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

How can attribution of observed impacts best be communicated without sacrificing scientific rigor? (2.3)‏ 2 2

How do we best communicate the magnitude and inevitability of uncertainty in order to support policy makers in dealing with climate-related risks? (2.3)‏ Be scientifically clear about character and magnitude of uncertainty and decide then how to communicate best Probability interpretation of frequency statements (e.g.: according to 10% of the models no change will occur – do you want to bet on this? – is that a scientifically acceptable statement?)‏ uncertainty should be communicated in a way that allows the decision maker at least to compare it with the certainty of other decision-leading projections (demographic, socio- economic etc) 3 3

Perception of uncertainty (risk aversion etc)‏ evaluation of uncertainty -> include (i.e. inform) all stakeholders/potentially affected people (assessment of uncertainty may be very different!)‏ Perception of uncertainty (risk aversion etc)‏ Do not communicate “small” uncertainties (what is “small”?)‏ should the “reasons” for uncertainty also be communicated? Suggest adaptation measures which are robust against uncertainty 4 4

How can attribution of observed impacts best be communicated without sacrificing scientific rigor? (2.3)‏ 5 5

Structuring discussion: Character of uncertainty How to communicate Michael: 14:20 one for the second question Concentrate on listening, not only uncertainty the Rumsfelds 6 6

IPCC is well listened/ discursive leader TEEB/Aicher 14:24 IPCC is well listened/ discursive leader Listening ok, but no political impacts Less uncertainty does not necessarily create political action -active involvement of potential users- how? in producing the results? In formulating the questions? Assess & communicate urgency of action Include ecosystem services into decisions Scaling: policy reports for national scale, regional, sectoral etc Social and political demands is starting points Dialog is more important than uncertainty 7 7

teeb/ipcc - uncertainty in monetariszation of ecosystems disc. teeb/ipcc - uncertainty in monetariszation of ecosystems Who reads the reports? How much resistance? Here comes uncertainty in. Forest community opposed, but not because of certainty Lot of people involved – observed political/business impacts? - teeb gets Anfragen, fairly young 8 8

Typology of uncertainty (sender/transmission/receiver)‏ Felix Creutzer 14:53 Typology of uncertainty (sender/transmission/receiver)‏ Impacts: probability distributions/mitigation: action dependent Sender: Unc. (quantifyable) → Ambiguity (not quantifyable)‏ contrasting Opinions of scientists Transmission: Media: manufacturing/fragmentation Receiver: Lot of bias introduced – belief-systems (CC exists), 2. we can do something, 3. → selective information stream 9 9

Sender: unc. Needs to be reported: interval, not distribution What to do ex. public health, how to deal with outbreak, doing the vaccination .... overconfidence backfires Sender: unc. Needs to be reported: interval, not distribution Media: good scientific journalism / audience relevance Receiver: audience relevance Disc. Who is the audience? Value/belief systems missing People tend to forget, repeat the obvious, best uncertainty rep. Depends on reciever How belief systems are formed – risk and benefits confounded 10 10

Skip media? → fragmentation does Avoid overconfidence! Tails mean anything could go Important: Capacity to block action, start to think strategically Reaching the public: mixing the abstract with the concrete example Make clear your role Tell how you got your scientific results 11 11

Analyze power structures/ data scarcity as an instrument Oles 15:29 Analyze power structures/ data scarcity as an instrument Skip media, inform civil society and decision makers Disc. Bring uncertainty to the peoples interest Uploading function Concern about administration, civil society uses it Who finds out what tools are available? 12 12

TEEB: Uncertainty plays no role CATHY: inst. Ecology Template, + socio-political context Purpose, sender-receiver model old-fashioned!!!! Who are General public, politicians,policy makers 13 13

Topic 2, group 3: How do we best communicate the magnitude and inevitability of uncertainty in order to support policy makers in dealing with climate-related risks? 14 14

Propagation of Uncertainty in Climate Change Communication Function Sender Transmitter Receiver 15 15

Propagation of Uncertainty in Climate Change Communication Social & political context (India, China, etc) Typical actor Sender Science Transmitter Media Politicians Policymakers Civil society Receiver 16 16

Propagation of Uncertainty in Climate Change Communication Social & political context (India, China, etc) Sources of distortions: Ambiguity (categorial) Uncertainty (quantifyable) Opinion Sender Science „Manufactoring“ Balancing bias Fragmentation Transmitter Media Politicians Policymakers Civil society Processing capacity Belief systems Vested interests Receiver 17 After Creutzig/Markowitz 2013 17

Reducing Uncertainty Propagation Ambiguity (categorial) Uncertainty (quantifyable) Opinion Science „Manufactoring“ Balancing bias Fragmentation Media Politicians Policymakers Civil society Processing capacity Belief systems Vested interests 18 18

Reducing Uncertainty Propagation Directly addressing policymakers AND civil society (information symmetry!) via open access web-based information Ambiguity (categorial) Uncertainty (quantifyable) Opinion Science „Manufactoring“ Balancing bias Fragmentation Media Politicians Policymakers Civil society Processing capacity Belief systems Vested interests 19 e.g. Kit/Lüdeke 2013 19

Reducing Uncertainty Propagation Directly addressing policymakers AND civil society (information symmetry!) via open access web-based information Ambiguity (categorial) Uncertainty (quantifyable) Opinion Science Representation ad-apted to receiver with concrete examples Combining general statements „Manufactoring“ Balancing bias Fragmentation Media Good science journalism Politicians Policymakers Civil society Processing capacity Belief systems Vested interests 20 e.g. Kit/Lüdeke 2013 20

Reducing Uncertainty Propagation Direct involvement of stakeholders/decision makers into the science process reduces the role of scientific uncertainty as alibi for non-action Ambiguity (categorial) Uncertainty (quantifyable) Opinion Science Representation ad-apted to receiver with concrete examples Combining general statements „Manufactoring“ Balancing bias Fragmentation Media Good science journalism Politicians Policymakers Civil society Processing capacity Belief systems Vested interests 21 e.g. Aicher/Beck 2013 21

Reducing Uncertainty Propagation Directly addressing policymakers AND civil society (information symmetry!) via open access web-based information sources Ambiguity (categorial) Uncertainty (quantifyable) Opinion Science „Manufactoring“ Balancing bias Fragmentation Media Good science journalism Politicians Policymakers Civil society Processing capacity/ Belief systems/ Vested interests 22 e.g. Kit/Lüdeke 2013 22

Propagation of Uncertainty in Climate Change Communication Function Typical actor Sources of distortions: Ambiguity (categorial) Uncertainty (quantifyable) Opinion Sender Science „Manufactoring“ Balancing bias Fragmentation Transmitter Media Politicians Policymakers Civil society Processing capacity Belief systems Vested interests Receiver 23 23