The SSP (Shared Socioeconomic Pathways) and
Scenarios
JAE EDMONDS, RICHARD MOSS AND JIYONG EOM
Joint GCAM Community Modeling Meeting and GTSP Technical Workshop
Joint Global Change Research Institute
College Park, Maryland, USA
19 September 2012
Scenarios
!   There is no limit to the number of
scenarios that could potentially
be used as a point of reference
for IAV research.
!   SRES (2000)
Scenarios
!   There is no limit to the number of
scenarios that could potentially
be used as a point of reference
for IAV research.
!   SRES (2000)
!   The design of the research
program for the next generation
of assessments included both the
RCPs and a “parallel process.”
Motivation for the Parallel Process
!   Better climate assessment; and better assessment in general.
!   One that added a new dimension to link IAM, IAV and CM.
!   New storylines and scenarios to provide a set of potentially usable
points of common references for analysis.
Climate
Modeling
Integrated
Assessment
Modeling
New Sto
ryli
and Sce nes
narios
The SSPs Impacts,
Adaptation &
Vulnerability
Research
Shared Socioeconomic Pathways (SSPs)
!
!
Narrative Storylines,
Quantitative scenarios (demographics, economics, technology), and
!
Other socieoeconomic indicators.
Narra$ve Storyline: The storyline is a verbal descrip6on of the state of the world. All non-­‐
quan6ta6ve aspects of the scenario are included in the storyline. !
Narrative Storylines are on the web and
OPEN FOR COMMENT
through the end of September.
h;ps://www.isp.ucar.edu/narra$ves-­‐ssps-­‐working-­‐group !
Preliminary demographic and
economic assumptions are on the web
and OPEN FOR COMMENT.
IAM Quan$ta$ve Variables that define IAM reference “no-­‐climate-­‐policy” scenario inputs. E.g. reference scenario popula6on by region by year. GDP, Technology Availability. h;ps://secure.iiasa.ac.at/web-­‐apps/ene/SspDb/ Non-­‐IAM Quan$ta$ve Variables that define reference “no-­‐climate-­‐policy” scenario, but which are not IAM drivers. E.g. governance index or ecosystem produc6vity and sensi6vity. Shared Socioeconomic Pathways
(SSPs)
!
SSPs are being used to develop NEW SCENARIOS to explore a
range of future societal circumstances that exhibit a wide range of
! Challenges to adaptation, and
! Challenges to mitigation.
Shared Socioeconomic Pathways
(SSPs)
!
SSPs are designed
to provide a link
between the RCPs
and the CMIP5
climate ensembles.
Reference SSP 1 SSP 2 SSP 3 SSP4 SSP5 X X X X X SPAs RCP Replica6on 8.5 Wm-­‐2 X 6.0 Wm-­‐2 X X X X X 4.5 Wm-­‐2 X X X X X 2.6 Wm-­‐2 X X X Shared Socioeconomic Pathways
(SSPs)
!
!
Storylines,
Quantitative scenarios (demographics, economics, technology), and
!
Other socieoeconomic indicators.
!
SSPs are being used to develop NEW SCENARIOS to explore a
range of future societal circumstances that exhibit a wide range of
! Challenges to adaptation, and
! Challenges to mitigation.
!
SSPs are designed to provide a link between
the RCPs and the CMIP5 climate ensembles.
! The FRAMEWORK paper
http://www.isp.ucar.edu/sites/default/files/Scenario_FrameworkPaper_15aug11_0.pdf
PRELIMINARY ASSUMPTIONS FOR
SSPS: POPULATION & GDP
IIASA Populations by SSP and GCAM
Region
OECD’s total GDP and Per Capita GDP
by SSP and GCAM Region
s
Technology
NEW SSP Pop & GDP
GCAM DRAFT SSP Input Assumptions
SSP1 Sustainability SSP2 Middle of the Road SSP3 Fragmenta$on SSP4 Inequality SSP5 Development First 2100 Popula$on [billion] (IIASA) 7.2 (5th) 9.8 (3rd) 14.1 (1st) 11.8 (2nd) 7.7 (4th) 2100 GDP [trillion 2005 USD, PPP] (OECD) 770 (2nd) 684 (3rd) 355 (5th) 461 (4th) 1,205 (1st) Energy Service Demands Low Medium High Medium High End-­‐Use Technology High Medium Low Low / High Medium Nuclear / CCS Low Medium Medium Mixed Medium Renewable Technology High Medium Low High Medium Fossil Fuel Extrac$on Low Medium High Medium High Crop Yield Improvement High Medium Low Low / Medium High Accession to Carbon Market All Instantaneous Delayed Delayed Delayed Delayed GCAM SSP SCENARIOS
End-of-the-Century Radiative Forcing in
Reference Scenarios (relative to RCPs)
We feel that it is important to have at least one scenario with RF > 8.5 Wm-­‐2 RCP 8.5 1313ppm CO2equiv
RCP 6.0 800ppm CO2equiv
RCP 4.5 630ppm CO2equiv
RCP 2.6 475ppm CO2equiv
2005
End-of-the-Century Radiative Forcing in
Reference Scenarios (relative to RCPs)
RCP 8.5 1313ppm CO2equiv
RCP 6.0 800ppm CO2equiv
RCP 4.5 630ppm CO2equiv
We would prefer to have some scenarios with RF < 6.0 Wm-­‐2 RCP 2.6 475ppm CO2equiv
2005
Preliminary assump6ons for popula6on and GDP Bas van Ruijven is sponsored by the Na6onal Science Founda6on SSP Quan6fica6on •  Country level projec6ons for: –  Popula6on •  IIASA –  Urbaniza6on •  NCAR –  Economy •  OECD •  IIASA •  PIK Global popula6on for five SSPs s15
n
o
ill 14
i
B
13
n
i n
o
it 12
al
u11
p
o
P10
9
8
7
6
ssp1
ssp2
ssp3
ssp4
ssp5
China-­‐ Propor6on Aged 65+ for five SSPs 0.6
0.5
+
5
6
0.4
d
e
g
A
n0.3
o
it
r
o0.2
p
o
r
P
0.1
0
ssp1
ssp2
ssp3
ssp4
ssp5
World-­‐ Propor6on At least Secondary for popula6on aged 20-­‐39 for five SSPs 1
0.9
0.8
+c0.7
e
S0.6
n
o
it0.5
r
o0.4
p
o
r0.3
P
0.2
0.1
0
ssp1
ssp2
ssp3
ssp4
ssp5
Urbaniza6on Projec6on Results 100 Western Europe 80 SSP1 Fast 70 SSP2 Central SSP3 Slow SSP4 Fast/Central SSP5 Fast La6n America 60 China 50 40 30 20 Year 2100 2090 2080 2070 2060 2050 2040 2030 2010 2000 1990 1980 1970 0 1960 10 2020 Eastern Africa 1950 % urban popula$on 90 Global GDP levels by scenario SSP5>SSP1>SSP2>SSP4>SSP3; range wider in per capita terms
1.4E+15
180000
World (OECD projection)
GDP per GDP: capita: World (OECD projection)
18fold increase 160000
1.2E+15
140000
1E+15
120000
8E+14
100000
80000
6E+14
60000
4E+14
5 fold increase 40000
2E+14
20000
SSP1new
SSP2new
SSP3new
SSP4new
3 fold increase SSP5new
0
2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 2090 2095 2100
Global GDP levels by scenario Often: IIASA start high, end low; PIK start low, end high; OECD in between. But not always!
SSP -­‐ Per Capita GDP (billion US$2005PPP / million people)
160
140
SSP2 -­‐ IIASA -­‐ World
SSP5 SSP1 SSP3 SSP4 -­‐ IIASA -­‐ World
SSP2 -­‐ PIK -­‐ World
SSP1 SSP3 SSP4 SSP5 -­‐ PIK -­‐ World
SSP2 -­‐ OECD -­‐ World
SSP1 SSP3 SSP4 SSP5 -­‐ OECD -­‐ World
-­‐ IIASA -­‐ World
SSP2 -­‐SSP2 IIASA -­‐ World
PIK -­‐ World
SSP2 -­‐SSP2 PIK -­‐-­‐World
-­‐ OECD -­‐ World
SSP2 -­‐SSP2 OECD -­‐ World
120
120
100
100
80
80
60
60
40
40
20
20
0
0
1980
1980
1990
1990
2000
2000
2010
2010
2020
2020
2030
2030
2040
2040
2050
2050
2060
2060
2070
2070
2080
2080
2090
2090
2100
2100
Popula6on (Indonesia) 450
400
Million Persons
350
History
300
SSP1
250
SSP2
200
SSP3
150
SSP4
100
SSP5
50
0
1950
1970
1990
2010
2030
2050
SSP1 and SSP5 have high urbaniza$on SSP5: Jakarta becomes Indonesia’s single megacity (e.g. Singapore) SSP1: Mul6ple medium scale ci6es around the country Urbaniza6on (Indonesia) 100%
90%
Urban populaation
80%
70%
History
60%
SSP1
50%
SSP2
40%
SSP3
30%
SSP4
20%
SSP5
10%
0%
1950
1970
1990
2010
2030
2050
GDP per capita (Indonesia) 40000
Int $ per capita (PPP)
35000
30000
History
25000
SSP1
20000
SSP2
SSP3
15000
SSP4
10000
SSP5
5000
0
1950
1970
1990
2010
2030
2050
IAV indicators Working Group •  Addi6onal indicators for IAV research –  Income distribu6on (mul6-­‐model process) –  Governance (Earth System Governance) –  Health (mul6-­‐model process) –  Spa6al popula6on projec6ons –  Conflicts DISCUSSION
BACKUP SLIDES
SSPs have three elements
Narra$ve Storyline: The narra6ve storyline is a verbal descrip6on of the state of the world. All non-­‐quan6ta6ve aspects of the scenario are included in the storyline. IAM Quan$ta$ve Variables that define IAM reference “no-­‐climate-­‐policy” scenario inputs. E.g. reference scenario popula6on by region by year. GDP, Technology Availability. Non-­‐IAM Quan$ta$ve Variables that define reference “no-­‐climate-­‐policy” scenario, but which are not IAM drivers. E.g. governance index or ecosystem produc6vity and sensi6vity. GCAM Technology Building Blocks
High Tech
Med Tech
Low Tech
Lower Tech
Nuclear Power
Lower capital recovery factor with capital and O&M costs declining at 0.3% per year
Base capital recovery factor with capital and O&M costs declining at 0.1% per year
Higher capital recovery factor with fixed capital and O&M costs
No new nuclear power plant
Carbon Capture & Storage (CCS)
Lower-­‐cost non-­‐tradable regional land-­‐
based storage with larger capacity, expensive global-­‐access offshore storage
Non-­‐tradable regional land-­‐based storage combined with expensive global-­‐access offshore storage
Total available resource to 5% of the medium case. Cost scales up rapidly without offshore storage
No deployment
Fossil Fuel Extrac$on
Extrac6on costs of coal, oil, and gas resource drop by 0.75% per year
Extrac6on costs of coal, oil, and gas resource drop by 0.5% per year
Extrac6on costs of coal, oil, and gas resource drop by 0.25% per year
NA
Advanced Grid for Renewable Tech
1:1 backup required when renewables supply 50% of capacity
1:1 backup required when renewables (central PV, CSP, rooqop PV, wind) supply 25% of capacity
1:1 backup required when renewables supply 15% of capacity
NA
Solar Tech
Capital and O&M costs decline at a faster rate (double)
Capital and O&M costs decline
Capital and O&M costs decline at a slower rate (50%)
NA
Wind Tech
Capital and O&M costs drop at 0.5% per year
Capital and O&M costs drop at 0.25% per year
Capital and O&M costs do not drop
NA
Geothermal Tech
Faster improvement in hydrothermal / EGS available with the improvement rate of 0.5% per year or more
Building Tech
Faster improvements in end-­‐use efficiencies
Transporta$on Tech
Base improvement in hydrothermal / EGS available only aqer the exhaus6on of No improvement in hydrothermal / EGS not available
hydrothermal resource / EGS improves at 0.25% per year or more
Base improvements in end-­‐use efficiencies
Slower improvements in end-­‐use efficiencies Faster declines in fuel intensi6es in all Slower declines in fuel intensi6es in all Base declines in fuel intensi6es in all modes
modes modes
NA
NA
NA
Industry Tech
Faster improvements in end-­‐use efficiencies
Base improvements in end-­‐use efficiencies
Slower improvements in end-­‐use efficiencies NA
Crop Produc$on
Crop yield improvements converging to 0.5% per year by 2050
Crop yield improvements converging to 0.25% per year by 2050
Crop yield improvements converging to 0% per year by 2050
NA
31
Global Total Primary Energy
Global Primary Energy (-2095)
SSP1
2000
SSP1
SSP2
SSP2
SSP3
1000
SSP3
1500
SSP4
[EJ/yr]
SSP5
[EJ/yr]
IPCC SRES (2000) Range
1500
SSP4
SSP5
1000
500
2085
2075
2065
2055
2045
2035
2025
2015
0
2005
2050
2045
2040
2035
2030
2025
2020
2015
2010
0
2005
500
2095
Global Primary Energy (-2050)
Global Total CO2 Emissions
Global CO2 Emissions (-2095)
Global CO2 Emissions (-2050)
30
SSP1
SSP2
SSP2
30
SSP3
20
SSP3
SSP4
[EJ/yr]
[EJ/yr]
SSP4
SSP5
SSP5
20
10
2085
2075
2065
2055
2045
2035
2025
0
2015
2050
2045
2040
2035
2030
2025
2020
2015
2010
2005
0
2005
10
2010 Actual (CDIAC)
2095
SSP1
IPCC SRES (2000) Range
40
Land Use Change Emissions
THE MATRIX
Into the Matrix where SSPs spawn RCP
Replications
SSPs The Movie:
The Matrix Architects
Reference SSP 1 SSP 2 SSP 3 SSP4 SSP5 X X X X X SPAs RCP Replica6on 8.5 Wm-­‐2 X 6.0 Wm-­‐2 X X X X X 4.5 Wm-­‐2 X X X X X 2.6 Wm-­‐2 X X X GCAM SPAs:
Accession to Global Carbon Market
Instantaneous Accession Scenario Delayed Accession Scenario Joins in 2070: • Africa global price by 2085 Global Carbon Tax from 2015: All global regions • India / La6n Joins in 2050: America / Southeast global price by 2065 Asia • USA / China / Joins in 2030: Canada / Australia / global price by 2045 NZ / Korea Europe / Global Carbon Tax • Western Eastern Europe / from 2015 Japan !   In delayed accession scenario, Former Soviet Union and Middle East Never
Join the global carbon market.
37
Global Primary Energy by Fuel: SPA 4.5 Scenarios
All Instantaneous / UCT Delayed Accession / UCT Delayed Accession / FFICT Land Use Change Emissions
Urbaniza6on assump6ons SSP 1 SSP 2 Urbaniza$on Feature SSP 4 SSP 5 Fast / Central Fast Country Income Groupings SSP Element SSP 3 Fast Central Slow environmentally friendly living arrangement, extension of current una;rac$ve ci$es, resource-­‐efficient trend limited mobility compact ci$es Privileged ci$es, amenity for elite, poor facility for the rest man-­‐made environment a;rac$ve ci$es with comfort, accommodate smaller in an aged popula$on in the society sprawled urban Common interpreta6on of the SSPs SSP1: Sustainability SSP2: Middle of the road SSP3: Fragmenta6on SSP4: Inequality SSP5: Conven6onal development Fron$er TFP growth Speed of convergence Medium high High Medium Medium Low Low Medium Low Income: Low Middle Income: Low High Income: Medium High High N.B. Quan6ta6ve interpreta6ons and methodology differ between models, illustra6ng the uncertain6es in making economic projec6ons 41 Educa6on Scenarios •  The fast track (FT) scenario is extremely ambi6ous; it assumes that all countries expand their school systems at the fastest possible rate, which would be comparable with best performers in the past such as Singapore and South Korea . •  The global educa5on trend (GET) scenario is more moderately op6mis6c and assumes that countries will follow the average path of school expansion that other countries already somewhat further advanced in this process have experienced. •  The constant enrollment rate (CER) scenario assumes that countries only keep the propor6ons of cohorts avending school constant at current levels. •  The most pessimis6c scenario, constant enrollment numbers (CEN), assumes that no more schools at all are being built and that the absolute number of students is kept constant, which under condi6ons of popula6on growth means declining enrollment rates. Country Groupings •  For defining these scenarios we dis6nguish among three groups of countries: •  High Fer5lity Countries (HiFert): Countries with current level of fer6lity less than 2.9 children per woman (2005-­‐2010). •  Low Fer5lity Countries (LoFert) Countries with current level of fer6lity less than or equal to 2.9 not belonging to Rich OECD countries (see below) •  High Income-­‐OECD Countries (Rich-­‐OECD) As per the defini6on of World Bank. Defini6on of assump6ons