Socioeconomic narrative discovery for the Fifth IPCC Assessment Report

1. Socioeconomic narrative discovery for the Fifth IPCC Assessment Report Vanessa Schweizer, ASP Postdoctoral Fellow ASP Research Review, NCAR April 13, 2011

2. Framework for scenarios in AR5

3. Representative concentration pathways What types of worlds could these be? Is adaptation effective? Is global wealth distributed more equitably? How is land used? Scenario uncertainty dominates Inman, 2011

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

5. Research needs under new socioeconomic scenario framework

6. Qualitative characterization of narrative space Scenario drivers affecting challenges to mitigation might affect challenges to adaptation and vice versa Kriegler et al., 2010

7. 4 determinants of new narrative axes • Baseline emissions • Mitigation capacity *For SSP 1 & SSP 4, differences in regional developments will also matter. • Sensitivity • Adaptive capacity

9. Identifying internally consistent narratives for socioeconomic scenarios

10. Assessing scenario consistency Traditionally, two checks provide confidence of internal consistency: • Plausibility of storyline • At least one established IA model finds the scenario solvable Note: Through these approaches, scenarios are selected or discovered by analysts; have been the results of partial exploration of possibility space. Questions: • Is “laugh test” sufficient for plausibility? (particularly for climate change ARs) • Do other interesting internally consistent scenarios exist, which the research community has overlooked?

11. A more systematic approach With cross-impact balance (CIB) analysis, an “expert” judges cross-impacts between scenario descriptors, two at a time. • Decomposition of system: If the only information you have about the system is that factor X has state x, would you evaluate the direct influence of X on Y as a clue that • Factor Y has state y (promoting influence)? OR • Factor Y does not have state y (restricting influence)? • Evaluation according to 7-point Likert scale

12. Judgments assembled as matrix Schweizer & Kriegler, 2011, under review (full baseline CIB matrix constructed with ScenarioWizard 2.0 beta (Weimer-Jehle, 2007))

13. Linked CIBA structure Results across levels consistent with each other narrow the set of consistent futures to consider Consistency check… Implies… World X Region A1 Region B1 Global M Region C1 World Y Region A2 Global N Region B2 Region C2 13

14. Top-down, bottom-up relationships Global CIB matrix descriptors Energy research focus Tech change: Fossil substitutes Tech change: Energy intensity Tech change: Biofuels Tech change: Emissions control Tech change: Fertilizers Regional CIB matrix descriptors Int’l research & learning Tech change: Crops Tech change: Meat Technology transfer Population Meat demand H2O-stressed population Coastal population Disaster prep Income Technology diffusion Infrastructure Innovation capacity Government accountability Citizen access to government Health Equity Education Insurance availability

15. Simple linked CIBA World X • Region A: OECD • Region B: ROW • Regional dynamics: • Income (GDP/capita) • Education (net secondary enrollment) Region A1 Region B1 Global M Region C1 • Top-down dynamics: • Global avg income (GDP/capita) • TC: Fossil substitutes

16. Example quantification: TC & income Judgments: • Low global per capita income suggests few funds available for research. This strongly restricts Fast technological change for fossil substitutes. • Medium global per capita income (status quo) also strongly restricts Fast technological change, and still somewhat promotes slow technological change for fossil substitutes. • High global per capita income slightly promotes rapid technological change and somewhat restricts technological change. Cross impacts: Balance:

17. Assessing internal consistency • Consider the test scenario: • Moderate TC • Medium global income • Internal consistency determined by simple test of superposition of pair-forces on the system, i.e. Internal consistency of test scenarios demonstrated when test scenario states are found to be system maxima. Inconsistency score: 2 – 1 = 1

18. Linked CIBA results, consistent worlds Region A: OECD Income High Education High Region B: ROW Income Low/Med/High Education Low/Med/High • Top-down dynamics: • Income Low, TC Slow • Income Med, TC Slow • Income High, TC Mod • Income High, TC Fast • Internally consistent worlds: • Income growth could be • Convergent • Fractured • Convergent income growth consistent with fast or moderate TC for fossil subs • Divergent income growth NOT consistent with fast TC World X Region A1 Region B1 Global M Region C1

19. Summary New socioeconomic scenarios • Willbe consistent with RCPs • Aim to address research needs of IAM and IAV communities Research needs under the new framework • What types of socioeconomic scenarios should be prioritized for further study? Internally consistent scenarios in complex possibility spaces can be systematically found through linked cross-impact balance analysis. Thanks for your attention! 

20. References Carter, T. R., Jones, R. N., Lu, X., Bhadwal, S., Conde, C., Mearns, L. O., O'Neill, B. C., Rounsevell, M. D. A. & Zurek, M. B. (2007) New assessment methods and the characterisation of future conditions. IN Parry, M. L., Canziani, O. F., Palutikof, J. P., Van Der Linden, P. J. & Hanson, C. E. (Eds.) Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK, Cambridge University Press. Inman, M. (2011) Opening the Future. Nature Climate Change, 1, 7-9. Füssell, H.-M., and Klein, R. J. T. (2006) Climate Change Vulnerability Assessments: An Evolution of Conceptual Thinking. Climatic Change 75: 301-329. Kriegler, E., O’Neill, B. C., Hallegatte, S., Kram, T., Lempert, R., Moss, R. H., Wilbanks, T. J. (2010) Socio‐economic Scenario Development for Climate Change Analysis, CIRED Working Paper DT/WP No. 2010‐23, October. Available at http://www.centre‐cired.fr/IMG/pdf/CIREDWP‐201023.pdf. Moss, R., Babiker, M., Brinkman, S., Calvo, E., Carter, T., Edmonds, J., Elgizouli, I., Emori, S., Erda, L., Hibbard, K., Jones, R., Kainuma, M., Kelleher, J., Lamarque, J. F., Manning, M., Matthews, B., Meehl, J., Meyer, L., Mitchell, J., Nakicenovic, N., O’Neill, B., Pichs, R., Riahi, K., Rose, S., Runci, P., Stouffer, R., van Vuuren, D., Weyant, J., Wilbanks, T., van Ypersele, J. P. & Zurek, M. (2008) Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies. Geneva, IPCC. Nakićenović, N., Alcamo, J., Davis, G., de Vries, B., Fenham, J., Gaffin, S., Gregory, K., Grübler, A., Jung, T. Y., Kram, T., La Rovere, E. L., Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H., Price, L., Riahi, K., Roehrl, A., Rogner, H.-H., Sankovski, A., Schlesinger, M., Shukla, P., Smith, S., Swart, R., van Rooijen, S., Victor, N. & Dadi, Z. (2000) Special Report on Emissions Scenarios, New York, Cambridge University Press.

21. References Schweizer, V., and Kriegler, E. (2011)Using Cross-Impact Balance Analysis to Improve Future Emissions Scenarios. Climatic Change, under review. Weimer-Jehle, W. (2006) Cross-impact balances: A system-theoretical approach to cross-impact analysis. Technological Forecasting and Social Change, 73, 334-361. Weimer-Jehle, W. (2007) ScenarioWizard. 2.0 beta ed. Stuttgart, ZIRN - Interdisciplinary Research unit on Risk Governance and Sustainable Technology Development; International Center for Cultural and Technological Studies; University of Stuttgart. Weimer-Jehle, W. (2010) ScenarioWizard. 3.22 ed. Stuttgart, ZIRN - Interdisciplinary Research unit on Risk Governance and Sustainable Technology Development; International Center for Cultural and Technological Studies; University of Stuttgart.

22. BACKUP

23. One framework for linking RCPs and socioeconomic pathways Kriegler et al., 2010

24. Internal consistency of scenarios Carter et al., 2007