SSP/RCP-based
scenarios:
Implementation
Detlef van Vuuren
1
Starting point: Causal chain
RCPs
Climate
SSPs
Impact
Exposed population, ability to
adapt
Drivers
(population
, GDP)
Energy
use,
Land use
Emissions
Conc./
forcing
Climate
The Scenario Matrix Architecture
SSPs
Forcing level (W/m2)
Narratives
Quantitative
drivers
Shared Socio-economic Pathways
SSP1
SSP2
SSP3
SSP4
RCPs
SSP5
Climate
8.5
IAM reference scenario
(e.g., SSP3-Ref)
Socioeconomic
information
6.0
4.5
Climate
information IAV study
2.6
IAM SSP-RCP scenario
(e.g., SSP3-4.5)
The Scenario Matrix Architecture
Forcing level (W/m2)
SSP
SPA =
= Shared
description
socio-economic
of mitigationpathway:
(to movestory
down a
RCP = trajectory of emissions
and
land-use
Shared
Socio-economic
Pathways
about
column)
how population,
and adaptation
GDP,
policies
income(to
etc.
deal
would
with
leading to a specifc forcing level
develop
climate
in
thepolicy)
future.
SSP1
SSP2 SSP3 SSP4 SSP5
8.5
6.0
Same socioeconomic pathway, different
mitigation; climate “consistent” with each
RCP’s forcing
4.5
2.6
Different socioeconomic pathways,
but
climate “consistent” with RCP 4.5
forcing
The Scenario Matrix Architecture
Shared Socio-economic Pathways
SSP2
SSP3
Challenge to mitigation
SSP1
Challenge to adaptation
SSP4
SSP5
Challenge to mitigation
SSP5: Conventional dev.
Rapid technology for fossil
High demand
High ec. Growth
Low population
SSP2:
Middle of the Road
SSP1:Sustainability
Rapid technology
High environmental
Awareness
Low energy demand
Medium-high economic growth
Low population
Challenge to adaptation
SSP3: Fragmentation
Slow technology
Development (dev-ing)
Reduced trade
V. Slow ec. growth
Very high population
SSP4: Inequality
Slow technology
High inequality
Low energy demand
Slow economic growth
High population
Key SSP elements
(three main products + IAV variables)
SSP Storylines
1
Iterative Process
Quantitative drivers 2
Population
Energy
(age, sex,
mortality, fertility,
education)
(technology,
resources, etc)
Urbanization
(national)
IAM Scenarios
Economic
development
(regional/national)
3
Emissions
Land-use
(forcing,
temperature)
(productivity,
diets, etc)
Qualitative /
quantitative
(population)
High economic
growth and
education of
women leads to
drop of fertility
SSP5
SSP3
SSP2
SSP1
D: low
I: High
D: high
I: low
D: Med
I: Med
D: Low
I: medium
Mortality D: low
I: low
D: high
I: high
D: Med
I: Med
D: Low
I: Low
Migration high
low
Medium
High
Variable
Fertility
13000
12000
High economic
growth and
investment into
health services
leads to drop of
mortality
11000
Globalised
world has high
migration rates
7000
Global population
SSP1
10000
SSP2
SSP3
9000
SSP4
SSP5
8000
6000
How low can we go?
Detlef van Vuuren – 2 February 2009
Urbanization Projection Results
100
Western Europe
80
70
Latin America
60
China
50
40
30
20
Eastern Africa
10
Source: O’Neill & Jiang,
2100
2090
2080
2070
2060
2050
Year
2040
2030
2020
2010
2000
1990
1980
1970
1960
0
1950
% urban population
90
SSP
1
Fast
SSP
2
Central
SSP
3
Slow
SSP
4
Fast/Central
SSP
5
Fast
2100
2090
2080
2070
2060
2050
2040
2030
2020
2010
GDP per capits ($/cap ‐ PPP)
160
Economic projections
140
120
SSP5
100
80
SSP1
60
SSP2
40
SSP4
20
SSP3
0
10
Order from
Strength
Energy
demand
Adapting Mosaic TechnoGarden
Global
Orchestration
lifestyle
regionalized
assumptions and assumptions
energy efficiency
investments based
on current North
American values
regionalized
assumptions
focus on domestic
Energy supply market
energy resources
liberalization;
selects least-cost
options; rapid
technology change
Climate policy No
no
some preference
for clean energy
resources
no
Depletion
11
Energy
demand
Price
Elasticity
Technology Depletion
development
Costs of
different
energy sources
Preferences
Income
Elasticity
Population
GDP
lifestyle
assumptions and
energy efficiency
investments based
on current Japan
and West
European values
preference for
renewable energy
resources and
rapid technology
change
yes,
Prices
Energy
supply
4 juni 2014
Technology
development
Costs of
different
energy sources
Trade restrictions
Climate policy
(Carbon tax)
How low can we go?
Detlef van Vuuren – 2 February 2009
Primary Energy
2500
2500
Other renewables
Nuclear
Gas
Oil
Coal
Biomass
1500
2000
1500
SSP3
IMAGE
EJ
EJ
SSP5
REMIND
1000
1000
500
500
2500
0
1850
1900
1950
Other renewables
2050
Nuclear
Gas
Oil
Coal
Biomass
2000
2000
1500
0
1850
2100
1900
1950
2000
2050
2100
2000
2050
2100
EJ
SSP2
MESSAGE
1000
500
2500
2500
2000
0
1850
Other renewables
Nuclear
Gas
Oil
Coal
Biomass
1900
1950
2000
2050
2000
Other renewables
Nuclear
2100
Gas
Oil
Coal
Biomass
SSP4
AIM
1500
1000
500
Other renewables 0
1850
Nuclear
Gas
Oil
Coal
Biomass
EJ
1500
EJ
Socio-economic
challenges for mitigation
2000
Other renewables
Nuclear
Gas
Oil
Coal
Biomass
SSP1
GCAM
1000
500
0
1850
1900
1950
2000
2050
1900
1950
2100
Socio-economic challenges
for adaptation
Mitigation,
including
land-based
mitigation
150
120
baseline
90
Sulphur
emissions
180
150
Emissions
180
60
0
2000
90
60
4.5 W/m2
2020
2040
2060
30
0
2000
2080 180 2100
2020
2040
2060
2080
2100
2020
2040
2060
2080
2100
150
120
90
60
30
200
0
2000
180
2020
2040
2060
2080 180 2100
160
150
140
120
Emissions
Challenge to mitigation
30
120
100
80
90
60
60
40
30
20
0
2000
120
2020
2040
2060
2080
2100
0
2000
Challenge to adaptation
Reconciling the old and the new:
Van Vuuren, Carter, 2014
15
4 juni 2014
16
4 juni 2014
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
17
4 juni 2014
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)
18
4 juni 2014
SSP database:
https://secure.iiasa.ac.at/web-apps/ene/SspDb