IA-SCENARIOS AND IA-MODELS

A CROSS-FERTILIZATION

SUMMERSCHOOL

Jan Rotmans

September 3rd 1999

SCENARIOS

• Hypothetical

• Dynamic

• Links of states, driving forces, events, consequences and actions

• Fixed time horizon

Characteristics:

Scenarios are NOT images of the future

BUT movies of the future (sequence of future images)

Scenarios are NOT predictions or forecasts of the future

BUT projections of the future (what …. if projections)

REMEMBER THE DUALITY BETWEEN ‘DOERS’ AND ‘THINKERS’!

Most scenarios have been developed by ‘doers’ instead of ‘thinkers’

Domination of engineers, economists and planners

Rare contributions from social sciences

No poets, painters, philosophers and free thinkers

DEFICIENCIES OF CURRENT SCENARIOS

• narrow-based (one disciplinary, one perspective)

• extrapolative (business-as-usual)

• boring (not imaginative)

• opaque (not transparent)

• inconsistent (assumptions do not match)

SCENARIO CLASSIFICATION

• forecasting versus backcasting

• descriptive versus normative

• model-based versus narrative

• participative versus desk-study

• multiple-issue versus single-issue

• multiple-scale versus single-scale

WHAT ARE IA-SCENARIOS?

Participative (stakeholder-based)

Consistent (key assumptions checked among different sectors, actors and factors)

Coherent (inclusion of relevant linkages and dimensions)

Multiple scale (cover various scales in space and time)

Integrated Assessment scenarios are:

EUROPEAN SCENARIOS IN HISTORICAL PERSPECTIVE:

• about 40 European scenario studies have been considered

• 10 European scenario studies have been studied in-depth

• social, economic, environmental and institutional dimensions have been analysed

• scenario exercises have been classified into:

model-based, narrative, participatory/single area, single issue

• scenarios have been clustered (comparable trends)

CLASSES OF INDICATORS

Indicators

Social Economic Environmental InstitutionalWRR (1992) * * *Button (1993) *EFILWC (1994) *ECN (1995) *McRae (1995) * *EC DGXII (1996) * * *EC DGXVII (1996) * * *CPB (1997) *Smith (1997) * *

Table: The classes of indicators used in the various studies

WHAT DID THE EUROPEAN SCENARIOS HAVE IN COMMON?

• Limited variety (look similar)

• Descriptive rather than normative

• Almost no surprises

• Forecasting rather than backcasting

• Hardly any concrete policy recommendations

GENERAL CONCLUSION

There are no scenarios available

that discuss sustainable development in Europe

in a balanced and integrated manner

CLUSTERING OF EUROPEAN SCENARIOS

• Money maker

high economic growth as binding element

•Think green

environmental protection as binding element

• Wait and see

with limited policy action as binding element

• Doom monger

with pessimistic character as binding element

Clustered scenarios

Dark ages

FragmentationBattlefield

Divided Europe

The Apocalypse

Doom monger

Regional development

Environmental protection

Transport ECOTECEuropean

Coordination

Energy ECOTEC

Transforming Communities

Think Green Forum

Integration scenarioOpening

Opportunities

Hypermarket

Free market free trade

Global Competition

Money maker

Wait & See

Plus ça change

McRae scenario

Nature and landscape

Conventional WisdomGuiding Change

Thord scenario

INTEGRATED ASSESSMENT MODELS

Computer simulation models that describe:

the cause-effect relations of a specific problem

and

the interlinkages with other problems

IA MODELS

First generation

on resource depletion and pollution

Second generation

on international environmental problems

Third generation

on sustainable development

on intangible issues

TWO TYPES OF IA-MODELS

• economic-oriented

parameterised

neo-classical/equilibrium

optimisation

poor representation of environment

e.g. DICE

• environment-oriented

process-based

complex

evaluation

poor representation of economics

e.g. IMAGE

TARGETS

ESSENTIAL

Complex models contain many interactions and feedbacks between processes

Complicated models contain many processes

COMPLEX COMPLICATED

SIMPLE = BEAUTIFUL

STRENGHTS OF IA-MODELS

• Exploration of feedbacks

• Flexible and rapid tools

• Exploration of critical uncertainties

• Communication tools

WEAKNESSES OF IA-MODELS

• High abstraction level

• Inadequate treatment of uncertainties

• Deterministic

• Limited calibration and validation

GENERAL STRUCTURE IA-MODEL CLIMATE CHANGE

Socio-economic impacts Ecological impact module

Demographic module

Atmospheric Chemistry module

Economic/Energy module

Terrestrial and Aquatic Biosphere module

Sea level rise module

Climate module

META CLIMATE INTEGRATED ASSESSMENT MODEL

A simple Integrated Assessment Model for Climate Change contains

mathematical equations

that represent

the cause-effect chain from emissions to impacts of climate change.

Here, only the greenhouse gas CO2 is taken into account.

Human activities - Emissions of CO2

EmCO2(t) = pop(t) * {En(t)/pop(t)}*{Em(t)/En(t)}

Emission CO2 - Concentration CO2

pCO2(t) = pCO2(t-1) + rf(t-1) * atmc * EmCO2(t-1)

Concentration CO2 - Radiative forcing

QCO2 = {Q2*CO2(t)/Ln(2)}/{Ln[pCO2(t)/pCO2in(t)]}

META CLIMATE INTEGRATED ASSESSMENT MODEL continued

META CLIMATE INTEGRATED ASSESSMENT MODEL continued

Radiative forcing - Emission of CO2

Teq(t) = {QCO2(t)/}

Equilibrium Temperature Change - Transient Temperature Change

Ttranssa(t) = {f *Teq + kToc}/{f + k}

Global-Mean Transient Temperature Change - Regional Temperature Change

Tregt(t) = 1/n {[Tregi(t)/Teq(t)] * Ttrans(t)}

n=1 Tregt(t) ={ Treg(t)/Teq(t)} * Ttrans(t)

n

i = 1

META CLIMATE INTEGRATED ASSESSMENT MODEL continued

Transient Temperature Change - Sea level Change

Seaglac(t) = * Ttrans (t) * e- Ttrans(t)/

Transient Temperature Change - Malaria Incidence Change

Nmal(t) = k * {-log(p)/a2p2}

Sea level Change - Adaptation Costs

Cadap(t) = Cdikes (t) + Cdunes(t) + Cwater(t)

f(safety-index) f(coastal retreat)