios and Decisions

Scenarios can inform climate-change mitigation

and adaptation decisions, but most uses so far

have had relatively indirect connections to such

decisions. Although there is no single global

climate-change decision-maker, scenarios can

inform the many decision-makers with diverse

responsibilities that will affect and be affected

by climate change. Three groups of decision-
4

The U.S. Climate Change Science Program Executive Summary

makers with distinct information needs can be

distinguished: mitigation policy-makers, who

are mostly but not exclusively national officials;

impacts and adaptation managers, including national officials and others who are responsible

for particular climate-sensitive assets, resources, or interests; and energy resource and

technology managers, who include owners, developers, and investors in energy resources and energy-related capital stock and new technologies.

A key issue in creating scenarios for all 

decision-makers is how to represent decisions

within scenarios. In general, decisions by the

scenario user should be explicitly examined relative to baseline conditions specified in scenarios, while decisions by others outside their

control should be treated like any exogenous uncertainty. The issue is most important in the

treatment of mitigation decisions: scenarios to

inform mitigation should allow explicit examination of the entire relevant range of mitigation

decisions, while scenarios to inform impacts

and adaptation should specify the likely range

of mitigation efforts – usually yielding a narrower range of emissions futures than is considered in scenarios to inform mitigation. 

Scenarios in Assessments 

and Policy Debates

In climate-change assessments, scenarios can

provide required inputs to other parts of the

analysis and help to organize multiple components of the assessment. When scenarios are

used in a prominent assessment, they may subsequently be adopted in planning or decisionsupport processes outside the original

assessment. Scenarios can also help frame public and policy debate, in part by providing an aggregate metric of the issue’s severity. They

consequently may gain prominence in contentious policy debates, and so become subject

to political attempts to influence their content and

political criticism based on their perceived implications for policy action. The unavoidable

judgments underlying construction of scenarios

provide opportunity for partisan efforts to make

scenarios policy prescriptive, and for claims that

only certain scenarios are plausible (e.g., highor low-emissions scenarios, depending on the

critic’s motivation). These claims are unavoidable, since scenarios represent key uncertainties

bearing on high-stakes policy decisions, but such

attempts to restrict scenarios should be resisted,

principally through prominent communication of

the reasoning, assumptions, and treatment of particular uncertainties underlying scenarios.

Scenario Development Process:

Expert-Stakeholder Interactions

Scenario developers must decide how and how

much to involve scenario users and stakeholders

in scenario development. In other fields – where

users are clearly identified – relatively few and

homogeneous, intensive collaboration between

scenario developers and users or their representatives is desirable. Close user involvement is

also advantageous in developing scenarios for

climate change, but potential users of these scenarios are more numerous and diverse, may not

be clearly identified, and may have contending

material interests in the scenarios’ content or

use. This situation calls for delicate decisions

about participation and representation to keep

scenarios tuned to practical users’ needs while

keeping the development process small enough

to be manageable.

Communication of Scenarios

Climate change scenarios must be communicated to multiple audiences with diverse interests and information needs. In addition to the

scenarios’ content, sufficient information must

be provided about the process and reasoning by

which the scenarios were developed, to allow

users to scrutinize the underlying data, models,

and reasoning; judge their confidence in the

scenarios; and have opportunities to critique the

scenarios and suggest alternative approaches.

Effective communication can help engage 

a broad user community in updating and improving scenarios. Open communication of the

decisions, assumptions, and uncertainties underlying scenarios is likely to both increase

users’ confidence that the scenarios have reasonably represented current knowledge and key

uncertainties, and help them develop alternatives if they are unconvinced.
5

Global-Change Scenarios - Their Development and Use

Consistency and Integration 

in Scenarios

Scenario developers should strive for internal

consistency. At one level, this means avoiding

clear contradictions with well-established

knowledge and not moving inadvertently outside bounds of historical experience – although

such sharp departures from experience may be

useful if pursued intentionally to examine lowprobability risks or broaden decision-makers’

perceptions. Perceptions of internal consistency

or coherence in scenarios ultimately rest on subjective judgments, which pose well-known risks

of bias if not carefully structured and controlled.

Potential inconsistencies grow when scenario

exercises use multiple models and attempt to

harmonize them, particularly when some key

quantities are externally specified for some

models and calculated within others. Attempting to avoid such inconsistency by standardizing

model outputs, however, can carry more serious

risks by obscuring interpretation of results and

precluding use of model variation to illuminate

uncertainty. Attempts to connect qualitative and

quantitative aspects of scenarios have been particularly challenging for pursuit of consistency.

Different narrative scenarios often reflect different assumptions about how the world works,

which correspond more closely to different

model structures than to parameter variation.

Better integrating the two approaches will require developing ways to connect narrative scenarios to model structures, rather than merely to

target values for a few variables that models are

then asked to reproduce. 

Treatment of Uncertainty 

in Scenarios

A scenario exercise can represent a few key uncertainties by variation among scenarios. Extreme economy is required in choosing which

uncertainties to represent, what variation (including potential extremes) to represent for each,

and how to combine them in a manageable number of scenarios. Complex narrative scenarios

pose special problems in representing and communicating uncertainty, usually addressed by

seeking underlying structural uncertainties –

e.g., deep societal trends such as globalization

or values shifts – that are judged to influence

many other factors of concern. The most prominent controversy in treatment of uncertainty in

scenarios has concerned whether or not to explicitly assign probabilities to scenarios or associated ranges of quantitative outcome

variables. The debate rests in part on different

views of the typical contents of scenarios, since

subjective probabilities can readily be assigned

to ranges of one or two quantitative variables.

Explicit probability assignment in such simple

cases offers clear benefits for assessing alternative choices and avoids the risk of users assigning their own, perhaps less informed,

probability judgments. Assigning probabilities

to rich multivariate scenarios, particularly if

these include narrative elements, is much more

problematic, since there is no clearly defined interval “between” such scenarios and their

boundaries are not clearly defined.

CONCLUSIONS AND

RECOMMENDATIONS 

Use of Scenarios 

in Climate-Change Decisions 

• Scenarios can make valuable contributions

to climate-change decision-making. There

is a big gap between the use of scenarios in

current practice and their potential contributions, but interest in using scenarios is increasing.

• Scenarios of global emissions and resultant

climate change are required by many diverse

climate-related decision-makers, but beyond

these common requirements decision-makers’

needs from climate-change scenarios are

highly diverse.

• Impacts and adaptation managers include

both national officials and others responsible

for more specific domains of impact. They

need climate-change scenarios, driven by

specified global emissions scenarios, to represent potential climate-related stresses on

their areas of responsibility, plus other environmental and socio-economic information

at appropriate scales. Their combined needs

– for centrally produced climate scenario information, associated tools and support, and

a capability to develop and apply additional

scenario information related to their responsibilities – suggest the need for a cross-scale

organizational structure to provide scenario

information.
6

The U.S. Climate Change Science Program Executive Summary

• Mitigation policy-makers, who are mainly

but not exclusively national officials, need

scenarios of global and national emissions

trends, resultant climate change, and aggregate impacts. In addition, they need scenario

information about the potential policy environment for their choices, including alternative scenarios of other nations’ mitigation

strategies, international mitigation decisions,

and implementation and compliance. In

some cases, they can usefully employ targetdriven scenarios for backcasting analysis.

Mitigation decisions require scenario development capacity at the national level.

• Scenarios for mitigation decisions should include a wide range of baseline emissions assumptions and should not pre-judge the

likely level of mitigation effort, while scenarios for impact and adaptation managers

should be based on emissions assumptions

that include the range of mitigation interventions they judge likely. 

• Energy resource and technology managers,

who are mainly private-sector actors, primarily need scenarios that represent alternative

policy regimes over the 30- to 50-year time

horizons relevant for investment and technology-development decisions. Scenarios

of emissions and climate change may provide background, but do not capture the

most important uncertainties for these 

decision-makers.

Use of Scenarios 

in Climate-Change Assessments 

• Large-scale, official assessments are currently the main users of scenarios and will

likely remain major users. Scenarios in assessments mostly support further analysis,

modeling, and assessment. They can also

help frame the climate issue for the public

and policy-makers. Presentation of scenarios in assessments leads to additional unforeseen uses. 

• Scenarios contain unavoidable elements of

judgment in their production and use. This

makes them vulnerable both to attempts at

bias and to partisan attack. The most productive response lies in transparency about the

process, reasoning, and assumptions used to

produce scenarios, which can both help limit 

bias in scenario production and focus subsequent argument on underlying uncertainties.

What Should Centrally Provided

Emissions and Climate Scenarios

Look Like?

• Centrally provided scenarios of emissions

and resultant climate change should be

global in scope, with major climate-relevant

emissions and other perturbations specified

at least for major world regions. They

should have a time horizon of a century or

longer, with interim results at roughly

decadal resolution. 

• Centrally provided scenarios of global emissions and climate change can help inform

mitigation and adaptation decisions at national and sub-national scales, but such decisions require additional information at

these scales. 

• Emissions scenarios of several types are

needed to serve diverse uses, including alternative baselines, alternative levels of incremental stringency of mitigation effort,

and specified future targets to support backcasting and feasibility analysis. Some emissions scenarios should be coupled to explicit

scenarios of wide-ranging alternative socioeconomic futures, but this is not necessary

for all uses. Scenarios should reflect various explicit degrees of coordination, including simple fully standardized scenarios for

evaluating and comparing downstream models, multi-model scenarios using common

input assumptions, and non-standardized

scenarios to explore alternative assumptions

or meet specific user needs.

• Some scenarios of socio-economic conditions should include qualitative and quantitative elements and sustained analytic efforts

to link the two. These elements can provide

a vehicle to explore major historical uncertainties with large implications for climate

change and vulnerability; provide a logical

structure to connect assumed trajectories for

multiple variables; and provide guidance to

other analysts or users to extend scenarios by

elaborating additional detail. Alternative qualitative and narrative elements should be linked

not just to alternative parameter values in

quantitative models, but also to alternative

forms of causal relations and model struc-
7

Global-Change Scenarios - Their Development and Use

tures.

Scenario Process: 

Developer-User Interactions

• There is value in close collaboration between scenario developers and users, particularly at the beginning and ending stages of

a scenario exercise. 

• The ease of achieving such collaboration

and its value are likely to be greater when

scenario users are clearly identified, few in

number, and similar in their interests 

and perspectives. 

Communication of Scenarios

• Effective communication of scenarios is essential, in forms useful to audiences of diverse interests and technical skills. In

addition to scenario contents, communication should include associated documentation, tools, and support. 

• Transparency of underlying reasoning, assumptions, and major uncertainties is crucial. Such transparency is necessary to

support the credibility of scenarios, to alert

potential users to conditions under which

they might wish to use or modify them, and

to inform criticism and improvement 

of scenarios. 

Consistency and Integration 

in Scenarios

• Any scenario should be internally consistent

in its assumptions and reasoning, to the extent this can be established. 

• In scenario exercises that use multiple models to explore potential uncertainties in future conditions, consistency among models

should be pursued primarily through coordination of inputs, not outputs, except when

coordinated outputs represent common

goals for policy evaluation. 

• Transparency in reporting scenario and

model differences as well as underlying assumptions and reasoning can help mitigate

the effects of inconsistencies among scenarios. 

Treatment of Uncertainty 

in Scenarios

• More explicit characterization of probability judgments should be included in some

future scenario exercises than has been practiced so far. Means available to express

these judgments are of widely varying specificity, ranging from agreed terminology to

explicitly quantified probability distributions. All such judgments should include

explicit acknowledgement of their inevitable

subjective elements and appropriate caveats.

• Explicit probability judgments are easiest to

produce and least controversial in scenarios

generated using quantitative models of climate change or specific impact domains.

These can be conditioned on specific assumptions for socio-economic inputs such as

emissions, and can represent explicitly and

quantitatively the effects of specified variation in initial conditions or unknown parameter values. These devices are also available,

although in less widespread use, in economic

models used to project emissions.

• Including explicit probability judgments is

likely to be most useful when key variables

are few, quantitative outcomes are needed,

and potential users are numerous and diverse. It is likely to be least useful when scenarios specify multiple characteristics,

including prominent qualitative elements;

when the purpose is sensitivity analysis or

heuristic exploration; and when potential

users are few, similar, and known. 

• Because of their large and diverse set of potential users, centrally provided scenarios of

global emissions and climate change should

attempt to include some explicit probability

judgments for ranges of key quantitative

outputs, including global emissions and

global-average temperature change. These

should span a wide range of judged uncertainty on these variables, e.g., 95 to 99 percent. Providing such explicit likelihood

statements lets users choose whether to use

them or not. 

• Scenario exercises should give more attention to low-probability, high-consequence

extreme cases, such as loss of a major con-
8

The U.S. Climate Change Science Program Executive Summary

tinental ice sheet or changes in meridional

ocean circulation. With these, it is especially

crucial to be explicit and transparent about

the reasoning and assumptions underlying

each scenario, including developers’ judgments of relative likelihoods.

Expanding and Sustaining Capacity

for Production and Use of Scenarios

• Present scenario capacity is inadequate. To

help fulfill these presently unmet needs, the

CCSP should establish a program to: 

• Commission scenarios for use in assessments and decision-support activities. 

• Disseminate scenarios with associated

documentation, tools, and guidance

materials.

• Commission various groups to evaluate

scenarios and their applications, and to

develop improved methods. 

• Archive results and documentation 

related to all these tasks, to provide

historical perspective and institutional

memory for future scenario-related activities. 

• Design and management conditions of this

new program should include six elements. 

• The program should build and maintain

strong connections with outside relevant

expertise, and analytic and modeling capability.

• The program should integrate and balance goals and criteria related to scientific and technical quality, and those

related to utility and relevance to users. 

• The program should be insulated from

political control. 

• The program should strive for maximum

transparency in its own activities, in addition to demanding it from activities it

supports. 

• The program will require the authority

and resources necessary to articulate and

promulgate standards for transparency,

consistency, and quality control. 

• The program will require adequate sustained resources level of effort.
Global-Change Scenarios - Their Development and Use

Introduction

9

INTRODUCTION

This report examines the development and use of scenarios in global climate change applications.

It considers scenarios of various types – including but not limited to emissions scenarios – and

reviews how they have been developed, what uses they have served, what consistent challenges

they have faced, what controversies they have raised, and how their development and use might

be made more effective. The report is Synthesis & Assessment Product 2.1b of the US Climate

Change Science Program. By synthesizing available literature and critically reviewing past experience, the report seeks to assist those who may be conducting, using, or commissioning scenarios related to global climate change.

Scenarios are used to support planning and decision-making when issues have deep or poorly

characterized uncertainty and high stakes, often accompanied by long time horizons. These conditions apply to the major decisions about how to respond to global climate change. As scientific

research advances our knowledge of the climate’s present state and trends, its patterns of variability, and its responses to external forcings, we are gaining an increasingly clear view of risks that

may be realized late this century or beyond. These future risks are linked to near-term socio-economic trends and decisions in both public and private sectors. Some near-term decisions – such

as investment in long-lived capital equipment, new resources, or new technologies in the energy

sector – can influence long-term trends in the emissions contributing to climate change. Other

near-term decisions – such as investment in water resources infrastructure or coastal development – can influence how adaptable and how vulnerable future society will be to the impacts of

climate change.
2 Morgan et al. 1998. 

3 Lempert et al. 2006.

4 See, e.g., Lomborg 2001; Michaels 2003b; Castles

and Henderson 2003a, b; UK House of Lords 2005.

10

The U.S. Climate Change Science Program Introduction

Although such decisions are being made now,

making them responsibly requires considering

their potential consequences over the longer

term, including associated uncertainties. This

requires thinking about the future conditions

that will shape their consequences, not just next

month or next year but 10, 30, 50, or 100 years

in the future – longer periods than the horizon of

conventional methods of planning or analysis.2

Attempting to describe potential future conditions over this long time horizon presents a

seeming paradox. On the one hand, conditions

this far in the future, and the factors and actors

that may influence them, are deeply uncertain.3

On the other hand, we have a great deal of

knowledge that can help make informed assumptions about future conditions, even over

such long horizons. This includes well-established

scientific knowledge about physical, chemical,

and biological processes; more weakly, relatively well-established causal mechanisms in

economics, sociology, and politics; and more

weakly still, certain seemingly robust empirical

patterns of historical change in population, economics, and technology. All of these give some

guidance to support judgments about future

conditions that are more or less likely, virtually

certain, or virtually impossible. In some ways

we might be highly confident that the future will

resemble the present, e.g., in the radiative properties of atmospheric trace gases. In others, we

might judge it likely that future conditions will

lie within some envelope extrapolated from

present and past trends, e.g., in projecting rates

of change in fertility, mortality, or labor productivity. Still other areas, such as the development and social consequences of major

technological advances, or large-scale political

events such as wars, political realignments, or

epidemics, may hold more fundamental uncertainties. In some cases, such uncertainties may

be adequately represented as wider distributions

of recognized uncertain quantities. In others,

they may represent events whose character or

even possibility we have not yet imagined.

Despite pervasive uncertainties, people must

make near-term decisions related to climate

change that have long-term consequences, including potential irreversibilities. Scenarios are

tools to help inform these decisions by gathering

and organizing relevant knowledge, organizing

associated uncertainties, and structuring and disciplining associated speculation. This report assesses experience to date in developing and using

scenarios for global climate change. 

Early climate-change debates mainly concerned

scientific questions such as whether and how

the climate is changing, how much change is

caused by human activities, and how sensitive

the climate system is. Scenarios did not figure

prominently in these debates. But as advancing

climate science has increasingly shifted the debate from confirming and describing the climate-change problem toward deciding what to

do about it, the need for long-term decision-support tools like scenarios has increased, as have

the scrutiny and criticism these have attracted.4

In a contentious public-policy area like climate

change, controversy over scenarios is to be expected: scenarios are a method to structure and

communicate the most important uncertainties,

and conflicting judgments about uncertainties

are a major source of disagreements over what

to do. Consequently, we expect the trend of scenarios’ increasing prominence and contentiousness to continue – particularly for emissions

scenarios, since these are the relevant metric of

human environmental burden and the point of

most contested proposed intervention.

Despite pervasive

uncertainties, people

must make near-term

decisions related to

climate change that

have long-term

consequences,

including potential

irreversibilities.
11

Global-Change Scenarios - Their Development and Use

In this report, we try to cast some light on current and coming debates over climate-change

scenarios. These debates presently exhibit basic

confusion about the definition, purposes, and

potential uses of scenarios. We aim to provide

clarification and practical advice to two related

audiences: those conducting assessments or

analyses that develop or use scenarios; and

those commissioning, using, and interpreting

such assessments or analyses. For the first

group, we seek to provide an organized summary of relevant experience in similar efforts,

discussion and clarification of key choices and

challenges, and – to the extent present knowledge allows – practical guidance about pitfalls,

challenges, and opportunities in particular approaches. For the second group, we seek to provide guidance on what to ask for, how and how

much to participate in its production, how to interpret the results, and what questions to ask.

Because the charge of this report is unlike those

of other Synthesis and Assessment products, the

approach we have taken to producing it is necessarily different as well. We were tasked with

reviewing, interpreting, and evaluating experience with scenario methods in global climate

change applications. This is not a narrowly focused question, and there is not a well-developed scientific literature on which we can draw

for answers. While we have reviewed the existing literature on scenarios, most of it concerns

scenarios in other decision domains than global

climate change. In addition, we have examined

several major scenario exercises in global-change

applications. In this, we have drawn on published

materials, both from the exercises themselves and

from commentary and criticism, as well as documentary materials and records, interviews with

participants and users, and the experience and

judgments of team members.

Our review of this experience has not been entirely independent, since members of this writing team were involved as participants,

reviewers, and critics in two of the scenario exercises we review, the IPCC SRES process and

the US National Assessment. While we have

drawn on the experience of these team members, we have attempted to limit the risk of idiosyncratic interpretations and bias by drawing on

other sources as well and by engaging all team

members in developing our summary and discussions of these exercises. Moreover, our purpose is not to either attack or defend these past

exercises, but to seek to understand the decisions made in conducting them, the factors that

influenced them, and the constraints under

which they operated, in order to assess their experience, identify successes and pitfalls, and to

the extent possible, provide guidance to advance

scenario methods for climate change and other

similar environmental issues. Because the experience we review does not provide a sufficiently

large or random sample to support strong scientific inference, the diagnoses, interpretations, and

recommendations we present rely on our collective judgment. We have endeavored to follow our

own advice, and be as transparent as possible

about the foundation and reasoning underlying

our conclusions and recommendations.

The report is organized as follows. Drawing on

the broader literature on scenarios – most of

which concerns domains other than climate

change – Section 1 introduces scenarios, sharpens their definition, and outlines a few major dimensions of variation and decisions that must

be made in developing a scenario exercise. Section 2 focuses specifically on scenarios for

global climate change, and outlines the types of

decisions that could use scenarios and the main

types of scenarios that have been developed for

this issue. Section 3 reviews four major expeWe aim to provide

clarification and

practical advice to two

related audiences:

those conducting

assessments or

analyses that use

scenarios; and those

commissioning, using,

and interpreting such

assessments or

analyses.
12

The U.S. Climate Change Science Program Introduction

riences in developing and using global-change

scenarios. Section 4 discusses several issues that

have posed key challenges in climate-change scenarios and that are likely to require particular attention in designing new scenario exercises. In

addition to drawing on Section 3, this discussion

also makes use of briefer discussions of eight

other examples of global-change scenarios that

illustrate particular issues or challenges; these examples are presented as short boxes in Section 4.

Section 5 provides our conclusions and recommendations for future development and use of

global climate-change scenarios.
5 IPCC 2001b:149.

6 Shell International 2003. 

7 Nakicenovic and Swart 2000:62.

Global-Change Scenarios - Their Development and Use

Scenarios, 

Their Characteristics 

and Uses

SECTION

1

13

1.1 DEFINING SCENARIOS

A scenario is a description of potential future conditions, developed to inform decision-making

under uncertainty. The decisions in question can be faced by individuals, groups, organizations, or

governments, and may pertain to any subject matter. While many writers on scenarios give no explicit definition, others have offered a wide range of definitions, often substantially more complex and

restrictive than this one. The published definitions gathered in Box 1.1 give a sense of both the

broad commonalities among many analysts’ conceptions and the significant differences among them.

A scenario is a coherent, internally consistent, and plausible description of a possible future state

of the world.5

A scenario is a story that describes a possible future. It identifies some significant events, the main

actors and their motivations, and it conveys how the world functions. Building and using scenarios

can help people explore what the future might look like and the likely challenges of living in it.6

Scenarios are images of the future, or alternative futures. They are neither predictions nor forecasts.

Rather, each scenario is one alternative image of how the future might unfold. A set of scenarios assists in the understanding of possible future developments of complex systems. Some systems, those

that are well understood and for which complete information is available, can be modeled with

some certainty, as is frequently the case in the physical sciences, and their future states predicted.

However, many physical and social systems are poorly understood, and information on the relevant

variables is so incomplete that they can be appreciated only through intuition and are best communicated by images and stories. Prediction is not possible in such cases.7

BOX 1.1 Scenarios: a Sampling of Published Definitions.

continued on next page
14

The U.S. Climate Change Science Program Section 1 - Scenarios, Their Characteristics and Uses

The historical uses of scenarios for planning and

analysis lie in war games, exercises of simulated

conflict used for military training, planning, and

operational decision-making. The roots of war

games extend to antiquity, although the first formalized war games were developed for officer

training in 19th-century Prussia.12 In the 1940s

and 1950s, exercises resembling war games

began to be applied outside the purely military

domain, to study potential international crises

that included both high-level political decisionmaking and the potential for military conflict.

These exercises were informed by the then-new

field of game theory, which promised new formal insights into situations of conflict and

strategic decision-making,13 motivated by the

recognition that the new nuclear age had both

raised the stakes of international diplomacy and

created profound new uncertainties over how to

proceed. In these exercises, principally developed at the Rand Corporation, scenarios were

sketches of challenging but plausible situations

to which participants had to respond, allowing

exploration of associated threats and opportunities. They adopted the term “scenario” from

film and theatre, where it denotes a brief sketch

of a story that includes only enough detail to

convey broad points of plot and character. As in

classic war games, scenarios in these exercises

served to help organizations and their leaders

prepare for novel, complex challenges that they

might not anticipate, and which – if they did

arise – would likely develop too fast to allow adequate reflection or analysis in real time.14

Over the past few decades, the use of scenarios

has moved outside the realm of military and

diplomatic activity. Beginning with strategic

planning at the Royal Dutch/Shell oil company,15 scenarios are now widely used for strategic planning, analysis, and assessment by

A climate scenario is a plausible representation of future climate that has been constructed for explicit use in investigating the potential impacts of anthropogenic climate change. Climate scenarios

often make use of climate projections (descriptions of the modeled response of the climate system

to scenarios of greenhouse gas and aerosol concentrations), by manipulating model outputs and

combining them with observed climate data.8

[Scenarios] are created as internally consistent and challenging descriptions of possible futures.

They are intended to be representative of the ranges of possible future developments and outcomes in the external world. What happens in them is essentially outside our own control.9

Scenarios are coherent, internally consistent and plausible descriptions of possible future states of

the world, used to inform future trends, potential decisions, or consequences. They can be considered as a convenient way of visioning a range of possible futures, constructing worlds outside the

normal timespans and processes covering the public policy environment.10

Scenarios are plausible, challenging, and relevant sets of stories about how the future might unfold.

They are generally developed to help decision-makers understand the wide range of potential futures, confront critical uncertainties, and understand how decisions made now may play out in the

future. They are intended to widen perspectives and illuminate key issues that might otherwise be

missed or dismissed. The goal of developing scenarios is often to support more informed and 

rational decision-making that takes both the known and the unknown into account.11

BOX 1.1, continued from previous page.

8 IPCC 2001a:741.

9 van der Heijden 1996:5.

10 Berkhout et al. 2001:i.

11 MEA 2006:xvii.

12 Brewer and Shubik 1979.

13 Von Neumann and Morgenstern 1944, Nash 1950.

14 Levine 1964a,b; Schelling 1964; DeWeerd 1967,

1975; Brewer and Shubik 1979.

15 For relevant history, see Hausrath 1971, Shubik 1975,

Greenberger et al. 1983, Huss 1988, Schoemaker 1995,

Schultz and Sullivan 1972, Schwartz 1991, Shell International 2003.
15

Global-Change Scenarios - Their Development and Use

businesses and other organizations. They have

also figured increasingly prominently in planning, analysis, and policy debate for long-term

environmental issues, in particular global climate change. Because the total body of experience with scenarios provides useful insights into

their use in any particular domain, this section

elaborates the meaning, characteristics, and potential uses of scenarios in general. The next

section turns to their specific use for global environmental issues.

1.1.1 Distinguishing scenarios from

assessments, models, and analyses

Confusion is widespread in discussions of scenarios, because their form and usage are highly

diverse, and because writers’ uses of the term

are often imprecise and occasionally contradictory. Scenarios must be distinguished, on the

one hand, from assessments and various types

of decision support activity that often use scenarios; and, on the other hand, from other types

of statements about future conditions, such as

predictions, projections, or forecasts.

An assessment is any process that reviews and

synthesizes scientific or other expert knowledge

to provide information of relevance to policyor decision-makers.16 The most common methods of assessment are deliberations of expert

panels and formal models, but other methods

combine human deliberations with formal

analysis or modeling, including war games or

other simulation games, policy exercises, 

political-military exercises, constructing future

histories, backcasting, and others.17 These methods may use specifications of potential future

conditions – i.e., scenarios – as inputs to or

components of their work. Scenarios may even

be essential for some of these methods. For example, a war or crisis gaming exercise needs a

scenario to specify the nature of the threat or crisis, while a formal model used to represent future development of some issue of concern needs

a scenario to specify future values of those inputs

not explicitly calculated within the model. But

these methods are broader than and distinct from

scenarios. For example, models do not need scenario-based inputs when used to reconstruct past

conditions or study causal processes. 

The distinction between assessments and scenarios is perhaps clearest in conventional assessments based on deliberations of expert

panels, such as the IPCC, US National Assessment, or Millennium Ecosystem Assessment

(MEA). Such assessments often construct representations of future development of an issue,

usually based on formal models. These representations require scenario-based inputs and

may produce outputs that are themselves used

as scenarios in other activities. But the scenario-related activities are frequently not the

central focus of the overall assessment, which

may examine many additional things, e.g., the

state of knowledge in particular scientific areas,

the status of and trends in particular environmental conditions, the evidence attributing particular environmental changes to human inputs,

or particular policy-relevant scientific questions. Assessments may also include evaluations of proposed actions or proposed criteria

for conducting such evaluations. Scenarios thus

may provide required inputs to assessments, but

are distinct from them.

1.1.2 Distinguishing scenarios from

projections, predictions, and

forecasts

Scenarios must also be distinguished from other

types of statements about the future, such as

predictions, projections, and forecasts. All of

these satisfy the basic definition above: they

are descriptions of potential future conditions

whose primary purpose in most cases is to support decisions. How can scenarios be distinguished? Examining the ways scenarios are

used and discussed by practitioners and researchers suggests four characteristics that distinguish them from other types of future

statements. Although these characteristics are

not essential, they are all more likely to be present in scenarios than in other types of future

statement, so they help to sharpen and delimit

the definition of a scenario.

First, scenarios are multi-dimensional: they describe multiple characteristics that collectively

make up a coherent representation of future

16 Parson 2003:9; Mitchell et al. 2006.

17 NRC 1996; Hausrath 1971; Brewer 1986; Shubik

1975; Svedin and Aniansson 1987; Schultz and Sullivan 1972; Jones 1985; Parson 1996, 1997. 

Scenarios have figured

increasingly prominently

in planning, analysis, and

policy debate for longterm environmental

issues, in particular

global climate change.
16

The U.S. Climate Change Science Program Section 1 - Scenarios, Their Characteristics and Uses

conditions. To achieve this, scenarios assemble

and organize available knowledge, information,

and assumptions from diverse bodies of 

research and expert judgment. The elements of

a scenario can be of diverse types: quantitative

or qualitative, precise or fuzzy, based on

well-established research or informed speculation. Effective scenarios integrate their diverse

elements in a way that is coherent, communicates a clear theme or organizing principle, and

avoids internal contradiction.

Second, scenarios are schematic: that is, they

are multidimensional but not without limit.

Scenarios do not seek to describe potential 

future conditions with complete precision or detail. Rather, they highlight essential characteristics and processes with enough detail that

knowledgeable observers perceive them as realistic and relevant, but not so much as to distract from large-scale patterns. Indeed, one

potential use of scenarios is to stimulate creative

thinking and insights, for which they must leave

something to the imagination. How much detail

and precision is appropriate is a judgment that

depends on the particular application.

Third, scenarios usually come in groups. To be

a useful tool to inform decision-making under

uncertainty, scenarios must represent uncertainty. This is most often done by providing

multiple scenarios, each presenting an alternative realization of uncertain future conditions.18

The number of scenarios depends on the application. Scenario exercises usually use between

two and seven, depending on the stakes of the

issue, the resources invested in the exercise, and

the depth of analysis devoted to each scenario.

The most frequently proposed numbers are

three or four.

Finally, scenarios tend to claim less confidence

than other types of future statements. Although

different authors’ usage is not consistent, “prediction” and “forecast” usually denote statements for which the highest confidence is

claimed. “Projection” denotes a less confident

statement, which may have some specified confidence level and may be explicitly contingent

on specified assumptions about other future

conditions. Calling a future statement a “scenario” usually implies still less confidence and

more associated contingencies. Any use of a

scenario for serious planning or analysis does,

however, presume some minimal threshold of

likelihood. The situation described must be

judged likely enough to merit attention, and to

justify expending resources and effort to study

its implications and potential responses to it.

There may also be a time ordering among these

three types of statements – predictions or forecasts tend to describe nearer-term futures and

scenarios longer-term futures – but there are exceptions, and the meaning of near term and long

term depend on the particular context.

1.2. CREATING A 

SCENARIO EXERCISE: 

KEY CHARACTERISTICS 

AND CHOICES

Beyond these general characteristics, scenarios

vary greatly in their use, production, and contents. Extensive scholarly effort has gone into

providing alternative scenario taxonomies.19

Scenarios can be distinguished, for example, by

whether they present a snapshot of a future state

or a dynamic account of changes over time to

reach that state; by their degree of complexity;

by the relative balance of deliberation and intuition versus formal analysis used in producing

them; or by their temporal and spatial scale.

The set of characteristics on which scenarios

could be sorted is long and open-ended, so we

make no attempt to provide an exhaustive list.

Instead, we summarize the main dimensions of

scenario variation in the form of a list of potentially open-ended design choices. 

1.2.1 Variation among scenarios: 

three basic dimensions 

Three dimensions of variation, concerned with

the purpose of a scenario exercise, have farreaching implications for its design and use and

so merit separate discussion. First, the intended

use of a scenario exercise can vary from the

more predictive to the more exploratory or

18 Crisis-response exercises are often an exception, presenting one scenario at a time showing a novel challenge, to which participants must respond and which

is implicitly contrasted to the status quo.

19 See, e.g., Duncan and Wack 1994, Godet and Roubelat 1996, van Notten et al. 2003.

Effective scenarios

integrate their diverse

elements in a way that

is coherent,

communicates a clear

theme or organizing

principle, and avoids

internal contradiction.
17

Global-Change Scenarios - Their Development and Use

heuristic. It is of course a fundamental error to

take a scenario’s illustrative description of potential future conditions as a confident prediction of what will actually happen – in our

terminology, to take a scenario as a projection or

even a prediction.20 Still, a scenario must be

judged likely enough to merit the attention of

busy people. Exploratory uses of scenarios may

presume only this low threshold, yet have great

value. For example, scenarios can be used to

probe and challenge the mental models, thought

habits, and unrecognized assumptions of 

decision-makers; to clarify points of agreement

and disagreement; to identify and engage

needed participants; to provide a preliminary

structure for advance analysis of potential future decisions; or to seek insights into unrecognized opportunities, risks, causal linkages, or

uncertainties.21 Such insights can arise not just

from examination of uncertainties, but also

from meticulous critical examination of future

factors that are essentially certain (e.g., strongly

determined demographic trends such as the

aging of industrialized-country populations) or

even of present conditions whose significance

has been overlooked.22 Still, the predictive confidence accorded to scenarios is a matter of degree: carefully developed scenarios that are

judged to have captured the most important uncertainties may claim some moderate degree of

confidence, and reasonable distinctions may be

drawn between scenarios that represent conventional versus surprising futures, best and worst

cases, etc.

A related dimension of variation among scenario exercises is their proximity to decisionmaking.23 Scenario exercises may involve

actual decision-makers and seek to directly advise a specific, identified, near-term decision,

but more frequently their relationship to concrete decisions and decision-makers is indirect.

Scenarios may be used for risk assessment, contingency planning, identification of potential

threats or actions to be considered, or early characterization of a poorly understood issue. In

such applications, exploratory uses dominate.

Scenario exercises that are closer to decisions

with significant stakes operate under very different requirements, usually driven by specific

user needs. Their uses tend to be more predictive – constrained by limits of available knowledge – so they might be expected, for example,

to provide more explicit and complete characterization of major uncertainties. They are also

likely to be more integrated with methods to

evaluate alternative choices and identify preferred ones.

A third basic dimension of variation concerns

whether scenarios are defined primarily normatively, on the basis of their perceived desirability or undesirability, or primarily on the basis of

their perceived plausibility or likelihood. Although all scenarios include both positive and

normative elements, it is important to keep as

clear as possible which elements are included

based on perceived likelihood or plausibility

and which because of perceived desirability or

undesirability. The most frequent use of explicitly normative scenarios involves constructing some hypothetical future state primarily on

the basis of its desirability. Such a future might

be constructed to embody participants’ general

intuitions about desirable social trends, or to

achieve specific environmental, development,

or other goals.24 The scenario exercise then consists primarily of backcasting – attempting to

construct paths that connect present conditions

to the specified future conditions, to examine

the feasibility of the target, and identify costs,

tradeoffs, and conditions associated with meeting it.25 Similarly, one can posit an undesirable

future state and then reason through conditions

associated with avoiding it. This approach is 20 Several such errors are collected and discussed in

Bracken 1977, 1990; and Brewer 1990. 

21 Brewer 1990. 

22 Shell International 2001, 2003. For example, in a

1960s crisis exercise on a Soviet invasion of Iran, one

participant realized the local supply of jet fuel available to support a rapid US response was ten times

larger than had been thought, because kerosene – an

acceptable substitute – was used for domestic cooking

and heating (Schelling 1994).

23 This dimension is presented by Van Notten et al. 2003

as “exploration” versus “decision support.”

24 See, for example, the simple scenario exercise in

NRC (1999:161-176) that posited specific targets to reduce world hunger and greenhouse-gas emissions by

year 2050, or the scenarios of the Global Scenario

Group, which included some defined by specified

trends and others back-cast from normatively specified

targets for 2050 (Kemp-Benedict et al. 2002, Raskin et

al. 2002).

25 Robinson 1982, 2003.

Scenarios can be used

to probe and

challenge the mental

models, thought

habits, and

unrecognized

assumptions of

decision-makers; to

clarify points of

agreement and

disagreement; to

identify and engage

needed participants;

to provide a

preliminary structure

for advanced analysis

of potential future

decisions; or to seek

insights into

unrecognized

opportunities, risks,

causal linkages, or

uncertainties.
18

The U.S. Climate Change Science Program Section 1 - Scenarios, Their Characteristics and Uses

sometimes proposed to reduce the risks of hidden bias in construction of scenarios which, like

any decision support tool, can be misused to

provide support for a decision already made for

other reasons, rather than to inform a decision

not yet made. By bundling normative assumptions into the future target state or boundary

conditions, analysts hope to reduce their penetration into the subsequent instrumental reasoning about actions and conditions to reach the

target.26 

1.2.2 Developing scenarios: 

main dimensions of choice

Table 1.1 extends the preceding discussion,

summarizing the main areas of variation and

choice involved in constructing a scenario exercise. This is a highly simplified representation of a complex set of choices. In any

particular scenario exercise some of these

choices may be made by default, without explicit consideration, perhaps because the preferred choice is obvious in context. Although

we present these choices in simple sequential

order, this is not necessary: choices might be

made in some other order, or iteratively adjusted. But while the process and sequence of

choices may be idealized, the set of choices is

not: creating a scenario requires explicit or implicit choices on all these dimensions.

The most basic choices in developing scenarios,

which include the three dimensions of variation

called out above, involve identifying the main

focus of the exercise: what issues are to be addressed or what decisions informed, for whom?

The decision to conduct a scenario-based exercise does not necessarily imply that these matters are clearly understood. The closer a

scenario exercise is to concrete decisions, the

more likely it is that these definitional issues

will be understood clearly, in part through discipline on the process imposed by the involvement of decision-makers. But most often, the

coupling of scenarios to decisions is relatively

weak.27 In some applications (e.g., corporate

strategic planning, responding to a novel military threat) the relevant decision-makers may be

clearly identified at the outset, but the issues to

be addressed and relevant choices may not be.

In other applications, scenarios may be developed to address some broad issue or concern

(e.g., climate change, emerging infectious diseases, or terrorism), but the potential users and

decisions to be informed might both be unspecified. But whether the relationship of a scenario

exercise to decisions is near or far, direct or indirect, clear understanding of its focus and purpose is important, and infrequently achieved:

many scenario exercises muddle through with

vagueness, confusion, or disagreement regarding the focus, purpose, and intended user of the

exercise. Clarifying the overall focus of a scenario exercise may require broad consultations

or scoping workshops involving many potentially interested decision-makers, other stakeholders, and analysts and researchers. 

A second basic set of decisions concerns the

process by which scenarios are developed. Like

the focus of the exercise, decisions about the

process of developing scenarios often receive

little thought, or are not even explicitly recognized as choices, but are nonetheless highly

consequential. What expertise must be included

to ensure the scenarios adequately reflect the

best available scientific knowledge, data, and

models? What decision-makers, stakeholders,

or their surrogates must be involved to keep the

scenarios relevant, plausible, and credible? For

Table 1.1. Idealized Sequence of Major Choices 

in Scenario Development.

Main focus, framing, users, question(s) to be addressed

Process and participation

Key uncertainties to explore: how many, over what range 

Narrative, quantitative, or both

Level of complexity (number of quantitative variables, detail of narrative)

Specific variables and factors to specify

Time horizon and spatial extent

Temporal and spatial resolution

26 This approach does not preclude such misuse: if a

goal is strongly desired, scenarios are at risk of conscious or unconscious bias to make it look easy. Japanese war-games of the Battle of Midway provide striking

examples (Bracken 1977).

27 E.g., note the predominance of scenarios on the “exploration,” rather than the “decision support” side in

the survey of Van Notten et al. 2003.

But whether the

relationship of a

scenario exercise to

decisions is near or far,

direct or indirect, clear

understanding of its

focus and purpose is

important, and

infrequently achieved. 
19

Global-Change Scenarios - Their Development and Use

scenario exercises that must integrate knowledge from diverse domains, individual participants’ knowledge, flexibility, and imagination

can be as important as the disciplines or stakeholder groups they represent. How intensively,

for how long, and by what means will participants interact? Will the process be open to outside observers or participants? How and when

will feedback on the scenarios be sought, and

how will it be used? How and to whom will results be communicated? And crucially, how

will the be process be led, and how will disagreements be resolved? With good leadership,

resolving differences in a scenario exercise can

be less arbitrary and more illuminating than in

other group tasks; when disagreements persist

after careful examination, they can be treated as

important uncertainties to be retained as alternative scenarios, not suppressed by picking a

winner, splitting the difference, or retreating to

vague language. 

Whatever process is chosen, a series of substantive choices must be made about what goes into

the scenarios. The most important of these concern what key uncertainties will be explored, and

how much richness and detail should be included

in scenarios to illuminate these.

What uncertainties are to be explored, and how?

Many dimensions of uncertainty may be relevant to the issue being examined, but only a few

can be examined explicitly in any scenario exercise. Defining these is a crucial choice that

shapes much of what follows in a scenario exercise. For those uncertainties judged most important, alternative outcomes are usually

represented in alternative scenarios. For example, scenarios might present high- and lowgrowth futures, or alternative forms that a

competitive threat might take. Other uncertainties judged less crucial are usually suppressed

by presenting a single “best guess” or “reference case.” The few key uncertainties chosen

can be represented in the number and character

of scenarios, depending on the intended use. A

particular uncertainty might be represented by

high and low values of some quantity, or by a

reference case supplemented with high and/or

low variants. If two or more uncertainties interact, they can be represented by scenarios that

combine different outcomes of each: in the simplest form, two interacting uncertainties can be

represented by four scenarios, often illustrated

by a two-by-two matrix.28 Several alternative

scenarios might seek to span a plausible range

for some key quantitative variable, or present

distinct qualitative outcomes for a single uncertainty, e.g., three types of competitive threat, or

three political futures for a region in turmoil.

Alternatively, scenarios can represent plausible

extreme or “worst-case” scenarios, to assess the

robustness of decisions or strategies.

How rich and complex should each scenario be?

Defining scenarios as we have, as multivariate

but synoptic, still leaves a wide range of levels

of complexity to choose from. At one extreme,

scenarios may specify time-paths for just a few

quantitative variables, or even just one. Such

scenarios are common, e.g., in applications such

as analyzing a firm’s profitability under alternative scenarios for oil prices, or projecting tax

revenues under alternative scenarios of productivity growth and inflation, often in a standard

“high, middle, low” format. A scenario can accommodate more complexity by projecting additional quantitative variables, but as the

number of variables increases, so also does the

need for an organizing principle or gestalt to tie

them together in a non-arbitrary way.

At the other extreme, the core of a set of scenarios can be a set of rich, coherent narratives,

an approach frequently called the Shell approach.29 Each narrative, described principally

in text, reflects a distinct conception of how the

world might develop with a persuasive underlying causal logic. A narrative scenario can stand

alone but may also include specifications of important quantitative variables, e.g., of population or economic growth, consistent with the

broad causal logic underlying the scenario. The

narrative provides the context and explanatory

logic that tie together the time-paths of quantitative variables, although particular time-paths

are regarded as illustrating, not defining, the

scenario – i.e., a different scenario would present substantially different time-paths or relationships among them.

28 Alternative interpretations of this matrix structure are

discussed in van’t Klooster and van Asselt 2006.

29 Van der Heijden 1996; Wack 1985a,b; Schwartz

1991; Shell International 2003.

Many dimensions of

uncertainty may be

relevant to the issue

being examined, but only

a few can be examined

explicitly in any 

scenario exercise.
30 Wack 1985a:74.

20

The U.S. Climate Change Science Program Section 1 - Scenarios, Their Characteristics and Uses

The choice of how rich and complex to make

scenarios has far-reaching implications for the

process of developing the scenarios, what can

be done with them, and the uses they can serve.

The two extreme approaches imply large differences in how uncertainty is treated, what aspects

of the problem receive attention, and the relationship between scenarios and their users,

which we discuss for climate-change scenarios

in Section 4. Richer and more complex scenarios require more time and effort to develop,

whether based on quantitative models, narratives, or both. Complex, narrative-based scenarios may require many person-months of

development to become realistic, relevant, and

persuasive, with consistent relationships among

scenario elements. In return for the extra effort,

this approach allows great flexibility in the way

potential futures are described. Narratives can

convey different aspects of a future situation

with varying degrees of salience or specificity,

and they can compactly convey the tone or character of a future situation by allusion, where a

precise specification would appear arbitrary or

labored. The narrative approach avoids limiting the defining characteristics of a scenario to

any particular set of pre-specified variables, but

attempts to be alert to a wide range of potentially important characteristics and mechanisms

of causal influence. Proponents of this approach argue that a coherent narrative at the

core of a scenario is necessary to avoid arbitrariness in specifying multiple variables, and to

make the exercise useful to decision-makers:

“Most scenarios merely quantify alternative

outcomes of obvious uncertainties (for example, the price of oil may be $20 or $40 a barrel

in 1995). Such scenarios are not helpful to decision-makers”.30

The remaining substantive choices in specifying a scenario follow from the preceding largescale choices. They include specifying the time

horizon and spatial extent of the scenarios, deciding the particular elements to include, and

the temporal and spatial resolution at which scenario outputs are stated. Decisions about temporal resolution (e.g., hourly to multi-decadal)

and spatial resolution (e.g., regional, national,

continental scales) are particularly important

when – as is often the case in global-change applications – scenarios are produced or used by

quantitative models. Such models may have very

precise requirements for the specification and

resolution of inputs and outputs, creating the possibility for serious mismatches between what

users need or expect, and what scenario developers feel comfortable and competent providing. 

This section has discussed the uses, types, and

characteristics of scenarios broadly, in any application area. The next section narrows the

focus to climate change and related areas of

global environmental change, summarizing the

types of scenarios that have been used and proposed, and that might be required, to explore

and inform decision-making in this area.
Global-Change Scenarios - Their Development and Use

Scenarios in 

Global-Change Analysis 

and Decision Support

SECTION

2

21

Analysts have tried to develop scenarios to support understanding of and decision-making for

global environmental issues, beginning with the global models of the mid-1970s and early assessment of acid rain and stratospheric ozone in the late 1970s to early 1980s.31 The reasons for using

scenarios in global change are similar to those that apply in other decision domains: high-stakes

decisions that must be made under deep uncertainty about the conditions that will determine

their consequences, the values at stake, or the relevant set of choices and actors. As in other domains, well-designed scenario exercises can provide a structure for assessing alternative choices

and help focus on the nature of the issue, the relevant choices and actors, the values that might

be at stake, and the types of research or analysis that might help clarify preferred choices.

For climate-change applications, scenario exercises have been conducted and sponsored by governments, international organizations, non-governmental organizations, and collaborative groups.

While these have been diverse in form, details, and purposes, they have tended to focus more on

heuristic and exploratory uses than on supporting specific decisions. The boundaries of the climate-change issue are not sharply defined, however: climate change implicates and connects to

many other areas of policy, including energy, agriculture, hazard protection, and broad questions

of economic development. Consequently, there is substantial uncertainty about what all the relevant decisions, decision-makers, and potentially affected values are. While some decisions are

clearly of primary relevance to climate change, many other decisions that appear to be connected

have not yet incorporated consideration of climate change or even recognized the connection.

Reflecting these fuzzy boundaries of the issue, scenario exercises developed for climate change

have overlapped with other exercises primarily focused on ecosystems, energy, and broad issues

of world development. The fuzziness of the climate issue’s definition increases the challenge of

developing useful scenarios, but also increases the potential value of well-crafted and executed scenario exercises.

31 See, e.g., Meadows et al. 1972, Barney 1981; summary of early ozone assessments in Parson 2003; and

summary history of scenarios in global-change applications in Swart et al. 2004. What was the earliest scenario work in global change depends, of course, on how

the boundaries of global change are defined. Kahn and

Wiener 1967 might be considered an early example. 
33 Weyant et al. 1996, Parson and Fisher-Vanden 1997.

22

The U.S. Climate Change Science Program Section 2 - Scenarios in Global-Change Analysis and Decision Support

The decisions most directly related to climate

change are conventionally sorted into two categories, mitigation and adaptation.32 Mitigation

consists of actions that reduce the human perturbations of the climate system, by reducing

net anthropogenic greenhouse-gas emissions.

Adaptation consists of actions to reduce the

harm or increase the benefit from climate

change and its impacts. Despite uncertainty

about the precise decision agenda, we can identify in general terms the type of information scenarios might provide that would be useful to each

type of decision. 

Scenarios can help inform adaptation decisions

by characterizing the nature and severity of relevant potential impacts; identifying key vulnerabilities, particularly those that might not

otherwise have been recognized; identifying research or monitoring priorities that might give

advance warning about impacts, particularly

acute vulnerabilities; expanding the perceived

set of potential responses; and providing a

framework for evaluating alternative adaptation

measures. They may also help to clarify the

time structure of relevant decisions, identifying

those near-term decisions that might have important but under-recognized connections to future impacts and vulnerability.

Similarly, scenarios can help inform mitigation

decisions by characterizing the potential impacts of climate change and their severity, since

these provide the motivation for mitigation.

But, in addition, mitigation decisions can benefit from information about potential emissions

trends, which determine the nature of the challenge of limiting emissions; about potential

pathways of the extraction and depletion of current energy resources and development of new

ones; and about potential pathways of technological development. Mitigation decisions may

also benefit from scenarios representing the potential policy context in which they are made.

To date, most climate-related uses of scenarios have not examined decisions directly, but

have been embedded in larger exercises of 

assessment, modeling, or characterization of 

the issue. These uses have included formal 

integrated-assessment models,33 comprehensive

assessments conducted by multi-disciplinary expert bodies (e.g., IPCC), and more narrowly focused assessment exercises targeting specific

aspects of the climate-change issue. In these

uses, scenarios represent components of the 

climate-change issue that are required inputs to

an assessment or model. 

The causal logic of the climate-change issue is

complex, including multiple two-way causal

links and feedbacks among socio-economic,

geophysical, and ecological systems.

Integrated-assessment models seek to represent

many of these linkages and feedbacks explicitly; Figure 2.1 shows a typical example of the

“wiring diagrams” that illustrate the increasingly dense linkages and feedbacks represented

in these models. But while such diagrams

might be taken to indicate that all relationships

are represented explicitly within the model – endogenously – this is not the case. All models of

the climate-change issue rely on scenarios to

specify some future quantities exogenously, and

in virtually all cases, scenario-specified inputs

are not modified to account for results of the

subsequent analysis: i.e., they are truly exogenous, and the causal logic does not close.

When scenarios are used to specify exogenous

inputs to a model of some aspect of the climatechange issue, the causal logic of the analysis can

be greatly simplified from that shown in Figure

2.1. Instead, the logic can be represented by a

simple linear structure that extends from human

activities to emissions to climate change to impacts. Figure 2.2 shows this highly simplified

structure. This representation is even more suitable for the uses of scenarios in other types of

global-change assessments, which have been organized around much simpler causal structures

than those that integrated-assessment models

seek to represent. Note that we are not claiming

this simple logical structure adequately represents the true structure of the climate-change

issue: only that it illustrates the ways that scenarios have been used to provide exogenous inputs

to global-change models and assessments.

32 While this categorization has frequently been criticized for neglecting actions with overlapping effects

and the third category of direct interventions in the climate system (Schelling 1983, Keith 2000, Keith et al.

2006, Parson 2006), it remains a useful approximation

for most currently proposed responses. 

To date, most climaterelated uses of

scenarios have not

examined decisions

directly, but have been

embedded in larger

exercises of

assessment, modeling,

or characterization of

the issue.
23

Global-Change Scenarios - Their Development and Use

This linear logical structure allows a simple,

practical categorization of five types of scenarios that have been developed for the climatechange issue. These types are defined by what

quantities they specify and what primary area

of analysis they provide input to. Their differences can be represented by where they cut the

causal chain in Figure 2.2, with the scenario

specifying quantities lying on one side of the

cut, and the assessment or other activity using

the scenario lying on the other side. The next

five subsections discuss these five types of climate-change-related scenarios in turn.

2.1. EMISSIONS SCENARIOS 

FOR FUTURE CLIMATE

SIMULATIONS

Scenarios of greenhouse-gas emissions, sometimes including other human perturbations such

as land-use change, are the best known type of

climate-change related scenario. Emissions

scenarios provide required inputs to model calculations of future climate change, as shown in

Figure 2.3. As the focus and intended use of climate-model studies have shifted over time, so

has the role of emissions scenarios. Early research studies examined the climate system’s response to potential (rather than projected)

emissions inputs in individual model studies or

standardized model comparisons. In such exercises, the purpose of a scenario is to provide a

known, consistent perturbation big enough to

generate an informative model response. Such

scenarios must be standardized, so differences

between model runs can be traced to scientific

uncertainties and model differences, but they

can be simple and arbitrary, making no claim to

being realistic. The earliest such scenarios

showed a “step-change” increase in atmospheric

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

• fresh water

• ecosystems

• agriculture

• human health

• property,

 infrastructure

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

IMPACTS

ATMOSPHERIC COMPOSITION

HUMAN ACTIVITIES

CLIMATE & SEA LEVEL

ECOSYSTEMS

Atmospheric

Chemistry

Ocean 

Carbon Cycle

Climate

Ocean 

• temperature

• sea level

Other Human

Systems

Energy

System

Coastal

System

Agriculture,

Livestock, &

Forestry

Unmanaged

Ecosystem

Hydrology

Terrestrial

Carbon Cycle

Crops &

Forestry

Figure 2.1. Wiring Diagram for Integrated Assessment

models of climate change. (Source: Weyant et al. 1996)

Figure 2.2.

Anthropogenic

climate change:

Simplified linear

causal chain.
24

The U.S. Climate Change Science Program Section 2 - Scenarios in Global-Change Analysis and Decision Support

concentration of CO2 from its pre-industrial

value, to either two or four times that value.34

Models’ equilibrium responses to doubled CO2

provided a standard benchmark of model responsiveness, which has remained around the

range of 1.5 to 4.5°C for more than 20 years.

This range of modeled equilibrium responses to

a standardized perturbation does not predict actual climate changes under human perturbations, although it has often mistakenly been

taken as such. 

The next generation of climate-model studies,

beginning in the early 1990s, specified a timepath of atmospheric concentrations rather than

a one-time perturbation. These studies for the

first time allowed comparison of models’ transient responses, by examining not just how much

the cimate changes, but how fast it changes. They

still used a simple, highly idealized standard scenario, most frequently a 1 percent per year increase in atmospheric concentration, expressed

as CO2-equivalent. Only two such transient

simulations had been conducted by the first

IPCC assessment (1990), but by the time of the

second assessment (1996), most modeling

groups had produced at least one.35

Since the mid-1990s, climate modelers have increasingly sought to produce realistic pictures

of how the climate may actually change, requiring a new approach to emissions scenarios.

Scenarios must now present well-founded judgments or guesses of actual future emissions

trends and their consequences for atmospheric

concentrations. The required emissions scenarios have been constructed either by extrapolating recent emissions trends, or, particularly for

energy-related CO2, representing emissions in

terms of underlying drivers such as population,

economic growth, and technological change and

projecting these drivers using some combination of modeling and trend extrapolation.

Driven by such scenarios, climate models for

the first time can claim to be reasonable estimates of how the climate might actually change.

In addition, comparisons using multiple models

and emissions scenarios have allowed partitioning of uncertainty in future climate change into

roughly equal shares attributed to uncertainty in

climate science and models, and in emissions

trends.36 These comparisons have also allowed

estimation of the climate-change benefits from

specified emissions reductions. 

As this shift occurred, advances in climate models – e.g., improved representations of atmospheric aerosols, tropospheric ozone, and

atmosphere-surface interactions – produced

mismatches between emissions scenarios and

the input needs of climate models. For example,

climate models now require emissions of several types of aerosols and reactive gases (principally the ozone precursors, hydrocarbons, CO

and NOx), explicit estimates of black carbon and

organic carbon, and some disaggregation of different types of volatile organic compound

(VOC) emissions. Moreover, because these

emissions act locally and regionally rather than

globally, they must be specified at the spatial

scale of a model grid-cell, about 150 sq. km.

Models of atmospheric chemistry and transport

then use these emissions to generate the concentrations and radiative forcings used by the

climate model. Since emissions scenarios often

do not provide the required detail, climate modContent of Scenarios Use of Scenarios

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

• fresh water

• ecosystems

• agriculture

• human health

• property,

 infrastructure

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

IMPACTS

34 e.g., Manabe and Wetherald 1967, Manabe and

Stouffer 1979.

35 Washington and Meehl 1989, Manabe et al. 1991,

IPCC 1996a.

36 Cubash et al. 2001.

Figure 2.3.

Emissions

scenarios for

climate

simulations. 
25

Global-Change Scenarios - Their Development and Use

elers meet these input needs through various ad

hoc approaches.

Changes in standard emissions scenarios pose

challenges for maintaining comparability with

past model results. For example, the IPCC’s

IS92 scenarios projected that future SO2 emissions would roughly double, then stabilize,

while the later SRES scenarios projected sharp

decreases, giving 2100 emissions about 

one-quarter the IS92 value. This change caused

significant increases in projected warming that

were not due to any changed scientific understanding. To help maintain backward comparability, many climate-model groups have

continued to run simulations using older standardized scenarios, to provide benchmarks for

comparisons both among current models and

between current and previous-generation models.

2.2. EMISSIONS SCENARIOS 

FOR EXPLORING ALTERNATIVE

ENERGY AND TECHNOLOGY

FUTURES

In addition to providing needed inputs to climate models, emissions scenarios have also

been produced to examine alternative 

socio-economic, energy, and technological futures, as shown in Figure 2.4. As in Figure 2.3

the content of the scenario is emissions, but the

scenario is now used to examine the socio-economic implications of alternative emission

paths, which lie upstream or to the left in the

causal chain. A scenario specifying a particular

emissions time-path can be used to explore what

patterns of demographic and economic change,

energy resource availability, and technology development are consistent with that trajectory.

Alternatively, scenarios can be used to examine

what changes in policies, technologies, or other

factors would be required to shift emissions

from some assumed baseline onto a specified

lower path, and to estimate the cost of such a

shift. To be used in this way, an emissions scenario might be specified arbitrarily, or might

specify some environmental target based on

normative criteria as discussed in Section 1.2.

Such scenarios have been most frequently used

to examine emissions trajectories that stabilize

atmospheric CO2 concentrations at specified

levels. More recent exercises have instead taken

stabilization of radiative forcing as the target, to

examine the role of non-CO2 greenhouse gases in

meeting stabilization goals.37

An important early example is the Wigley,

Richels, Edmonds (WRE) scenarios, which presented emissions pathways that stabilized atmospheric CO2 concentration at five levels,

ranging from 450 to 1000 ppm.38 Developed

heuristically from a simple model of the global

carbon cycle and two energy-economic models,

these scenarios illustrated the large cost savings

attainable by approaching stable concentrations

through emission paths that initially rise and

then decline steeply, rather than by beginning a

more gradual decline immediately.

Several other sets of stabilization scenarios have

been proposed and used for similar explorations. For example, the Energy Modeling

Forum (EMF) has convened several multimodel scenario exercises focusing on emissions,

emissions constraints, and their socio-economic

effects. These have studied decision-making

under uncertainty, international distribution of

costs and benefits, the costs and benefits of the

Content of Scenarios Use of Scenarios

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

• fresh water

• ecosystems

• agriculture

• human health

• property,

 infrastructure

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

IMPACTS

37 de la Chesnaye and Weyant 2006, EMF 2006, CCSP

2007.

38 Wigley et al. 1997.

Figure 2.4.

emissions 

scenarios for

energy/technology

futures. 

Models’ equilibrium

responses to doubled

CO2 provided a

standard benchmark of

model responsiveness,

which has remained

around the range of

1.5 to 4.5 ̊C for more

than 20 years.
26

The U.S. Climate Change Science Program Section 2 - Scenarios in Global-Change Analysis and Decision Support

Kyoto Protocol, the implications of potential future energy technologies and technological

change for emissions, and the implications of including non-CO2 gases and carbon sequestration

in mitigation targets and policies.39

In a recent scenario exercise of this type sponsored by the CCSP, three modeling teams constructed separate reference-case scenarios to

examine the implications of stabilizing radiative

forcing at levels roughly corresponding to CO2

concentrations of 450, 550, 650, and 750 ppm.

They examined the energy system, land-use,

and economic implications of moving to stabilization. This project explored the role of multiple gases and alternative multi-gas control

strategies in pursuing atmospheric stabilization.

These scenarios may also provide a basis for future analyses by the CCSP, the Climate Change

Technology Program (CCTP), or others.40

2.3. CLIMATE CHANGE

SCENARIOS

Climate scenarios describe potential future climate conditions (Figure 2.5). They are used to

provide inputs to assessments of climate-change

impacts, vulnerabilities, and associated options

for adaptation, and to inform decision-making

related to either adaptation or mitigation. Depending on their specific use, climate scenarios

may include multiple variables, such as temperature, precipitation, cloudiness, humidity, and

winds. They may describe these at spatial scales

ranging from the entire globe, through broad

latitude bands, large continental and sub-continental regions, to climate model grid-cells or

finer scales. They may project these at time resolutions ranging from annual or seasonal averages to daily or even finer-scale weather.41

Three major types of climate scenarios are distinguished by how they are produced: incremental scenarios, analog scenarios, and

climate-model scenarios.42 Incremental scenarios change current conditions by plausible but

arbitrary amounts. For example, a region’s temperature might be warmed by 2, 3, or 4°C from

present conditions, or its precipitation increased

or decreased by 5, 10, or 20 percent. Such adjustments can be made to annual or seasonal averages, to finer-period measurements of current

conditions, or to the variability of temperature

or precipitation over days, months, or years.43

Like the simple emissions scenarios used for

climate-model comparisons, incremental climate scenarios are simple to produce but make

no claim to represent actual future conditions.

They are used for initial exploratory studies of

climate impacts and to test the sensitivity of impact models.

Analog climate scenarios represent potential future climates by the observed climate regime at

another place or time. A spatial analog imposes

the climate of one location on another, e.g., representing the potential climate of New York in

the 2050s by that of Atlanta today or that of Illinois in the 2050s by that of Kansas today.44 A

temporal analog imposes climate conditions observed in the past, in the historical record or earlier paleoclimatic observations, e.g., using the

Content of Scenarios Use of Scenarios

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

• fresh water

• ecosystems

• agriculture

• human health

• property,

 infrastructure

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

IMPACTS

Figure 2.5. Climatechange scenarios. 

39 See, e.g., Weyant and Hill 1999; Weyant 2004; de la

Chesnaye and Weyant 2006; EMF 2006. 

40 CCSP 2007.

41 IPCC – TGCIA 1999, Barrow et al. 2004.

42 Mearns et al. 2001.

43 e.g., Mearns et al. 1992, 1996; Semenov and Porter 1995.

44 E.g., Kalkstein and Greene 1997.
27

Global-Change Scenarios - Their Development and Use

hot, dry period of the 1930s to study impacts of

potential future hot, dry climates.45 Like incremental scenarios, analog climate scenarios are

more useful for exploratory studies of the climate sensitivity of particular resources or systems than for projecting likely impacts. While

they represent climate states that are known to

be physically possible, they are limited as representations of potential future states since they

do not consider the changes in greenhouse-gas

concentrations that are the principal driver of

climate change. 

Climate-model scenarios use computers to produce a physically consistent representation of

the movement of air, water, energy, and radiation through the atmosphere. Climate models,

also called General Circulation Models or

GCMs, approximate this calculation by dividing the atmosphere into thousands of grid-cells,

roughly 150 km. square in today’s models, with

a dozen vertical layers, treating conditions as uniform within each cell and representing finerscale processes by numerical relationships, called

“parameterizations,” that are defined at the scale

of a grid cell. Climate models are used to study

the present climate and its responses to past perturbations like variation in the sun’s output or volcanic eruptions, and to construct scenarios of

future climate change under any specified scenario of emissions and other disturbances. 

Unlike incremental and analog scenarios, 

climate-model scenarios use emissions scenarios as inputs. Model-based scenarios have a

greater claim than the other types to being realistic descriptions of how the climate might actually change, because they are based on

specified assumptions of future emissions

trends acting on modeled representations of

known physical processes. Even with a given

emissions scenario, model-based climate scenarios are uncertain. Since climate models are

driven by the radiative effects of atmospheric concentrations of relevant species, some of this uncertainty comes from the carbon-cycle and

chemical processes by which specified emission

paths determine concentrations and radiative forcings. Some of the uncertainty can be seen in the

slight differences among different runs of the same

climate model, because the models are sensitive

to small differences in starting conditions. And

some of the uncertainty can be seen in differences

between calculations by different models, mainly

caused by differences in the computational methods they use to handle errors introduced by finite

grid-cells, and the parameterizations they use to

represent small-scale processes. 

Just as modeling future climate change requires

specification of future emissions trends, assessments of future climate-change impacts require

specification of future climate change. Data

from a climate-change scenario might be used

as input to impact assessments of freshwater

systems, agriculture, forests, or any other 

climate-sensitive system or activity. Impact

studies can use various methods, including

quantitative models such as hydrologic and crop

models, threshold analyses that examine qualitative disruptions in the behavior of climate-sensitive systems, or expert judgments that

integrate various pieces of scientific knowledge.

As with all scenarios, the usefulness of climate

scenarios depends on how well they meet users’

information needs. The highly specific climatedata needs of impact analyses may not readily

be provided by climate-model outputs, or may

include results of whose validity climate modelers are not confident. For example, a common need of impact analyses is for data at

substantially finer scales than the relative coarse

grid of a climate model, which might have only

60 to 100 cells over the continental United

States. One advantage of incremental and analog scenarios is that they can typically provide

data at substantially finer scales. “Downscaling” techniques seek to combine the benefits of

model-based scenarios – physical realism and

explicit emissions-scenario drivers – and data at

finer scales. The two major approaches are

statistical downscaling and nested regional

modeling.46 Statistical downscaling involves estimating statistical relationships between

large-scale variables of observed climate, such

as regional-average temperature, and local variables such as site-specific temperature and 

precipitation.47 These relationships are then assumed to remain constant under global climate

45 E.g., Rosenberg et al. 1993.

46 Giorgi et al. 2001.

47 Wilby and Wigley 1997.

Just as modeling future

climate change

requires specification

of future emissions

trends, assessment of

future climate-change

impacts requires

specification of future

climate change.
28

The U.S. Climate Change Science Program Section 2 - Scenarios in Global-Change Analysis and Decision Support

change. A nested regional climate model provides an explicit physical representation of climate for a specific region, including local

factors such as mountain ranges, complex coastlines, and surface vegetation patterns, with initial and boundary conditions provided by a

GCM. Regional climate models can provide

projections at scales as small as 10 to 20 km.

Although downscaled results are anchored to

local features with well-understood climatic effects, downscaling introduces uncertainties beyond

those already present in GSM results.48

2.4. SCENARIOS OF DIRECT

BIOPHYSICAL IMPACTS: 

SEA LEVEL RISE

Although climate-change scenarios can provide

inputs to studies of any impact, scenarios can

also be constructed of particularly important

forms of impact, such as sea level rise – one of

the more costly and certain consequences of climate warming (Figure 2.6).49 Changes in global

mean sea level as the climate warms can be calculated using a GCM with a coupled ocean and

atmosphere, which can simulate the transfer of

heat to the ocean and the variation of ocean temperature with depth. To construct sea level rise

scenarios for particular coastal locations,

model-derived projections of global mean sea

level rise must be combined with projections of

local subsidence or uplift of coastal lands, as

well as local tidal variations derived from historical tide-gauge data.

Sea level rise will increase circulation and

change salinity regimes in estuaries, threaten

coastal wetlands, alter shorelines through increased erosion, and increase the intensity of

coastal flooding associated with normal tides

and storm surge. Scenarios of sea level rise are

consequently needed to assess multiple linked

impacts on coastal ecosystems and settlements.

In specific locations, these impacts will depend

on many characteristics of coastal topography,

ecosystems, and land use – e.g., coastal elevation and slope, rate of shoreline erosion or accretion, tide range, wave height, local land use

and coastal protection, salinity tolerance of

coastal plant communities, etc. – in addition to

local sea level rise.50

In addition to its gradual impacts, sea level rise

is subject to large uncertainties from the potential loss of continental ice sheets in Greenland

and West Antarctica. The consequences of these

events for global sea level rise are well known

because they can be calculated quite precisely

from the volume of the ice sheets – roughly 7

meters rise from complete loss of the West

Antarctic Ice Sheet and 5 meters from Greenland – but the probabilities of these events and

their likely speed of occurrence are both highly

uncertain. One recent study has suggested a

probability of a few per cent that the West

Antarctic Ice Sheet will contribute an additional

one meter per century beyond that calculated

from gradual warming.51

There are several reasons to call out sea level

rise from other climate-change impacts to be

represented in separate scenarios. First, sea

level rise is a powerful driver of other forms of

climate-change impact, probably the most important driver of impacts in coastal regions.

Since it is a direct physical impact of climate

change that can be described precisely and compactly, a sea level rise scenario is an efficient

way to transmit the most important information

about climate change to coastal impact assessments. Moreover, since sea level rise does not

depend on socio-economic processes and cannot be significantly influenced by human actions (other than by limiting climate change

itself), it may be reasonably treated as exogenous for purposes of impact assessment. For all

these reasons, sea level rise is a good proxy for

the most important causal routes by which climate

change will affect coastal regions. 

Finally, because sea level rise is subject to large

uncertainties with known consequences but unknown probabilities, it is a useful variable for

exploratory analysis of worst-case scenarios in

long-range planning. Other forms of climate

impact might also merit being called out in separate scenarios: changes in snowpack in mountain regions, seasonal flow regimes in major

river basins, or the structure and function of

major ecosystem types. Based on present

48 Mearns et al. 2001, Giorgi et al. 2001.

49 IPCC 2001a.

50 Burkett et al. 2005.

51 Vaughan and Spouge 2002.
52 MEA 2005.

29

Global-Change Scenarios - Their Development and Use

knowledge, however, only sea level rise has

shown these characteristics strongly enough to

motivate construction of separate scenarios.

2.5. MULTIVARIATE SCENARIOS

FOR ASSESSING IMPACTS,

ADAPTATION, AND

VULNERABILITY

Many potentially important impacts of climate

change cannot be adequately assessed by considering only how the climate might change.

These impacts require multivariate scenarios

that include climate change and other characteristics likely to influence impacts. This is the

case, for different reasons, for both ecosystems

and socio-economic systems, although the nature of the multivariate scenarios that are required – i.e., the number and identity of the

characteristics that must be specified – will vary

widely among particular impacts. 

Ecosystems are affected by climate change, but

also by many other changes in environmental

conditions that are influenced by human activities, such as nitrogen and sulfur deposition, tropospheric ozone and smog, and changes in

erosion, runoff, loadings of other pollutants,

land use, land cover, and coastal-zone characteristics. Consequently, realistic assessments of

potential future impacts on ecosystems require

specifying the most important forms of humandriven stresses jointly, not just climate.52

In addition, many important forms of climatechange impact depend not just on climate

change, its direct biophysical impacts such as

sea level rise, and perhaps other forms of environmental stress, but also on the nature of the

society on which these climate and other environmental changes are imposed – e.g., how

many people there are; where and how they live;

how wealthy they are; how they gain their livelihoods; and what types of infrastructure, institutions, and policies they have in place.53

Assessment of climate impact on ecosystems

that are intensively managed for human use,

such as agriculture, managed forests, rangelands, and hydrologic systems, must consider

human management as a factor in impacts. The

non-climatic factors that influence these management decisions – e.g., changes in market

conditions, technologies, or cultural practices –

must be considered for inclusion in scenarios if

they are sufficiently important in mediating climate impacts.

In other domains, socio-economic factors can

mediate climate impacts by influencing vulnerability and adaptive capacity. No general model

of the socio-economic determinants of adaptive

capacity exists. Important factors are likely to

vary across specific types of impact, locations,

and cultures, and may include many demographic, economic, technological, institutional,

and cultural characteristics.

Some socio-economic characteristics that are

likely to be relevant for many impact assessments – e.g., the size and sometimes the age

structure of population, the size and sometimes

the sectoral mix of GDP – are normally generated in the course of producing emissions scenarios. Consequently, when current emissions

scenarios exist for the region for which an impact assessment is being conducted, it makes

sense to strive for consistency with them.54

Even for these variables, however, there may be

Content of Scenarios Use of Scenarios

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

DIRECT

BIOPHYSICAL

IMPACTS

OTHER

IMPACTS

• coastal erosion

• estuaries

• ecosystems

• property,

 infrastructure

• fresh water 

Figure 2.6.:

Scenarios of 

direct biophysical

impacts: sea level

rise. 

53 Parson et al. 2001, 2003; Arnell et al. 2004.

54 Berkhout et al. 2001, citing UNEP 1994 guidelines.
30

The U.S. Climate Change Science Program Section 2 - Scenarios in Global-Change Analysis and Decision Support

significant problems of incompatible spatial

scale. Impact assessments often examine

smaller spatial scales than emissions projections, so they may need these socio-economic

data at finer scale than is available. Downscaling future socio-economic projections has

proved challenging thus far. There is no generally accepted method for doing so, and several

research groups are exploring development of

alternative methods.55

In contrast to the few clearly identified aggregate characteristics needed to construct emissions scenarios, the socio-economic factors that

most strongly shape adaptive capacity and vulnerability for particular impacts may be detailed, subtle, and location-specific. It may not

even be clear what characteristics are most important before doing a comprehensive analysis

of potential causal pathways shaping impacts.

The most important characteristics may interact

strongly with each other or with other economic

or social trends, or may not be readily quantifiable. All these factors make the development

of socio-economic scenarios for impact assessment a much more difficult endeavor than constructing emissions scenarios.

Because scenarios are schematic, not all factors

that might be important for impacts can be included. Details are typically not included or

treated as merely illustrative. But particular details, which cannot be identified in advance,

may be crucial determinants of vulnerability to

climate impacts.56 Impact assessments have responded to this dilemma in two broad ways.57

First, constructing scenarios of relevant socioeconomic conditions has been delegated to local

or regional teams with expertise in the impacts

being assessed, subject to constraints to maintain consistency with other assessments. Second, since local or regional scenario groups may

not have access to all knowledge relevant to understanding the main determinants of impacts,

more open-ended approaches have been employed – e.g., exploratory analyses that iterate

between considering particular characteristics

that might be important, examining their implications for impacts using the data and models

available, then re-assessing what variables are

most important.

This section has sketched a typology of globalchange scenarios and identified major types of

decision-makers who might use global-change

scenario-based information. The next section

turns to current experience with global-change

scenarios, summarizing the development, contents, and uses of four major exercises. Informed by these cases plus additional short

scenario examples presented in text boxes, Section 4 will summarize and discuss the major

challenges for making and using scenarios that

are raised by this experience, providing the basis

for the conclusions and recommendations presented in Section 5.

Content of Scenarios Use of Scenarios

SOCIOECONOMIC

CONDITIONS

• population

• GDP

• energy system

• industry

• technology

• agriculture, 

 land-use

EMISSIONS

• greenhouse gases

• aerosols

• other drivers,

 e.g. land-cover

 change

• sea level rise

• fresh water

• ecosystems

ATMOSPHERE

& CLIMATE

• carbon cycle

• temperature

• precipitation

• humidity

• soil moisture

• extreme events

DIRECT

BIOPHYSICAL

IMPACTS

OTHER

IMPACTS

• agriculture

• human health

• property,

 infrastructure

Figure 2.7:

Multivariate

scenarios for

impact assessment.

55 Toth and Wilbanks 2004, Pitcher 2005. 

56 Berkhout et al. 2002. 

57 Berkhout et al. 2001, Parson et al. 2001.
Global-Change Scenarios - Their Development and Use

Review of 

Major Climate-Change 

Scenario Exercises

SECTION

3

31

In this section, we review experience to date developing and using scenarios for global climate

change applications. Because little literature on these activities yet exists, our selection of cases

has inevitably been both limited by time and resources at our disposal and reliant in part on the

knowledge and experience of team members. We discuss four exercises in detail, in an attempt

to cover the largest-scale and most important activities. Section 3.1 reviews the IPCC emission

scenarios, with particular detail on the most recent and important exercise, the Special Report

on Emissions Scenarios (SRES). Section 3.2 considers the US National Assessment, which developed and used scenarios of both climate and socio-economic conditions. Section 3.3 considers

the UK Climate Impacts Programme, which has also both developed and used scenarios, following a different approach from the US National Assessment. Section 3.4 reviews the ambitious

scenario-generating exercise conducted as part of the Millennium Ecosystem Assessment (MEA),

in which climate change was one of several dimensions of stress considered on global ecosystems.

For each exercise, we consider only the development and use of scenarios, rather than examining the larger assessment processes of which the scenarios were part. We consider how the scenarios were developed, including both methods of reasoning and managerial process; how and by

whom they were used; and subsequent evaluations, when these are available. General issues and

challenges that emerge from these experiences are discussed in Section 4.

To provide more illustrative variation, we also provide shorter summaries of eight additional scenario activities, some of them related to the four we consider in detail. Presented in text boxes

throughout Section 4, these are intended to provide additional information to highlight particular issues. We have particularly sought experiences that illuminate potential relationships between

scenarios and decision-making. 

All these scenario exercises represent early work in an immature field. Our aim is not to criticize particular exercises, but to seek insights from their experience into the general problems of

making useful global-change scenarios.
32

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

3.1. IPCC EMISSIONS SCENARIOS 

Since its establishment in 1989, the IPCC has

organized three exercises to develop scenarios

of greenhouse-gas emissions, of increasing

scale and complexity. For its first report,

IPCC’s Working Group 3 on “Response Strategies” included a sub-group on emissions scenarios. Four scenarios were produced but little

used in this assessment because of time limits

and because, with one exception, only doubledCO2 equilibrium climate-model runs were available at the time.58 The next exercise produced

six new scenarios, called IS92a through IS92f.59

These were the first global emissions scenarios

with a full suite of greenhouse gases and at least

some explicit calculation underlying each. The

IS92a scenario, one of the central scenarios in

this group, was used in climate-model comparisons conducted for the 1996 IPCC assessment,

along with the simpler transient scenario of 1

percent annual increase in equivalent-CO2 concentration and further equilibrium runs.60

The third and most ambitious IPCC scenario

process was established in 1997 and worked for

two years to produce the Special Report on

Emissions Scenarios (SRES).61 In part, this

process was established in response to two

widely circulated criticisms of the IS92 scenarios. The first of these criticized the 1992 scenarios for inconsistency with other published

scenarios of energy and carbon intensity for

major world regions; failing to reflect important

recent trends, including the collapse of the Soviet Union and increasing restrictions on sulfur

emissions worldwide; relying inappropriately

on a single model; and only being useful as climate-model inputs, not for other purposes such

as mitigation studies or supporting climatechange negotiations.62 The second criticized the

IS92a scenario for assuming increasing divergence in the per capita emissions of industrialized and developing regions, arguing that this

represented a strong bias in favor of already developed regions.63

In response, the 1996 plenary session of the

IPCC requested a new set of emissions scenarios. These new scenarios were to improve treatment of sulfur aerosols and emissions from

land-use change, and were not to rely on a single model or expert team, but instead to draw

on the existing literature and invite any group

with relevant expertise to participate in an

“open process.”64 They were also charged to

serve more uses than climate-model inputs,

such as supporting impact analyses, but to assume no new climate-policy interventions. Although not explicitly in the terms of reference,

it was also clearly understood that the scenarios

would address the criticism of the IS92 scenarios by focusing on convergent development

paths between North and South.

In January 1997 the IPCC established a writing team,

including members of several energy-economic

modeling groups and experts in related areas

such as population, technological change, and

scenario development methods. The process

ran under tight time pressure to provide preliminary scenarios by early 1998 for climate-model

runs in the IPCC Third Assessment. 

Prior scenarios were compiled in a web-based

database,65 and any researcher was invited to

submit new ones. By mid-1998 the database

contained more than 400 scenarios. Most of

these projected only energy-related CO2 emissions, but they were highly diverse in their coverage and resolution, the variables included, and

their methodologies. The usefulness of these

scenarios in constructing new ones was limited

by several weaknesses, however. Many were incomplete, lacked documentation of inputs, or

made inconsistent assumptions. Few included

sulfur or land-use emissions, which were specif58 The scenarios were mentioned in a 1-page Appendix

to the Working Group 1 report. The one non-equilibrium run available was a preliminary transient run

using 1 percent annual CO2 concentration increase.

See Mitchell et al. 1990, Bretherton et al. 1990, IPCC

1990.

59 Leggett et al. 1992.

60 The 1 percent scenario was similar to IS92a, but gave

total radiative forcing about 20 percent greater by 2100.

Washington and Meehl 1989; Stouffer et al. 1989;

Bretherton et al. 1990:180-182.

61 Nakicenovic and Swart 2000.

62 Alcamo et al. 1995.

63 Parikh 1992, 1998.

64 Nakicenovic and Swart 2000: 324, Appendix I (terms

of reference).

65 Morita and Lee 1998.
33

Global-Change Scenarios - Their Development and Use

ically requested of the new scenarios. Many

were unclear on whether they assumed mitigation efforts, while the new scenarios were instructed to exclude them. Consequently, the

development of new scenarios had to proceed

largely independently of the collection of existing scenarios through the literature review and

open process.

Early on, participants decided to use narrative

scenarios in addition to quantitative models, and

to include experts in this approach on the writing team. This decision drew on recent successes using such scenarios for energy and

environmental applications,66 and responded to

the charge to make the scenarios more integrated and more broadly useful. Participants in

an April 1997 workshop chose two key uncertainties to explore in the scenarios: whether

world values would mainly stress economic

prosperity or balance economic and ecological

concerns (labeled “A” vs. “B” scenarios); and

whether the organization of economies and institutions would continue shifting toward global

integration, or reverse and move toward regional

fragmentation (labeled “1” vs. “2” scenarios).67

Combined, these gave four scenarios, which

were sketched in preliminary terms at the workshop. In the A1 (economic, global) scenario,

economic growth and inter-regional income

convergence continue strongly worldwide – all

developing countries grow like Japan and Korea

from the 1950s to the 1980s – while world population peaks at 9 billion by 2050. Rapid innovation yields many advanced energy sources,

while acid rain and other local and regional environmental problems are aggressively controlled. In contrast, the A2 (economic, regional)

scenario has higher population growth, lower

economic growth with more continuing regional disparities, slower innovation, and

weaker international institutions. B1 (ecological, global) has low population growth, moderate economic growth with strong convergence,

and strong reductions in per capita energy use,

mostly through higher efficiency, while B2 has

intermediate population growth, low economic

growth with weaker convergence, and moderate

improvements in energy efficiency and development of non-carbon energy sources.68 The

storylines were elaborated in short text descriptions with some preliminary numbers attached

in fall 1997.69

Modeling teams were asked to produce initial

quantifications of these scenarios in fall 1997,

to match specified 2100 target values within 10

percent. In February 1998, the preliminary

quantitative targets were re-confirmed and modelers asked to continue work on quantifications,

now including a breakdown of economic output

into four world regions.70 In April, one model’s

quantification was chosen as a “marker scenario” for each of the four scenarios – a particular scenario that would provide the basis for

interim reporting to climate modelers, some of

whose results other participating models would

be asked to replicate. The specifications and

models for these marker scenarios are shown in

Table 3.1.

These interim marker scenarios were used to

provide emissions scenarios to climate models

participating in the IPCC third assessment. An

IPCC climate modelers’ meeting in June 1998

agreed to use SRES scenarios and asked for

three cases, central emissions, stabilization, and

high emissions.71 The writing team initially discussed meeting this request by identifying scenarios corresponding to each of these requested

cases,72 but decided to provide only the marker

scenarios and recommend that all four be used

without identifying any as “central.”

66 See, e.g., WEC/IIASA 1995, WBCSD 1997.

67 Minutes, Lead Authors Meeting, Paris, April 13-15,

1997. 

68 Arnell et al. 2004; Minutes, Lead Authors Meeting,

Paris, April 13-15, 1997.

69 Minutes, informal modelers meeting, Berkeley, Feb

7-8.

70 Draft minutes, informal modelers meeting, Berkeley,

Feb 7-8:4.

71 Minutes of the Laxenburg meeting, July 2-3, 1998,

reporting results of June 29-July 1 IPCC Scoping

Meeting, Bonn.

72 In July 1998, members decided that A1F or A2 could

be the requested high-emissions scenario (with emissions of ~ 30 GtC in 2100), B2 or A1B a central case

(~15 GtC in 2100, with two different SO2 profiles),

and B1 or an A1 variant called A1R a stabilization case

(at about 550 ppm) (Laxenburg report, July 2-3,

1998:1).

The SRES interim

marker scenarios were

used to provide

emissions scenarios to

climate models

participating in the

IPCC third assessment.
34

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

The marker scenarios also provided the basis for

coordination of subsequent scenario development. Up to this point, there had been substantial discrepancy between different models’

quantifications of the same scenarios, particularly at regional level. With the adoption of the

markers, other groups were asked to replicate

(within 5-10 percent) the marker results on population, GDP, and final energy for the four

world regions, for 2100 and several interim

years.73 Achieving this requested replication

posed significant challenges for modelers.74

With a further year of work, modeling teams

produced a total of 40 scenarios that were retained in the report, of which 26 replicated one

of the marker scenarios. Although a few of the

14 non-replicates reflected a model’s inability

to match the results of a marker scenario, most

were produced because a modeling team intentionally sought to explore alternative assumptions. For example, the A1 scenario, which

originally balanced fossil and non-fossil energy

sources, was augmented by variants with different assumptions about fossil resources and

non-fossil technology development, giving

widely divergent emissions paths stressing coal,

gas, and non-fossil energy technology. Modifications of the scenario set continued until late

in the process. For example, it was decided in

October 1998 to drop several B variants with

explicit mitigation, including one stabilization

scenario.75 At the final IPCC approval meeting,

it was decided at the request of the Saudi delegation to reduce the two fossil-intensive variants of A1 to one, a variant of the gas-intensive

scenario which was renamed A1FI (for “fossilintensive”).76

3.1.1 Significance and use

The SRES scenarios have been the most comprehensive, ambitious, and carefully documented emissions scenarios produced to date.

They represented a substantial advance from

prior scenarios, and contributed to assessments

and subsequent research on climate impacts and

responses. The SRES scenarios formed the

basis for climate-model comparisons in the

IPCC Third Assessment (2001) and continuing

work in the Fourth Assessment. Most subsequent climate-model work has used only a few

of the marker scenarios – typically A2 and B2,

sometimes with A1B added. SRES scenarios

also provided baselines for analysis of mitigation scenarios in the Third Assessment.77

Several significant insights were illuminated by

the SRES scenarios. 

• Scenarios with similar emissions in 2100

can follow markedly different paths in the

interim, giving wide differences in cumulative emissions and concentrations. 

• Technology and energy-resource assumptions can strongly perturb future emissions,

even with constant socio-economic assumptions. For example, the three A1 variants

show that changing these assumptions alone

can generate as wide a range of emissions

futures as substantial variation of demographic and economic futures.

Table 3.1. 

Target Values

for 2100 in

Initial Scenario

Quantifications

SCENARIO A1B A2 B1 B2

Population 7.1 15.1 7.1 10.4

GDP (trillion) $530 $250 $340 $235

Final Energy (EJ) ~1,700 870 770 950

Model for 

Marker scenario AIM ASF IMAGE MESSAGE

Source: Minutes of Laxenburg meeting, July 2-3, 1998.

73 Because markers were produced by different models

with different time steps, the interim years to be harmonized differed for each scenario.

74 For example, discussions in Beijing re-confirmed that

allowed deviation from markers at 4-region level would

be 5 percent for GDP and 10 percent for final energy,

but substantial discrepancies in base-year energy could

not be harmonized due to time constraints (SRES modelers meeting report, Beijing, October 6-7, 1998:2). 

75 SRES modelers meeting report, Beijing, October 6-

7, 1998:4. At this meeting, B1 was also proposed for

removal, but was retained based on a decision that none

of the many policy interventions it presumed was an

explicit greenhouse-gas limitation, so it was consistent

with the terms of reference.

76 A1FI was the gas-intensive scenario, A1G, with revisions to methane emissions and additional non-CO2

gases added from the A1 run of the MESSAGE model.

77 Morita et al. 2001.

The SRES scenarios

have been the most

comprehensive,

ambitious, and

carefully documented

emissions scenarios

produced to date.
35

Global-Change Scenarios - Their Development and Use

• Highly distinct combinations of demographic, socio-economic, and energy-market conditions can produce similar

emissions trajectories, suggesting that a particular emissions trajectory can pose very

different types of mitigation problems, depending on what combination of driving factors underlies the emissions.

3.1.2 Criticisms and controversies

The SRES experience raised issues of great significance for subsequent attempts to develop

more useful climate-change scenarios: the desirability of and appropriate methods for characterizing probabilities associated with

scenarios; the quantitative representation of the

relationship between North and South; methods

for developing and using narrative scenarios

and integrating them with quantitative model results; alternative modes for coordinating use of

multiple models and their implications for the

interpretation and use of scenarios; and the relationship between scenario exercises and their

users, including the need for clarity about specific intended uses, appropriate methods for engaging users in scenario development, and how

to improve utility of scenarios when not all potential user groups are specifically identified.

These are discussed in Sections 4 and 5. 

The first two of these issues were the subjects of

forceful public criticisms. We discuss these, followed by several other issues that have received

less attention but which in our view pose more

central and instructive challenges for future scenario exercises.

Assigning explicit probabilities

The SRES team decided at the outset to make

no probabilistic statements about the scenarios.

Their report used great care in its language to

avoid any suggestion that one scenario might be

more central or more likely than any other.78

This decision was consistent both with standard

practice in developing narrative scenarios, and

with the instruction in their terms of reference

not to favor any model.79

They were sharply criticized for this decision.80

Critics argued that there were no technical obstacles to assigning probabilities to emissions

ranges bounded by the marker scenarios; that

scenario developers must have made probabilistic judgments in generating and evaluating

the scenario quantifications and that not making these judgments explicit would withhold

relevant information; and that if scenario developers decline to assign probabilities, others who

are less informed will do so. Indeed, many

probabilistic emissions calculations have been

produced since the SRES, using various methods such as assigning uniform or other specified distributions over the emissions range of

the marker scenarios, counting scenarios lying

in specified intervals in the larger SRES set, unbundling and recombining alternative values of

the drivers underlying SRES emissions figures,

or sampling over parameter distributions within

a single model. In response to these criticisms,

SRES authors argued that attempting to assign

probabilities to scenarios would require assigning joint distributions to the underlying driving

factors, and that this would lead to an explosion

of combinatoric possibilities over which any attempt to assign probabilities would be spurious

and arbitrary.81

The situation of the SRES scenarios is in fact

more nuanced than the arguments of either their

authors or critics would suggest. It may well be

unhelpful to assign probabilities to rich, multidimensional narrative scenarios, yet still useful

to assign interval probabilities when scenarios

principally represent uncertainty in one or two

quantitative variables. And while the SRES scenarios began their lives like the former type of

storyline scenario, they finished more like the

latter. For many users, the scenarios are their

projections of greenhouse-gas emission trends.

When they are viewed in this way, a potential

user may reasonably ask, how likely are emissions to be higher than this – a distinct and better-posed question than, what is the probability

of an A1 world? The uncertainty issue has no

clear resolution in this case, and poses hard design problem for scenarios and assessments

more broadly. Although the SRES exercise has

78 E.g., Minutes of London meeting, March 1999.

79 Draft minutes of the Washington, DC, meeting, April

29-30, 1998:6.

80 Schneider 2001, 2002; Pittock et al. 2001; Allen et

al. 2001; Reilly et al. 2001.

81 Grubler and Nakicenovic 2001. 

It may well be

unhelpful to assign

probabilities to rich,

multi-dimensional

narrative scenarios,

yet still useful to

assign interval

probabilities when

scenarios principally

represent uncertainty

in one or two

quantitative variables
36

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

raised this controversy most explicitly to date, the

problem is a general one that any scenario exercise

must confront. We discuss it further in section 4.6.

Exchange rates: PPP versus MER

The most prominently publicized criticism of

SRES focused on the fact that all but one of the

participating models compared GDP across regions using market exchange rates (MER), instead of the more correct purchasing-power

parity (PPP) approach. PPP comparisons correct for price differences among countries, providing a more accurate comparison of real incomes.

Because lower-income countries have lower price

levels, MER-based comparisons overstate the income gap between rich and poor countries.

In a series of letters to the IPCC chairman and

several subsequent publications, two critics argued that the use of MER caused SRES scenarios to over-estimate future income growth in

developing countries (because they over-estimated the initial income gap), and consequently

to over-estimate future emissions growth. Their

criticism was widely circulated and repeated by

prominent climate-change skeptics.82

But, although using MER does overstate future

income growth, it does not necessarily follow

that future projections of emissions growth are

also overstated. MER is universally recognized

as a flawed measure of income, whose use in

global-change scenarios is only justified by better availability of current and historical data,

and the fact that international emissions trades

in any future mitigation regime will likely be

made at market exchange rates. But changing

the measure of income also changes the relationship between income and such physical

quantities as energy and food consumption,

which determine emissions. Consequently,

while MER overstates future income growth in

poor countries, it also overstates future reductions in energy and emissions intensity. These

opposing errors are likely to be similar in size,

in which case any error in emissions projections

from using MER will be small.83

A related, more serious concern is that all SRES

scenarios assumed varying degrees of real income convergence between North and South;

this was done in response to criticisms that the

IS92 scenarios were biased in favor of the

North. But an exercise to construct potential

climate-change futures may need to consider

less optimistic and less desirable futures in

which some currently poor regions fail to solve

the development problem. Not considering less

fortunate futures, including ones that might

challenge the adequacy of current responses, institutions, and decision-making capacity, may

limit scenarios’ usefulness in supporting longterm risk assessment and planning for the societal response to climate change.

Underdevelopment 

of narrative scenarios

Although the SRES storylines were produced

first and featured prominently in publications,

they remained underdeveloped and underused

throughout the process. In part due to time

pressure, in part due to the predominance of

quantitative modelers in the process, little attention was given to further development of the

storylines once initial quantifications were established and modeling work began. Nor was

significant effort devoted to integration and

cross-checking between storylines and quantitative scenarios, although a major purpose of

the narratives was to give coherent structure to

quantifications.84 Concerns raised about the

storylines included lacking specification of

characteristics other than those needed to generate emissions; imbalance between the storylines, with A1 much more developed than the

others and B2, the least developed, likely to be

heavily used as the median scenario for emissions; apparent inconsistencies within A2; and

lack of clarity regarding the distinctions between A2 and B2 – a serious enough concern

that merging them was repeatedly considered

until late in the process.85

82 Castles and Henderson 2003a, 2003b; The Economist

2003a,b; Michaels 2003b.

83 Nakicenovic et al. 2003, McKibben et al. 2004,

Holtsmark and Alfsen 2005, Manne et al. 2005, Gr bler

et al. 2004.

84 Minutes of the Beijing meeting, October 6-7,

1998:10.

85 Draft minutes of the Bilthoven meeting, September

17-19, 1997:7-8; draft minutes of the Berkeley meeting, February 7-8, 1997:6; draft minutes of the Washington, DC, meeting, April 29-30, 1998.

...while MER

overstates future

income growth in poor

countries, it also

overstates future

reductions in energy

and emissions intensity.
37

Global-Change Scenarios - Their Development and Use

Moreover, participants disagreed over the meaning of some of the scenarios, as indicated by the

persistent difficulty they had in agreeing on descriptive names.86 These names were dropped

late in the project, in the context of a broad retreat from attempting to flesh out the storylines.

That so little integration of qualitative and

quantitative components was achieved in spite

of serious and persistent efforts suggests the

magnitude of the analytical and methodological

challenges involved. 

Harmonizing scenarios, interpreting

the results

Scenario exercise that use multiple models can

coordinate them in several ways: choosing one

or a few illustrative scenarios as coordinating

devices for subsequent analyses, as was done

with the SRES marker scenarios; fixing values

of a small set of exogenous inputs to multiple

models, to characterize resultant uncertainties

and examine their origins through focused

model intercomparisons; or fixing key outputs

as targets, to reason backwards and examine requirements for achieving them.

Choosing a few quantitative variables as the initial link between storylines and models makes

these variables serve as a framework to capture

the storylines’ basic logical structure. Although

these choices are not obvious, the variables chosen here appear reasonable. But the causal

structure of a model will not generally mirror

the presumed causal logic of a narrative, so a

model cannot be expected to calculate values

for other variables that flesh out the storyline

logic. Moreover, the few key variables so chosen may not be exogenous inputs for every

model used in the subsequent quantification.

Of the three variables specified in the SRES

process, only population was exogenous for all

participating models. Because GDP and final

energy were endogenous for some or all participating models, matching their specified values

required manipulating other internal model

characteristics. Once one model run was chosen as the marker for each scenario, subsequent

attempts by other models to replicate the results

posed the same problem more acutely, since

more outputs were specified at this point.

The problems associated with attempting to harmonize model outputs are related to the underdevelopment of narrative scenarios and limited

integration of qualitative and quantitative components. The storylines were associated with

relatively restrictive numerical targets even

though the storylines did not develop the richness or coherence that would carry implications

for additional characteristics. The preliminary

targets were only slightly modified throughout

the project, despite subsequent discovery of 

significant problems. For example, the United

Nations 1998 population projections, with substantial reductions in projected fertility, were

completed while the scenario development

work was underway but not incorporated.87

Clarity about uses, involving users:

The SRES scenarios were charged with serving

uses beyond driving climate models but given

little guidance on what specific additional uses

or users to serve, or how the scenarios might

best serve them, neither of which is obvious.88

Providing climate-model inputs remained the

most prominent and most clearly specified use,

as well as the only use that had an early deadline. But climate modelers were not involved in

the scenario development process, and there

was substantial divergence between their needs

and the outputs and capabilities of the SRES

process. A September 1997 briefing identified

the principal needs of climate modelers as early

availability of scenarios and greater emissions

detail.89 They wanted separate emissions trajectories for major greenhouse gases, not just

86 While names proposed for the “1” storylines suggest

substantial common understanding (A1 was called

“High Growth,” “Productivity,” and “Golden Economic Age,” B1 was “Green” and “Sustainable development”), names proposed for the “2” scenarios,

particularly B2, do not (A2 was called “Regional Consolidation,” Divided World,” and “Clash of Civilizations”; B2, “Regional Stewardship,” “Small Is

Beautiful,” “Dynamics as Usual,” “Gradually Better,”

and “Muddling Through”) (draft minutes of the

Bilthoven meeting, September 17-19:7-8; draft minutes of the Berkeley meeting, February 7-8, 1997;

UKCIP 1998 report summarizing SRES progress;

Pitcher 1998 presentation slides.

87 Minutes of the Bilthoven meeting, September 17-19,

1997:11.

88 Alcamo et al. 1995.

89 Draft minutes of the Bilthoven meeting, September

17-19, 1997:5.
38

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

CO2-equivalent, including regional detail for

some emissions such as sulfur – even suggesting that it would be desirable to have sulfur

emissions disaggregated by stack height, to distinguish dispersed emissions from large point

sources. Although SRES provided gridded sulfur data by post-processing model outputs, in

most cases the emissions included and their spatial detail (not to mention stack height) were

limited by the capabilities and structures of participating models.

Other uses received less attention, and representatives of other potential uses were even less

involved than climate modelers in the process.

Supporting assessment of mitigation strategies

was largely deferred to the post-SRES scenarios

prepared for the IPCC Third Assessment Report, although ambiguity about the degree of

mitigation effort implied by some SRES scenarios complicated that task. Impact and vulnerability assessments depend on diverse,

small-scale socio-economic and ecological factors that a global exercise centered on energyeconomic models cannot provide.90 For the

population and economic projections that were

provided in the course of generating emissions

scenarios, the key issue for impacts and adaptation was the degree of spatial detail provided.

For consistency among scenarios, and to avoid

base-year discrepancies with national and regional datasets, SRES scenario results were reported only for four large world regions.

Greater regional detail was available from individual models, but with inconsistent regional

boundaries. Providing the greater regional detail desired for impact assessments would generate discrepancies between the global-model

results represented in scenarios and the more detailed data and projections available at national

and regional levels.91 Developing valid methods

to downscale socio-economic scenario information and integrate it with national and regional

datasets remains a key challenge for producing

useful scenarios for impact assessment.92

3.2. THE US NATIONAL

ASSESSMENT 

The US National Assessment was the most

comprehensive attempt to date to assess climate

impacts on the United States over 25-year and

100-year horizons, and to consider both major

sub-national regions and sectors.93 Responding

to a requirement in the 1990 Global Change Research Act, the National Assessment was organized by federal agencies participating in the

US Global Change Research Program. Work

began in 1997, with various components completed between 1999 and 2003. Regional impacts were initially considered in 20 regional

workshops, followed by more extended analyses of impacts, leading to published assessments

for 12 regions, conducted by university-based

teams. Sectoral impacts were examined by national teams focusing on agriculture, water,

human health, coastal areas and marine resources, and forests. A federal advisory committee, the National Assessment Synthesis Team

(NAST), provided direction for the assessment

and synthesized its results in two published reports.94 Roughly two thousand experts and

stakeholders participated.

As an assessment focused on climate impacts,

the National Assessment needed both climate

scenarios and scenarios of potential future

socio-economic conditions over the 21st century,

since substantial changes are likely over this period in socio-economic conditions that might influence vulnerability to climate and adaptive

capacity. 

3.2.1. Emission and climate

scenarios 

For climate scenarios, the National Assessment

relied predominantly on data and model results

previously produced. Study teams conducted

additional checking, processing, documentation, and dissemination as needed to make these

90 See, e.g., discussion with Mike Hulme on behalf of

TGICA, draft minutes of the Washington, DC, meeting, April 29-30, 1998:9.

91 January 1998, meeting with Richard Moss, WG2

Technical Support Unit, described in draft meetings of

the Berkeley meeting, February 7-8, 1997.

92 Pitcher 2005.

93 There had been two previous assessments of US climate impacts. The US EPA (1989) did a preliminary

assessment for five representative US regions and five

sectors (agriculture, forests, water resources, health,

and coasts), while the US OTA (1993) examined impacts for six sectors – coasts, water, agriculture, wetlands, protected areas, and forests.

94 NAST 2000, 2001. 

The US National

Assessment was the

most comprehensive

attempt to date to

assess climate impacts

on the United States

over 25-year and 100-

year horizons, and to

consider both major

sub-national regions

and sectors.
39

Global-Change Scenarios - Their Development and Use

usable. The assessment encouraged the use of

three types of climate scenarios: historical scenarios produced by extrapolating observed

trends or re-imposing historical climate variability or extremes; an inverse approach using

sensitivity analyses to explore the responses of

climate-sensitive systems, with particular emphasis on thresholds defining key vulnerabilities; and climate model simulations of future

climate conditions.95

Of these three approaches, the climate-model

scenarios were the most precisely specified and

the most widely used. The National Assessment

did not have the resources or time to commission new climate model runs and so had to rely

on those completed and published when it

began its work. A set of criteria was developed

by the NAST for the climate model scenarios to

be used in the assessment. Climate-model scenarios used in the assessment should, to the

greatest extent possible:96

1. Include comprehensive representations of

the atmosphere, oceans, and land surface,

and key feedbacks among them

2. Simulate the climate from 1900 to 2100,

based on a well-documented emissions scenario

that includes greenhouse gases and aerosols

3. Have the finest practicable spatial and temporal resolution, with grid cells of less than

5 ̊ latitude x longitude

4. Include the daily cycle of solar radiation, to

allow projections of daily maximum and

minimum temperatures

5. Be able to represent significant aspects of

climate variability such as the El NiñoSouthern Oscillation (ENSO) cycle

6. Be completed in time to be quality-checked

and interpolated to the finer time and spatial scales needed for impact studies

7. Be based on well-documented models participating in the IPCC Third Assessment (for

comparability between US and international

efforts)

8. Be able to interface results with higher-resolution regional model studies 

9. Provide a comprehensive array of results

openly over the internet.

To ensure timely dissemination, the National

Assessment chose climate-model scenarios to

be used in its analyses in mid-1998. At that

time, only two groups had completed runs that

met most of the key criteria: the UK Hadley

Centre (Model Version 2) and the Canadian

Centre for Climate Modeling and Analysis

(Model Version 1).97 All participating regional

and sector teams were asked to use these scenarios. The climate sensitivity of these models

was 2.5°C (UK Hadley) and 3.6°C (Canadian),

lying in the middle of the 1.7 to 4.2°C range of

sensitivities represented by models participating in the IPCC Third Assessment.98

These two models were limited in their ability to

reproduce observed patterns of inter-annual and

inter-decadal climate variability. But other climate-model runs available at the time failed to

meet essential requirements of the ecosystem

models that were the basis for an important part

of the assessment: availability of documented

results, projections to 2100, standard/comparable emissions scenarios, and explicit treatment

of the day-night cycle.

For these two climate models, model runs using

only one emissions scenario were available, and

only one ensemble run was used for each.99 The

95 NAST 2001:25. It is arguable whether or not the inverse approach involves scenarios by the definition we

have adopted here, because it does not stipulate specified future climate conditions, but attempts to identify

them from presumed thresholds or breakpoints. However, we are following the usage of the NAST reports

in calling these approaches three types of scenarios. 

96 NAST 2001:31-32; MacCracken et al. 2001; MacCracken et al. 2003:1714.

97 Johns et al. 1997; Boer et al. 1999a, 1999b; MacCracken et al. 2003.

98 Cubasch et al. 2001, Table 9.1:538-540; and Table

9A.1:577.

99 Ensembles of climate-model runs are repeated simulations with small variations in initial conditions which

improve the characterization of climate variability. The

Canadian group had completed only one ensemble run

at this time. The Hadley Center had completed three,

but the National Assessment was only able to use one.

Of the three

approaches, the

climate-model

scenarios were the

most precisely

specified and the most

widely used.
40

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

emissions scenario was IS92a, which represented the middle of the range of IPCC’s 1992

scenarios.100 In addition to greenhouse gases,

the scenario included atmospheric loadings of

sulfate aerosols, which were assumed to increase sharply through 2050 and then level off

for the rest of the 21st century.101

The applicability of these two scenarios was

tested by checking the models’ ability to replicate broad patterns of US climate change over

the 20th century when driven by historical greenhouse-gas forcings. Model results were compared against the VEMAP (VegetationEcosystem Mapping and Analysis Project)

dataset, a corrected climatic dataset for the 20th

century. This comparison showed reasonable

accuracy in reproducing the spatial distribution

of average temperatures and century-long temperature trends, but significantly weaker reproduction of observed patterns of precipitation,

mainly because the spatial distribution of precipitation depends on topographic detail that is

too fine-scale to be captured even by the 0.5-

degree VEMAP grid.102

With the specified scenario of future emissions,

the two climate-model scenarios projected

global warming by 2100 of 4.2°C (Canadian)

and 2.6°C (Hadley).103 These projections were

at the high end and in the middle, respectively,

of the range of warming projected for this emissions scenario by models participating in the

IPCC Third Assessment Report.104 For the continental United States, the two models projected

warming by 2100 of 5.0°C (Canadian) and 2.6°C

(Hadley), at the high end and below the middle,

respectively, of the range of projections in the

IPCC Third Assessment.105 In their projections of

precipitation change over the United States, these

scenarios both lay at the high end – the Hadley

scenario projected the highest precipitation in

2100 and the Canadian the second-highest106 – but

the Canadian model’s greater warming offset the

effect of this precipitation increase on soil moisture, which was projected to decrease over most of

the continental United States.107

Although only the Hadley and Canadian climate-model scenarios were used throughout the

assessment, several others that met some or all

of the assessment’s needs became available during its work. Several region and sector teams

were able to use these additional scenarios. In

some cases, the additional scenarios allowed

groups to strengthen their conclusions. For example, an analysis of future Great Lakes water

levels under climate change using eleven climate models found that ten of these showed

lower levels and only one higher.108 In other

cases, using multiple models allowed more detailed characterization of uncertainties in future

regional changes. For example, the Pacific

Northwest team presented distributions of regional temperature and precipitation change in

the 2030s and 2090s using seven GCMs.109

Despite the National Assessment’s aim of exploring future climate using three distinct types

of scenario, historical scenarios and sensitivity

analyses were less extensively used than GCM

scenarios and featured less prominently in the

100 The IS92a scenario is described in section 3.1. There

were small differences among climate-modeling

groups in the way they converted emissions trajectories into atmospheric concentrations and radiative forcings, making the actual scenarios driving each model

run very close, but not quite identical.

101 See www.usgcrp.gov/usgcrp/nacc/background/scenarios/emissions.html for further detail on emissions

scenarios used in the National Assessment.

102 VEMAP members 1995, Kittel et al. 1995.

103 NAST 2001:36, Table 2.

104 Cubasch et al. 2001, Figure 9.5a:541. While the

Canadian model lies at the high end, it is not an outlier.

The GFDL model (which was more responsive than

the Canadian model, with a climate sensitivity of 4.2°

C) projected higher global warming than the Canadian

model in this scenario for the first few decades of the

century, but only had results through 2060 in time for

the TAR.

105 The seven models for which these results were available clustered at the top and the bottom. Three of them

– the Canadian, GFDL, and Hadley 3 models – lay very

close together at the high end, the Canadian the highest by a fraction of a degree; three others lay close together at the low end, Hadley 2 the highest of them by

somewhat less than a degree. A seventh model,

ECHAM4, tracked the high group through 2050, the

last year for which its results were available. Since

these comparisons usually reflect only one ensemble

run of each model, small differences between runs may

reflect consistent inter-model differences, or noise reflected in a single ensemble run. See NAST 2001:547,

Figure 7.

106 NAST 2001:545, Figure 8.

107 NAST 2001:552, Figure 16 and 18.

108 Lofgren et al. 2000; NAST 2001:175.

109 NAST 2001:256.
41

Global-Change Scenarios - Their Development and Use

assessment’s publications. Two uses of historical climate data – describing observed impacts

of climate variability and using observed historical extremes as benchmarks to compare projected future changes – were made by all

groups. To support systematic use of historical

scenarios, the VEMAP 20th-century dataset was

provided to all groups, but no further guidance

was provided on how to generate climate scenarios from these historical data, e.g., on what

periods to choose or how to use them to assess

potential future impacts. Several groups used

these historical data to describe the impacts of

particular recognized patterns of climate variability, such as ENSO or the Pacific Decadal

Oscillation (PDO).110 Many groups examined

past climate extremes, but only in qualitative

ways; most did not follow the approach, taken in

some previous impact studies, of using historical extreme periods as quantitative proxies for

potential future climate.111

The third approach, vulnerability analysis, was

the least used in the National Assessment. This

“inverse” approach involves describing the

properties of a climate-sensitive system, specifying some important change or disruption, and

asking what climate changes would be required

to bring about that disruption and how likely –

based on historical data and model calculations

– such climate changes appear to be. Given the

complex dynamics of climate-sensitive systems

and models of these systems, and the multiple

dimensions of climate on which these can 

depend, this approach requires a substantial program of new research, analysis, and methodological development.112 In part because of the

intrinsic difficulty of this task – and in part due

to management and resource problems – this

approach was not pursued. The NAST proposed it, but more tractable approaches to 

analyzing climate impacts dominated the assessment’s work. This remains an important

area for further work in development of assessment and modeling methods.

3.2.2. Socio-economic scenarios 

As discussed in Section 2.5 above, assessing

impacts of future climate change can require

specifying not just scenarios of future climate,

but also socio-economic characteristics of the

future society that will experience the changed

climate. Specifying future socio-economic conditions might be necessary for two reasons.

First, socio-economic conditions may influence

the demands placed on particular resources that

are also sensitive to climate change, the value

assigned to them, and the non-climatic stresses

imposed on them. For example, future flow

regimes in river systems will be influenced by

upstream demands for municipal and irrigation

water use, in addition to the changes caused by

climate. Socio-economic scenarios are also

needed to assess climate-change impacts on

human communities – e.g., economic impacts

and their distribution, human health effects, and

vulnerability to extreme events – because socioeconomic characteristics of a community experiencing a changed climate will strongly

influence the community’s vulnerability to

changes and its capacity to adapt. 

In contrast to climate scenarios, little prior 

information or experience was available on constructing scenarios of socio-economic conditions for impact assessment. Consequently, the

assessment developed new methods, using an

approach that combined centralized and decentralized elements. Centralization was needed

because a few variables, such as population,

economic growth, and employment, are likely

to be important in all regions and sectors. For

these, consistent assumptions are required to

allow comparison of impacts across regions and

sectors, and to aggregate from separate assessments up to overall national impacts. A NAST

sub-group developed high, medium, and lowgrowth scenarios of these variables at the national level. These followed the US Census

Bureau high, middle, and low scenarios for fertility and mortality through 2030, but assumed

a wider range of values for net immigration to

account for possible illegal immigration.113

Over this period, national population, GDP, and

employment were disaggregated among regions

and sectors using a commercial regional eco110 E.g., Mote et al. 2003, Southeast Regional Assessment Team 2002.

111 Rosenberg et al. 1993.

112 For an example of such efforts, see the AIACC (Assessments of Impacts and Adaptations to Climate

Change) project, information at http://www.aiaccproject.org. 113 Parson et al. 2001:102-103. 

Socio-economic

scenarios are also

needed to assess

climate-change

impacts on human

communities.
42

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

nomic model.114 Beyond 2030, national projections of these variables followed OECD growth

rates in the SRES marker scenarios.115

Decentralization was also needed because the

particular socio-economic characteristics that

most strongly influence climate impacts and

vulnerability may differ among regions, activities, and resources. For example, major socioeconomic determinants of climate impacts on

Great Plains agriculture may include the crops

grown, the extent of irrigation, and the technologies used to provide it, while the main determinants of coastal-zone impacts may be

patterns of coastal development, zoning, infrastructure, and local property values. The NAST

judged that those assessing regional or sector

impacts were likely to know more about such

factors than a central body. Consequently, to

support decentralized scenario development, the

NAST proposed a consistent template for assessment teams to follow in creating their own

scenarios. Teams were asked to identify two

socio-economic factors they judged most important for their impacts of concern; to identify

a range of these factors to represent roughly 90

percent confidence; and to create socio-economic scenarios by combining high and low

values of these factors, plus middle or bestguess values if they so chose.

Implementation of socio-economic scenarios in

the National Assessment was weak. Few assessment teams used the proposed approach.

Many made no socio-economic projections at

all, but rather projected only biophysical impacts based on GCM results. One assessment

team found the socio-economic scenarios were

inconsistent with superior local estimates of

current population, and so decided not to use

them.116 The teams that did use the socio-economic scenarios used only aggregate projections of population and economic growth, or in

some cases assumed continuation of present

conditions in the assessment period. None used

the proposed template for identifying and projecting additional important socio-economic

characteristics. 

Several factors contributed to this limited use of

socio-economic scenarios. In addition to various managerial and communication problems,

many participants were reluctant to use socioeconomic scenarios, especially the proposed decentralized approach. Some preferred to avoid

any socio-economic projections, implicitly presuming either that socio-economic conditions

did not matter for impacts, or that those that did

matter would remain similar to present conditions. Others objected to specific contents 

of the scenarios or the methods used to generate them, or judged that their team lacked 

the expertise required to evaluate them. Still

others objected that uncertainties in future 

socio-economic conditions made any attempt to

construct scenarios for more than a few years in

the future unacceptably speculative.117 Consequently, while the assessment attempted to advance scenario methods, weak implementation

of these methods limited its ability to identify

key vulnerabilities. More useful assessments of

impacts and vulnerability will require more extensive use of socio-economic scenarios, improved integration of socio-economic with

climatic and environmental scenarios, and substantial further investment in development and

testing of new methods.118

3.2.3. Criticisms and controversies

The National Assessment was the object of substantial political and scientific controversy.

Here, we summarize the major criticisms that

pertain to the development and use of scenarios. Criticisms focused predominantly on the

climate scenarios, especially those derived from

GCMs, probably because these were more precisely defined, widely used in the analyses, and

featured in the assessment’s publications. Three

criticisms of these were advanced. 

The first, widely circulated during 2000, was

that the use of non-American climate models

for climate scenarios was inappropriate and potentially injurious to national interests.119 While

this criticism indicates a dimension of political

114 Terleckyj 1999a,b.

115 The high-growth scenario was roughly comparable

with A1, medium with B1, and low with A2 and B2.

116 Rosenzweig and Solecki 2001.

117 Morgan et al. 2005. 

118 Lorenzoni et al. 2000, Berkhout and Hertin 2000,

Parson et al. 2003.

119 Congressional Record, June 16, 2001, Statements of

Senators Hagel (page S5292) and Craig (page S5294).

More useful

assessments of impacts

and vulnerability will

require more extensive

use of socio-economic

scenarios, improved

integration of socioeconomic with climatic

and environmental

scenarios, and

substantial further

investment in

development and

testing of new

methods.
43

Global-Change Scenarios - Their Development and Use

vulnerability of the assessment, it does not address the assessment’s technical quality. Since

climate models represent the physics of the

global atmosphere, they contain no representation of political or economic factors. The

Hadley and Canadian global climate models

were extensively documented in peer-reviewed

scientific literature – and, moreover, were the

only models that met the most critical of the assessment’s criteria. That they were developed

by scientific groups outside the United States

has no significance for their ability to provide

scenarios to assess US impacts. Using US models would have avoided this criticism, but at the

cost of either weakening the analysis by using

scenarios that did not meet the assessment’s

needs, or delaying the work by one to two years.

In deciding to proceed with non-US models, assessment organizers judged that these costs

were too high.

The second major criticism was that the two climate-model scenarios used were at the extreme

end of available models in their projected climate change. This is partially correct. When

temperature and precipitation factors are considered together (because high precipitation in

some cases may offset the impacts of high temperature), the Canadian scenario lies at the highimpact end – although not an outlier, as other

IPCC model projections lie close to it – while

the Hadley lies at or somewhat below the middle for most analyses. 

The National Assessment’s organizers and its

critics agreed that using more models would

have been preferable, but the assessment was

limited by its schedule and its technical requirements. Given a limit of only two, there can

be good reasons to choose one scenario in the

middle of current projections and one near the

top that provides a plausible upper-bound, but

the significance of the results must then be communicated with great care. Some critics suggested that presentation of results based on the

relatively high Canadian scenario should be

more carefully qualified to highlight its position

near the top of current projections.120 Such

qualifications must be crafted very subtly, however, lest they imply these results may safely be

ignored, when most analyses suggest the full

range of future climate-change uncertainty extends both below the Hadley scenario and – in

a long, thin tail – above the Canadian.

A related criticism of the climate scenarios

claimed that the emissions scenario driving

them was implausibly high. The issues bearing

on choice of emission scenarios are similar to

those for choice of climate models. It would be

preferable to have a wide and relevant range of

emissions scenarios driving an impact assessment – at least for the post-2050 period. Using

a wide range of emissions scenarios would also

allow comparison of projected impacts under

high and low emissions futures, and so give insights into what degree of impacts could be

avoided by what degree of mitigation effort.

Model runs with this emissions scenario were

all that were available, however. Moreover,

there is no clear basis to reject this particular

scenario, since it was the scenario most widely

used in climate-model runs at the time and lies

near the middle of the range of both the 1992

and the 2001 IPCC scenarios. Finally, there is

no support for the claim that this scenario was

chosen with the aim of making 21st-century climate change appear as frightening as possible.121 But, although using just two climate

models with one emissions scenario was unavoidable in this assessment, it still represented

a serious limitation. With more model simulations testing a range of emission scenarios already available, future assessments will be able

to remedy this deficiency.

In contrast with the preceding criticisms that the

scenarios used in the assessment understated

uncertainty, another criticism focused on the

disparities between the two scenarios’ projections. Some critics argued that such disparities

– e.g., the Canadian scenario projects the Southeastern states becoming much drier than the

Hadley model does – show that our limited

knowledge of regional climate change makes

any attempt to assess future impacts and vulnerabilities irresponsible.122 This criticism im120 MIT Integrated Assessment project, comments on

National Assessment, Aug 11, 2000:15.

121 Michaels 2003a:171-192.

122 Disparities between the two models’ projections were

the basis of an unsuccessful lawsuit brought against the

Assessment under the Federal Data Quality Act (See

Competitive Enterprise Institute, “Complaint for Declarative Relief,” http://www.cei.org/pdf/3595.pdf, at

paragraph 24.)
44

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

plies that impact assessment should wait until

precise, high-confidence regional climate projections are available. Since a major purpose of

the assessment was to represent current uncertainty about climate change and its impacts,

such discrepancies between model projections

served a valuable purpose, as indications of the

uncertainty of projections at the regional scale –

particularly when the model disparities had a

clear origin, such as differences in projected jetstream location. 

In sum, the National Assessment’s use of climate-change scenarios was hampered by the

lack of available relevant runs, but reflected an

adequate attempt to represent then-understood

variation in climate projections for the United

States. Future assessments will need to use

more climate-model projections – including

multiple ensemble runs – informed by a wider

range of relevant emissions scenarios. The National Assessment attempted to advance the

state of the art in using socio-economic scenarios, but achieved only limited success in implementing its plans. Future assessments will need

to invest substantial resources in developing the

state of underlying knowledge, models, and assessment methods for integrating socio-economic considerations into assessments of

climate impacts. This includes further development of novel approaches to link climate and

socio-economic scenarios, such as the proposed

“inverse” approach to vulnerability analysis.

The experience of the National Assessment

raises three significant issues for future climatechange scenario exercises. First, like several of

the experiences reviewed here, it illustrates the

difficulty and scale of effort involved in producing scenario-based assessments. Second,

the large required start-up effort and time to

build the capacity to conduct such an exercise

illustrates the great value of sustaining analytic

and institutional capacity over time, rather than

relying on separate projects. Such continuity of

capacity will avoid wasteful repetition of startup efforts, support accumulation of learning and

experience, and develop and maintain the required collaborative networks. Finally, the assessment’s experience illustrates both the need

for consistency in large-scale assessments, and

the great specificity of information needs within

particular impact and adaptation assessments.

This combination of centralized and decentralized information requirements suggests the

need for a cross-scale organizational structure

for developing and applying scenarios, including scenarios of both climate and socio-economic conditions.

3.3. THE UK CLIMATE IMPACTS

PROGRAMME

The UK Climate Impacts Programme (UKCIP)

was established in April 1997 as one element of

a broad program of scientific research, assessment, and support for policy-making on climate

change. The UKCIP supports research and

analysis of impacts for particular regions, sectors, and activities in the UK. The program provides common datasets and tools, as well as

ongoing support to university researchers and

organized stakeholder groups in all UK regions.

As part of its role in stimulating, supporting,

and coordinating decentralized and stakeholderdriven impact analyses, the UKCIP has produced and disseminated three sets of scenarios:

climate scenarios in 1998 and 2002, and socioeconomic scenarios in 2001. 

The 1998 climate scenarios provided information only at the rather coarse scale of the Hadley

Centre’s HadCM2 climate model, with four

grid-cells over the entire UK. Four scenarios,

called “high,” “medium-high,” “medium-low,”

and “low,” combined variation in emissions assumptions with variation in assumed climate

sensitivity. The medium-high and medium-low

scenarios both used the HadCM2 model, with a

sensitivity of 2.5°C.123 The medium-high scenario was driven by a 1 percent per year equivalent-CO2 transient scenario, similar to IS92a.

The medium-low scenario was driven by a 0.5

percent per year equivalent-CO2 transient scenario, similar to the lowest IS92 scenario,

IS92d. The high and low scenarios used the

same two emissions scenarios driving a simpler

climate model, whose sensitivity was set at

4.5°C for the high scenario and 1.5°C for the

low. These scenarios were used in an initial impact assessment focusing predominantly on direct biophysical impacts.124 The scenarios did

not include any explicit statements of probabil123 UKCIP 1998:13-15.

124 UKCIP 2000.

Future assessments

will need to invest

substantial resources

in developing the state

of underlying

knowledge, models,

and assessment

methods for

integrating socioeconomic

considerations into

assessments of 

climate impacts.
45

Global-Change Scenarios - Their Development and Use

ity, although their documentation suggested that

the medium-high and medium-low scenarios

“in one sense ... may be seen as being equally

likely,”125 while the high and low scenarios captured part of the tails of the distribution. Nor

did they include any potential extreme climate

events such as those associated with large

changes in the North Atlantic circulation.

The UKCIP’s socio-economic scenarios drew

on the Foresight Program, a broader exercise of

the UK Department of Trade and Industry to develop scenarios for long-range planning in several policy areas, with additional detail in areas

relevant to greenhouse-gas emissions and climate impacts.126 As in several other scenario

exercises, developers identified two fundamental uncertainties and combined two alternative

outcomes of each to produce four scenarios.

The two core uncertainties they chose were similar to those used in the SRES exercise: social

and political values, which varied from an increased focus on individual consumption and

personal freedom (“consumerism”) to a widespread elevation of concern for the common

good (“community”); and governance, which

varied from authority and power concentrated

at the national level (“autonomy”), to power 

increasingly flowing to global institutions,

downward to local ones, and outward to nongovernmental institutions and civil society 

(“interdependence”). The two dimensions of

uncertainty, values and governance, were assumed to be independent of each other. Other

major uncertainties such as demographic

change, the rate and composition of economic

growth, and the rate and direction of technological change, were treated largely as consequences of alternative realizations of the two

core dimensions of values and governance.127

The four scenarios built around these two 

dimensions of variation were called “National

Enterprise,” “World Markets,” “Local Stewardship,” and “Global Sustainability.” Each was

initially developed as a qualitative narrative of

future conditions in UK society intended to

apply broadly to both the 2020s and 2050s.

Each scenario specified several dozen socioeconomic characteristics qualitatively, including multiple aspects of economic development,

settlement and planning, values and policy, agriculture, water, biodiversity, coastal zone development, and the built environment.128

Each scenario was also realized in projections

of multiple quantitative variables, at the national

scale only. For the 2020s, these provided detail

on population, GDP (including the governmental share and the sector split between industry,

agriculture, and services); household numbers

and average household size; land use and rates

of change; total transport and modal split; agricultural production (including such details as

chemical and financial inputs, subsidies, yields,

and organic area); freshwater supply, demand,

and quality; and several indicators of biodiversity and coastal vulnerability. For the 2050s a

smaller set of quantitative variables was projected, describing population, GDP, land use,

and transport. The plausibility of projections

was checked, mainly by comparing projected

future rates of change to historical experience.

The scenarios were published with a detailed

guidance document, which provided suggestions on how to use them together with climate

scenarios for impact studies.129

As of 2005, the socio-economic scenarios had

been used in six impact studies.130 There has

been some difficulty applying the national-level

scenarios in specific, smaller-scale regions. 

The most ambitious use has been a preliminary 

integrated assessment of climate impacts 

and responses in two regions of England, the

Northwest and East Anglia.131 This study produced four integrated scenarios of regional 

climate impacts, by pairing each of the four

socio-economic scenarios with one climate scenario based on a rough correspondence between

the socio-economic scenario and the IPCC

emissions scenario underlying the climate scenario132 Based on these four scenarios, the

125 UKCIP 1998:iv.

126 UKCIP 2001.

127 UKCIP, 2001.

128 Berkhout et al. 2001.

129 Berkhout and Hertin 2001. 

130 UKCIP 2005. 

131 Holman et al. 2002.

132 Regional (National) Enterprise was taken as UKCIP

High (IPCC A2); Global Markets as UKCIP MediumHigh (A1B); Regional (Local) Stewardship UKCIP

Medium-Low (B2); and Global Sustainability UKCIP

Low (B1).

The UKCIP’s socioeconomic scenarios

drew on the Foresight

Program, a broader

exercise of the UK

Department of Trade

and Industry to

develop scenarios for

long-range planning in

several policy areas,

with additional detail in

areas relevant to

greenhouse-gas

emissions.
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The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

study elaborated preliminary regional scenarios

corresponding to the four national socio-economic scenarios, and conducted an assessment

of coastal-zone impacts and responses using

these scenarios and a formal land-use model.

Four new climate scenarios were produced in

2002, based on the SRES marker scenarios and

new versions of Hadley Center climate models.

These new scenarios differed only in their emissions assumptions, not climate sensitivity. The

high, medium-high, medium-low, and low scenarios were driven by the A1FI, A2, B2, and B1

marker scenarios, respectively. These were used

to drive the HadCM3 global climate model

(with a grid-scale of 250-300 km), generating

climate-change projections for 30-year future

periods centered on the decades of the 2020s,

2050s, and 2080s. For some emissions scenarios and time periods, climate projections were

processed through a nested hierarchy of three

Hadley Center climate models: the HadCM3

model at global scale, the HadAM3H model at

intermediate scale, with a horizontal resolution

of about 120 km, and the HadRM3 model for

high-resolution climate projections in the

United Kingdom and Europe, with a horizontal

resolution of about 50 km. This nested processing was done for the baseline period (1960-

1990), and for the most distant projection period

(2070-2100) to produce three ensemble runs for

the medium-high (A2) emissions scenario and

one for the medium-low (B2). For the other

emissions scenarios and the intervening projection periods, results of the global-scale model

were downscaled using statistical patterns of

fine spatial-scale climate variation derived from

full runs using scenario A2. These scenarios

were widely distributed and supported through

a web-based interface, including map-based

graphical display of projected changes in more

than a dozen climate indicators on a fine-scale

(50 km) grid of the United Kingdom.

Several analyses are continuing to use the 2002

climate scenarios in conjunction with the socioeconomic scenarios. For example, a 2004 integrated analysis of flood risk and erosion control

over a 30-100 year time horizon produced a

threat assessment, a set of scenarios of flood

risk, and a set of policy recommendations. An

evaluation of this study’s effects one year later

found that it was being used by several public

and private actors to inform decision-making.133

The UKCIP, in contrast to the US National Assessment, has built a sustained assessment capability. In addition, the central program has

less authority over the separate assessments, instead acting more as motivator, resource, and

light coordinator. Access to scenarios is to licensed users, of whom there are about 130 –

roughly half in universities, the rest about

equally split among private sector and all levels

of government. Most active users have been national officials responsible for climate-sensitive

resources, with less participation from the private sector and local governments.134

The program has invested in generating, disseminating, and documenting useful climate

scenarios for impacts users. The jury appears

to still be out on whether the level of effort and

success is similar for socio-economic scenarios,

which have not yet been either downscaled or

repeated. Getting scenarios used is a slow

process, but the scenarios produced by this program are starting to be used by decision-makers

in support of their practical responsibilities. A

significant limitation of the program, however,

is its exclusive reliance on just one family 

of climate models. This may pose risks of

under-estimating future climate uncertainty and 

over-confidence in assessments of potential climate impacts and responses. Although the UK 

program followed a substantially different organizational model from the US National Assessment, its experience highlights some of the

same issues for future scenario exercises, in particular the importance of continuity of institutional and analytic capacity and the desirability

of developing and supporting scenarios using

an organizational structure that combines centralized and decentralized elements.

133 UK Office of Science and Technology 2002.

134 West and Gawith 2005.

The UK program’s

experience highlights

some of the same

issues for future

scenario exercises as

the US National

Assessment, in

particular the

importance of

continuity of

institutional and

analytic capability and

the desirability of

developing and

supporting scenarios

using an organizational

structure that

combines centralized

and decentralized

elements.
47

Global-Change Scenarios - Their Development and Use

3.4. THE MILLENNIUM

ECOSYSTEM ASSESSMENT

The Millennium Ecosystem Assessment (MEA)

was a large, United Nations (UN)-sponsored assessment of the current status, present trends,

and longer-term challenges to the world’s

ecosystems, including climate change and other

sources of stress. Conducted between 2001 and

2005, the MEA sought to assess changes in

ecosystems in terms of the services they provide

to people and the effects of ecosystem change

on human well-being. It also sought to identify

and assess methods to mitigate and respond to

ecosystem change, for various private and public-sector decision-makers, including those responsible for the several international treaties

that deal with ecosystems.135 More than 1350

authors from 95 countries participated in the

global assessment’s four working groups, and

hundreds more in about 30 associated subglobal assessments. The assessment’s goals

were broad, ranging from providing a benchmark for future assessments and guiding future

research to identifying priorities for action.136

Results of the global assessment were presented

in a March 2005 synthesis report, and in additional volumes presenting the output of the assessment’s four working groups, “Current State

and Trends,” “Scenarios,” “Policy Responses,”

and “Multi-Scale Assessments.” The current

state and trends group examined ecosystem

trends over the past 50 years and projections to

2015; the scenarios group took a longer view to

2050 and beyond. Because of time limitations,

the work of these two groups proceeded 

largely independently.

All components of the assessment used a common large-scale conceptual framework, which

distinguished indirect drivers of ecosystem

change, direct drivers, ecosystem indicators,

ecosystem services, measures of human wellbeing, and response options. Direct drivers included direct human perturbations of the

environment such as climate change, air pollution, land-use and land-cover change, resource

consumption, and external inputs to ecosystems

such as irrigation and synthetic fertilizer use.

Indirect drivers included underlying socio-economic factors such as population, economic

growth, technological change, policies, attitudes, and lifestyles.137

The scenarios working group sought to apply

this conceptual framework to long-term trends

in ecosystems, looking ahead to 2050 with more

limited projections to 2100. They developed the

structure of the scenarios in an iterative process,

including consultations with potential scenario

users and experts in a wide range of decisionmaking positions around the world.138 Like several other major scenario exercises, they initially

sought to identify two basic dimensions of uncertainty in long-term ecosystem stresses,

which together would produce four scenarios.139

For the first dimension, like SRES they chose

globalization: continuation and acceleration of

present global integration trends, versus reversal

of these trends to increasing separation and isolation of nations and regions. For the second dimension, in contrast to the broad value-based

uncertainties used in the SRES and UKCIP scenarios, they chose one more specifically related

to ecosystems: whether responses to increasing

ecosystem stresses are predominantly reactive

– waiting until evidence of deterioration and

loss of services is clear – or predominantly

proactive, taking protective measures in advance of their clear need. The combination of

two polar values of each of these uncertainties

yielded four scenarios, summarized in Table 3.2.

The Global Orchestration (global, reactive) scenario presented a globally integrated world with

low population growth, high economic growth,

and strong efforts to reduce poverty and invest

in public goods such as education. In this scenario, society focuses on liberal economic values, follows an energy-intensive lifestyle with

no explicit greenhouse-gas mitigation policy,

135 E.g., the Convention on Biological Diversity, the

Convention to Combat Desertification, the Convention

on Migratory Species, and the Ramsar Convention on

Wetlands.

136 MEA 2006:xii.

137 MEA 2006:153 (Table 6.1) and 304 (Table 9.2).

138 MEA 2006:152.

139 MEA 2006, Figure 5.2.

The MEA sought to

assess changes in

ecosystems in terms of

the services they

provide to people and

the effects of

ecosystem change on

human well-being.
48

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

and takes a reactive approach to ecosystem

problems.140 In Order from Strength (regional,

reactive) the reactive approach to ecosystem

problems takes place in a fragmented world preoccupied with security and less attentive to public goods.141 This scenario exhibits the highest

population growth and lowest economic growth.

Economic growth is particularly low in the developing countries, and it decreases over time.

In Adapting Mosaic (regional, proactive), political and economic activity are concentrated at

the regional ecosystem scale. Societies invest

heavily in protection and management of

ecosystems in locally organized and diverse efforts. Population growth is nearly as high as in

Order from Strength, and economic growth is

initially slow but increases after 2020. Finally,

TechnoGarden (global, proactive) presents a

world that is both focused on ecosystem management and globally connected, with strong

development of environmentally friendly technology. Population growth is moderate, and economic growth is relatively high and increasing.142

Each scenario was initially constructed as a

qualitative description. Population and GDP

were specified quantitatively, while all other indirect drivers – including social, political, and

cultural factors – were qualitative. Population

scenarios were derived from the International

Institute for Applied Systems Analysis’

(IIASA’s) 2001 probabilistic projections, capturing the middle 50-60 percent of the distribution, with world population in 2050 ranging

from 8.1 billion (Global Orchestration) to 9.6

billion (Order from Strength).143 No statements

of probability or likelihood were made about the

scenarios.

From the indirect drivers, a more specific and

quantified set of direct drivers was developed,

using formal models where possible. Species

introduction and removal was the only unquantified direct driver.144 Separate pre-existing models were used of the world energy-economy,

greenhouse-gas emissions and climate change,

air pollution, land-use change, freshwater, terrestrial ecosystems, biodiversity, and marine

and freshwater fisheries. To the extent possible, these quantitative models were used to reason from indirect and direct drivers to

ecosystem effects, changes in ecosystem services, and effects on human well-being.145 In

some cases this was achieved by soft-linking

models, using outputs from one as inputs to another, but this was limited by different variable

definitions, spatial and temporal resolution, and

other model incompatibilities.146 Not all scenario elements could be modeled quantitatively,

so expert judgments were also extensively used.

The qualitative scenario process proceeded in

parallel with quantitative modeling – elaborating aspects of the scenarios that were not

amenable to modeling, filling gaps, and stipulating feedbacks between ecosystem services

and human well-being and behavior.147

ECOSYSTEM 

MANAGEMENT

WORLD DEVELOPMENT

Global Regional

Reactive Global Orchestration Order from Strength 

Proactive TechnoGarden Adapting Mosaic 

Table 3.2.

Millennium

Ecosystem

Assessment

Scenarios

140 MEA 2006, Ch 5.5.1

141 This scenario was originally named “Fortress World”

(report of first meeting of MEA global modeling

group, Jan 7, 2003). The later name reflected participants’ judgments that in such a decentralized world

preoccupied with security concerns, maintaining global

order would require democratic nations to be militarily

strong – i.e., it is a world of “realist” international affairs (MEA 2006:133)

142 MEA 2006:131. 

143 MEA 2006:182.

144 MEA 2006:304, Table 9.2.

145 MEA 2006, Table S3. 

146 MEA 2005, Table S2.

147 MEA 2006:155.
49

Global-Change Scenarios - Their Development and Use

The groups attempted to check for consistency

between quantitative and qualitative scenario elements through periodic consultations,

particularly for feedbacks that could not be

modeled analytically. Some of these were 

interactions between direct drivers and ecosystems, but the most difficult occurred in scenarios that assumed strong socio-economic

feedbacks and regulating mechanisms. Adapting Mosaic, for example, assumed strong feedbacks from new ecosystem observations and

knowledge to changes in human behavior that

could not be incorporated into the models used.

Representing these required allowing qualitative scenario logic to override both the quantitative results and the structure of models.

Unfortunately, time limits prevented this consistency checking from being done thoroughly,

so unexamined disparities between qualitative

and quantitative aspects of the scenarios remained a significant weakness.

Many of the conclusions developed from the

scenarios are common to all four scenarios,

while in others Order from Strength is the exception. For example, one major conclusion is

that rapid conversion of ecosystems for use in

agriculture, cities, and infrastructure will continue, and that habitat loss will continue to 

contribute to biodiversity loss. However, if

ecosystem services increase as projected, some

ecosystem services – although not biodiversity

– may be decoupled from ecosystem stresses.

Food security is projected to remain out of

reach for many people. Extreme, spatially 

diverse changes are projected for freshwater resources, with general deterioration in developing

countries under both “reactive” scenarios. Increasing demands for fishery products are projected to increase risks of regional marine fishery

collapses.148 In sum, ecosystem services show

mixes of improving and worsening trends in all

scenarios except Order from Strength, in which

nearly all ecosystem services are projected to be

more impaired in 2050 than in 2000. The same

three scenarios also suggest that significant

changes in policies, institutions, and practices

can mitigate some negative consequences.149

In sum, the MEA scenarios project invested

substantially more effort in developing rich

qualitative and narrative scenarios than the

SRES, but also fell short on integrating qualitative and quantitative components. In part because of the greater elaboration of the

qualitative components, this limited coordination resulted in significant inconsistencies and

requirements to resolve conflicts between the

two components. These inconsistencies arose

even with just one model used for several components of the assessment, so the challenges of

harmonization among models – and the associated possibility to explore model-structure uncertainty – did not arise. A related problem was

that for many factors it was difficult to generate

the desired level of variation between scenarios.150 This raises issues of potential methodological interest, such as how to distinguish

robust results from inadvertent convergence of

assumptions or model structures, which remain

to be investigated. Finally, the great breadth of

conditions represented in the scenarios, as well

as possible concerns with logical circularity 

between their presumptions and results,151

make interpreting the significance of the 

results difficult.

The experience of this scenario exercise provides a different perspective on some of the

same key challenges for future scenarios highlighted by the other activities reviewed. The

quite distinct difficulties faced here in attempting to combine quantitative and qualitative scenarios highlight the central importance and the

difficulty of developing new methods to integrate these two approaches. In addition, this experience highlights the value of clarity about the

intended uses of scenarios, including clarity

about whether they are intended to address specific questions, guide decisions, or explore longterm conditions. The risk of scenarios becoming

148 MEA 2006, Table S3.

149 MEA 2006:127.

150 Report of the First Meeting of the MEA Global Modeling Group, 7 Jan 2003, at www.usf.uni-kassel.de/magmgroup/dl/first_report.doc; Second Report of the

MEA Global Modeling Group, 7 March 2003, available at www.usf.uni-kassel.de/ma-gmgroup/dl/sanjose

_report.doc.

151 This concern is particularly present regarding implications of the assumption that ecosystem management

is either proactive or reactive (See, e.g., MEA 2006, Ch

8.4.2.1 and Ch 9).
152 NAST 2001.

50

The U.S. Climate Change Science Program Section 3 - Review of Major Climate-Change Scenario Exercises

less useful due to breadth and vagueness may be

particularly acute for scenarios that attempt to

capture multiple stresses on some system – even

though such multi-stress assessment is repeatedly

advocated for climate-change and other forms of

environmental assessment.152
Global-Change Scenarios - Their Development and Use

Challenges and 

Controversies in 

Scenarios for Climate Change

SECTION

4

51

This section discusses several issues that have arisen in multiple scenario exercises related to climate change, issues that pose challenges for expanding the usefulness of scenarios to climate

change analysis, assessment, and decision support. Section 4.1 examines the type of information

needs of specific types of decisions related to climate change and considers the requirements and

challenges of crafting scenarios to serve these needs. Section 4.2 considers the use of scenarios

that has been more common thus far, in structuring climate-change assessments and framing

broad policy debates, and identifies the distinct challenges in enhancing the value of scenarios in

these purposes. The remaining sub-sections examine particular design challenges in crafting scenario exercises: how to structure interactions between experts and stakeholders in developing

scenarios; how to communicate scenarios to potential users not involved in their creation; how

to pursue the two, not perfectly aligned goals of consistency and integration in scenarios; and

how to represent and interpret uncertainty in scenarios. Throughout this section, we present illustrative examples of scenario activities in text boxes. These examples shed additional light on

various challenges, especially relating to scenarios’ use in decision-making.

4.1. SCENARIOS AND DECISIONS

As discussed in Section 1, the general purpose of scenarios is to inform decisions, but their connection to specific, identified decisions can be more or less close and direct. In interpreting and

evaluating present experience with scenarios and identifying key challenges in making them more

useful, it is important to distinguish scenario exercises by their major characteristics, including

their specificity, their proximity to decisions, the degree of normative presumptions embedded in

them, and where they lie in the causal chain outlined in Section 2. To consider how scenarios can

help inform climate-change decisions, we must first specify the relevant decisions and decisionmakers more sharply. This section considers the major concrete decisions that comprise a response

to climate change. Decisions related to assessment, modeling, and research are considered in Section 4.2. This discussion must be somewhat hypothetical, extending from rather thin current practice to reasonable speculation about future decisions and likely information needs.

Because the dynamics of climate change operate on multiple spatial scales from the local to the

global, there is no single global climate-change decision-maker. Rather, many distinct decisionmakers with diverse responsibilities will affect and be affected by climate change. Because of climate’s recent appearance on policy agendas and its dense connections to other issues, many of

these decision-makers’ primary responsibilities are defined as something other than climate change.

Some of them are already considering how climate change might affect their responsibilities, but

many are not. 
52

The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

Section 2 described climate-change decisions

using the conventional dichotomy of mitigation

versus adaptation. To consider potential contributions of scenarios in more detail, we discuss

three types of decision-maker: national officials,

impacts and adaptation managers, and energy

resource and technology managers. These can

often be identified as particular programs, divisions, agencies, organizations, or individuals,

each with different responsibilities and types of

information they might consider in making their

decisions. All three groups face decisions under

uncertainty with long-term consequences related

to climate change, and so might benefit from scenarios providing structured information and assumptions about the values at stake, the available

choices, and their consequences under alternative climate-change futures. 

National officials’ responsibilities are the broadest and the most likely to be explicitly related to

climate change. They develop national policies

that target greenhouse-gas emissions and motivate investment in technologies that will influence future emissions trends. They negotiate

policies internationally with officials from other

nations, and with sub-national officials who

may share mitigation responsibilities or undertake mitigation measures at their own initiative.

They also have responsibilities to anticipate and

respond to climate-change impacts in their nations. Their climate-change responsibilities are

open-ended, not limited to mitigation and

adaptation: these decision-makes will determine the extent to which other responses such

as geoengineering are considered, and the design of systems and institutions for assessment. They are also responsible for overall 

national welfare, including not just the environmental effects of their decisions but also other

linked national interests such as economic prosperity and security. 

Impacts and adaptation managers have responsibility for particular assets, resources, or interests that might be sensitive to climate change.

They must decide how to anticipate, prepare for,

and respond to the threat, minimize its harm,

and maximize any associated benefit. They

may be private or public actors – e.g., owners 

or managers of long-lived assets such as ports

or water-management facilities; managers of

lands, forests, or protected areas; emergency

preparedness or public health officials; officials

making zoning or coastal development policy;

or firms in insurance or financial markets who

may bear secondary risks from impacts or seek

to develop new instruments to exchange these

risks. Unlike national officials, these actors’ 

decisions are purely responses to climate

change, realized or anticipated: they have little

influence over how the climate will change.

Their responsibilities will often connect with

the impacts-related responsibilities of national 

officials, but are narrower in scale or scope. Impacts and adaptation managers would be concerned not with aggregate climate-change

impacts on the United States, but with more

specific impacts such as those on seasonal flows

and water-management operations on the 

Upper Mississippi.

Energy resource and technology managers include developers and operators of fossil or nonfossil energy resources, investors in long-lived

energy-dependent capital stock such as electrical utilities, and researchers, innovators, and investors in new energy-related technologies.

These decision-makers are mostly but not exclusively in the private sector. Their decisions

may have consequences that interact with various processes operating over multiple timescales, from short-term market responses, to

decadal-scale processes of investment, resource

development and depletion, and penetration of

new technologies, to century-scale processes of

climate change.153 These actors’ decisions will

strongly influence society’s ability to control

greenhouse-gas emissions. This group also includes energy consumers such as firms or public agencies considering mitigation actions in their

own operations. While their areas of responsibility may be vulnerable to climate change and its

impacts, the largest climate-related risks for this

group are likely to come not from climate

change itself, but from climate-change policies:

national mitigation policies, and other market

and regulatory decisions that shape the outcomes

of private mitigation activities.

At greatly varying levels of precision and specificity, scenarios can present two types of information to support decisions by these three types

153 Shell International 2001, Davis 2003. 

All three groups face

decisions under

uncertainty with longterm consequences

related to climate

change, and so might

benefit from scenarios

providing structured

information and

assumptions about the

values at stake, the

available choices, and

their consequences

under alternative

climate-change futures.
53

Global-Change Scenarios - Their Development and Use

of actors. Scenarios can represent potential future developments that may threaten decisionmakers’ interests or values, call for decisions,

or challenge conventional thinking and practices. And they can provide a structure to assess potential consequences of alternative

decisions for things that matter to the decisionmaker. Beyond this generalization, the three

types of decision-makers will differ substantially in the specific types of information they

need, the time horizons of their decisions, and

the type and extent of causal connections between their decisions and the conditions

specified in scenarios.

4.1.1. Scenario needs: 

national officials 

As national officials have the broadest responsibilities related to climate change, they are also

likely to have the broadest information needs.

In their responsibilities to build national adaptation capacity and manage key vulnerabilities,

their needs are similar to those of impacts and

adaptation managers: scenarios of potential future climate change under specified emissions

assumptions and resultant impacts on particular

resources and communities in their nation, with

particular focus on areas of greatest vulnerability. They will likely have less need for fine spatial and sectoral detail in potential impacts, but

more need for consistent scenarios that allow

comparison and aggregation across sub-national

regions and sectors. These will help to prioritize, identify key areas of vulnerability, and estimate aggregate costs for planning purposes.

In their responsibilities for national mitigation

policy, national decision-makers will also need

information about the aggregate impacts of 

climate change, since the more severe climate

impacts are likely to be, the greater the justification and likely political support for mitigation

measures. But mitigation decisions also require

additional information – including projections

of future emissions in the absence of explicit

mitigation efforts, and the consequences of alternative mitigation policies, in their effects on emissions, their cost, and their implications for other

dimensions of national interest. 

These needs introduce a dimension of complexity into mitigation scenarios, sometimes

called “reflexivity.” Because mitigation policies

seek to reduce future emissions by altering the

socio-economic drivers of emissions growth,

the analysis of mitigation policies and their consequences must be coupled to the causal logic of

emissions scenarios. Whereas climate scenarios

can be treated as exogenous when assessing

adaptation decisions, emissions scenarios cannot be treated as exogenous in assessing mitigation decisions. Any emissions scenario

embeds some assumptions about mitigation

policies, assumptions that may have to be

changed to assess particular mitigation policies.

This effect will be strongest when emissions

projections and mitigation options are being

considered at the same spatial scale, e.g., national mitigation policies are being assessed relative to national emissions projections. The

effect of national mitigation strategies on global

emissions will be weaker: no nation controls

global emissions trends, and the effects of small

nations’ mitigation strategies on global trends

can be very small.

Scenarios to inform mitigation decisions are

also likely to require considering alternative assumptions about the policy context in which

these decisions are made. The effects of national mitigation strategies – including how

much they reduce national emissions, as well as

their costs and other consequences – will depend on the economic, technological, and policy

context, including related decisions by other

major nations, individually and through international coordination. Assumptions about the

policy context will be less important in scenarios to inform international mitigation decisions,

since when decisions are globally coordinated

there is no “elsewhere” – but alternative assumptions about nations’ degrees of compliance

and form of implementation of international

commitments may still be needed.

Scenarios of emissions, climate change, and impacts inform mitigation decisions by helping to

characterize the potential severity of climate

change and therefore how important it is to control emissions. This support is indirect, serving

primarily to elevate or moderate the general

level of concern on the issue. More focused

work on mitigation has been done using conAny emissions scenario

embeds some

assumptions about

mitigation policies,

assumptions that may

have to be changed to

assess particular

mitigation policies.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

structed scenarios of limited emissions, often

aiming at stabilizing atmospheric concentrations

or radiative forcing at various levels, and examining the configurations of technology, energy resources, and economic and population growth

that are consistent with the specified scenario.

Some studies have used quantitative models to

estimate costs of such scenarios, relative to an assumed baseline emissions scenario.154

4.1.2. Scenario needs: impacts and

adaptation managers

To assess the threats and opportunities they face

and evaluate responses, impacts and adaptation

managers need scenarios of potential future climate change, its impacts in their areas of responsibility, and the factors that influence

vulnerabilities. With few exceptions, these actors’ decisions will have no effect on the climate

change to which they must respond, so scenarios of climate-change stresses can be constructed independently of the assessment of

potential adaptation decisions, without concern

for feedbacks that may modify the conditions

specified in the scenario.

Particular decision-makers’ needs will be highly

specific in the variables they require, and their

time and spatial scale and resolution. A planner

of water-management infrastructure may need

monthly or finer-scale rain and snow projections over a watershed; a designer of coastal infrastructure may need probabilistic projections

of sea level, storm intensity and frequency,

storm surge, or saltwater intrusion. But in their

climatic elements, these information needs all

rest on a common core of scenarios of global

climate change and emissions drivers. This dual

structure of information – highly particular climate variables, based on a set of common “core

scenarios” – suggests a cross-scale organizational structure for providing scenario information: commonly produced scenarios of

climate change and other components requiring consistency, specialized expertise, or highcost resources; development of decentralized

capabilities in impact assessments to adapt these

core scenario elements and develop assessmentspecific extensions; and close communication

between these groups to ensure that useful variables are generated and saved, and that data and

documentation are transferred accurately.

This is the area of climate-related decisions for

which the provision of information from climate-change scenarios is most advanced. Still,

further progress is needed in the development

and use of scenarios of socio-economic conditions, and in creation of methods and tools 

to augment centrally provided scenario information with information tailored to specific 

impact assessments. In addition, many impactsrelated decisions will require scenarios of climate change in the context of other linked

stresses and changes. 

4.1.3. Scenario needs: energy

resource and technology managers

Energy and technology managers will most benefit from scenarios that explore alternative policy regimes and their consequences for the

value of energy and technology assets and investments. For some, the predominant concern

may be overall policy stringency, perhaps summarized as alternative emissions-price trajectories over time; for others, specific details of

policy design and implementation may need to

be considered. Scenarios of emissions, climate

change, and impacts only matter for decisions

via their likely influence on policy stringency,

and so do not need to be explicitly represented

in scenarios. These actors may have some influence on policy, but probably not such strong

influence that climate-policy scenarios would

have to incorporate feedbacks from their own

advocacy efforts.

Unlike the other two types of decision-makers,

these actors are likely to compete with each

other. If, for example, they are investors allocating research effort between higher and loweremitting energy sources, those who better

anticipate future policy will benefit relative to

those who do worse. If they use scenarios, they

may consequently choose to produce them privately, perhaps coupled with other analyses to

generate practical guidelines for investments.155

As for the other types of decision-makers, these

specialized scenarios could be based on general

scenarios of global emissions and climate

154 Morita et al. 2001, CCSP 2007. 

155 Ged Davis, personal communication. (posted expert

review comments).

Impacts and adaptation

managers need

scenarios of potential

future climate change,

its impacts in their

areas of responsibility,

and the factors 

that influence

vulnerabilities. Energy

and technology

managers will most

benefit from scenarios

that explore

alternative policy

regimes and their

consequences for the

value of energy and

technology assets and

investments.
55

Global-Change Scenarios - Their Development and Use

change. Published scenarios produced to date

on the climate-change issue, however, have not

considered mitigation policies with the specificity necessary to inform these actors’ decisions.

4.1.4. Representing decisions 

in scenarios

A major challenge to developing scenarios to

support decisions is reflexivity, that is, how to

represent decisions within scenarios without

making scenarios either circular or contradictory. In meeting this challenge, the most basic

distinction to draw is between decisions by the

scenario’s targeted users and decisions by other

actors. From the users’ perspective, decisions

by others over which they have no influence are

indistinguishable from non-choice events. If the

factors influencing these decisions are confidently understood, they might be represented

deterministically, like well-understood biophysical or economic processes. In the more frequent case that others’ choices cannot be

confidently predicted, they might be represented

as uncertainties – again, just like uncertain biophysical or economic processes. As with all uncertainties, how to treat them depends on their

judged importance for the users’ decisions: if it

is high, they can be represented in alternative

scenarios; if not, they can be fixed at some bestguess value for all scenarios. In either case,

these decisions are treated exogenously.

Representing decisions by the scenario users is

fundamentally different. Since the scenarios are

intended to inform these decisions, alternative

choices should not be represented as exogenous

uncertainties but be stipulated independently

from the scenarios. Users can then explore their

implications under conditions imposed by scenarios, including representation of major uncertainties. Various degrees of coupling can be

required between the logic of scenarios and the

analysis of consequences of the users’ decisions.

In scenarios for impacts, these can usually be

separate; in scenarios for mitigation, they may

have to be closely coupled, since emissions scenarios may change under alternative assumptions about mitigation decisions.

In scenarios to inform global climate-change

decisions, the sharpest question is how to represent mitigation decisions within scenarios.

Following the general reasoning above, how

these are treated should depend on what type of

decision is being informed. In climate scenarios to inform impact assessments and related

decisions, the scenario users are not considering mitigation decisions and have little influence over them, so emissions scenarios should

include assumptions about the likely or plausible range of mitigation efforts. The range of future climate change considered may thus be

narrowed to reflect the possibility of negative

social and political feedbacks: sustained rapid

emissions growth may generate pressure for aggressive mitigation, due to increasing signs of

climate change, alarming projections of future

change, or other environmental harms from

rapid expansion of coal or synthetic fuels. 

Such a negative-feedback mechanism may not

be effective, of course. Many factors could intervene: mitigation measures may not gain

enough support to be adopted, socio-political

capacity to enact stringent policies may be diminished, policies adopted may be ineffective,

or early technology or policy decisions may

lock in high-emitting future paths. But to the

extent that such a negative-feedback mechanism

does operate, persistence of the highest emissions paths beyond a few decades would become unlikely. 

Parallel reasoning may apply to extremely low

emission paths, if sustaining such low emissions

requires continued costly mitigation efforts that

come to be seen as unnecessary. This negativefeedback mechanism would likely be weaker

than that operating at the high end of the emissions distribution, however, because long timeconstants mean that increasing signs of climate

change are likely to continue through most of

the 21st century even if we follow a low-emissions path. If impacts assessors and managers

judge these negative feedbacks to make extreme

emissions paths sufficiently unlikely, particularly high ones, they may reasonably decide not

to consider these extreme emissions futures in

their planning for adaptation.

For scenarios to inform mitigation decisions,

particularly at the international level, the situation is different. Informing these choices requires information about potential emissions

paths and their consequences under all levels of

In climate scenarios to

inform impact

assessments and

related decisions ...

emissions scenarios

should include

assumptions about the

likely or plausible

range of mitigation

efforts.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

mitigation effort that decision-makers might

plausibly consider – including no additional

measures, or even reversal of previous measures

if this is on the agenda. Consequently, in contrast to scenarios for impacts, extreme emissions futures should not be excluded when

assessing mitigation decisions. For example, if

scenarios that truncate high-emissions futures

by assuming stringent mitigation are used to

support a decision that stringent mitigation is

not necessary, the result is contradictory: a conclusion supporting a decision is based on the

presumption of the contrary decision. To avoid

such contradictions, scenarios to inform mitigation decisions must consider alternative mitigation choices explicitly, not embed them

implicitly in the underlying logic of the scenario.

Moreover, national officials act only for their

own nations in the near term, even when they

negotiate global mitigation. They may make

choices for long-term planning and institutional

design for future mitigation as well, but it is

their successors who will decide whether to

continue, strengthen, or otherwise change measures adopted today. From the perspective of

current national officials, mitigation decisions

by other nations and in the future fall between

the two cases discussed above: they are not controlled by the scenario user, but can be influenced to some degree. For policy choices by

other nations, national officials may need to be

advised in two modes, reflecting their dual responsibilities to make national policy and to negotiate international agreements. In the latter

capacity, alternative approaches to global mitigation strategy should be represented as

choices. But when they consider national decisions separate from globally coordinated strategy, relevant decisions of other major nations

should be represented as uncertainties. This

may require use of two distinct types of scenarios to advise development of different aspects

of national mitigation policy.

How to represent future mitigation decisions

poses a still harder dilemma. On the one hand,

it appears risky or even irresponsible to assume

that the bulk of mitigation efforts can be left to

future decision-makers, even if we assume this

will be easier for them because of greater wealth

or technological prowess. On the other hand,

assuming that future decision-makers cannot be

relied on to act responsibly at all can easily lead

to decisions that incur excessive costs, by trying to achieve rapid mitigation immediately or

tie future decision-makers’ hands. 

Two approaches appear promising for integrating future mitigation decisions into scenarios to

inform current decisions. Scenarios could presume that today’s decision-makers choose the

future path of mitigation, allowing them to assess and contribute to a trajectory of effort that

considers the welfare of both current and future

citizens. Alternatively, scenarios could treat future large-scale mitigation choices as uncertainties represented in alternative scenarios,

while also considering how current choices can

seek to influence the opportunities and incentives faced by future decision-makers. 

In sum, the importance of connecting scenarios

to actual decisions is widely recognized, but

there is a large gap between, on the one hand,

the value scenarios could provide to climatechange decisions and the aspirations of scenario

producers to provide that value, and current

practice on the other hand. There has been little use of scenarios to directly inform climatechange related decisions, although there appears

to be a sharp increase in the interest of decisionmakers and early attempts. The rapid increase

in interest is particularly evident for informing

decisions related to climate-change impacts and

adaptation. There are fewer indications of similarly direct use of scenarios to inform mitigation

decisions, perhaps in part because nearly all current mitigation decisions have been near-term.

Mitigation decisions at the national and international level have taken scenarios into account

indirectly. Most scenarios have been constructed to provide inputs to assessments, models, or other analyses. This has included serving

as inputs to the production of other types of scenarios, which then describe other potential future conditions that depend on those specified

in the scenario, as for example a model-based

climate scenario depends on inputs from an

emissions scenario. While these uses can be

characterized as supporting decisions (i.e., decisions about assessments, modeling, and research), their connection to concrete decisions

of mitigation and adaptation is indirect,

achieved through contributions such as sup-

...in contrast to

scenarios for impacts,

extreme emissions

futures should not be

excluded when

assessing mitigation

decisions. ... Scenarios

to inform mitigation

decisions must

consider alternative

mitigation choices

explicitly, not embed

them implicitly in the

underlying logic of the

scenario.
156 Rosenzweig and Solecki 2001; Kinney et al. 2005,

2006; Rosenzweig and Major 2006.

57

Global-Change Scenarios - Their Development and Use

porting strategic planning and risk assessment,

providing advance analysis for potential future

decisions, exploring plausible extreme cases,

helping to characterize and prioritize key uncertainties, or educating decision-makers or the

public. This description applies to the major

scenario exercises discussed in this report, including the IPCC emissions and climate scenarios, the US and UK assessments of climate

impacts, and the MEA scenarios. 

Three linked activities – the Metropolitan East Coast (MEC) assessment of the US National Assessment, the New York Climate and Health project (NYCHP), and the New York City Department

of Environmental Protection (NYCDEP) Task Force on Climate Change – have used or are using

scenarios to assess impacts of climate change on the New York Metropolitan Region, identify areas

of vulnerability, and inform regional planning and decision-making.156

The MEC assessment began with a regional workshop in April 1998, involving about 150 participants,

including public agencies at all levels of government as well as climate researchers. The subsequent

assessment was conducted by sector teams of researchers and officials from agencies responsible

for the study sectors. Teams developed regional scenarios of climate change and sea level rise based

on the downscaled climate-model scenarios provided by the US National Assessment, plus two additional scenarios based on extrapolation of recent regional climate trends and historical extremes.

The scenarios were used to project climate-change impacts on beach nourishment, 100 and 500-

year flood heights, wetland aggregation and loss, adequacy of the water supply system under

droughts and floods, illnesses from acute air-pollution episodes, and peak energy loads. These impact projections were used for preliminary assessment of adaptation strategies and policies.

Following the MEC Assessment, the NYCHP created updated regional climate scenarios in consultation with an expert-stakeholder Advisory Board. This study further analyzed public health impacts,

focusing on air quality and extreme heat events. The updated climate scenarios used the IPCC A2

and B2 emissions scenarios driving global and regional climate models to create downscaled scenarios for the region. These were augmented with newly developed scenarios of future regional land

use and population growth based on the IPCC A2 and B2 storylines. 

In response to the widespread public attention received by the MEC Assessment Report, the Commissioner of the NYCDEP established the Climate Change Task Force, a collaboration among regional researchers and the agency that manages the water system. The Task Force uses the latest

climate-model simulations from the IPCC Fourth Assessment Report, as well as additional global and

regional climate models, to develop new regional scenarios. These will include probability distributions of average and extreme temperature and precipitation change, as well as sea level rise. The

Task Force is also developing qualitative scenarios of extreme sea level rise in the region. DEP is

using these results to develop a comprehensive adaptation strategy for the New York City water

system, including assessment of many specific adaptation options, that considers both uncertainties

in future climate change and managerial factors such as the time horizon of different adaptation responses and capital turnover cycles. 

This is a successful example of scenario-based assessment of climate impacts and adaptation options.

The scenarios are connected with the concrete responsibilities and concerns of stakeholders, who

were involved in their design from the outset. Although officials have found the wide range of uncertainty in climate scenarios difficult to incorporate into infrastructure design specifications, particularly for precipitation, the exercise has effectively conveyed the challenges posed by future

climate uncertainty to current decisions of planning and infrastructure design. Stakeholders’ willingness to support and participate in three separate phases of these activities and NYCDEP’s incorporation of them into a strategic planning exercise provides clear evidence of the practical utility

of the exercises.

BOX 4.1. Scenarios for Climate-Change Adaptation 

in the New York Metropolitan Region
157 Gosselink 1984, Williams et al. 1999, Burkett et al.

2005, Morton et al. 2002.

158 Shinkle and Dokka 2004, Barras et al. 2003.

159 US Army Corps of Engineers 2004.

160 See, e.g., http://www.clear.lsu.edu/clear/web-content

/index.html.

161 Presentation by Randy Hanchey, Louisiana Department of Natural Resources, to Governor’s Advisory

Commission on Coastal Protection, Restoration and

Conservation, Baton Rouge, LA, June 22, 2006. 

162 Cook 1939, Doyle et al. 2003.

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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

Sea-level rise is one of several factors that contributed to the decline of coastal ecosystems along the US Gulf

of Mexico coast in the 20th century (Figure 4.1).157 In southeastern Louisiana, where the local rate of land surface subsidence is as high as 2.5 cm per year, rise in local “relative sea level” may be the most important factor in the rapid loss of coastal zone wetlands over the past several decades.158

Despite the importance of sea level rise in historical losses of coastal lands, planning projections of future

changes in coastal Louisiana used by both federal and state agencies prior to the devastating impact of Hurricanes Katrina and Rita in 2005 were based on just one scenario: no change in the rate of sea level rise. No alternative sea level scenario was considered in the plans then being developed to restore and protect the

Louisiana coastal zone.159 This assumption sharply contrasts with the IPCC projections, which state that the

global average rate of sea level rise in the 21st century may increase 2- to 4-fold over that of the 20th. Such increases will exacerbate wetland losses throughout the Gulf Coast region and obstruct restoration plans that

do not take account of likely increases in water levels and salinity. 

The ecosystem modeling team working for the State of Louisiana and the US Army Corps of Engineers is

presently integrating accelerated sea level rise scenarios into planning exercises that will aid federal and state

agencies in evaluating restoration alternatives.160 The State of Louisiana is consulting with the Rand Corporation to obtain probability estimates for various scenarios of sea level change to help guide engineering decisions and the design of projects aimed at restoring levees and coastal landforms that protect coastal

communities.161 Sea level rise scenarios are also being used to assess the impacts of climate change and variability on the Gulf Coast transportation sector. To assess transportation impacts, a sea level rise simulation

model developed by the US Geological Survey generates scenarios of sea level change using over a dozen

GCMs and six SRES emission scenarios. 

Sea level rise scenarios are important not just in regions like Louisiana. The Big Bend region of the Florida panhandle is experiencing very little vertical movement of the land surface, so sea level there has been rising at

approximately the global average rate of 1 to 2 mm per year. But even here, coastal wetlands positioned on

flat limestone surfaces may be subject to highly nonlinear effects as sea level reaches a threshold at which large

areas are subject to increased salinity or inundation.162

Regional scenarios of potential sea level rise are needed to support coastal management and protection activities, as well as plans for wetland restoration and post-hurricane reconstruction. Absent consideration of

such scenarios, restoration and rebuilding programs are likely to lock in errors that result in wasted resources and

avoidable increases in future vulnerability.

BOX 4.2. Scenarios of Sea Level Rise along the Gulf Coast

-.5

0

.5

1

1.5

2

1910 1930 1950 1970 1990 2010 2030 2050 2070 2090

Historical Data

Low (B1) Scenario 

Middle (A1B) Scenario

High (A1FI) Scenario

Linear Trend from 1909−2003 Monthly Data

Figure 4.1. Output from a Gulf Coast

sea level rise scenario tool

Historical sea level change and projected sea level

rise under three greenhouse-gas emissions

scenarios, in meters, are shown for Galveston,

Texas. Both historical data and future projections

are smoothed from monthly data using a 

12-month moving average. (Source: Thomas W.

Doyle, National Wetlands Research Center, United

States Geological Survey.)
59

Global-Change Scenarios - Their Development and Use

4.2. SCENARIOS IN

ASSESSMENTS AND POLICY

DEBATES

Within large-scale assessments of climate

change or other environmental issues, scenarios

can serve several roles. Most straightforwardly,

they can provide required inputs to other parts

of the analysis, as the IPCC emissions scenarios

support the controlled comparison of climatemodel runs. They can also serve as devices to

organize and coordinate the multiple components of a large-scale assessment, particularly

when much of the assessment is forward-looking. In the IPCC assessments, for example,

emissions scenarios have not just been used to

drive coordinated climate-model projections,

but have also increasingly been followed

through to coordinate characterization of climate impacts and adaptation opportunities, and

used in a more preliminary way to organize assessments of the economic and technological

implications of alternative mitigation strategies.

Similarly, the US National Assessment and UK

Climate Impacts Programme have both attempted to identify a small set of climate and

socio-economic scenarios, to coordinate and

gain comparability across multiple studies and

allow aggregate assessment of impacts and vulnerabilities at the national level.

In a broad assessment including many teams

considering separate questions of climatechange, impacts, mitigation, and adaptation,

simple coordinating devices are needed to make

teams’ work comparable and allow synthesis to

produce aggregate conclusions. Emissions scenarios are natural devices to provide such coordination, both because emissions hold the

clearest near-term opportunities for intervention, and because they have clear and recognized connections both directions in the causal

chain, to every aspect of the climate-change

issue. However, in part due to management issues, these efforts to use scenarios as broad coordinating devices have not been wholly

The California Department of Water Resources (DWR) produces an updated California Water Plan every five years. The plan projects water supplies and demands, and evaluates current and proposed demand-management programs and supply investments, to

“provide a framework for water managers, legislators, and the public to consider options

and make decisions regarding California’s water future.”163

In contrast to prior plans that constructed only one future scenario, the 2005 plan explicitly considered uncertainty in supply and demand projections. Three alternative scenarios of supply and demand conditions were constructed through 2030: one extending

current trends in population and economic growth, agricultural production, environmental restrictions on water use, and water conservation occurring without policy initiatives (e.g., through equipment replacement, technological change, and revised building

codes); and two presenting higher and lower increases in demands. The report of the

2005 plan discusses global climate change and the potential challenges it poses to water

supply and demand in California, but climate change is not explicitly represented in the

plan’s three scenarios. 

In addition to adopting these scenarios, the State of California is developing data and analytic capacity to enrich the treatment of uncertainty and climate change in future plans.

In parallel with development of the three principal scenarios in this plan update, DWR

sponsored development of several analytic tools to strengthen the treatment of uncertainty in future plans. In addition, the California Climate Change Research Center with

co-sponsorship from DWR is developing fine-scale regional climate-model scenarios to

support analysis of climate-change impacts on water resources.164 The DWR plans to

incorporate these climate-change scenarios explicitly in the next plan update in 2010.

BOX 4.1.3. Scenarios in the California Water Plan

163 California Water Plan home page, http://www.waterplan.water.ca.gov. 164 California DWR 2005:4-32. 
60

The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

satisfactory in practice. To serve as coordinating devices, scenarios must be developed and

disseminated early in the process, preferably before the work of assessment teams even begins.

Moreover, they must be documented with detailed information about the process and reasoning used to generate them, including explicit

identification of underlying assumptions and

supporting data, models, and arguments. In

practice, timely, detailed, and transparent dissemination of scenario information has rarely

been achieved. 

Scenarios used in large-scale assessments can

also make other contributions that are related to

the prominent dissemination a major assessment receives. They may, for example, be used

as inputs to planning or decision-support

processes that were not part of the original assessment. In such use, they may gain a more direct connection to decision-making than they

had in their original production or use. Scenarios of global emissions and the model-based climate scenarios based on them especially lend

themselves to such derivative uses, informing

many different decisions by diverse actors. 

Scenarios in prominent assessments can also

contribute to the framing of public and policy

debates. In this role, scenarios inevitably become political objects, in two senses. They are

subject to political forces that seek to influence

their development, and political reactions to

them once developed. These pressures pose

challenges and risks that differ quite markedly

from those that apply in using scenarios to inform decision-making, where we tend to assume a greater degree of commonality of

knowledge, perspective, and interest in the

process among participants and some group of

relatively well-defined users. 

Within scenario exercises, various actors may

seek to bias scenarios’ content to help advance

their policy preferences or their broader political objectives, by limiting consideration to futures they judge desirable or showing some

problem in an acute state that would appear to

demand a response. While it is not possible to

eliminate biases in scenarios, unacknowledged

normative biases in scenarios can pose the risk

of excluding consideration of futures that are

judged undesirable or that pose sharp decisionmaking challenges. Such biases can be difficult

both to detect and to correct. Beyond exhorting

developers to scrutinize scenarios critically to

avoid bias, the best protection against such biases

lies in transparency about the assumptions and

information underlying scenarios and associated

judgments of likelihood.

Other political pressures come onto scenarios in

the broader use, debate, and criticism that they

encounter after release. For impartial support

of policy decisions, scenarios should fairly present knowledge and uncertainty about potential

variation on important dimensions. This typically requires consideration of a wide range of

potential futures – often a wider range than relevant decision-makers might initially think

plausible, due to well-known habits of conventional thinking and excessive confidence. 

Sometimes a scenario’s implications for decisions may be obvious. For example, a scenario

might represent developments so severe that

most people would judge it to demand intervention. Another might represent developments

that most people would judge inconsequential

or beneficial, so not meriting any intervention.

A wide-ranging set of scenarios may include examples of both such extremes. Consequently,

such a wide range of potential futures in a set

of scenarios – even if this is faithful representation of present knowledge and uncertainty –

provides opportunity for partisan distortion and

efforts to make scenarios policy-prescriptive.

In global change scenarios, conflicts and opportunities for bias arise most acutely over

emissions scenarios. Since much of the uncertainty about climate change beyond 2050 comes

from uncertainty in future emissions trends, actors with strong policy preferences can highlight

emissions scenarios that lend support to their

views. Those who advocate aggressive mitigation may highlight the highest-emissions scenarios to emphasize the elevated risk of 

climate change that would follow. Those who

oppose mitigation may highlight the lowestScenarios inevitably

become political

objects, in two senses.

They are subject to

political forces that

seek to influence their

development, and

political reactions to

them once developed.
61

Global-Change Scenarios - Their Development and Use

emission scenarios to suggest that no action to

limit emissions is warranted. Because scenarios

are used when knowledge of causal processes is

weak, it is easy to make any scenario appear

salient and likely, even if it is extreme. It is

equally easy to probe inside the details of any

scenario to find inconsistent or implausible implications, particularly when a scenario is rich in

detail.

But, although political actors may have legitimate reasons to highlight one extreme scenario,

it is not appropriate for any scenario to dominate assessment or consideration of decisions.

A claim that only a single scenario is plausible

– especially one near the top or bottom of the

present range – is a claim to predict the future,

which can be readily dismissed. Claims that a

particular scenario is implausible cannot be so

easily dismissed, however, since scenarios represent only the imperfect judgment of the team

that produced them. Leaving aside scenarios

that violate clear principles of science (e.g., one

whose energy assumptions violate the laws of

thermodynamics) or economics (e.g., one that

presumes a large new capital stock in a few

decades without the investments needed to create it), it is possible to construct pictures of the

next century so extreme or unprecedented that

most observers would agree they do not merit

serious consideration. But short of such an extreme – which describes no global-change scenario discussed here or known to us – claims

that a broad class of potential futures is implausible should have to pass a high hurdle. Identifying specific extreme or implausible elements

within a scenario does not suffice to make this

case, since virtually any scenario will be found

to contain these if scrutinized closely enough.

Nor does identifying ways that a scenario of future change diverges from some established

trend or pattern, since established trends can

and do change.

Historical studies of forecasting exercises such

as energy forecasts have repeatedly found them

too confident that the future will extend recent

trends.165 The threshold any single scenario

must pass is to appear sufficiently plausible or

instructive to merit consideration in planning

and analysis, and this is a judgment to be made

by developers and users – with enough transparency about underlying assumptions and reasoning that users can make an informed

judgment. A set of scenarios should be constructed so that the range of conditions they represent encompasses present knowledge and

relevant uncertainties that might influence

mitigation or adaptation decisions. Since

subjective judgments cannot be avoided in

constructing scenarios, the range provided

should err on the side of being broad rather than

narrow, at least initially. Identifying problems

with one scenario does not necessarily impugn

the credibility even of that one scenario, certainly not the whole set, because scenarios cannot be consistent in every underlying detail.

In subsequent revisions as knowledge advances,

scenarios can continue to play their role coordinating assessments and framing policy debates

with more focus and less arbitrariness. Continuing research and analysis might come to

identify some scenarios as severe in their consequences and others as inconsequential, or

might revise the initial characterization of the

determinants and feasibility of particular scenarios, including suggesting that some are too

unlikely to merit serious consideration. These

judgments can feed into decisions about continuing analysis of scenarios: which ones can be

dropped and what new ones should be added.

One major basis for updates in scenarios will be

policies adopted, which can set a baseline to

focus further deliberations. Perfect attainment

of targets and success of policies should not be

assumed, but scenarios can focus subsequent

debate by posing such questions as “What if we

just meet this target; what if we fall short by this

much; and what if we exceed it by this much, or

adopt these additional measures?” 

A claim that only a

single scenario is

plausible – especially

one near the top or

bottom of the present

range – is a claim to

predict the future,

which can be 

readily dismissed.

165 Smil 2005, Greenberger et al. 1983.
166 This example is drawn from Parson 2003.

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Emission scenarios of chlorofluorocarbons (CFCs) and other ozone-depleting chemicals

substantially influenced policy debates over control of these chemicals to protect the

ozone layer. Until the early 1980s, these policy debates used a convention to project

ozone losses that originally served as a simplifying research assumption: constant emissions forever. This convention has obvious research benefits, like the simple doubledCO2 equilibrium scenarios used in climate models. It standardized input assumptions,

allowing exploration of scientific and modeling uncertainties without the confounding effect of different emissions assumptions. Moreover, this convention made no claim to realism, and so avoided distracting arguments over whether one emissions projection or

another was more realistic. Nevertheless, the resultant calculations were frequently

mistaken for projections of realistic future trends.

The question of what future emissions trends were likely only became prominent in

policy debates around 1983. World CFC production had dropped nearly a third in the

late 1970s due to both regulatory and market-driven reductions in their largest use,

aerosol spray propellants, and declined further in the early 1980s recession. It was

widely argued that further restrictions were unnecessary—CFCs’ major markets were

saturated and further growth was highly unlikely. The resumption of sharp growth in

1983 undermined this claim, making it clear for the first time that managing the ozone

risk required considering scenarios of CFC growth as well as steady-state and decline.

How much emissions might grow and what that would mean for the atmosphere remained highly controversial, however.

Emissions of other chemicals complicated the picture. Advances in stratospheric chemistry showed that future ozone loss depended not just on CFCs, but also on emissions

of several other gases, including carbon dioxide, methane, and nitrous oxide. But the

knowledge and computing capacity to credibly model interactions among all these pollutants only began to appear in the early 1980s. In 1984, a major scientific assessment

conducted the first standardized comparison of multiple stratospheric models using a

few simple scenarios of emissions trends for CFCs and other chemicals. This exercise

had the striking result that under a wide range of trends in other emissions, constant

CFC emissions would lead to only very small ozone losses, while CFC growth above

about 1 percent per year would lead to large losses. 

This result, together with resumed growth in CFC production, had a powerful effect in

breaking the deadlock in international negotiations that had persisted since the mid1970s. Although not the only factor that mattered, this result was crucial in persuading

long-standing opponents of CFC controls to accept limits on their future growth. This

decisively shifted the agenda for the subsequent negotiations that in 1987 yielded agreement on the Montreal Protocol, which cut CFCs by 50 percent. 

In this debate, scenarios used in model-based projections of ozone loss identified divergent trends in future risk that were robust to a wide range of assumptions about

trends in other emissions over which there was disagreement. By parsing projected futures into high-risk and low-risk cases, scenarios served to coordinate and simplify a

policy debate and so help to focus an agenda for collective decision-making.

BOX 4.4. Scenarios of Ozone Depletion in International Policy-making166
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Global-Change Scenarios - Their Development and Use

The insurance and reinsurance industries face large financial risks from climate change.

These are present in many business lines, but the clearest risk is in insurance for property damage from weather-related events, especially windstorms and floods. 

In the past two decades, weather-related insurance losses have increased rapidly. By

some estimates losses have doubled, even controlling for population and insured value

– a much faster increase than that in losses from non-weather events. Climate change

is likely to increase insurance risks in multiple ways, increasing the frequency and severity of loss events and also their correlation. Historically based pricing, which is often required by regulations or market conditions, can compound insurers’ vulnerability by

preventing them from anticipating and adapting to a changed risk environment.

Insurance companies do not use scenarios of future climate change in pricing decisions,

because property and casualty contracts are written for short periods, usually one year.

Since 1992’s Hurricane Andrew, these have mostly been priced using historically based

Catastrophic Event Risk Models (Cat models). These estimate losses using a simulated

distribution of storm conditions based on historical experience, together with estimates

of the durability of insured property. While future climate change poses no risk for

these short-term pricing decisions, insurers are concerned that climate change may already have invalidated the historical distributions on which these models are based, by

increasing either the probability of severe events or the correlation among them.

Two published exercises have used climate-change scenarios to explore longer-term

risks to the insurance industry. The first, conducted for the Association of British Insurers in June 2005, examined potential impacts of climate change on the costs of extreme weather events (both insured and total economic costs) under the six SRES

marker scenarios, as well as IS92a and CO2 stabilization at 550 ppm. The analysis 

calculated changes in losses due to US hurricanes, Japanese typhoons, and European

windstorms.

The second scenario exercise, conducted by Harvard Medical School researchers with

sponsorship by Swiss Re and the United Nations Development Program, used two scenarios of 21st-century climate change to examine potential impacts on human and

ecosystem health, and associated economic costs, not limited to the insurance industry.

The two climate scenarios both assumed CO2 doubling by approximately mid-century,

one with continued incremental climate changes and one with hypothesized nonlinear

impacts and abrupt events. The exercise examined potential changes in infectious and

water-borne diseases, asthma, agricultural productivity, marine ecosystems, freshwater

availability, and natural disasters (including heat waves and floods). The analysis was based

primarily on qualitative judgments.

The first scenario showed increased property losses and business interruptions relative

to recent trends, emergence of new types of health-related losses, and increasing difficulty in underwriting. The second scenario was qualitatively similar but more severe, with

substantial increases in both average losses and variability leading to large premium increases and withdrawal of insurers from many markets, particularly along coastlines. As

many insurance firms succumbed to mounting losses, those remaining established strict

limits on coverage, shifting more exposure back to individuals and businesses.

Neither of these exercises was connected to any specific, near-term business decision

faced by insurance companies. Both could serve longer-term decision-making, however,

including planning for reserve accumulation, providing supporting analysis for advocating mitigation and adaptation policies, and supporting changed regulations to allow more

flexible pricing of risks experiencing long-term increases. Such exercises can also serve

to inform firms’ long-term risk-avoidance strategies, including decisions to exit certain

areas of business.

BOX4.2.2. Climate-Change Scenarios for the Insurance Industry
168 www.nwcouncil.org/energy/powerplan/plan.

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In conjunction with the US National Assessment, researchers at the University of Washington studied climate impacts on the Columbia River system, which is the primary

source of energy and irrigation water for the Northwest and one of the most intensively

managed river systems in the world.167 The project examined the response of annual and

seasonal flows both to existing patterns of climate variability – the El Niño Southern Oscillation (ENSO) and the Pacific Decodal Oscillation (PDO) – and to projected 21st century climate change. 

The study projected climate change through 2050 using eight climate models driven by

one emissions scenario (1 percent per year CO2 concentration increase), which on average projected 2.3°C regional warming by the 2040s with precipitation increases of 10

percent in winter and a few percent in summer. In the Columbia, these changes are

projected to increase flows in winter (because there is more winter precipitation and

more of it falls as rain) and to decrease flows in summer (because there is less snowpack and it melts earlier in the spring). The impact of summer decreases is likely to be

substantially more serious than that of winter increases. Because the Columbia is a

snowmelt-dominated system, winter flows could double or even triple and remain below

the present spring peak.

Assessing the impacts of these flow changes requires assumptions about water demands

and system management. The study used a reservoir operations model that calculated

the combined effects of flow changes and alternative system-operation rules on the reliability of different water-management objectives, such as electrical generation, flood

control, irrigation supply, and preserving flows for salmon. Under historical climate variability, all objectives can achieve high reliability in high-flow years (i.e., in the cool phase

of ENSO or PDO), but conflict between them occurs in low-flow (warm) years, when

only one top-priority objective can be maintained at or near 100 percent reliability and

other uses suffer substantial risks of shortfall. Different operating rules distribute this

risk among uses. 

Under the projected climate and flows of the 2040s, this model showed a pattern of

competition between uses similar but additional to what already prevails in low-flow

years, suggesting increases in already sharp conflict among uses over flow allocations.

One objective could be maintained near full reliability, but other uses suffered reliability

losses up to 10 percent from the changed climate, in addition to effects of continued climate variability. 

In this analysis, scenarios helped to illustrate interactions between management decisions

and climate change and variability, and to explore opportunities and limits for adaptation

through management changes alone, with no change in infrastructure or larger-scale

policies. This analysis has not been incorporated into any operational decisions, but has

been integrated into the Fifth Conservation Plan issued by the Northwest Power and

Conservation Council.168 More detailed assessment of climate-change impacts would require extending this analysis to include projected changes in water demands, both

through direct climate effects and through scenarios of regional economic and population growth, allowing a more realistic assessment of potential effects of new water-management investments and changes in large-scale policies to alter water demand, balance

competing uses, or improve coordination among the multiple organizations involved in

managing the river system.

BOX 4.6. Scenarios of Climate Impacts in the Columbia River Basin

167 Mote et al. 2003, Payne et al. 2004.
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Global-Change Scenarios - Their Development and Use

4.3. THE PROCESS OF

DEVELOPING SCENARIOS:

EXPERT-STAKEHOLDER

INTERACTIONS 

Scenario exercises are collaborative activities

that need to be managed. As Section 1 discussed, managing a scenario exercise includes

deciding who participates, what jobs they are

assigned and how these jobs fit together, how

disagreements are resolved, and how much time

and money are dedicated to the exercise. These

matters can be decisive for the success of an exercise. For some of them, the nature of challenges and tradeoffs they pose are fairly

obvious. For example, scenario exercises need

enough time to build a team, research scenario

components, consult with users, and disseminate results, but often too little time is available,

so various compromises must be made. Adding

participants expands the expertise and the range

of views represented, but increases the time

needed for team building and internal communication. Delegating parts of the exercise to

smaller groups can overcome this tradeoff, but

can introduce coordination problems and inconsistencies among groups. Accepting external direction on scenario exercises increases the

chance that decision-makers will take the scenarios seriously, but also increases the risk that

they are seen as biased or simply reflect conventional wisdom. These issues pose various

challenges, but the challenges are not unique to

scenario exercises.

The more central process problems for scenarios concern the relationship between experts

and stakeholders in the design, creation, evaluation, and application of scenarios. There has

been substantial experience and research in

processes for involving stakeholders in environmental decisions, in the United States and

other regions.169 In the most well-established

areas of scenario use – e.g., strategic planning

for corporations or other organizations, and military and security planning – it is widely understood that there should be close, intensive

collaboration between developers and users in

the production, revision, and application of scenarios. While high-level decision-makers are

not usually involved in the detailed work of scenario construction, they or their surrogates may

be intensively involved in problem definition,

identification and elaboration of key uncertainties, large-scale scenario design, evaluation and

criticism of scenario outputs, and deliberation

over lessons and implications. Their level of involvement must be high for results to be useful,

particularly if a major purpose of the exercise

is to challenge decision-makers’ assumptions

and promote creative thinking.

In these areas, scenarios typically serve a clearly

identified, relatively small and homogeneous set

of users who have some degree of agreement on

what values they are trying to advance, what issues are relevant, and what choices are feasible,

acceptable, and within their power and authority. This is most clearly the case when scenarios are developed for a single organization, but

also applies to scenario exercises for larger

groups that are sufficiently homogeneous in

their interests and perspectives, e.g., scenarios

for property and casualty insurers, for organized

labor in the United States, or for European environmental groups. In such context, the problems of deciding participation are likely to be

manageable.

Intensive user involvement has also been advocated in developing scenarios for climate

change. This is obviously correct when climatechange scenario exercises serve specific, clearly

identified user groups. The strongest examples

are scenarios to support narrowly targeted assessments of impacts and adaptation in particular industries, resources, or regions, e.g.,

scenarios for coastal managers considering the

establishment or revision of setback lines for

coastal-zone construction as sea level rises,170

for rangeland managers considering the purchase of conservation lands or easements for the

purpose of providing migration corridors, or for

insurance and reinsurance firms examining the

nature of climate-change risks they may face

and potential responses. In such cases, intensive participation of users is relatively easy to

achieve and provides access to valuable expertise and assurance of practical utility. 

169 Chess and Purcell 1999; Gregory and McDaniels

2005; Holling 1978; NRC 1996, 2005; Renn et al.

1995. 170 McLean et al. 2001.

Managing a scenario

exercise includes

deciding who

participates, what jobs

they are assigned and

how these jobs fit

together, how

disagreements are

resolved, and how

much time and money

are devoted to the

exercise. These matters

can be decisive for the

success of an exercise.
171 CCSP 2003:112.

172 See, e.g., Envision Sustainability Tools 1999, Rothman et al. 2003, Stockholm Environment Institute

1999.

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But climate-change scenarios typically serve

larger and more diverse sets of users and stakeholders. This is especially true for scenarios

produced in large-scale, official assessments

such as the IPCC or US National Assessment.

Climate-change stakeholders – defined by the

CCSP as “individuals or groups whose interests

(financial, cultural, value-based, or other) are

affected by climate variability, climate change,

or options for adapting to or mitigating these

phenomena”171 – are an enormous group, diverse in their interests and responsibilities.

Even when the set of all potential users is numerous and diverse, there may be some types of

users who are clearly identified – e.g., climate

modelers who need input from emissions scenarios or impact assessors who need input from

climate-change scenarios – and who have highly

specific scenario needs, including such prosaic

factors as data format and resolution. Close

consultation with such users is clearly important, especially when their desires exceed what

scenario developers can confidently provide,

e.g., when climate modelers need emissions

data at fine spatial resolution and for specific

gases or aerosols, which are not readily available from the energy-economic models used for

emissions scenarios. These situations call for

particularly close and sustained consultation, so

the two sides can understand each other’s needs

and capabilities in enough detail to develop

workable resolutions.

Other users, however, may be numerous, diverse

in their disciplinary foundations, methods, and

tools, and not clearly identified. Their information needs may have some commonalities

but substantial differences. They may even have

points of conflicting interest in the construction

and use of scenarios. The general case for

stakeholder involvement remains strong with

such diverse users, especially in the initial design of a scenario exercise, and in the evaluation and refinement of scenarios for relevance,

practicality, and utility. In principle, the required approach is to involve a reasonably diverse and representative group of users and

stakeholders, as well as an appropriate range of

disciplinary and modeling experts, while keeping the size of the scenario team manageable.

But the judgments about participation and representation needed to carry out this approach in

any particular scenario exercise will be complex

and challenging.

Can a scenario process be completely open? In

political settings, some insulation from users

may be needed to insure consistency across participating models and analyses. Whatever approach to stakeholder participation is adopted,

numbers must be kept manageable. Despite recent progress in scenario methods allowing a

substantial increase in the number of participants, there are still practical limits. Although

requirements for expertise external to the core

scenario team increase with scenario complexity, a scenario process is unlikely to work with

a hundred people in the room. A few scenario

processes have engaged much larger numbers

of participants, but these have greatly reduced

the complexity of the scenario-creation process

by limiting it to specifying inputs to a single interactive model, or have involved large numbers

of participants in independent, parallel sessions

interacting with a computer-based model or scenario construction system.172 These tensions between representational realism, participation,

and managerial feasibility pose challenges for

design of processes of representation and consultation in scenario development, on which further progress is needed.

Climate-change

stakeholders are an

enormous group,

diverse in their

interests and

responsibilities.
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Global-Change Scenarios - Their Development and Use

4.4. COMMUNICATION 

OF SCENARIOS

Scenarios related to climate change must be

communicated to multiple audiences, with diverse interests and information needs. Involving users in scenario development can aid

subsequent communication in various ways –

e.g., by ensuring that scenarios are understandable and practically oriented, and helping to disseminating scenarios to their constituencies.

But, in all likelihood, most users to whom scenarios must be communicated did not participate directly in scenario development. 

Although specific needs will vary from case to

case, any communication of scenario-based information to a large, diverse public audience is

likely to require a few common elements. First,

in addition to the scenarios’ content, information should be provided about the process and

reasoning by which the scenarios were developed. This allows users and stakeholders to unTwo programs, one in the United States and one in Europe, developed scenarios in

integrated-assessment models of acid rain to inform policy decisions over sulfur emissions. Among

many other differences, the two programs differed strongly in their approaches to involving stakeholders and in their effectiveness at informing decision-making. 

The US National Acid Precipitation Assessment Program (NAPAP) was created in 1980 as a 10-year

program to study all aspects of acid deposition: emissions, transport and deposition, impacts, and

control strategies.173 Managed by a committee of six government agencies and supported by a fulltime staff office, the program involved roughly 2,000 researchers.174 Although charged to conduct

both scientific research and assessment, NAPAP strongly emphasized research. Its assessment report was opaque on the origin and interpretation of its scenarios, and did not use the scenarios to

integrate across the issue or examine implications of alternative policies. Overall, NAPAP is regarded as having succeeded as a research program, but fallen critically short in providing useful information for decision-making.175

An alternative approach to acid-rain assessment was taken in Europe as part of the policy debates

under the Convention on Long-Range Transboundary Air Pollution (LRTAP). The core of this assessment was a cooperative program to monitor and model acid emissions, transport, deposition,

and impacts. In contrast to NAPAP, this program focused more on assessment than research, being

specifically established to inform the policy process.176 Scientific models of components of the 

acid-rain issue were chosen to contribute to a simplified integration of the problem; scenarios of

emissions and controls were chosen in consultation with officials, in an attempt to replicate the

policy alternatives under consideration.

The culmination of this pursuit of simple, accessible, and policy-relevant analyses was the RAINS

model, developed at the International Institute for Applied Systems Analysis (IIASA) in Austria. As

a result of its flexibility, ease of use, and relevance to policies under consideration, the RAINS model

was used extensively by policy-makers in the negotiation of sulfur-control agreements under the

Convention, and had substantial influence over the controls adopted.177

The contrast in approach and outcome between these two programs suggests the potential value

of close interaction between experts and stakeholders in producing scenarios, at least when the

stakeholders are relatively expert officials responsible for a specific set of decisions. In the European

case, such close interaction helped to ensure the credibility of baseline emissions scenarios and the

relevance of proposed control scenarios, despite the diverse and sometimes contending interests

of the participating officials. The contrast between the two programs also suggests that there can

be significant tradeoffs between scientific and assessment objectives in programs that seek to integrate the two activities.

BOX 4.7. Scenarios in Acid-Rain Assessments: Two Approaches 

173 NAPAP 1982, Herrick 2002.

174 Herrick 2002.

175 Roberts 1991, Cowling 1992, Russell 1992, Miller

1990, Perhac 1991, Rubin 1991.

176 Gough et al. 1998.

177 Levy 1995.
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derstand and critique scenarios, and to determine their own levels of confidence. Second,

scenario developers should identify the uncertainties considered. A particularly important

distinction to communicate clearly is between

scientific uncertainty and scenario uncertainty,

including explicit statements of when and how

scenarios change (e.g., the reduced SO2 projections in the IPCC SRES scenarios), and clear

explanations of the effects of such changes.

Third, related to uncertainty, developers should

acknowledge the unavoidable elements of subjective judgment in developing scenarios, and

be prepared to explain and defend the judgments they made. Fourth, when particular scenarios were constructed to have specific

meanings – e.g., a reference case, a plausible

worst-case, or the exploration of a particular

causal process taken to its extreme – these

should be clearly conveyed. Fifth, if scenario

developers have articulated any indicators of the

confidence they place on scenarios or distributions of associated variables, this information

and any supporting reasoning should also be

made available. 

A communication strategy should attempt to

steer users away from certain common pitfalls,

such as choosing one scenario and treating it as

a highly confident prediction, or taking the

range spanned by a set of scenarios as encompassing all that can possibly happen. An effective strategy of communicating scenarios and

their underlying reasoning can help to engage

users in the process of updating and improving

scenarios. Providing transparency rather than

claiming authoritative status for scenarios is

likely to increase users’ confidence that the scenarios have reasonably represented current

knowledge and key uncertainties. It also provides users with the tools to develop alternative

representations if they are unconvinced.

In large and complex assessments such as the

IPCC and US National Assessment, communication of scenarios and underlying information

both to various groups within the assessment

and to potential outside users poses representational and managerial challenges. Scenario developers have experimented with various visual

techniques for conveying complex information

in vivid and understandable form, including

landscape representations, maps, and pictures,

as well as various graphical and tabular formats.178 In the US National Assessment, climate scenarios and other related information

were provided to participating assessment teams

in several formats (e.g., tabular summaries,

models, graphic representations), through websites backed up with workshop presentations. In

the IPCC, the Task Group on Data and Scenario

Support for Impact and Climate Analysis

(TGICA) was established in 1997 to facilitate

distribution of climate scenario data, model results, and baseline and scenario information on

other environmental and socio-economic conditions, for use in climate impact and adaptation

assessments. Data, scenarios, and supporting

information are distributed over the internet by

the IPCC Data Distribution Center (DDC).179

To compactly communicate uncertainty in climate scenarios, the TGICA and several national

scenario efforts have developed various graphical methods, including scattergrams showing

the range of projected temperature and precipitation changes generated by several climate

models using four SRES marker scenarios, and

comparing these projected changes to estimates

of natural variability.180 In Figure 4.2, each data

point represents one climate-model projection

associated with a given SRES emissions scenario. Efforts to develop similarly compact representations of the distribution of scenarios for

extremes as well as annual and seasonal averages are underway. 

To help users select climate scenarios for

impact assessments, an alternative to summarizing climate-model scenarios in such scattergrams is to combine various climate-model

results using statistical methods to construct explicit probability distributions for important climate variables.181 Figure 4.3 shows one such

method, which assigns weights to model results

178 See, e.g., Svedin and Aniansson 1987.

179 Information on the TGICA is at ipccwg1.ucar.edu/wg1/wg1_tgica.html. The DDC is jointly

operated by the UK Climatic Research Unit and the

Deutsches Klimarechenzentrum, with several mirror

sites around the world. Data are provided via the web

or CD-ROM. All data distributed are in the public domain.

180 Ruosteenoja et al. 2003. 

181 Raisanen and Palmer 2001; Tebaldi et al. 2004, 2005.

Developers should

acknowledge the

unavoidable elements

of subjective judgment

in developing scenarios,

and be prepared to

explain and defend the

judgments they made.
69

Global-Change Scenarios - Their Development and Use

Figure 4.2. Regional

scattergram for

eastern North America,

2040-2069. 

The x-axis shows

temperature changes in °C,

the y-axis precipitation

changes in percent. Each

point shows one model’s

projection under one

emissions scenario. A point’s

color denotes the

corresponding emissions

scenario, its shape the

corresponding model (per

legends in upper left figure).

Ovals show 95 percent

confidence bounds for

natural 30-year climate

variability, calculated from

unforced 1000-year runs of

the models CGCM2 (orange)

and HadCM3 (blue). Points

outside the ellipses indicated

projected climate change

significantly outside the range

of natural variability, most

frequently due to changes in

temperature rather than

precipitation. (Source:

Ruosteenoja et al. 2003.)

Figure 4.3.

Constructed

probability

distributions of modelsimulated temperature

change in 2080-2099 

The x axis shows projected

temperature change in

Eastern North America from

the 1980-1999 historical

average, using 19 climate

models participating in the

IPCC Fourth Assessment

Report driven by the SRES

A2 (red) and B1 (blue)

emissions scenarios. Each

point on the x axis shows the

result from one model. The

curves above the axis show

probability distributions

constructed from these

individual model results.

(Source: Tebaldi et al. 2005.)

1 2 3 4 5 6

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Change in Temperature (deg. C)

Density
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based on their bias in simulating the current climate (smaller biases are assigned higher

weight) and their correspondence with other

model results (outliers are assigned lower

weights). This method compactly communicates multiple model results, clearly conveying

which ones fall at the top and bottom of the distribution (“unlikely to be higher/lower than

this”), and which fall in the middle of the range. 

This current focus on collections and intercomparisons of model-based projections with various emission scenarios represents a new

approach for communicating scenario-driven

model output to users engaged in assessment

and adaptation activities. It has enabled users

to consider a broader range of emission scenarios and climate models than was feasible in the

US National Assessment and previous IPCC assessments. It allows users to consider all available model and scenario combinations to span

the literature, or to select only scenarios that exceed some threshold of interest or fall within

some specified probability range. Future assessments should benefit from this type of

multi-model, multi-scenario approach, which

allows users more effective and informed choice

over scenarios to consider. 

4.5. CONSISTENCY AND

INTEGRATION IN SCENARIOS 

One of the most often stated requirements for

scenarios is that they be “coherent” or “internally consistent.” This is clearly an important

goal. Scenarios usually specify multiple characteristics of an assumed future, whether as

multiple elements of a narrative or multiple

quantitative variables, so these elements should

fit together. Difficulties arise in the pursuit of

such consistency, however, and in some scenario

exercises the pursuit of consistency, together

with the goal that scenarios integrate many

components of a broad issue such as climate

change, may jeopardize the validity and usefulness of the scenarios.

Certain elements of internal consistency in scenarios are unproblematic, such as avoiding

gross contradictions with well known principles

of behavior of biophysical or socio-economic

systems, and not inadvertently moving far outside the bounds of historical experience. Inadvertently implausible assumptions can arise, for

example, when multiple elements of a scenario

are specified without cross-checking; e.g., endyear specifications of a region’s population and

GDP without checking the implied growth rate

in GDP per capita, or specifying energy-related

emissions trajectories without checking what

they imply for resource availability. Avoiding

these pitfalls requires thorough cross-comparisons of related values with each other, of terminal values with implied time-trends in the

intervening period, and of values within and

among regions. Scenario developers should not

always and necessarily avoid extreme or unprecedented outcomes, however. Presenting

extreme or seemingly implausible future conditions intentionally, with an explanation of

how they could in fact arise, can contribute to

several of the major purposes of scenarios, e.g.,

shaking up habitual thinking and broadening

expectations of what future developments 

are plausible. 

But statements about internal consistency in

scenarios usually claim much more than the

mere absence of gross contradictions and inadvertently implausible values. They tend to

claim that the multiple elements of a scenario

are related in a way that reflects reasonable,

well-informed judgments about causal relations,

suggesting that some events or trends are more

likely to occur together, some less. Expressing

the goal as “coherence” rather than “internal

consistency” suggests a higher level of perceived affinity among scenario elements, evoking normative or even aesthetic aspects.

Expressed in probabilistic terms, statements

about internal consistency may be interpreted

as claims that alignments of factors similar to

those in the scenario are more likely than other,

dissimilar alignments. One might, for example,

claim that a scenario with rapid growth in both

the economy and energy use is more internally

consistent than one in which the economy grew

rapidly but energy use did not. But where do

these perceptions of greater or lesser likelihood

come from, and how valid are they? In some

cases a well-founded theory or model might say

that certain outcomes tend to be related. Alternatively, explicit analyses might connect the

claim to underlying assumptions that are open

to scrutiny and criticism. But in the absence of

The current focus on

collections and

intercomparisons of

model-based

projections with

various emissions

scenarios represents a

new approach for

communicating

scenario-driven model

output to users

engaged in assessment

and adaptation

activities.
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Global-Change Scenarios - Their Development and Use

such transparent foundations for judgments of

what scenario conditions are consistent and

what are not, these claims can only rest on more

diffuse judgments by scenario developers, refined and tested through various deliberative

processes – e.g., arguing about the claims,

working through their implications relative to

those of alternative specifications, and identifying additional bodies of research and scholarship that can be brought to bear. 

These difficulties can be compounded when, in

addition to consistency, a goal of scenario “integration” is also pursued (although the precise

meaning of “integrated” can be difficult to ascertain). The integration of a scenario is a function of its complexity or breadth, which is

related to the number of characteristics it jointly

specifies. In global climate-change scenario applications, integration typically refers to including all major elements of the causal chain of

the issue, i.e., multiple dimensions of emissions

and their socio-economic drivers, climate, impacts of climate change, and responses. 

Asking a scenario to be integrated in this way

imposes on the scenario the burden of capturing all relevant elements of the future. Such an

expansive scenario may occasionally be needed

– e.g., for preliminary assessment of a threat for

which no relevant data or current research exists. However, the risks of error, bias, and arbitrariness in such a scenario are greatly increased,

because so much of reality (with whatever unknown causal processes by which it actually operates) is being stuffed into the scenario.

More likely, an integrated scenario would be

constructed by combining exogenous assumptions about some elements with model-calculated values for others. This approach does not

avoid increasing risks of inconsistency and contradiction as a scenario is expanded, particularly

when multiple models are used. Since models

embody specific, quantitative causal relations

among variables, they do not require – or indeed

allow – all variables to be specified. Scenarios

provide only those exogenous inputs that the

model does not produce. These scenario-based

inputs should be consistent with each other, but

to a lesser extent than the precise standard that

defines consistency in a scenario. These exogenous inputs, together with model results, can

jointly comprise a scenario that is generated for

some alternative use.

Consistency problems grow when scenario exercises involve multiple models and attempts

are made to achieve model harmonization.

When scenarios are constructed partly out of

exogenous inputs provided by a scenario (made

consistent as much as possible through qualitative or intuitive causal reasoning) and partly out

of models, multiple models are often used.

Using multiple models in parallel can allow for

more extensive exploration of causal relations,

and helps to characterize uncertainty in scenarios since different models embody different representations of causal processes. It may also

enhance the credibility of the process. But

models of the same broad set of phenomena –

e.g., models of the economy and energy sector

– frequently differ in which variables they require

as exogenous inputs and which ones they calculate endogenously. In this case, some variables

must be specified exogenously for some models,

but are calculated endogenously by others.

This creates various problems for consistency.

In general, when scenario exercises are conducted in this way, some elements are assumed

and others are model-calculated. Attempting to

avoid this poses even more serious problems,

however. It is not usually possible to arbitrarily

perturb the exogenous input variables so all inputs and outputs match across all models, since

such perturbations will influence other variables

in the model. Consequently, avoiding these inconsistencies will require manipulating internal

relationships within models to make their outputs match the specified values, given the common inputs. But such reverse-engineering of

internal model relationships to match specified

outputs, in addition to being exceedingly cumbersome and arbitrary, can corrupt the internal

logic of models, obscure the interpretation and

significance of results, and make it impossible

to use model variation to illuminate uncertainty.

For example, in an exercise to generate

non-intervention scenarios of potential future

emissions, little insight is likely to be gained

from defining scenarios in terms of the resulting

emissions and forcing the different models to

In the absence of

transparent

foundations for

judgments of what

scenario conditions are

consistent and what

are not, claims can only

rest on more diffuse

judgments by scenario

developers, refined and

tested through various

deliberative processes.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

generate these emissions targets.182 It may be

equally fruitless to define scenarios in terms of

GDP and energy consumption trajectories and

to force multiple models to reproduce these.

For this reason, multi-model exercises such as

the Energy Modeling Forum usually seek to

harmonize only a few of the most essential and

commonly used inputs.183 When multiple models are used to generate scenarios, the most useful way to pursue consistency may be to develop

common assumptions for the variables furthest

back in the causal chain, but the wide variation

of model structure can make even this approach

to harmonization challenging.

In addition to consistency within a scenario,

consistency across scenarios within an exercise

also requires attention. Ideally, factors not explicitly recognized as the basis for inter-scenario

differences should be consistent across scenarios. Or alternatively, all bases for differences

between scenarios should be explicitly recognized and stated.

When models are used in a scenario exercise,

significant variation in model structures suggests less mature underlying knowledge, or at

least greater recognition of knowledge gaps,

than when model structures converge and all remaining uncertainty is over exogenous input parameters. For scenarios to provide faithful

representation of present knowledge and uncertainty, this variation should not be suppressed or

concealed. Consequently, when scenarios are defined over variables that include outputs of some

participating models as well as inputs, it is crucial

not to pursue false consistency by forcing models to match the target outputs through manipulation of their internal causal processes. This is

suppressing model uncertainty. 

One preferable alternative would be for the results of scenario exercises involving both exogenous inputs and multiple models to

explicitly distinguish between three classes of

variables: (1) a minimal set, exogenous to all;

(2) those specified exogenously for some models, but generated by others; (3) model outputs,

whose variation reflects partly model and partly

parameter uncertainty. 

An alternative way to use multiple models is to

let each model produce one scenario, as was

done in the selection of the SRES marker scenarios. With this approach, each scenario represents a particular realization of uncertainty

over both exogenous inputs and model structure. But this approach confounds model uncertainty with parameter uncertainty. It may be

preferable to cross exogenous inputs with models to produce a larger number of scenarios from

which subsets can be extracted as needed, perhaps organizing these as a nested hierarchy of

scenarios similar to the SRES: six marker scenarios, 40 SRES scenarios in total, and hundreds of scenarios in the literature review.

There are good reasons to combine narrative

with quantitative approaches, as scenario exercises have increasingly sought to do. But the

connection between qualitative and quantitative

aspects of global-change scenarios has been inadequate, diminishing the usefulness of the exercises due to inconsistencies within each type

of scenario and between the two types. This

problem has partly been due to limited time and

resources, but has also reflected substantive difficulties in linking the two types of scenario,

difficulties that have not been understood or

managed well. Narrative scenarios typically

specify deep structural characteristics like social values and the nature of institutions, which

are associated with structural characteristics of

models such as the determinants of fertility

trends, labor-force participation, savings and investment decisions, and substitutability in the

economy. Consequently, the differences among

alternative narrative scenarios, reflecting different basic assumptions about how the world

works, correspond more closely to variation of

model structure than to variation of parameters.

Better integrating the two approaches will require developing ways to connect narrative scenarios to model structures, rather than merely

to target values for a few variables that models

are then asked to reproduce. This has not hap182 Note that this is not the case if the purpose of scenarios is to explore the implications of specified limits

on future emissions. If an emission constraint is assumed to be imposed by policy, then different models

can be used to explore the implications of that constraint for costs, technologies, and other impacts. In

this case, caution is needed in deciding what other

model variables, if any, should be constrained. 

183 Weyant and Hill 1999.

When multiple models

are used to generate

scenarios, the most

useful way to pursue

consistency may be to

develop common

assumptions for the

variables furthest back

in the causal chain, but

the wide variation of

model structure can

make even this

approach to

harmonization

challenging.
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Global-Change Scenarios - Their Development and Use

pened because scenario exercises have not had

the capability or resources to direct new model

development, or to induce modelers to undertake substantial structural changes to their models. This would require substantial efforts,

including getting modelers to interact with scenario exercises in a new way, but might hold

more promise for allowing scenarios to usefully

inform discussions about large-scale policy

choices for mitigation and adaptation.

4.6. TREATMENT OF

UNCERTAINTY IN SCENARIOS

Representing and communicating uncertainty is

perhaps the most fundamental purpose of scenarios. This section discusses how scenarios

represent uncertainties, how these methods connect scenario exercises to simpler formal exercises in the analysis of decisions under

uncertainty, and what challenges are posed in

how uncertainty is represented. It also addresses several important debates in the treatment of uncertainties.

In most scenario exercises, uncertainty is represented not in a single scenario, but in variation

across several scenarios considered together.184

The choices to be made in deciding how to represent uncertainty include the following:

• What characteristics are varied 

• By how much these characteristics are varied, separately and together (e.g., should extreme values of multiple characteristics be

combined, or extremes of some combined

with the middle cases of others?)

• How many scenarios to create and consider

together

• What description, documentation, or other

information is attached – including whether

and how specifically measures of likelihood

are assigned.

4.6.1. Uncertainty in simple

quantitative projections: 

basic approaches

How these choices are made and their implications for scenario use and effectiveness are

closely related to the large-scale decisions in designing a scenario exercise outlined in Section

2.1. In particular, the role of uncertainty in a

scenario exercise is strongly linked to scenario

complexity, richness, and use. In the simplest

case, a scenario exercise may be dominated by

a single quantitative variable, so all uncertainty

could be represented by alternative future levels or time-paths of that variable. This case is so

simple that many scholars and practitioners

argue it should not be considered a scenario at

all.185 Still, even this simple and extreme case

raises significant issues. We begin here and

then move to more complex cases. 

If we also assume that the probability distribution is known, the situation reduces to a formal

exercise in analysis of decision-making under

uncertainty. Given a known set of choices and

outcomes of each choice under each uncertain

outcome, alternative choices can be evaluated

by formal methods such as seeking the best outcome on average or under some risk-averse valuation scheme, or seeking robust strategies. This

decision-analytic approach can be extended to

situations of a few uncertain variables with a

known joint distribution, multiple decisionmakers who evaluate outcomes differently, or

(with somewhat more difficulty) decision makers with different probability distributions.

Further relaxation of these simplifying assumptions moves us toward activities that are more

widely recognized as scenario exercises. First,

if a scenario exercise is addressed to more than

just a few decision-makers with known choice

sets and outcome valuations, scenarios can no

longer simply be inputs to an analytic exercise,

but rather become descriptions of potential future states that must be communicated directly

or indirectly to decision-makers for their reflection and deliberation. Second, if distributions

of important quantities are unknown, it is necessary to exercise judgment regarding how to 184 When a scenario exercise uses just one scenario, this

usually presents some specific threat or challenge

posed to existing procedures or decision-makers. In

these cases, uncertainty is still represented by differences among scenarios, but the single scenario is implicitly contrasted to the status quo. 

185 E.g., Wack (1985a:74) states that such a scenario is

just “quantification of a clearly recognized uncertainty.”

Representing and

communicating

uncertainty is perhaps

the most fundamental

purpose of scenarios.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

draw on relevant knowledge to construct and

describe alternative future values of the quantities, and how to represent these values to users

with a manageable number of scenarios.

Since scenarios describe future conditions, the

distributions of quantities in scenarios cannot

be known in the same sense that the distribution

of current characteristics – e.g., the November

daily high temperature at O’Hare Airport – can

be known through repeated observations. Probabilistic statements about future conditions always incorporate elements of subjective

judgment. Many forms of current knowledge –

including data, models, and expert judgments –

are relevant to forming these judgments about

future conditions. In constructing scenarios of

population growth, for example, the distribution

of observed past growth rates can be used to

construct a range or distribution of plausible future values. But while scenarios can draw on,

and be made conditional on, such knowledge,

this does not overcome their unavoidable reliance on subjective judgments as well. 

Scenarios can also be based on model representations of knowledge of causal processes.

For example, instead of simply extrapolating

past population growth rates, one could use a

demographic model that represents trends in

fertility rates, lifespan, and migration to calculate a resultant population trend. Formal modeling can represent the structural relationships

transparently, reducing the risk of generating inconsistent projections. Structural models can

possibly also perform better in extrapolating to

conditions beyond the observed range of behavior. Because models represent causal relationships among multiple variables, these

models can extend the range of current and historical data that are relevant to projections, although this may result in an expansion of data

needs. Models can also help characterize uncertainty in future quantities of interest, by allowing the uncertainty to be attributed to input

parameters – explored through sensitivity analysis or simulation techniques such as Monte

Carlo – or to model structure.

Estimating output distributions based on assumed

distributions of uncertain input parameters does

not capture all uncertainty of importance for 

assessment and decision-making. The input

probability distributions are not known with

certainty, nor are the structural assumptions that

determine the mapping of inputs onto outputs

within any particular model. Uncertainty analysis can embrace this additional level of uncertainty, sometimes called “meta-uncertainty,” by

stepping up one more level of abstraction –

considering not just uncertain quantities, but

uncertainty about their uncertainty, or alternatively, probability distributions over probability

distributions of unknown quantities. Methods

to represent and process such meta-uncertainty

mirror those used for first-order uncertainty.

This is an active area of research, but its importance for assessment methods and their application is unclear. This level of abstraction

increases the difficulty of communicating scenarios and their underlying reasoning transparently and comprehensibly to non-specialists.

Moreover, since any step of analysis represents

an act of potentially fallible judgment, taking

the step to meta-uncertainty still does not capture all possible uncertainty. It is not clear

whether, for purposes of constructing and using

scenarios, the explicit separation of uncertainty

in outcomes from uncertainty in probability distributions brings more benefit than could be

gained from simple heuristic guidance to assume distributions are wider than initially seems

necessary. 

A major risk in all scenarios is subjective bias,

which can be reduced but not eliminated

through use of existing data and formal modeling. Judgment is an essential element in constructing scenarios, both to apply relevant data

and models when these are available, and to

build future descriptions using less formal

methods when they are not. The expert judgments supporting such less formal projections

may be better founded than mere uninformed

speculation, since there is typically much relevant knowledge available beyond what is explicitly captured in present datasets and models. 

Approaches to developing expert-judgment

based projections vary widely in their structure

and formality, from simply asking one or more

experts to state their best estimate of some unknown quantity, to highly structured elicitation

exercises that provide multiple cross-checked

Probabilistic

statements about

future conditions

always incorporate

elements of subjective

judgment. Many

forms of current

knowledge – including

data, models, and

expert judgments –

are relevant to

forming these

judgments about

future conditions.
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Global-Change Scenarios - Their Development and Use

estimates of the same quantity.186 Such methods must attend to risks of overconfidence and

bias, which are well documented in experts as

well as laypeople. Carefully designed elicitation protocols can reduce the effects of such biases, e.g., by prompting experts to broaden their

estimates of uncertain quantities, but cannot

eliminate them.187 An additional challenge to

these methods is that there is no generally accepted method for selecting or aggregating estimates from multiple experts. 

4.6.2. How many scenarios, over

what range?

In communications of scenarios, limited time,

resources, and attention usually require that

only a few discrete values or time-paths are

specified, not a complete distribution. Scenario

developers must decide how many scenarios to

provide and how to space them. 

How many scenarios to provide rests on a judgment of the value provided by each additional

point from the underlying distribution relative

to the burden of producing and using each new

scenario. If the use made of each scenario is expensive – e.g., consuming large quantities of

time of busy senior people, or running a large

model – then the number of scenarios that can

be adequately treated may be very few. The

1992 IPCC scenario exercise provided six separate scenarios, of which nearly all subsequent

analyses used just one or two. Of the 40 scenarios

produced by the SRES process, only 6 (initially 4)

were highlighted as “marker” scenarios, while

most subsequent analyses used just 2 or 3.188

Deciding how many scenarios to provide also

involves some element of attempting to avoid

predictable errors in their use. While the most

obvious and frequent choice in providing scenarios of a quantitative variable has been to provide three – one high, one low, and one in the

middle – it has been widely noted that this practice runs the risk that users will ignore the top

and bottom, pick the middle, and treat it as a

highly confident projection, suppressing the uncertainty that scenario developers tried to communicate by providing, and carefully spacing,

three scenarios. The same risk applies to any

odd number of scenarios, leading many developers of quantitative scenarios to the informal

guideline that the number provided should always be even, so there is no “middle” scenario

that users can inappropriately fix on.

More specific guidance on the appropriate number and range of scenarios must reflect both 

scenario developers’ sense of the underlying distribution from which scenarios are drawn, and

their intended use. One must consider whether

departures in both directions from the middle are

of similar importance, or whether only departures

in one direction need be represented. For example, one might judge that in an assessment of impacts of climate change a scenario drawn from

the lower tail of potential climate change is likely

to provide little substantive insight, since in most

cases the impacts of a small-change scenario are

predictably small. 

One must also consider how far a set of scenarios should extend toward including extreme or

unlikely futures. In estimating unknown quantities, many fields of empirical research draw

intervals to capture from 90 percent to 99 percent probability, but in constructing scenarios

to inform decisions there may be good reasons

to consider more extreme and less likely possibilities, whether these likelihood judgments are

expressed quantitatively or qualitatively. Assessments and policies in both regulation of

health and safety risks and national security, for

example, routinely focus on high-consequence

risks that are judged much less than 1 percent

likely. Similarly for global environmental

change, low-probability risks might need to be

considered if their consequences or their effects

on preferred decisions are large enough.

It is often suggested that a set of scenarios

should “span the literature” of prior scenarios

or projections of the same quantities. However,

there may be good reasons for a wider or different range, or even a narrower range – although developers should be cautious about a

set of scenarios that spans a much narrower

range than published estimates of the same

quantities. A published scenario may have been

186 Morgan and Keith 1995.

187 Tversky and Kahnemann 1974, Wallsten and Whitfield 1986.

188 Initially A2 and B2 were most widely used. More recent work has used A2 and B1, sometimes with A1B.

Similarly for global

environmental change,

low-probability risks

might need to be

considered if their

consequences or their

effects on preferred

decisions are large

enough.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

constructed to serve various purposes other than

providing an independent new estimate of a

quantity of interest. Previous scenarios developed to serve some particular purpose may or

may not be relevant to a new scenario exercise,

depending on the relationship between their intended purposes. Moreover, previously published scenarios can be highly self-referential,

since many published analyses use prominent

pre-existing scenarios as inputs to a new study,

or examine a new model by forcing it to reproduce some pre-existing scenario. For all these

reasons, previously published scenarios are better regarded as one input to the judgment of developers of new scenarios than an authoritative

picture of present knowledge that new scenarios

must follow.

4.6.3. Bifurcations and major 

state changes

While many uncertainties may be treated as a

continuous range of possible values, some uncertainties may capture large-scale bifurcations

or abrupt changes. For climate change, potential abrupt changes include melting of major

continental ice sheets or shifts to some new

mode of ocean circulation.189 Large-scale bifurcations may also arise from breakthroughs in

energy technology. Such possibilities are typically not captured in either historical data (because they are by assumption novel), or models

(because they would represent a change in the

causal structure represented in models).

Abrupt changes can pose particular challenges

for deciding the number and range of scenarios

to include in an assessment or decision-support

exercise, either because their consequences are

so extreme or because they would fundamentally change our understanding of how the system operates. The decision of whether and how

to consider these uncertainties consequently

turns on the balance between their probability

– which is believed to be low but not well characterized – and their high consequences, which

must be evaluated relative to the scenarios’ intended use. This will be a particularly difficult

choice when only a few scenarios are being generated. For example, in a coastal impacts assessment the enormous consequences of the

difference between a half-meter and a fivemeter sea level rise over this century – and the

well-identified mechanism by which such a

large rise could occur – may suggest the importance of explicitly considering a scenario involving loss of one of the major continental ice

masses. But including such a scenario runs the

risk that users will assign it a much higher probability than is appropriate, either because of its

vividness and extremity or because they presume that developers’ decision to include the

scenario meant that they assigned high probability to it. When such a scenario is included,

scenario developers have a serious responsibility to communicate, loudly and consistently, its

different status.

A further challenge in representing large-scale

or discrete changes in scenarios is that there

might be many such possibilities, all of them

high-consequence but believed to be unlikely.

Including any particular one may mislead both

by exaggerating its likelihood and by strengthening users’ tendency to ignore others, when

these all represent “unknown unknowns” that

should receive some consideration. The more

there are, the more the right approach might be

to shift all scenarios further out to reflect the

various mechanisms by which conventional understanding may under-represent the tail of the

distribution, rather than highlighting any particular abrupt-change mechanism by giving it a

scenario of its own. 

4.6.4. Uncertainty in multivariate 

or qualitative scenarios

As the characterization of future conditions

within scenarios grows more complex, so does

the process of representing uncertainty within

them. While many of the issues discussed above

in the simplified context of scenarios on a single

variable also apply to multi-dimensional scenarios, several additional issues arise.

The most basic of these is that with multiple 

dimensions of variation in scenarios, it is necessary to decide which uncertainties are represented. Even when scenarios include only

multiple quantitative variables, it is no longer

possible for a few scenarios to span all corners

of the joint distribution of these variables.

Rather, they must combine variations in ways 189 NRC 2002.

Previously published

scenarios are better

regarded as one input

to the judgment of

developers of new

scenarios than an

authoritative picture

of present knowledge

that new scenarios

must follow.
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Global-Change Scenarios - Their Development and Use

that are most illuminating and important for the

purpose at hand, massively reducing the dimensionality of the problem to make it intelligible

for users. In addition, increasingly detailed and

realistic scenarios often specify characteristics

that are qualitative, or described less precisely

than cardinal variables. For example, alternative scenarios might specify that current trends

of globalization increase, stagnate, or reverse,

or that decision-making capacity on climate

change increases or decreases. Such characteristics may be judged crucial to include because they may be among the most important

drivers of preferred choices or consequences

of concern.

Scenarios of this kind pose substantial further

challenges in representing uncertainty and interpreting its meaning. Relative to the simple

quantitative scenarios we have considered up to

this point, these lie in a much higher dimensionality space of future possibilities; they may

not lie in any ordinal relationship to each other;

and they may include characteristics whose definitional boundaries are not precisely specified.

Defining a small set of scenarios to reasonably

span the most important uncertainties is consequently even more difficult than for simple

quantitative scenarios.

The approach most widely proposed to represent key uncertainties in such scenarios is to

seek underlying structural uncertainties that satisfy two conditions: they appear to be most important in influencing outcomes of concern or

relevant decisions; and they are linked with variation in many other factors. These underlying

uncertainties can be simple discrete states such

as peace or war, prosperity or stagnation; or, as

in several major global environmental scenarios, they can be deeper societal trends, such as

more or less globalization or shifts in societal

values toward greater environmental concern,

from which variation in many factors is assumed to follow.

This approach, formalized in the Shell scenarios

method,190 involves two steps: first identifying a

small number of fundamental uncertainties and

a small set of alternative realizations of each;

and then elaborating additional future characteristics associated with each realization

through both qualitative reasoning to fill in a

narrative, and assembly of data and model results to build a parallel quantitative description

to the extent this is judged useful. Repeated,

critical iteration between the qualitative and

quantitative elements is conducted, to bring additional relevant knowledge and expertise to

bear and to check for consistency. 

Even rich narrative multivariate scenarios must

imply certain claims of likelihood. Every scenario included must be deemed likely enough

to merit the resources and attention spent on developing and analyzing it. This applies even to

extreme-event scenarios that are intentionally

constructed to capture the low-probability tail

of the distribution, since even they must be perceived likely enough to merit time and attention

given their severity. Since users would reject

any scenario that they persistently judged too

implausible to consider, when decision-makers

find a scenario exercise useful, it validates developers’ judgment that each scenario was

likely enough to consider. 

In a purely mathematical sense, any one specific

rich multivariate scenario must be arbitrary and

of vanishingly small probability. There are,

however, ways in which it may be reasonable to

assign non-zero probabilities to multivariate

scenarios. First, if scenario designers in fact

succeed at identifying a few deep structural uncertainties that strongly condition outcomes on

many other characteristics in a scenario, then

the richness of a scenario description need not

imply that it is vanishingly unlikely. Whether

this is true or not is a judgment to be made by

scenario developers and users in each application. If they are sufficiently careful in their development and critical examination of

scenarios, their judgment may well be correct.

But there will often be no way to further test

these judgments, so it is of course possible that

the proliferation of additional detail in scenarios

– even detail that developers and users recognize is crucial for determining valued outcomes

and preferred choices – is arbitrary or erroneous.

A second way in which rich, detailed scenarios

may be judged sufficiently likely to consider

concerns the precision with which scenario

characteristics are specified. In rich multivari- 190 Shell International 2003. 

The approach most

widely proposed to

represent key

uncertainties in

scenarios is to seek

underlying structural

uncertainties that

satisfy two conditions:

they appear to be

most important in

influencing outcomes

of concern, and they

are linked with

variation in many

other factors.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

ate scenarios, many characteristics are often

specified diffusely: economic growth may be

merely “high” or “low,” rather than being stated

as a particular value. Even when a characteristic is stated quantitatively, its particular value

may be treated as merely illustrative of a range

of similar values; e.g., annual GDP growth

might be set at 4 percent because a user needs a

numerical model input, but it is understood to

represent a broad range of similar values that all

count as “high” growth. Interpreted in this way,

a multivariate description may remain likely

enough to merit examination – and indeed, a

modest number of scenarios may exhaust the set

of potential futures that matter for the issue at

hand. Here one is not assigning likelihood to

the precise numerical assumptions used to flesh

out the details of a scenario, but rather to a thick

slice of future conditions that resemble that scenario more than the other scenarios in the set.

4.6.5 The debate 

over quantifying probabilities

A major debate in the use of global-change scenarios has concerned whether or not to specify

quantitative probabilities associated with scenarios. This debate is central to the meaning

and use of scenarios, and has been sharpest over

the IPCC’s SRES scenarios. Developers of the

SRES scenarios decided at the outset of their

process that they would make no attempt to assign probabilities to scenarios, in part because

they were adopting the Shell approach of developing scenarios from storylines, in which

quantitative probabilities are usually avoided.

After the scenarios were published, several critics argued that since the most prominent and

important outputs were the projections of emissions under the six marker scenarios, it was natural – and essential for development of rational

climate-change policy – to describe the distribution of emissions in probabilistic terms. For

example, how likely are 2100 emissions to lie

above the 30 GtC of scenario A2 or below the

5.2 GtC of B1? Should the range spanned by

all 40 SRES scenarios be understood to comprise 90 percent of all probability? 99 percent?

All of it? 

Developers of the SRES scenarios stood by

their initial decision not to quantify probabilities. Since the controversy only became prominent long after the decision had been made by a

writing team no longer in operation, it would

have been virtually impossible for the group to

retrospectively assign such probabilities. But

rather than rely on this argument of managerial

infeasibility alone, SRES organizers offered a

vigorous substantive defense of their initial decision. This defense relied in part on the statement that the six marker scenarios were all

“equally sound,” without providing any guidance regarding what this meant other than explicitly denying that it meant “equally likely.”

Describing each of the six marker scenarios as

“equally sound” represents the entirely reasonable case that in the developers’ judgment these

all needed to be considered seriously – without

making any further judgment as to their likelihood. While clearly frustrating to those wanting

to use the scenarios as a basis for policy, the result is entirely consistent with the IPCC mandate to do assessment, but not to reach policy

conclusions. 

However, this debate will continue; it rests in

part on different conceptions of the meaning

and typical contents of a scenario. The simpler

the contents of scenarios, the more readily they

lend themselves to explicit quantification of

probabilities. When scenarios consist only of

alternative time-paths of a single quantitative

variable, or one such variable is of predominant

importance, it is straightforward and sensible to

understand the intervals between those timepaths to have probabilities associated with them

and there are several strong arguments for being

explicit about these probabilities. First, stating

probabilities allows comparative risk assessment between scenarios and explicit exploration

of risk-reducing strategies.191 Second, sophisticated decision-makers whose choices depend

on uncertainty in these variables need probability information about possible values, not just a

set of alternative values, to evaluate choices –

whether their approach to decision-making is

based on expected values, risk-aversion, seeking robust strategies, or some other approach.

Finally, when such scenarios are presented without probability judgments, users may attach

their own, often via simple heuristic devices that

may misrepresent the developers’ understanding. For example, many subsequent users of the

191 Webster 2003.

The simpler the

contents of

scenarios, the

more readily they

lend themselves to

explicit

quantification of

probabilities.
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Global-Change Scenarios - Their Development and Use

SRES emissions scenarios have simply assumed

the probabilities they needed to conduct further

assessments, using such simple devices as

counting scenarios or assuming a uniform distribution over the entire range.

Opponents of explicit quantification of probabilities do not dispute that such probabilities can

coherently be assigned to simple scenarios in

one or two quantitative variables. Rather, they

raise principled objections to the appropriateness of attempting to quantify probabilities for

more complex scenarios, particularly those involving socio-economic conditions, as well as

practical objections to the use of probabilities

even in the case of simple quantitative scenarios. 

Many researchers are less comfortable using

probabilities for complex scenarios that include

explicit socio-economic elements than for uncertainties that are purely bio-physical, such as

probabilities of different rates of climate change,

conditional on a particular emissions scenario.

Four main arguments are advanced against the

use of probabilities for such scenarios. 

First, some argue that the large multivariate

space of possibilities from which such scenarios

are drawn, and the vague and qualitative way

that some scenario characteristics are specified,

make it impossible to coherently define the

boundaries of the outcome space to which probabilities are being assigned. There is no way to

clearly define the interval “between” one scenario and another; and if probability is attributed to a slice of possibilities around each

scenario rather than to the intervals between

them, is it not possible to define clearly the

boundaries of the slice to which the probability

is assigned. To the extent that scenarios describe different types of worlds, which are distinguished from each other by alternative

resolution of a few key uncertainties – e.g., high

or low growth, high or low globalization –

where the location of the boundary is not precisely specified, it may be difficult to create a

shared understanding of these boundaries between users and creators. But if assigning a precise numerical probability is judged too difficult

in these cases, less precise descriptions such as

“highly likely,” “more likely,” “less likely,” or

“roughly equal” could be assigned. In some applications where scenarios are intended to capture all the uncertainty of concern to the decision-maker – i.e., scenarios are intended to be

mutually exclusive and collectively exhaustive –

there may even be a reasonable basis for numerical probability.

The second argument for rejecting probabilistic

description of socio-economic conditions is

based on “reflexivity” – the proposition that

scenarios may influence the behavior or decisions driving the scenarios, so probability judgments about scenarios could reflect back on

themselves, becoming either “self-fulfilling” or

(more plausibly) “self-denying” prophecies.

Section 4.1 addresses this issue in some detail,

in particular in the distinction between how to

treat mitigation decisions in scenarios to inform

mitigation decisions and impacts or adaptationrelated decisions. We might only add here that

for scenarios of global emissions, reflexivity

could only operate if both the influence of scenario judgments on their users’ behavior and the

influence of their users’ behavior on global

emissions were extremely strong. Moreover, it

is not evident why scenarios with explicit likelihood judgments should raise this concern,

while scenarios presented without such judgments – which also presume some claims of

plausibility or likelihood – should not. Concern

about reflexivity appears more serious for scenarios prepared in close consultation with national mitigation policy-makers, and it is for this

reason (among others) that we judge explicit attempts to assign probabilities less valuable for

scenarios prepared in such settings.

Third, some argue that it should not be scenario

developers or experts who make judgments

about likelihood of alternative scenarios, but

users – particularly when scenarios are used to

inform high-stakes public decisions. But this

depends on the details of the content and use of

scenarios. For some scenario elements in some

settings, particularly use of scenarios to advise

specific policy decisions, the scenario users

may be as expert as the developers in associated

uncertainties and risks, or more so. But in such

settings, the use of scenarios normally highlights critical examination of these assumptions,

and users have the knowledge and assertiveness

to probe, critique, modify, or reject scenario elements that they find weak, including probability judgments. When scenarios are produced to

Concern about

reflexivity appears

more serious for

scenarios prepared in

close consultation

with national

mitigation policymakers, and it is for

this reason (among

others) that we judge

explicit attempts to

assign probabilities

less valuable for

scenarios prepared in

such settings.
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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

serve many diverse users and consequently cannot rely on intensive interplay with representative, well-informed, and challenging users,

scenario developers frequently have the best access to available knowledge relevant to forming

probability judgments. Not making these judgments explicit is withholding information that

users may need to understand and interpret the

scenarios. If scenarios and their underlying reasoning and assumptions are presented clearly

enough, users can make informed choices

whether or not to use probability judgments that

are provided. 

Finally, some argue that probabilities cannot 

be known, or even sensibly estimated, for 

socio-economic futures – perhaps because

socio-economic processes and mechanisms are

intrinsically less knowable than biophysical

ones, perhaps due to the unpredictable effects

of human creativity and leadership, and perhaps

because causation does not operate in the

human domain as it does in the bio-physical domain. Although these arguments raise deep

philosophical questions, as a practical matter

probabilistic projections are routinely done in

some socio-economic domains, including projections of population and economic growth,

but not, or not well, in others, such as projecting

technological innovation. Provided the basic

concept of subjective probability is accepted,

weaker knowledge and deeper uncertainties can

be accommodated by broadening the relevant

uncertainties rather than declining to make

probabilistic judgments, but the question remains

of whether the resultant broad uncertainty ranges

are meaningful or operationally useful.

Several practical objections have also been

raised to associating explicit likelihood judgments with scenarios. These include the difficulty of developing probability estimates from

multiple information sources that can achieve

sufficient agreement from diverse experts, and

the non-intuitive nature of probability distributions in using scenarios to communicate with

non-expert users. These are both valid concerns, although active areas of research and development in expert elicitation techniques and

in simple intuitive devices to communicate uncertainty are making some progress in mitigating them.

An additional practical argument against quantifying probabilities is that attempting to do so

may represent a distraction that uses time, generates conflicts, and is of little value to scenario

users. Whether this is indeed the case, however,

is in part a judgment to be made by scenario

users, not developers. Opponents of quantified

probability argue that users typically only need

scenarios to pass some probability threshold.

Beyond this threshold, they will seek robust

choices that yield acceptable outcomes under all

possibilities, so further refinement of probability serves no purpose. This argument has merit,

but only to the extent that it accurately describes

how these scenarios will be used. Quantitative

assignment of probabilities to scenarios when

high-stakes decisions are implicated is clearly

difficult and contentious, as the SRES controversy illustrates. Even if this argument correctly characterizes how scenarios are used,

users might still be able to profitably exploit

more detailed probability information if it were

available – although one must also consider the

risk that non-technical users might somehow be

more likely to misunderstand scenarios with explicit probability judgments attached (perhaps

by taking a stated probability distribution as the

“true” distribution) than to misunderstand a

simple collection of scenarios presented with no

such probability information (perhaps by taking

the range presented to embrace the totality of

all possibilities). It is also possible that engaging scenario users in an attempt to assign probabilities, even only illustratively, could both

draw on relevant knowledge of uncertainties

that they possess more than scenario developers, and provide a valuable device to probe and

sharpen their understanding of the situation.

Any argument based on the information needs

of specific users becomes less persuasive as the

set of potential uses and users, and the likely diversity of their information needs, grow larger.

Overall, we find the arguments in favor of quantifying probabilities to be strongest for scenarios whose major outputs are projections of one

quantitative variable (or very few), and weakest

for complex multivariate scenarios with substantial qualitative or narrative elements. The

controversy over probabilities in SRES reflected

in part different perceptions of what type of scenarios these were. SRES initially followed a

storyline-based process and rejected quantifiOverall, we find the

arguments in favor of

quantifying

probabilities to be

strongest for

scenarios whose

major outputs are

projections of one

quantitative variable

(or very few), and

weakest for complex

multivariate scenarios

with substantial

qualitative or

narrative elements.
195 Alley et al. 1997. 

196 Note: these regional projections are 5-10 times faster

than the IPCC’s projected global 21st-century warming.

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Global-Change Scenarios - Their Development and Use

cation of probabilities on that basis. Subsequent

efforts, however, consisted predominantly of developing quantitative emissions projections and

neglected further development of the storylines.

Moreover, with a few significant exceptions,

subsequent applications of the scenarios have

principally used their emissions figures, sometimes together with population and GDP, and

made little or no use of the underdeveloped storylines that lay behind them. The controversy

over quantitative probability in this case suggests that when quantitative projections are a

major output of a scenario exercise, developers

may have a responsibility to go further in characterizing the likelihood of the resultant emissions intervals than would be appropriate for the

more complex underlying storylines.

Moreover, even for rich narrative scenarios, the

arguments against rendering probability judgments are strongest when the exercise is produced for a small number of users with similar

responsibilities and concerns. In such a setting,

intensive interaction between scenario developers and users can provide whatever additional

detail about, or confidence in, the scenarios that

users may require to benefit from the scenarios.

When scenarios serve potential users who are

more numerous and diverse, however, such intensive interaction is not possible. As a result,

the value of explicit likelihood judgments increases. To the extent that future global-change

exercises continue to strengthen their qualitative aspects and the integration between qualitative and quantitative – valuable directions for

future efforts – they should still seek to move further toward explicit characterization of likelihood

than has been done thus far.

In 2002, the Office of Net Assessments (ONA), a small strategic planning office in the Office of the

US Secretary of Defense, asked the Global Business Network (GBN), a consulting firm expert in

scenario methods, to develop a scenario of potential national-security implications of abrupt climate

change. This request was stimulated by widespread scientific interest at the time in abrupt climate

change, particularly shifts in North Atlantic circulation, including a 2002 report by the National

Academy of Sciences.192 In addition, several scientific papers had reported changes in Atlantic circulation and salinity that some scientists thought might indicate impending larger disruption, as well

as new evidence of rapid climate shifts in the past.193

GBN staff developed the scenario by reviewing scientific literature and informally consulting with

climate and ocean scientists.194 They reviewed three past climate events of diverse severity and decided to base their scenario on the one in the middle, the century-long period of strong cooling

8,200 years ago. Coming after an extended warm period, this event brought cooling of about 5 °F

over Greenland, with cold and dry conditions extending around the North Atlantic basin and substantial drying in mid-continental regions of North America, Eurasia, and Africa.195

For their future abrupt-change scenario, the authors constructed a path of climate change to reach

these conditions by 2020. The pathway involved rapid warming through 2010, as high as 4 – 5 °F

per decade in some regions,196 followed by a rapid turn to cooling around 2010, as melting in Greenland freshens the North Atlantic and substantially shuts down the thermohaline circulation. By

2020, hypothesized conditions have approached those of the 8,200-year event – cooling of 5 °F in

Asia and North America and 6 °F in Europe, with widespread drying in major agricultural regions

and intensification of winter storm winds. The authors acknowledge that the scenario pushes the

boundaries of what is plausible, both in the rapidity of changes and in the simultaneous occurrence 

BOX 4.8. The Global Business Network Abrupt Climate Change Exercise 

continued on next page

192 NRC 2002.

193 See, e.g., Dickson et al. 2002, Hansen et al. 2001,

Gagosian 2003, Curry and Mauritzen 2005, Fairbanks

1989. 

194 Global Business Network 2004. 
197 GBN 2004a:7, 2004b; Schwartz interview. 

198 Stipp 2004 (released, January 26, 2004).

199 London Observer 2004. 

200 San Francisco Chronicle 2004, Providence Journal

2004.

201 E.g., Alley 2004 cites it as a useful worst-case 

assessment. 

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The U.S. Climate Change Science Program Section 4 - Challenges and Controversies in Scenarios for Climate Change

of extreme changes in multiple world regions. They contend that this is defensible and useful, 

however, for an exercise focused on sketching the nature of challenges posed by a plausible 

worst case.197

The socio-economic and security implications of the climate scenario were developed judgmentally,

in consultation with ONA. Incremental changes are projected for the first 10 years, with general

increase in environmental stresses and approximate maintenance of present disparities between

rich and poor countries. After 2010, catastrophic cooling in Europe and drying of major agricultural

regions worldwide brings widespread shortages of food, due to decreased agricultural production;

of water, due to shifted precipitation patterns; and of energy, due to shipping disruptions from increased sea ice and storminess. These shortages produce 400 million migrants over the period

2010-2020, as desperate scarcity generates violent conflict in Europe, Asia, and the Americas. Extending their speculation on security implications into the 2020s, the authors hypothesize widespread southward migration of Europeans and near-collapse of the European Union, sustained

conflict in East and Southeast Asia including struggles between China and Japan over access to Russian energy supplies, and increasing political integration of a fortress North America to manage security risks and refugee flows.

Controversy and criticism

The project was completed in October 2003, its report published in February 2004 and reported

in Fortune Magazine the same month.198 A few weeks later, the London Observer claimed to have obtained the report secretly and used the scenario to criticize US refusal to join the Kyoto Protocol.199

Subsequent news coverage took up the theme that the report was secret or suppressed, and suggested the reason was that the scenario called for more urgent action on climate change.200 In the

resultant controversy, ONA stated – correctly – that the report did not represent US policy, but

was merely a speculative consultant’s study. Although the controversy subsided after a few weeks,

interest and concern about the possibility of abrupt climate change, although not of this precise character, have continued to grow.201

This scenario is a sketch of an abrupt climate-change event, with little fine-scale detail about the hypothesized changes or underlying reasoning and no attempt to suggest how likely or unlikely such

an event is. Rather, it seeks a preliminary answer to the question, what might the worst case look

like? Such questions are more often posed in security studies than other fields, because of the

unique nature of responsibilities of military organizations – responding to diverse, novel, unknown

threats with extremely high cost of failure. Many climate-change decision-makers could likely benefit from such upper-bound scenarios too, but this exercise is the only example of a worst-case scenario produced for climate change. Major official assessments have focused overwhelmingly on

average or best-guess projections.

But the response to this report vividly illustrates the risks of worst-case or extreme scenarios.

Produced in consultation with a sophisticated user – and in this case, one closely connected to senior decision-makers – who thoroughly understands the outer-bound nature of the underlying assumptions, they can be valuable devices for preliminary risk assessment and threat identification. But

in a wider and polarized policy debate they are hard to explain and may be misunderstood or misrepresented. Attempting to manage the process through secrecy appears counterproductive, foregoing the potential value such analyses could provide to multiple decision-makers. More promising

might be to integrate extreme-case scenarios explicitly into analyses that also present multiple midrange scenarios.

BOX 4.8., continued from previous page.
Global-Change Scenarios - Their Development and Use

Conclusions and 

Recommendations

SECTION

5

83

This section presents our conclusions regarding the present state of development and use of scenarios for climate-change applications, and some recommendations for specific changes or initiatives to advance current practice to make scenarios more useful.

Before doing so, we briefly reprise some key definitional points, because uses of the term scenarios

are so divergent. We have defined scenarios as descriptions of future conditions produced to inform decision-making under uncertainty. This definition distinguishes scenarios from assessments,

models, decision analyses, and other decision-support activities. Scenarios may be developed and

used in conjunction with these – for example, scenarios can provide descriptions of potential future conditions used as inputs to such activities – but are not identical to these, and not alternatives to them. 

We have also distinguished scenarios from other types of future statements intended to inform

decisions, such as projections, predictions, and forecasts. Relative to these, scenarios tend to be

more multivariate (but still schematic), tend to be developed in groups, and tend to presume

lower predictive confidence. The last condition is the case in part because scenarios tend to be

used in situations where the basis for forecasting is less established because of deeper uncertainties, or for situations that pertain to further in the future beyond the range for which there

is high confidence in specific projections, even contingent ones. 

Having distinguished scenarios from these related activities, we consider a broad set of scenarios

of diverse characteristics and uses, including simple and complex scenarios, quantitative and qualitative scenarios as well as various combinations of the two, and scenarios whose primary use and

interpretation is positive or normative. Where we intend our conclusions and recommendations

to apply to only certain types or uses of scenarios, we state this explicitly. Unless stated otherwise, they pertain to all types of global-change scenarios we are considering. 
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The U.S. Climate Change Science Program Section 5 - Conclusions and Recommendations

5.1 USE OF SCENARIOS IN 

CLIMATE-CHANGE DECISIONS 

Scenarios can make valuable contributions to climate-change decision-making.

Many of the decisions that will comprise

society’s response to climate change –

whether mitigation, adaptation, or other responses – involve high stakes, deep uncertainties, and long time horizons. Scenarios

can help inform these decisions by structuring present knowledge and uncertainty,

prompting critical examination of present

assumptions and practices, stimulating new

insights, identifying key pitfalls and opportunities, or providing a framework for the assessment of particular decisions. For some

decisions, which involve irreversible nearterm commitment to choices whose consequences extend over a horizon involving

substantial uncertainties, some form of scenario-based reasoning may be essential.

There is a big gap between the use of scenarios in current practice and their potential contributions. Despite their evident

value and capability, many climate-related

decisions that could benefit from scenarios

(e.g., many decisions regarding long-term

management and investments in climatesensitive areas such as freshwater systems

or coastal zones) are not using them. Indeed, many such decisions are still being

made without considering climate change

at all. Conversely, many climate-change

scenarios have only weak and indirect connections to practical decisions related to

climate-change mitigation or adaptation.

Interest in considering and using climatechange scenarios is sharply increasing.

There is increasing interest in considering

climate-change scenarios in diverse decision and planning processes. This trend is

strongest for planning and decisions concerned with climate-change impacts and

adaptation. The trend reflects advances in

scientific understanding of climate change,

gradual maturation of models and analytic

tools, and increasing recognition by decision-makers of the potential importance of

climate change. Given the high general concern about climate change and the advance

of background scientific knowledge, we expect this trend to continue, and to broaden

to other types of climate-related decisions.

Scenarios of global emissions and resultant changes in atmospheric trace-gas 

concentrations and climate are a core 

requirement shared by many diverse

climate-related decisions. Although climate-change decision-makers and their

particular information needs are highly diverse, many will need scenarios of global

emissions and resultant climate change,

and many more will need information that

depends on these. Consistent scenarios of

global emissions and climate change, provided centrally at the national or international level, can serve these diverse needs –

if they are presented with enough transparency and documentation of their underlying reasoning and assumptions.

Beyond global emissions and resultant climate change, decision-makers’ needs

from scenarios are highly diverse. Different climate-change decision-makers will

have highly variable needs from scenarios,

in the factors and variables included, the

time and spatial scale at which they are provided, and the nature of uncertainties represented. The means for meeting these

additional needs will likely be diverse, too.

Some will call for separate, specialized scenario production capabilities. A major distinction in scenario-related needs can be

drawn between impacts and adaptation

managers, mitigation policy-makers, and

energy resource and technology managers.

Impacts and adaptation managers need

scenarios that project impacts relevant to

their specific responsibilities, and the

major determinants of vulnerability and

adaptive capacity. Impacts and adaptation

managers include both national officials

and others responsible for more specific

domains of impact. These decision-makers need climate-change scenarios, driven

by specified global emissions scenarios, to

provide information about potential climate-related stresses on their areas of responsibility. In addition, they need other

environmental and socio-economic infor-
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Global-Change Scenarios - Their Development and Use

mation specific to their areas of responsibility, at appropriate spatial and temporal

scales. Meeting these needs will require

both easy access to centrally produced climate scenario information with associated

tools and support, and development of decentralized capabilities for developing and

applying additional scenario-related information. Many of these specific information needs are likely to be similar in

character for many particular locations and

types of impact. 

Meeting information needs for impacts

and adaptation requires a cross-scale organizational structure. These decisions’

combination of centralized and decentralized information needs suggests the need

for a linked network of institutions at national and sub-national levels to develop

scenarios. Such a structure would combine

central provision of globally consistent

emissions and climate change scenarios;

decentralized elaboration of these scenarios with additional variables required for

regional impacts and adaptation analyses;

and provision of tools and resources to support development and use of scenarios. 

Scenarios for impact and adaptation managers should be based on emissions assumptions that include a likely range of

mitigation interventions, now and in the

future. The emissions assumptions underlying scenarios for impacts managers

should be based on the likely range of future global emissions trajectories, including explicit assumptions about what

degrees of further mitigation effort are

likely over time. This will typically imply

a narrower range of emission futures than is

considered in scenarios to support mitigation decisions.

Mitigation policy-makers need scenarios

that project alternative emissions trends in

their own jurisdiction and others, and the

major factors that will influence mitigation opportunities, constraints, and costs.

Mitigation policy-makers are usually officials who make national policy and participate in international negotiations, but this

group also includes sub-national officials

when they share mitigation responsibilities

or undertake mitigation initiatives. Serious

pursuit of greenhouse-gas mitigation will

require major policy innovations that carry

significant risks of many kinds, including

the effectiveness and cost of the policies

but also their effects on government budgets, competitiveness of particular industries,

opportunities for national technological capabilities, etc. Decision-makers considering such policies will need scenarios of

global and national emissions trends, resultant climate change, and aggregate impacts. In addition, they will need to

consider many factors specific to their jurisdictions – e.g., national policies, institutions, economic structure, technological

capabilities, and the detailed structure of national emissions – and information about the

policy environment for their choices, including alternative scenarios of other nations’ mitigation strategies, international

mitigation decisions, and implementation

and compliance.

Scenarios for mitigation decisions should

include a wide range of baseline emissions assumptions and should not prejudge the likely level of mitigation effort.

Scenarios used to inform mitigation decisions should consider the full range of potential mitigation choices on the agenda,

defined relative to baseline assumptions

that, as much as possible, reflect only efforts already enacted or committed, including a range of reasonable assumptions

about implementation and compliance.

This assumption typically implies a wider

range of emissions futures than is considered in scenarios to support impacts and

adaptation decisions. 

Mitigation decision-makers can use target-driven scenarios for backcasting. Mitigation decision-making may also benefit

from scenarios that impose explicit future

environmental targets such as limits on

emissions or atmospheric concentrations,

together with assumptions about policy and

implementation elsewhere, and reason

backwards to explore alternative paths to,

and implications and requirements of attaining that goal, including feasibility, costs, and
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The U.S. Climate Change Science Program Section 5 - Conclusions and Recommendations

tradeoffs. These must be defined in ways relevant to the level of decision-making being

informed, i.e., alternative national targets 

to inform national policy-making, in the

broader context of alternative global baselines or global targets.

Informing mitigation decisions requires

capacity for scenario development at the

national level. While core scenarios of

global emissions and climate-change can

provide some of the required input into mitigation decisions, these decisions require

additional information that must be provided at the national or sub-national level

where the decisions are being considered,

generated in consultation with relevant decision-makers or their surrogates.

Energy resource and technology managers need scenarios that represent the

political and economic environment for

energy investments, including mitigation

policies. Energy resource and technology

managers concerned with private responses

to mitigation policy primarily need scenarios that represent alternative policy

regimes. Emissions and climate change

underlie these as influences on policy decisions, but do not capture the most important uncertainties for these decisionmakers. While many actors may wish to

generate these scenarios privately to keep

their assumptions and analyses confidential, there may also be value in multi-party

collaborative scenario-building exercises in

which today’s policy-makers and corporate

planners jointly examine what range of policy, economic, and energy regimes is plausible or likely over the 30- to 50-year time

horizons relevant for investment and technology-development decisions.

Scenarios must be periodically revised and

updated. For all types of decisions and decision-makers, developing scenarios, applying them to inform decisions, and

refining scenario methods, are iterative

processes. Limitations to present scenarios or methods do not in general justify delaying consideration of such decisions, any

more than scientific uncertainties do. Still,

scenarios must be periodically updated,

based on new knowledge, experience, and

priorities, as well as further developments

in scenario-related methods. Such updates

are needed much more frequently than the

decision time horizons.

5.2 USE OF SCENARIOS 

IN CLIMATE-CHANGE

ASSESSMENTS 

Large-scale, official assessments are the

major use for scenarios at present and are

likely to remain an important use. Largescale, official assessments represent the

most prominent demand for climate-related

scenarios at present, and are likely to remain major users, particularly for coordinated scenarios of global emissions and

resultant climate-change.

Within assessments, scenarios mainly

serve to support further analysis, modeling, and assessment. When scenarios are

used in assessments, certain users are

clearly identified: e.g., climate modelers

are major users of emissions scenarios,

while impacts assessors and modelers are

major users of climate-change scenarios.

These users have specific scenario needs,

and close consultation is possible between

scenario producers and users to meet these

needs. Substantial progress has been made

in providing useful scenarios for these

groups, at both the national and international level. These efforts should be continued and expanded. 

The presentation of scenarios in assessments leads to many additional, unforeseen

uses. Scenarios presented in large-scale assessments gain prominent dissemination

that results in their being put to many uses

their developers did not foresee. Scenarios

should pursue clarity of documentation and

transparency about underlying reasoning

and assumptions, to improve the ease of use

and reduce the risk of misunderstanding in

such derivative uses, although they cannot

anticipate all information needs of an openended set of diverse potential uses.

In assessments, scenarios can strongly influence issue framing. Also because of
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Global-Change Scenarios - Their Development and Use

their prominent dissemination, scenarios

presented in major assessments can exercise substantial influence over the framing

of policy discussions or provide simple,

widely used metrics of the seriousness of

the issue. They may consequently exercise

broad influence over many decisions that

depend upon such aggregate perceptions of

seriousness. The prospect of such influence further heightens the responsibility for

transparency in production of scenarios.

Scenarios contain unavoidable elements

of judgment in both their production and

use. Although they draw on relevant data,

knowledge, and analysis, scenarios inevitably contain elements of judgment. In

addition to putting serious responsibilities

onto scenario developers, this implies that

there is no authoritative way to resolve arguments over whether a scenario is plausible or not. When a wide enough range of

potential futures is considered, some scenarios are likely to draw criticism, in part

motivated by opposition to their foreseeable implications for action. Any scenario

can be attacked as unreasonable, speculative or unlikely, and close enough scrutiny

of any scenario can usually reveal inconsistencies, but these do not provide sufficient basis for excluding a scenario from

consideration. Indeed, scenarios designed

to represent extreme events, or to lie near

one end of a distribution of potential outcomes, should by definition appear unlikely. The most productive response to

such criticisms lies in transparency about

the process, reasoning, and assumptions

used to produce scenarios. Such transparency can shift arguments to underlying

uncertainties, and help limit biases in the

production of scenarios. 

5.3 CHARACTERISTICS 

OF “CORE” EMISSIONS AND

CLIMATE SCENARIOS

Centrally provided scenarios of emissions

and climate change can help inform mitigation and adaptation decisions at national and sub-national scale, but these

will usually require additional information as well. Central scenarios can provide

information about trends in world emissions, underlying socio-economic conditions at the scale of major world regions,

and the large-scale pattern of global policy

response. They can also provide access to

climate-model scenario output, plus tools,

data, and support for producing finer-scale

scenario information needed for particular

impact and adaptation applications. Mitigation and adaptation decisions and associated assessments at national or smaller

spatial scale will need more detailed and

finer-scale climate and socio-economic information than can be provided by centralized scenarios, so these must be extended

and/or modified by national and sub-national scenario processes. 

Scenarios of emissions and resultant climate change should be global in scope

and century-scale in time horizon. Core

emissions and climate-change scenarios

should specify major climate-relevant

emissions and other perturbations, globally

and for major world regions. They should

extend over a time horizon of at least 100

years (including some that extend 200-300

years to support assessments of sea level

rise), with interim results at roughly

decadal resolution. 

Emissions scenarios of several distinct

logical types will be needed to serve diverse purposes. These will include some

combination of alternative baselines, alternative levels of incremental stringency of mitigation effort, and specified future targets to

support backcasting and feasibility analysis.

For some uses, emissions scenarios should

be coupled to explicit scenarios of alternative socio-economic futures. For these

scenarios, the range of potential socio-economic and policy futures considered should

be wider than has been considered to date,

including scenarios of policy failure and

conflict, and a wide range of stringency and

timing of mitigation effort. For example,

what if development stagnates in major

world regions? What if world emissions

grow sharply for several decades with little control effort, followed by a subsequent

shift to stringent mitigation efforts? What
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The U.S. Climate Change Science Program Section 5 - Conclusions and Recommendations

if part of the world makes a lot of effort and

part makes very little? Considering such

varied future histories is crucial for considering long-term risks and opportunities

from major mitigation choices.

Scenarios should reflect various explicit

degrees of coordination, depending on

their intended uses. Some uses will require groups of simple coordinated scenarios to provide standardized inputs for

downstream modeling and analysis – e.g.,

standard emissions scenarios as inputs to

climate models and standard climate scenarios as inputs to impact assessments – for

exploring present uncertainties and tracking developments of knowledge over time.

Other scenarios should be based on multiple

models using common input assumptions.

Non-standardized scenarios produced at the

initiative of researchers and modelers should

also be produced, which explore alternative

assumptions or meet specific user needs,

provided these meet basic standards of

quality control, transparency, and documentation. 

Some scenarios should seek to link qualitative and quantitative elements. Some

scenarios of socio-economic conditions,

whether produced to support global emissions scenarios or impacts assessments,

should include both qualitative and quantitative elements and sustained analytic efforts to link the two. Qualitative or narrative

scenario elements can provide a vehicle to

explore major historical uncertainties with

large implications for global emissions, climate change, and vulnerability to climate

impacts; provide a coherent rationale and

logical structure to connect assumed trajectories for multiple variables, including

both quantitative and qualitative ones; and

provide guidance to other analysts or users

who may wish to extend the scenarios by

elaborating additional detail. Achieving

these benefits will require more sustained

effort to integrate model-based projections

of quantitative variables with qualitative

and narrative scenario elements, to iterate

between these, and to critically examine

each element in light of the other, than has

been made thus far. These efforts should

seek to connect alternative qualitative and

narrative scenarios not just to alternative

parameter values in quantitative models,

but also to alternative forms of causal relations and model structures. Generating

multiple alternative model quantifications

based on the same narrative and associated

causal logic is one promising route to enriching understanding of uncertainties in

key quantitative variables such as future

economic output and emissions.

5.4 SCENARIO PROCESS:

DEVELOPER-USER

INTERACTIONS

There is value in collaboration between

scenario developers and users, particularly at the beginning and ending stages

of a scenario exercise. The appropriate degree and means of this collaboration vary

substantially among scenario exercises.

User engagement is most important in the

initial scoping and design of a scenario exercise, and in the evaluation and application of the scenarios generated. The value

of user engagement in details of scenario

development, quantification, elaboration,

and checking, depends on the specific case.

The ease of achieving such collaboration

and its value are likely to be greater when

scenario users are clearly identified, few

in number, and similar in their interests

and perspectives. When potential scenario

users are identified, relatively few, and relatively homogenous, close and intensive

collaboration between users and developers is likely to be most productive. When

potential users are numerous and diverse,

intensive engagement may be infeasible

and more structured processes for consultation, representation, and information exchange are needed. While progress has

been made in new methods to allow larger

numbers to participate in scenario exercises, further development of such methods

is needed. 
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Global-Change Scenarios - Their Development and Use

5.5 COMMUNICATION 

OF SCENARIOS

Effective communication of scenarios is

essential, in forms useful to audiences of

diverse interests and technical skills. Scenarios must be communicated effectively to

their potential users, including both technical and non-technical audiences. In addition to the contents or outputs of scenarios,

communication should include associated

documentation, tools, and support for their

use. Various methods should be used to

promote broad dissemination of scenario

information; for instance, presentations, reports, websites, and centralized data distribution centers. To facilitate user

understanding of results, various methods

should be used to communicate numerical

and technical information, including multiple tabular, summary, and graphical formats,

ideally with user-interactive capabilities.

Transparency of underlying reasoning

and assumptions is crucial. Scenario communication should include transparent disclosure of underlying assumptions, models,

and reasoning used to produce the scenarios, to support the credibility of scenarios,

to alert potential users to conditions under

which they might wish to use or modify

them, and to inform criticism and improvement of scenarios. This should include explicit identification of the major

uncertainties represented in each scenario

and the sources of underlying information,

whether drawn from the scientific literature, formal expert-elicitation exercises, or

informal judgments of the scenario team.

It is possible in virtually all cases to formulate simple, accessible, honest descriptions of why a scenario was undertaken,

why it was necessary, what was done, how

and why, and why it merits respect as a reasonable judgment. 

5.6 CONSISTENCY AND

INTEGRATION IN SCENARIOS

Any scenario should be internally consistent in its assumptions and reasoning, to

the extent this can be established given

present knowledge. Carefully pursuing

consistency within individual scenarios 

can be an intensive and time-consuming

process, but is crucial to avoid problems

that can discredit a scenario exercise.

In scenario exercises that use multiple

models to explore potential uncertainties

in future conditions, consistency between

models should be pursued primarily

through coordination of inputs, not outputs. Use of multiple models in parallel to

produce alternative descriptions of future

conditions can improve understanding of

uncertainties, if models are run under 

consistent assumptions about exogenous

inputs. Forcing models to generate consistent trajectories for endogenous outputs

poses several risks, including suppressing

variation from alternative causal structures

that could provide valuable insights into

uncertainties, and encouraging over-confidence from spurious precision. For quantities that are exogenous in some models and

endogenous in others, the appropriate treatment varies case by case, but it is not generally desirable to force multiple models to

convergent values of such variables without more detailed examination of the underlying uncertainties.

Imposing consistent outputs in multimodel exercises can be useful, however,

when these outputs represent common

goals for policy evaluation. For example,

consistent constraints on some environmentally relevant target such as emissions,

atmospheric concentrations, or radiative

forcings, can be used to examine intermodel uncertainties in the technological,

economic, and resource conditions associated with meeting the specified targets.

Transparency in reporting scenario and

model differences as well as underlying

assumptions and reasoning can help mitigate the effects of inconsistencies among

scenarios. Ideally, multiple scenarios in an

exercise should differ only on those elements intentionally chosen to distinguish

them, and be consistent in all other factors.

However, this is not always possible, particularly when scenarios are produced

using different models. Pursuing maximal
90

The U.S. Climate Change Science Program Section 5 - Conclusions and Recommendations

transparency about the models, assumptions, and reasoning underlying each 

scenario – perhaps by issuing detailed diagnostic reports that include explicit discussion of points of weakness, uncertainty,

and disagreements, and the means used to

resolve them – can mitigate any resultant

confusion.

5.7 TREATMENT OF

UNCERTAINTY IN SCENARIOS

Some scenario exercises should include

more explicit characterization of likelihood judgments than has been practiced

so far. The advantages of being more explicit about the probability judgments that

underlie scenario exercises are likely to

outweigh the disadvantages. Such specification should be pursued further than has

been done in major global-change scenario

exercises to date, although not necessarily

in all scenario exercises. The means available to express these judgments are of

widely varying specificity, ranging from

agreed terminology202 to explicitly quantified probability distributions. All such

judgments should include explicit acknowledgement of their inevitably subjective elements and appropriate caveats to

help users avoid mistaking them as objectively true.

Explicit probability judgments are easiest

to produce and least controversial in scenarios generated using quantitative models of climate change or specific impact

domains. Scenarios generated using such

models can be conditioned on specific assumed values for socio-economic inputs

such as emissions, and can represent explicitly and quantitatively the effects of

specified variation in initial conditions or

unknown parameter values. These devices

are also available, although in less widespread use, in economic models used to

project emissions. These devices aid in

constructing distributions of key quantitative characteristics, such as measures of

global or regional climate, or of prominent

quantitative impact measures, such as

changes in river flows or sea level, although they neither capture all relevant 

uncertainty nor avoid the inevitably subjective nature of such probability judgments. Explicit probability judgments are

more difficult and controversial when they

involve socio-economic factors for which

quantitative models are not available, and

that do not depend in well understood ways

on identified quantitative parameters. Such

factors include major technological innovations, large-scale changes in attitudes or

norms, or policy response.

Attempting to include explicit probability

judgments is likely to be most useful and

successful when key variables are few,

quantitative outcomes are needed, and potential users are numerous and diverse.

The case for assigning explicit likelihood

judgments is strongest when scenarios’

most salient components are quantitative

projections of a few key variables, such as

emissions or average temperature change

over the globe or some region, because the

technical barriers to assigning probabilities

are least severe in this case. The case is

strongest when a primary purpose of the

scenario exercise is to provide inputs to

other quantitative assessment activities, or

to inform decisions that primarily depend

on one or a few key quantitative variables,

because such uses are most likely to require

probability judgments. The case is

strongest when the set of potential scenario

users and uses is large and heterogeneous,

because this situation provides the least opportunity for informal communication of

implicit judgments of likelihood or priority

through intense, sustained collaboration between scenario developers and users.

Attempting to include explicit probability

judgments is likely to be least useful and

successful when scenarios specify multiple characteristics, including prominent

narrative or qualitative components; when

the purpose of a scenario exercise is sensitivity analysis or heuristic exploration;

202 See, e.g., the consistent uncertainty language proposed for IPCC reports by Moss and Schneider 2000. 
91

Global-Change Scenarios - Their Development and Use

and when potential users are few, similar,

and known. When scenarios are primarily

construed as rich, qualitative narratives that

present major alternative historical and

socio-economic trajectories, the technical

obstacles to explicit probability assignment

are greatest and the likely confidence in

scenario developers’ subjective probability

judgments lowest. When the main purpose

of a scenario exercise is to stimulate critical

or creative thought, to probe the limits of a

model or decision strategy through sensitivity analysis, or to explore ways of meeting a specified target, explicit probability

assignment provides little or no benefit.

When users are few, similar, and specifically identified, they can be intensively involved in scenario production, allowing

effective informal communication of likelihood judgments without stating them explicitly. Under these conditions, scenario

exercises can also be structured to engage

users in the potentially instructive activity

of assigning and discussing their own probability judgments, rather than putting that

responsibility exclusively on the researchers

or analysts developing scenarios.

Centrally provided scenarios of global

emissions and climate change should attempt to include explicit probability judgments. Because of the large, diverse set of

users for these scenarios, explicit likelihood

judgments should be provided for ranges of

key quantitative outputs, including global

emissions and global-average temperature

change. Scenarios should typically include

several paths that span a wide range of

judged uncertainty, e.g., 95 percent to 99

percent. The associated probability judgments may include some that are unconditional and some that are conditioned on

specific assumed prior conditions. Such estimates should be provided by multiple

groups using diverse methods. As for all

such probability judgments, their unavoidably subjective nature and the specific assumptions on which they are conditioned

should be stated explicitly and prominently

.

Providing explicit probability judgments allows scenario users to choose whether to

use them or not. Some users may choose

to use these explicitly in their subsequent

analysis or decision support, while others

may use them only to help decide which scenarios to use, and still others may disregard

them entirely. Users may select a different

group of scenarios or a different subset of

the uncertainty range for various reasons, including differences in risk aversion, differences in the scope of their decision authority, or differences in their assumptions

about decisions by other actors (present or

future). Presenting complete descriptions of

scenarios together with underlying assumptions and reasoning, including probability judgments, preserves all these options

for users.

Scenario exercises should give more attention to extreme cases. Some uses of scenarios require consideration of low-probability,

high-consequence extreme cases, such as loss

of a major continental ice sheet or major

changes in meridional ocean circulation.

Consequently, such scenarios should be included in large, general-purpose scenario exercises producing emissions or climatechange scenarios, together with more likely

middle-case scenarios. When extreme scenarios are included in an exercise, it is especially critical to be explicit and transparent

about the reasoning and assumptions underlying each scenario, and scenario developers’

judgments of relative likelihoods.

In addition to enhancing the utility of scenario outputs, probabilistic methods can

contribute throughout the scenario development process. Developing scenarios requires making many judgments about unknown characteristics and developing many

arguments and pathways to link these. Scenarios based on quantitative models typically

require specifying many exogenous inputs

and parameters. Even narrative scenarios require specifying values of multiple characteristics, both qualitative and quantitative.

Explicit discussion of uncertainties and associated probabilities can help structure
92

The U.S. Climate Change Science Program Section 5 - Conclusions and Recommendations

and facilitate many aspects of the scenario

development process, including deciding appropriate ranges of variables to consider,

defining boundaries of what outcomes are

considered plausible, elaborating associated causal mechanisms and linkages, discussing and integrating knowledge and

judgments from multiple participants, and

clarifying disagreements. Explicit conversation about probabilities can support insights throughout these processes, in addition to supporting communication of scenario

judgments to users.

5.8 EXPANDING AND SUSTAINING CAPACITY FOR PRODUCTION AND USE OF SCENARIOS203

Present scenario capacity is inadequate. Although scenario-based reasoning is required

for many aspects of global change assessment

and decision support, the present capacity to

produce, disseminate, apply, evaluate, and

adapt scenarios is inadequate. There has not

been enough continuity to enable effective

learning, because scenarios are typically

produced de novo for each major application.

There has not been enough transparency about

methods, reasoning, and assumptions. Constructing integrated scenarios and exploring

alternative methods has been difficult, in part

because scenario exercises have tended to be

dominated by use of quantitative models, separated along disciplinary lines. Inadequate resources have been devoted to methods development, for scenarios and related decisionsupport tools Finally, there has been no systematic evaluation and critique of scenarios

or their application.

To help fulfill these presently unmet

needs, CCSP should establish a

program to: 

• Commission scenarios for use in assessments and decision-support

activities. This task includes facilitating agreement among relevant

producers and users on standard scenarios in cases where multiple assessment activities require standard scenarios for comparability, and

convening and supporting a diverse collection of more extensive

and detailed scenario-related exercises, by multiple groups using a

wide range of models and approaches. 

• Disseminate scenarios with associated

documentation, tools, and guidance

materials. This task includes multiple forms of support and program-building for diverse groups

seeking to apply, modify, and extend

existing scenario-based information at various regional and sectoral

scales, through providing data,

models, tools, resources, and associated documentation and technical

support, in multiple forms and

through multiple media.

• Commission various groups to evaluate scenarios and their applications and to develop improved

methods. This task includes defining and promulgating standards for

quality control – which, given the

need for diverse approaches, would

principally concern matters of

process such as transparency, documentation, evaluation, and dissemination of results and supporting information. The task also includes broad efforts to develop scenario-related skills, tools, and methods, e.g., by providing resources for

methods development and evaluation projects; conducting and establishing procedures for evaluation

of particular activities and programs; and convening workshops,

203 Recommendations made in this report regarding programmatic and organizational changes, and the adequacy of current budgets, reflect the judgment of the

report’s authors and the CPDAC and are not necessarily the views of the U.S. Government.
93

Global-Change Scenarios - Their Development and Use

conferences, etc., to evaluate

progress overall, or in particular

methodological areas.

• Archive results and documentation related to all these tasks, to provide

historical perspective and institutional memory for future scenariorelated activities. This task includes preserving for retrospective

scrutiny a wide range of materials:

not just the methods, contents, and

results of scenario exercises, but also

the progressive evaluations of particular activities and approaches, and

of the entire program. In its ongoing development and evaluation of

methods, the program should not

draw rigid boundaries between scenario development and application

and other related methods of assessment and decision support for

long-term global change issues.

Several conditions in the design and

management of this new program

would be required to ensure its effectiveness. 

• The program should build and maintain strong connections with outside relevant expertise, and analytic

and modeling capability. While

the program must develop enough

internal expertise to be a full participant in debates over scenarios

and assessment methods, it cannot

and should not attempt to impose a

unilateral vision of preferred scenarios, methods, or approaches.

Rather, it must build and maintain

close collegial connections with

outside networks of researchers

and analysts in multiple fields of expertise, including emissions modelers, climate scientists and modelers, impacts researchers, and resource managers. These relationships would be facilitated by establishing governing mechanisms,

such as a senior advisory board,

drawn from the broad communities

of researchers, modelers, and analysts who are developing and using

scenarios and related methods. Although established as a US national program, it must also support, collaborate, and coordinate with parallel activities in other nations and

internationally, and with relevant

sub-national activities. 

• The program should integrate and balance goals and criteria related to

scientific and technical quality,

and those related to utility and relevance to users. This balance is

needed for the program to support

promising but speculative activities,

to encourage creativity and diversity

of approach, to avoid being captured

by any particular discipline or modeling approach, and to be willing to

make and explain judgments about

quality and promise that reflect

both scientific and practical considerations. To achieve this, the program needs broad discretion over the

type of projects supported, including sponsoring fairly sharply targeted activities, supporting speculative activities, and investing to develop and assess capabilities that do

not yet exist. 

• The program should be insulated from

political control. For the scenarios

and analyses based on them to be

perceived as credible by their diverse

users, the program needs enough insulation from political control, at

both the national or international

level, to prevent scenarios from

becoming proxies for conflict over

near-term policies, and to allow

exploration of the implications of alternative futures that represent plausible risks but that some political actors would find objectionable. 

• The program should strive for maximum transparency in its own activities, in addition to demanding

it from activities it supports. The

program should strive for maximal

transparency regarding inputs, mod-
94

The U.S. Climate Change Science Program Section 5 - Conclusions and Recommendations

els, assumptions, and reasoning

employed in developing scenarios,

as well as any significant disagreements that arose and how they

were resolved and any remaining

weaknesses recognized by the developers. The broader and more diverse the collection of intended

uses and users, the more crucial is

transparency of the scenario-production process – because different

users may require scenarios produced using different underlying assumptions, and they must be able to

track the underlying logic to exercise this choice. This would enhance

credibility in the scenario-development process. While calls for such

transparency are widely made, experience suggests it is difficult to

achieve, particularly for such matters as disagreements or recognized

weaknesses that may risk professional embarrassment. Still, achieving more transparency and more

widely informed debate on such matters is essential for advancing scenario methods.

• The program will require the authority

and resources necessary to articulate and promulgate standards for

transparency, consistency (e.g., of

units and formats), and quality control. This task involves facilitating

discussions among the community

and formulating persuasive guidelines and supporting arguments. It

also requires use of incentives such

as seals of approval, access to participation in particular processes, access to particular dissemination

outlets, and access to resources. A

weak “clearinghouse” that solicits,

supports, or publicizes scenarios but

cannot exercise quality control,

propose and stimulate new directions, or convene critical reviews, of

the whole enterprise and of particular exercises, is not an adequate

model for the program.

• The program will require an adequate

sustained resources. The program

must build and maintain a sophisticated analytic capability, and develop skills and institutional memory regarding prior experiences,

successes, and failures. This requirement precludes the program

being a series of ad hoc one-time activities or a part-time, unfunded burden imposed on people and organizations with other full-time responsibilities.
ACRONYMS

95

Global-Change Scenarios - Their Development and Use

A1, A2, B1, B2, A1FI

names of specific emissions scenarios 

published in the IPCC Special Report on 

Emissions Scenarios

CCSP Climate Change Science Program

CCTP Climate Change Technology Program 

CFCs chlorofluorocarbons

DDC Data Distribution Center (IPCC)

DOD Department of Defense (U.S.)

DWR Department of Water Resources 

(California)

EMF Energy Modeling Forum

ENSO El Ni o/Southern Oscillation

EPA Environmental Protection Agency

GBN Global Business Network

GCM general circulation model

GDP gross domestic product

GFDL Geophysical Fluid Dynamics Laboratory, 

US National Oceanographic and Atmos

pheric Administration (NOAA), and 

climate model produced by this 

laboratory

GtC gigatonnes (billion metric tons) of carbon 

HadCM2 UK Hadley Centre climate model, 

Version 2

IIASA International Institute for Applied 

Systems Analysis, Laxenburg, Austria

IPCC Inter-governmental Panel on 

Climate Change

IS92 series of emissions scenarios produced by 

the IPCC in 1992, including specific 

scenarios named IS92a through IS92f

LRTAP Convention on Long-Range 

Transboundary Air Pollution

MEA Millennium Ecosystem Assessment

MEC Metropolitan East Coast assessment of 

US National Assessment

MER market exchange rates

NAPAP National Acid Precipitation 

Assessment Program

NAST National Assessment Synthesis Team

NRC National Research Council (U.S.)

NYCDEP New York City Department of 

Environmental Protection

NYCHP New York Climate and Health Project

OECD Organization for Economic Co-operation 

and Development

ONA Office of Net Assessments (Office of US 

Secretary of Defense)

OTA Office of Technology Assessment, 

United States Congress

PDO Pacific Decadal Oscillation

PPP purchasing-power parity

SRES Special Report on Emissions Scenarios 

(IPCC)

TGICA Task Group on Data and Scenario 

Support for Impact and Climate 

Analysis (IPCC)

UKCIP United Kingdom Climate Impacts 

Program

VEMAP Vegetation Ecosystem Mapping and 

Analysis Project 

VOC olatile organic compounds
96

The U.S. Climate Change Science Program Acronyms
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