update: socioeconomic narrative discovery for the fifth ipcc assessment report vanessa schweizer,...
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Update: Socioeconomic narrative discovery for the Fifth IPCC Assessment Report
Vanessa Schweizer, ASP Postdoctoral Fellow
ASP Research Review, NCARNovember 10, 2011
Overview of the new scenario framework
3
Representative concentration pathways
Inman, 2011
Scenario uncertainty dominates
What types of worlds could these be?
Is adaptation effective?
Is global wealth distributed more equitably?
How is land used?
Concept map for AR5 parallel process
SharedSocioeconomicPathways
O’Neill & Schweizer, 2011
Socioeconomic challenges to mitigation
Socioeconomic challenges to adaptation
5
Qualitative characterization of narrative space
Scenario elements affecting challenges to mitigation might affect challenges to adaptation and vice versa
Core Writing Team, 2011
A systematic approach to SSP definition
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A systematic proposalI. Operationalize concepts in axes for each SSP; II. Transparently evaluate internally
consistent combos of SSP elements
Determinants for SSP axes
Baseline emissions
Mitigation capacity
Adaptive capacity
Sensitivity
SSP elements
Population
Income
C intensity
Extreme poverty
Element pathways
Low/Med/HighQuant ranges
Cross-impact balance (CIB)
analysis
Inconsistency scores
Consistent combinations
of states in SSP space
Mapping of pathways to
SSP axes
Population(H), Income(M), C intensity(H), Equity(L)?
Population(M), Income(M), C intensity(M), Equity(M)?
Population(L), Income(H), C intensity(L), Equity(M)?
8
How we approached the stepsI. Operationalize concepts in axes for each SSP;
Indexing of pathways to
SSP axes
Ordinal scaling of L/M/H pathways for each element
Determinants for SSP axes
SSP elements
Expert Internet survey on challenges to mitigation, adaptation(n = 27)
Element pathways
Low/Med/HighProjections, scenario review
Expert elicitations on pathway interrelationships (n = 13)
Cross-impact balance (CIB)
analysis
Inconsistency scores
Mathematical software package
Consistent combinations
of states in SSP space
Identification of unique qualities of SSP domains
(n=1000)
II. Transparently evaluate internally consistent combos of SSP elements
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I. Operationalizing concepts in axes for each SSP
10
Elements: Challenges to mitigation, adaptation
• Internet survey sent to participants of Berlin IPCC workshop on new socioeconomic scenarios, Korea scenario matrix architecture meeting, select WGII lead authors for the AR5 (early responders, n = 27)
• Top elements for challenges to mitigation
• Top elements for challenges to adaptation
Average income Energy intensity Energy-related technological change
Population Carbon intensity Agricultural productivity
Average income Urbanization Education Coastal population
Extreme poverty Governance Water scarcity Innovation capacity
11
Element pathways: Low, Medium, High
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II. Transparent evaluation of internally consistent combinations of SSP elements
13
What does it mean for combinations of SSP elements to be internally consistent?
With CIB analysis, internally consistent combinations “evoke a self-consistent network of influences”; can be considered self-reinforcing (Weimer-Jehle 2006, p. 342)
Inconsistent combinations instead evoke corrections
Population
Education
Income per capita
High
Low
High
Low
X
X
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Pairwise judgments underpin consistency
Evaluation according to 7-point Likert scale
-3 3Strongly Stronglydiscourage encourage pathway pathway
Target variable:
ROW VARIABLES INFLUENCE COLUMN VARIABLE èèèè Confidence of +/-
judgmentConfidence in
judging importance L M HEducational attainment (post-primary) Guess Accepted Guess Accepted
Low (<65% global population) è 3 -1 -2 ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢
Med (65%-75% population) è -2 3 -1 ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢
High (>75% global population) è -2 -1 3 ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢ ¢
Income
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Flavor of cross-impact balances Pop GDP/cap
E intensity
C intensity
E tech chg Ag prod Urban
L M H L M H L M H L M H L M H L M H L M HPopulation Low (< 8 billion) -1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Medium (8-13 billion) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 High (> 13 billion) 0 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 1Average income Low (annual growth < 1.5%) -1 0 1 -2 0 2 -1 0 1 3 0 -3 0 0 0 1 1 -2 Med (1.5% - 2.0% growth/yr) -1 1 0 -1 0 1 0 0 0 -1 1 0 0 0 0 0 1 -1 High (annual growth > 2.0%) 1 0 -1 2 0 -2 1 0 -1 -3 0 3 0 0 0 -1 -1 2Total primary energy intensity Low (> 1% decrease/yr) 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0 0 0 Med (0.5% - 1.0% decrease/yr) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 High (< 0.5% annual decrease) 0 0 0 0 0 0 -1 0 1 0 0 0 0 0 0 0 0 0Average carbon intensity Low (>0.5% decrease/yr) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Med (0.1% - 0.5% decrease/yr) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 High (<0.1% decrease/yr) 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Rate of technological change: Energy Low (AEEI ~0.5% per year) 0 0 0 1 0 -1 -2 0 2 -3 0 3 1 0 -1 0 0 0 Med (AEEI ~1.0% per year) 0 0 0 0 0 0 -1 0 1 0 1 -1 -1 1 0 0 0 0 High (AEEI ~1.5% per year) 0 0 0 -1 0 1 2 0 -2 3 0 -3 -1 0 1 0 0 0Agricultural productivity Low (<0.75% improvement/yr) 0 0 0 2 0 -2 0 0 0 -2 0 2 0 0 0 1 0 -1 Med (0.75% - 1.25% improvement/yr) 0 0 0 0 0 0 0 0 0 0 1 -1 0 0 0 -1 1 0 High (>1.25% improvement/yr 0 0 0 -2 0 2 0 0 0 2 0 -2 0 0 0 -1 0 1
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Frequency distribution for inconsistency scores
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
0
50,000
100,000
150,000
200,000
5 30 2971,450
6,14319,253N
umbe
r of d
iffer
ent c
ombi
natio
ns
Inconsistency score(Best) (Worst)
Cumulative # combinations > 1.5 million
17
SSP element pathways, axes
Y-axis: Challenges to mitigation
• Population (Pop)
• Energy intensity (EI)
• Carbon intensity (CI)
• Agricultural productivity (AgP)
• Energy-related technological change (Tech)
HIGH challenges
MEDIUM challenges
LOW challenges
All pathways Medium
Pop(L), EI(L), CI(L), AgP(H), Tech(H)Chal
leng
es to
miti
gatio
n
Pop(H), EI(H), CI(H), AgP(L), Tech(L)
18
SSP element pathways, axes
X-axis: Challenges to adaptation
• Extreme poverty (XPov)
• Water scarcity (-H2O)
• Average income (GDP)
• Education (Ed)
• Governance (Gov)
• Innovation capacity (Innov)
• Agricultural productivity (AgP)
MEDIUM challenges
LOW challenges
All pathways Medium
XPov(L)-H2O(L)GDP(H)Ed(H)Gov(H)Innov(H)AgP(H)
HIGH challenges
Challenges to adaptation
XPov(H)-H2O(H)GDP(L)Ed(L)Gov(L)Innov(L)AgP(L)
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Mapping 1000 consistent membersCh
alle
nges
to m
itiga
tion
Challenges to adaptation
Equal weightingSSP 1: 483SSP 2: 187 SSP 3: 193SSP 4: 084SSP 5: 053
3-tiered weightingSSP 1: 358SSP 2: 162SSP 3: 241SSP 4: 030SSP 5: 209
20
Interpreting domain characteristics
SSP1 SSP2 SSP3 SSP4 SSP50%
10%20%30%40%50%60%70%80%90%
Population pathways
Low Medium High
Mitigation challenges Both Adaptation challenges
Pop EI CI Tech AgP GDP XPov -H2O Gov Innov
SSP1
SSP2
SSP3
SSP4
SSP5
SSP1 SSP2 SSP3 SSP4 SSP50%
10%20%30%40%50%60%70%80%90%
100%Energy intensity pathways
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Summary of domain characteristics
SSP2: Most variety in outcomes for challenges to adaptation -- Opposing outcomes “cancel” in SSP mapping; heterogeneity averages to medium challenges -- At localized scales, challenges could actually be high or low
SSP4: Divergence in mitigation and adaptation challenges -- 80% have low pathways for aggregate quality of governance; keeps adaptation challenges high -- Difficult to characterize “mixed world” further without separate regions in basic SSPs
SSP5: Most members resemble SSP2, but clearly have lower challenges to adaptation -- 100% of members have high pathways for aggregate quality of governance
Mitigation challenges Both Adaptation challenges
Pop EI CI Tech AgP GDP XPov -H2O Gov Innov
SSP1
SSP2
SSP3
SSP4
SSP5
22
Conclusions for SSP domains
• Preliminary results suggest an essential element for challenges to adaptation is quality of governance
• Future work– Similar analysis of narrative elements specifically for
lower income economies– More judgments for element interactions to be
obtained via Internet survey– Further investigation of internally consistent
combinations that differ from SSP archetypesYour comments are appreciated! [email protected]
References
Core Writing Team (2011) A framework for a new generation of socioeconomic scenarios for climate change impact, adaptation, vulnerability and mitigation research, August. Available at http://www.isp.ucar.edu/socio economic-pathways.‐
Inman, M. (2011) Opening the Future. Nature Climate Change, 1, 7-9.O’Neill, B.C. and Schweizer, V. (2011) Mapping the Road Ahead.
Nature Climate Change, 1, 352-353.UCAR (2011) Socioeconomic Pathways for Climate Change Research.
http://www.isp.ucar.edu/socio-economic-pathways.Weimer-Jehle, W. (2006) Cross-impact balances: A system-theoretical
approach to cross-impact analysis. Technological Forecasting and Social Change, 73, 334-361.
BACKUP
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Detailed concept map for AR5 parallel process
Emissions
Concen-trations
Climate change
Climate variability
Exposureto climatic stimuli
Residual impactsof climate change
Non-climatic factors
Adaptive capacity
Sensitivityto climatic stimuli
Non-climatic drivers
Mitigative capacity
Policies affecting
mitigation
Policies affecting
adaptation
Füssel & Klein, 2006 adapted by O’Neill & Schweizer
Forcing
SSPsRCPs
Climate Modeling Integrated Assessment Modeling Impacts, Adaptation, Vulnerability
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Scenario matrix architecture enables new research questions
LEFT: Costs, benefits of mitigation for certain set of socioeconomic conditions
RIGHT: Anticipation of mitigation, adaptation,
unavoidable climate impacts for different socioeconomic
futures at some level of climate forcing
27
Issues with narratives
I don’t like any of these SSPs – can we go back to the drawing board?
SSP X doesn’t seem likely – can we skip that one?
I like SSP Y – let’s focus on THAT one!
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SSP1 SSP2 SSP3 SSP4 SSP50%
10%20%30%40%50%60%70%80%90%
100%Carbon intensity pathways
SSP1 SSP2 SSP3 SSP4 SSP50%
10%20%30%40%50%60%70%80%90%
100%Energy-related technological change
Mitigation challenges Both Adaptation challenges
Pop EI CI Tech AgP GDP XPov -H2O Gov Innov
SSP1
SSP2
SSP3
SSP4
SSP5
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Combinations of element pathways
Ideally there would be a way to determine if any particular combination of narrative element pathways is internally consistent.
• Method suited for this purpose: Cross-impact balance (CIB) analysis (Weimer-Jehle 2006)
• CIB analysis requires judgments of how pathways for elements directly influence each other
• Questionnaires developed, workshops held to elicit these judgments (n = 13)