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

7

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 capacitySensitivity

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

9

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

12

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

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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

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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

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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 archetypes

Your comments are appreciated! vanessa@ucar.edu

ReferencesCore 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

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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 challengesPop EI CI Tech AgP GDP XPov -H2O Gov Innov

SSP1SSP2SSP3SSP4SSP5

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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)