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Advancing Knowledge Systems to Inform Climate Adaptation Decisions

Advancing Knowledge Systems to Inform Climate Adaptation Decisions. Suraje Dessai Adaptation to Climate Change - Debates on Framings and Knowledge Workshop co -organized by ANR projects ClimaConf & MEDEA May 29, 2013, Paris. Outline.

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Advancing Knowledge Systems to Inform Climate Adaptation Decisions

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  1. Advancing Knowledge Systems to Inform Climate Adaptation Decisions Suraje Dessai Adaptation to Climate Change - Debates on Framings and Knowledge Workshop co-organized by ANR projects ClimaConf & MEDEA May 29, 2013, Paris

  2. Outline • Evidence-based policymaking and science for policy • The challenge of adaptation • Limits to predictability • Introduction to Project ICAD

  3. Evidence-based policymaking and science for policy • Scientific knowledge and scientific expertise are heavily used to inform policymaking • Belief that new/more science will solve existing problems • The UK Government has placed strong emphasis on evidence-based policymaking (since the 1999 white paper ‘Modernising Government’) • Considerable financial support is given to the development of new science to bolster research and further knowledge in key policy issues • The aim is that investment will produce more socially useful and usable science • More science = better decisions = successful adaptation

  4. Evidence from the scientific peer-review literature • The traditional method of producing science for policy (mode-1 science, the linear model or loading-dock approach) has experienced mixed success. Unsubstantiated assumptions; oversimplification of the complex science-policy interface • ‘Disconnect’ between the science produced supposedly to inform decision-making and actual policy processes (Lemos and Moorhouse, 2005) • While scientific knowledge and associated perceptions are powerful determinants of policy action, numerous other factors affect decision-making (context, institutions, culture, etc.) • Alternative models: mode-2 (Nowotny et al. 2001), post-normal (Funtowicz and Ravetz 1993), use-inspired science (Stokes 1997); co-production of knowledge?

  5. Evidence from the scientific peer-review literature • Effective decision support emerges when the information decision-makers’ need is identified and aligned alongside with what is feasible for science to deliver (NRC, 2009). • The creation of ‘‘boundary organizations’’ and ‘‘boundary objects’’ helps improve the usability of science by linking science and policy across different levels (Guston1999) • “Knowledge systems”: what kinds of programs, institutional arrangements and types of knowledge can most effectively harness science and technology for sustainability (Cash et al. 2003) • Reconciling supply of and demand for sciences (Sarewitz and Pielke Jr.)

  6. The challenge of adaptation to a changing climate • Climate variability and change are a major threat for the sustainable development of society • Adaptation to the impacts of climate change is unavoidable • There are significant uncertainties about how regional/local climate will change in the future • Informing adaptation decisions will require new kinds of information and new ways of thinking and learning (NRC, 2009)

  7. Informing adaptation policy From: Dessai, S., and M. Hulme (2004), Does climate adaptation policy need probabilities?, Climate Policy, 4(2), 107-128.

  8. End-to-end uncertainty quantification Changes in mean river runoff (2xCO2-1xCO2) at the Thames New, M., et al. (2007), Challenges in using probabilistic climate change information for impact assessments: an example from the water sector, Philos T R Soc A, 365(1857), 2117-2131.

  9. Limits to predictability • End-to-end analysis have found large uncertainties in climate impacts; deep/severe uncertainty (Lempert/Ben-Haim) • The search for ‘objective’ constraints remains elusive (Allen & Frame 2007) • Equifinality: many different model structures and many different parameter sets of a model can produce similar observed behaviour of the system under study (Keith Beven) • Verification and validation of numerical models in the earth sciences is impossible (Oreskeset al. 1994); “statements about future climate relate to a never before experienced state of the system”(Stainforth et al. 2007) • Models are heuristic tools and not ‘truth machines’ (Ravetz2003) • Climate is only part of the story when considering adaptation – multiple drivers and stressors

  10. Science policy implications • Decision-makers need to be able to live with deep uncertainty; little prospect of reducing uncertainty in the near term • There are analytical approaches that enable the identification of adaptation options that are immune to large ranges of uncertainty (e.g., robust decision-making, information-gap decision theory, adaptation pathways/tipping points) • Society will benefit more from a greater understanding of the vulnerability of climate-influenced decisions to large irreducible uncertainties than an increase in the accuracy and precision of the next generation of climate models • Dessai, S., M. Hulme, R. Lempert and R. Pielke, Jr. (2009) Climate prediction: a limit to adaptation?, 64-78. In W.N Adger, I. Lorenzoni and K. O’Brien (eds.) Adapting to climate change: thresholds, values, governance Cambridge University Press, Cambridge. • Dessai, S., M. Hulme, R. Lempert and R. Pielke, Jr. (2009) Do we need better predictions to adapt to a changing climate? EOSTransactions of the American Geophysical Union, Vol. 90, No. 13, 111-112.

  11. A Framework for Robust AdaptationWilby, R. L. and S. Dessai (2010). "Robust adaptation to climate change." Weather 65(7): 180-185.Dessai, S. and R. Wilby. “How Can Developing Country Decision Makers Incorporate Uncertainty about Climate Risks into Existing Planning and Policymaking Processes?” World Resources Report, Washington DC.

  12. Are current climate prediction systems useful for decision making? • How useful and usable is UKCP09 for adaptation decision-making? • Mixed methods approach: analysis of adaptation reports (n=95), a quantitative survey (n=33) and semi-structured interviews with decision-makers (11), knowledge producers (11) and knowledge translators (4) • Knowledgesystem criteria used to assess credibility, legitimacy and saliency (Cash et al. 2003) Tang, S., Dessai S. (2012) Usable Science? The U.K. Climate Projections 2009 and Decision Support for Adaptation Planning. Weather, Climate and Society, 4(4): 300-313.

  13. The UK Climate Projections 2009 (UKCP09) • A suite of UK-wide (national) climate change projections • Designed to help assess climate change impacts and explore adaptation options • Lots of simple and complex information available • Bayesian probabilistic projections • Explores multiple future outcomes • Probability = degree of change consistent with the evidence • Less confidence in the range and probability of the tail ends of each curves http://ukclimateprojections.defra.gov.uk/content/view/641/500/

  14. UKCP09 and decision support for adaptation planning • Stakeholders perceived UKCP09 to be credible and legitimate due to its sophistication, funding source and the scientific reputation of organizations involved in its development • Perception of saliency is less positive (47%) than credibility and legitimacy (89%). • Sectoral variations: 42% of the Water sector felt UKCP09 was ‘Extremely’ salient, 67% of Energy and 100% of Environment perceived it was ‘Quite a bit’ salient, 83% of Transport perceived it was ‘Moderately’ salient, while Local Authority responses were split equally between ‘A little’ (50%) and ‘Moderately’ (50%).

  15. UKCP09’s saliency • “the UKCP09 data and tools are so wide ranging it is difficult to know which is the best method / tool / dataset to use” Severn Trent Water Ltd. (2011, p. 48) • “All the probabilistic estimates they did are all very difficult to interpret because they are not probabilities in the way that a decision-making would use probabilities” (Knowledge producer D). • “It’s an enormous amount of information for somebody who is not normally dealing with that sort of thing allied with dealing with issues of understanding probability and all that kind of malarkey, you know it’s quite indigestible if your coming in cold” (Knowledge translator A). • “I think if you have a scientific background you are used to using this type of data or the methodologies. If you’re not used to it, then it is harder” (Decision-maker G).

  16. Research Domain 1 Understanding climate information needs across society Research Domain 2 The social status of techno-scientific knowledge in adaptation to climate change The research project aim: significantly advance knowledge systems to enable society to adapt effectively to an uncertain climate • Is information? • credible • legitimate • actionable • salient Focus on multi-decadal planning horizon: >30 years New et al. 2007

  17. Research Streams • Understanding Climate Information Needs Across Society • Led by Geoff Whitman: • What is the capacity for different users to apply climate information? • How do organisations use climate information in their decision-making? • What levels of uncertainty are they able, or willing, to tolerate in decision-making? • To what extent is climate change knowledge co-produced? Social Status of Technical Climate Knowledge for Adaptation Decision-Making Led by James Porter: • How, and why, does climate knowledge come to take a particular form in adaptation? • What do experts’ think users’ need? • To what extent is climate change knowledge co-produced? • How, and with what effect, does climate knowledge come to be translated across different social worlds?

  18. Work in progress • Survey of English organisations (53 responses of 150) • Survey of Local Authorities in GB (28.5% response rate) • Analysis of 91 adaptation reports • Interviews with knowledge producers, translators and users • Initial outputs: • Kirchhoff,C.J., M.C. Lemos, and S. Dessai (2013) Actionable Knowledge for Environmental Decision Making: Broadening the Usability of Climate Science. Annual Review of Environment and Resources (in press), doi: 10.1146/annurev-environ-022112-112828 • Lorenz, S., S. Dessai, J. Paavola and P.M. Forster (2013) The communication of physical science uncertainty in European National Adaptation Strategies. Climatic Change (in press) • http://www.icad.leeds.ac.uk/

  19. Concluding remarks • Future climate, climate impacts and society are characterised by deep/severe uncertainty • Where uncertainty dominates robust decision-making methods are likely to be more useful to decision-makers than traditional “predict and provide” methods • Adaptation efforts should not be limited by the lack of reliable foresight about future climate conditions • We need a better understanding of what is useful, usable and valuable climate knowledge for adaptation decision-making • s.dessai@leeds.ac.uk

  20. Extras

  21. ICAD Local Authority survey • Climate Adaptation: A Survey of Local Authorities in the Great Britain: • Aim: • Assess the awareness, experience and reflections of LAs use of climate information • Examine which sources are most frequently used and what are their perceived accuracy and reliability, and • Identify any challenges and obstacles faced in taking up that information • Response: • 407 Local Authorities in GB - 28.5% response rate • Targeted at Environmental, Sustainability and Climate Change officers. • Follow-up interviews (n=20) across different Government Office regions • Comparison with Demeritt & Langdon (2004) survey

  22. Good News: Better Informed! • Overall , do you feel that your Local Authority has enough information to decide whether they should change any of their plans or policies because of climate change? A decade ago hardly anyone had heard of UKCIP02 (cf. 40.2% didn’t know of it and 12% were unsure) compared to UKCP09 only 9% of respondents haven’t heard of it.

  23. Climate Info: Frequency of Use • How often do you use the following sources of information to understand the potential impacts of climate change for your Local Authority? 70% 60% 50% 40% 30% 20% 0

  24. Climate Info: Accessibility • When thinking about climate change, how easy is it to understand these sources of information?

  25. Climate Info: Reliability • How reliable do you think these sources of climate information are? All technical sources of information

  26. But What Does “Use” Mean? • Remember: • 40.9% respondents said they “always” use UKCP09 with another 38.3%“sometimes” • 49.1% thought the projections were “easy” to understand/use whereas 41.9% felt they were “difficult” • Why the difference? • Only used the briefing report, graphics and text to support arguments (cf. flood risk) – NOT the underlying data/observations • Heavier use involved specialist consultants translating the projections into simpler tools for them

  27. Adaptation in Austerity • When asked what their Local Authority is most concerned about (e.g. weather extremes, transport network failure, terrorism etc.), the economic downturn received most attention • Budget cuts, restructuring, and juggling of multiple roles for staff meant adaptation has lost it’s impact against mitigation (cf. business case, NI-188) • Increasing, or at least ring-fencing, funding was the most popular response (67%) to what they wanted from Central Government • Climate work must be done in-house, which places an onus on staff having the skills, time resources and capacity to use tools like UKCP09 • Reluctance to sign-up to things like Climate Local due to the reputational risks of not being able to see through the work.

  28. Thoughts… • Good News: LA workforce better informed and more confident about accessing and using climate information and willingness to take responsibility • BUT: challenges remain over (i) the current fiscal situation is squeezing staffing and allocation of resources (cf. deprioritisation), and (ii) the framing of climate change (mitigation has value adaption doesn’t, language, local politics) • Loss of statutory targets (cf. NI-188) – productive vsperformative audit regimes • Rise of resilience (political short-termism) • Regional differences (England Vs. Scotland and Wales)

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