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  1. Summary of interactive discussion groups Topic 2: Isanybodylistening Bill Hare with contributions from B.Hezel, M.Hanemann, L.Costa, M.Obersteiner, M.Lüdecke, M.Rounsevell, R.Gudipudi

  2. Listening issues… • People are listening but we are not telling them what they want to hear. • As long as impacts are not translated into economic endpoints they are invisible to many policymakers • Uncertainty grows with the length of the information transmission chain…. • Translation of issues and messages from local to global scale can be difficult: • Local policy makers “hear” an extreme event now but may not hear noise from the future…

  3. How do we improve the construction of damage functions, in order to produce more consistent economic risk assessments? • How do we appropriately address concerns of equity and discounting? Topic 2: Isanybodylistening?

  4. Disconnect between damage functions in many IAMs and many biophysical impact models • ICES and PESETA are important exceptions. • Examples • Sea level rise - hard to believe that IAMs now represent best available knowledge on impacts. • Contrast between agricultural damage functions in DICE, FUND and ENVISAGE and findings of (i) crop models and (ii) statistical analyses of the observed effects of weather on crops

  5. Existing IAM damage functions not well designed to handle probabilities of, and changes in, extreme • Comes naturally from biophysical impact models. • Combining IAM damage functions with a risk-based approach to decision making for adaptation as well as mitigation would be a valuable improvement

  6. Recommendations • Economists need to sit down with bio-physical modellers and learn from them; • Biophysical modellers need to bite the bullet and include economic metrics among the impacts they track. • Need to have a forum where the two communities can have a systematic discourse before the next IPCC assessment

  7. How do we best communicate the magnitude and inevitability of uncertainty in order to support policy makers in dealing with climate-related risks? Topic 2: Isanybodylistening?

  8. Propagation of uncertainty in climate change communication Function Sender Transmitter Receiver 8

  9. Politicians Policymakers Civil society Social & political context (India, China, etc) Propagation of uncertainty in climate change communication Typical actor Sender Science Transmitter Media Receiver 9

  10. Uncertainty (quantifyable) Ambiguity (categorial) Opinion Balancing bias „Manufactoring“ Fragmentation Belief systems Politicians Processing capacity Policymakers Vested interests Civil society Social & political context (India, China, etc) Propagation of uncertainty in climate change communication Sources of distortions: Sender Science Transmitter Media Receiver 10 After Creutzig/Markowitz 2013

  11. Uncertainty (quantifyable) Ambiguity (categorial) Opinion Balancing bias „Manufactoring“ Fragmentation Belief systems Politicians Processing capacity Policymakers Vested interests Civil society Reducing uncertainty propagation Science Media 11

  12. Uncertainty (quantifyable) Ambiguity (categorial) Opinion Balancing bias „Manufactoring“ Fragmentation Belief systems Politicians Processing capacity Policymakers Vested interests Civil society Reducing uncertainty propagation: direct communication Directly addressing policymakers AND civil society (information symmetry!) via open access web-based information Science Media 12 e.g. Kit/Lüdeke 2013

  13. Uncertainty (quantifyable) Ambiguity (categorial) Opinion Combining general statements with concrete examples Balancing bias „Manufactoring“ Fragmentation Belief systems Politicians Processing capacity Policymakers Vested interests Civil society Reducing uncertainty propagation: better communication Directly addressing policymakers AND civil society (information symmetry!) via open access web-based information Science Representation ad-apted to receiver Media Good science journalism 13 e.g. Kit/Lüdeke 2013

  14. Uncertainty (quantifyable) Ambiguity (categorial) Opinion Combining general statements with concrete examples Balancing bias „Manufactoring“ Fragmentation Belief systems Politicians Processing capacity Policymakers Vested interests Civil society Reducing uncertainty propagation: participation Direct involvement of stakeholders/decision makers into the science process reduces the role of scientific uncertainty as alibi for non-action Science Representation ad-apted to receiver Media Good science journalism 14 e.g. Aicher/Beck 2013

  15. How can the widespread use of global mean temperature as base variable among policy makers be reconciled with a broader approach suggested by science? Topic 2: Isanybodylistening?

  16. Extreme events (for e.g Hurricane Sandy in New York) are triggering actions already at local level. • Though this might be valid from an adaptation point of view, mitigation still needs a broader political commitment • Action responding to climate change at a national level is not neutral because of political polarity and cultural cognition at local level • Long term strategic coordination between scientists and policy makers is found to be an effective way of enhancing climate responsive action at local level (aiming at both mitigation and on a longer run increasing resilience to deal with uncertainities) • The impact community itself is very heterogeneous (natural scientists, social scientists and economists, etc) with quite different objectives. Therefore it will be relevant to focus on “Science for science”

  17. Some lessons and conclusions… • Policy recommendations for climate actions on both mitigation and adaptatation differ from each other depending on various local parameters (socio-economic background, projected climate patterns, etc.) • Cross sectoral integration of various climatic impacts can be a more efective way of communication for policy recommendations • Better understanding of possible climate actions on both mitigation and adaptatation at various policy making levels is required • Burden sharing by all coutries globally might bring together for action aganist climate change • Global mean temperature target is irrelevant for actions at local level but regional/spatial climatic variations do play a crucial role • Though it is irrelevant at local level, there exists no better indicator than the current 2 degree target at global level which is tangible, mutually agreeable and achievable)

  18. How has impacts research influenced adaptation policy-making thus far? • What has and has not worked at the science policy interface? • How can we ensure a systematic quantification of adaptation options including local knowledge? Topic 2: Isanybodylistening?

  19. Lessons…. • Doorstep model of implementation does not work -> Think about an engagement strategy facilitating a co-production and co-design of knowledge • Experiences with institutional and cultural barriers between researchers and policy-makers do not necessarily travel between countries • Build trust with local community and local decision-makers • Stakeholder involvement → suitable, effective fair and legitimate adaptation measures • Context specific, streamlined information that is understandable and relevant works • Understand scenarios less as a product rather to be co developed an co-creative process → stakeholder perceptions have value, they are often close to the model outputs • Robustness analysis can mitigate uncertainty problem

  20. Recommendations, ideas and needs… • Correct framing for policy makers and stakeholders is very important • Start from existing maladapatation to existing climate variabilty… • ..then addition explain that climate change will make this worse. • Identify people managing systems right now… they are likely to be the experts to “sell” the information to. • Recurrent need in many contexts for a dedicated science/policy translator/Communicator • Need for new incentives for scientists to go the “extra mile” for co-creation and communication activities (in-house appreciation, new trans-disciplinary journals..)

  21. Group 2.2 Raw Material

  22. People are listening but we are not telling them what they want to hear. • As long as impacts are not translated into economic endpoints they are invisible to many policymakers. • A disconnect between the damage functions in many IAMs and the biophysical impact models • ICES and PESETA are important exceptions. • Examples • Sea level rise - hard to believe that IAMs now represent best available knowledge on impacts. • Contrast between the agricultural damage functions in DICE, FUND and ENVISAGE and finding of (i) crop models and (ii) statistical analyses of the observed effects of weather on crop yields. Recommendations • Economists need to sit down with bio-physical modellers and learn from them; • biophysical modellers need to bite the bullet and include economic metrics among the impacts they track.

  23. There exists no forum which provides for a systematic discourse among the two communities. IPCC doesn’t fill this role. This forum needs to be created before the next IPCC. The existing IAM damage functions are not well designed to handle probabilities of extreme events and changes in those probabilities. Such probabilities can come naturally from biophysical impact models. Combining IAM damage functions with a risk-based approach to decision making for adaptation as well as mitigation would be a valuable improvement. Connecting IAMs with biophysical models is a computational challenge because it involves bridging different levels of spatial resolution, but this needs to be tackled.

  24. Group 2.4 Raw Material

  25. Extreme events (for e.g Hurricane Sandy in New York) are triggering actions already at local level. • Though this might be valid from an adaptation point of view, mitigation still needs a broader political commitment • Action responding to climate change at a national level is not neutral because of political polarity and cultural cognition at local level • Long term strategic coordination between scientists and policy makers is found to be an effective way of enhancing climate responsive action at local level (aiming at both mitigation and on a longer run increasing resilience to deal with uncertainities) • The impact community itself is very heterogeneous (natural scientists, social scientists and economists, etc) with quite different objectives. Therefore it will be relevant to focus on “Science for science”