1. Update: Socioeconomic narrative discovery for the Fifth IPCC Assessment Report Vanessa Schweizer, ASP Postdoctoral Fellow ASP Research Review, NCAR November 10, 2011

2. Overview of the new scenario framework

3. Representative concentration pathways 3 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?

4. Concept map for AR5 parallel process 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 5 Core Writing Team, 2011

6. A systematic approach to SSP definition

7. A systematic proposal I. 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/High Quant 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)? 7

8. How we approached the steps I. Operationalize concepts in axes for each SSP; Indexing of pathways to SSP axes Ordinal scaling of L/M/H pathways for each element 8 Determinants for SSP axes SSP elements Expert Internet survey on challenges to mitigation, adaptation (n = 27) Element pathways Low/Med/High Projections, 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 9

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 incomeEnergy intensityEnergy-related technological change PopulationCarbon intensityAgricultural productivity Average incomeUrbanizationEducationCoastal population Extreme povertyGovernanceWater scarcityInnovation capacity 10

11. Element pathways: Low, Medium, High 11

12. II. Transparent evaluation of internally consistent combinations of SSP elements 12

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 13 Population Education Income per capita High Low High Low X X

14. Pairwise judgments underpin consistency 14 Evaluation according to 7-point Likert scale -3 3 Strongly discourage encourage pathway pathway Target variable: ROW VARIABLES INFLUENCE COLUMN VARIABLE  Confidence of +/- judgment Confidence in judging importance LMH Educational attainment (post-primary) GuessAcceptedGuessAccepted Low (<65% global population)  3 -2 Med (65%-75% population)  -2 3 High (>75% global population)  -2 3 Income

15. Flavor of cross-impact balances 15 Pop GDP/cap E intensity C intensity E tech chg Ag prod Urban LMH LMH LMH LMH LMH LMH LMH Population Low (< 8 billion) 01000 000 000 000 000 Medium (8-13 billion) 000000 000 000 000 000 High (> 13 billion) 01000 000 000 000 01 Average income Low (annual growth < 1.5%)01 -202 01 30-3 000 11-2 Med (1.5% - 2.0% growth/yr)10 01 000 10 000 01 High (annual growth > 2.0%)10 20-2 10 -303 000 2 Total primary energy intensity Low (> 1% decrease/yr)000 000 10 000 000 000 Med (0.5% - 1.0% decrease/yr)000 000 000 000 000 000 High (< 0.5% annual decrease)000 000 01 000 000 000 Average carbon intensity Low (>0.5% decrease/yr)000 000 000 000 000 000 Med (0.1% - 0.5% decrease/yr)000 000 000 000 000 000 High (<0.1% decrease/yr)000 000 000 000 000 000 Rate of technological change: Energy Low (AEEI ~0.5% per year)000 10 -202 -303 10 000 Med (AEEI ~1.0% per year)000 000 01 01 10 000 High (AEEI ~1.5% per year)000 01 20-2 30-3 01 000 Agricultural productivity Low (<0.75% improvement/yr) 000 20-2 000 02 000 10 Med (0.75% - 1.25% improvement/yr) 000 000 000 01 000 10 High (>1.25% improvement/yr 000 -202 000 20 000 01

16. Frequency distribution for inconsistency scores 16 Number of different combinations 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) 17 HIGH challenges MEDIUM challenges LOW challenges All pathways Medium Pop(L), EI(L), CI(L), AgP(H), Tech(H) Challenges to mitigation 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) 18 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)

19. Mapping 1000 consistent members 19 Challenges to mitigation Challenges to adaptation Equal weighting SSP 1: 483 SSP 2: 187 SSP 3: 193 SSP 4: 084 SSP 5: 053 3-tiered weighting SSP 1: 358 SSP 2: 162 SSP 3: 241 SSP 4: 030 SSP 5: 209

20. Interpreting domain characteristics 20 Mitigation challengesBothAdaptation challenges PopEICITechAgPGDPXPov-H2OGovInnov SSP1 SSP2 SSP3 SSP4 SSP5

21. Summary of domain characteristics 21 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 challengesBothAdaptation challenges PopEICITechAgPGDPXPov-H2OGovInnov 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 archetypes 22 Your comments are appreciated! vanessa@ucar.edu

23. References Core Writing Team (2011) A framework for a new generation of so cioeconomic 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.

24. BACKUP

25. Detailed concept map for AR5 parallel process 25 Emissions Concen- trations Climate change Climate variability Exposure to climatic stimuli Residual impacts of climate change Non-climatic factors Adaptive capacity Sensitivity to climatic stimuli Non-climatic drivers Mitigative capacity Policies affecting mitigation Policies affecting adaptation Füssel & Klein, 2006 adapted by O’Neill & Schweizer Forcing RCPs Integrated Assessment Modeling Impacts, Adaptation, Vulnerability

26. Scenario matrix architecture enables new research questions 26 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 27 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!

28. 28 Mitigation challengesBothAdaptation challenges PopEICITechAgPGDPXPov-H2OGovInnov SSP1 SSP2 SSP3 SSP4 SSP5

29. 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) 29