SSP/RCP-based scenarios: · PDF fileRCPs SSPs Climate Starting point: Causal chain Drivers (population, GDP) Energy use, Land use Emissions Conc./ forcing Climate Exposed population,

1

SSP/RCP-based scenarios: Implementation

Detlef van Vuuren

RCPsClimateSSPs

Starting point: Causal chain

Drivers (population

, GDP)

Energy use,

Land useEmissions Conc./

forcing Climate

ImpactExposed population, ability to adapt

Forc

ing

leve

l (W

/m

2)

8.5

6.0

4.5

2.6

SSP1 SSP2 SSP3Shared Socio-economic Pathways

SSP4 SSP5RCPsClimateSSPs

NarrativesQuantitative

drivers

IAM reference scenario(e.g., SSP3-Ref)

IAM SSP-RCP scenario(e.g., SSP3-4.5)

The Scenario Matrix Architecture

IAV study

Socioeconomicinformation

Climateinformation

Forc

ing

leve

l (W

/m

2)

8.5

6.0

4.5

2.6


SSP4 SSP5

Different socioeconomic pathways, butclimate “consistent” with RCP 4.5 forcing

Same socioeconomic pathway, different mitigation; climate “consistent” with each RCP’s forcing


RCP = trajectory of emissions and land-useleading to a specifc forcing level

SSP = Shared socio-economic pathway: story about how population, GDP, income etc. would

develop in the future.

SPA = description of mitigation (to move down a column) and adaptation policies (to deal with

climate policy)


SSP4 SSP5


Challenge to adaptation

Cha

lleng

e to

miti

gatio

n


Cha

lleng

e to

miti

gatio

n

SSP1:SustainabilityRapid technologyHigh environmentalAwarenessLow energy demandMedium-high economic growthLow population

SSP2:Middle of the Road

SSP3: FragmentationSlow technologyDevelopment (dev-ing)Reduced tradeV. Slow ec. growthVery high population

SSP4: InequalitySlow technologyHigh inequalityLow energy demandSlow economic growthHigh population

SSP5: Conventional dev.Rapid technology for fossilHigh demandHigh ec. GrowthLow population

Key SSP elements(three main products + IAV variables)

SSP StorylinesSSP Storylines

Population(age, sex,

mortality, fertility, education)

Urbanization(national)

Economic development(regional/national)

Quantitative drivers

Energy(technology,

resources, etc)

Emissions(forcing,

temperature)

Land-use(productivity,

diets, etc)

IAM Scenarios

1

2 3

Iterative Process

How low can we go? Detlef van Vuuren – 2 February 2009

Qualitative / quantitative(population)

VariableSSP5 SSP3 SSP2 SSP1

Fertility D: lowI: High

D: highI: low

D: MedI: Med

D: LowI: medium

Mortality D: lowI: low

D: highI: high

D: MedI: Med

D: LowI: Low

Migration high low Medium HighHigh economic

growth and education of

women leads to drop of fertility

High economic growth and

investment into health services leads to drop of

mortality

Globalised world has high migration rates

6000

7000

8000

9000

10000

11000

12000

13000

SSP1

SSP2

SSP3

SSP4

SSP5

Global population

Urbanization Projection Results

0

10

20

30

40

50

60

70

80

90

100

1950

1960

1970

1980

1990

2000

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

% u

rban

pop

ula

tion

Year

Western Europe

Latin America

China

Eastern Africa

SSP1

Fast

SSP2

Central

SSP3

Slow

SSP4

Fast/Central

SSP5

Fast

Source: O’Neill & Jiang,

10

0

20

40

60

80

100

120

140

160

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

GDP pe

r cap

its ($/cap

‐PP

P) SSP5

SSP3

SSP2

SSP4

SSP1

Economic projections

4 juni 201411 How low can we go? Detlef van Vuuren – 2 February 2009

Global Orchestration

Order from Strength

Adapting Mosaic TechnoGarden

Energy demand

lifestyle assumptions and energy efficiency investments based on current North American values

regionalized assumptions

regionalized assumptions

lifestyle assumptions and energy efficiency investments based on current Japan and West European values

Energy supply market liberalization; selects least-cost options; rapid technology change

focus on domestic energy resources

some preference for clean energy resources

preference for renewable energy resources and rapid technology change

Climate policy No no no yes,

PopulationGDP

IncomeElasticity

Energy demand

Costs of differentenergy sources

Depletion Technologydevelopment

Preferences

Energy supply

Costs of differentenergy sources

Depletion Technologydevelopment

Trade restrictions

PricesPriceElasticity

Climate policy(Carbon tax)

Socio-economic challengesfor adaptation

Soc

io-e

con

omic

chal

len

ges

for

mit

igat

ion

1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000

2500Other renewablesNuclearGasOilCoalBiomass

1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


1850 1900 1950 2000 2050 2100E

J0

500

1000

1500

2000


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


Other renewablesNuclearGasOilCoalBiomass

Primary Energy

SSP3IMAGE

SSP5REMIND

SSP2MESSAGE

SSP4AIMSSP1

GCAM

Mitigation, including land-based mitigation

Cha

lleng

e to

miti

gatio

n


2000 2020 2040 2060 2080 21000

20

40

60

80

100

120

140

160

180

2002000 2020 2040 2060 2080 21000

30

60

90

120

150

180 2000 2020 2040 2060 2080 21000

30

60

90

120

150

180

Emis

sion

s2000 2020 2040 2060 2080 21000

30

60

90

120

150

180

Emis

sion

s

2000 2020 2040 2060 2080 21000

30

60

90

120

150

180

4.5 W/m2

Sulphuremissions

baseline

4 juni 201415

Reconciling the old and the new:

Van Vuuren, Carter, 2014

4 juni 201416

Process of the quantification group GDP and population data : finished March 2013 (IIASA, OECD, PIK) IAM teams elaborating scenarios (IIASA, PIK, PBL, GCAM, NIES,

FEEM….). June/July 2014: final submission Special Issue on SSPs in GEC (storylines, GDP, population, IAMs) From Summer 2014: Data available for impact/mitigation studies Summer 2014?: Decisions on use of scenarios in CMIP6

4 juni 201417

Conclusions SSPs: combination of storylines and initial, global, quantification Storylines can be the basis of downscaling / use outside original

domain:– SSP1: Sustainable dev. world (env. tech, good governance, low

popultation, wealthy, social/env goals important)– SSP2: Medium– SSP3: Fragmented world (regional competition, low tech., little

trade, poor)– SSP4: Fragmentation in regions (strong rich/poor divide, poor on

average)– SSP5: High economic growth (strong technology, fossil fuel

driven, consumption, human development)

4 juni 201418

SSP database: https://secure.iiasa.ac.at/web-apps/ene/SspDb

Documents

SSP/RCP-based scenarios: · PDF fileRCPs SSPs Climate Starting point: Causal chain Drivers (population, GDP) Energy use, Land use Emissions Conc./ forcing Climate Exposed population,