Help Wanted – AR4 Gary Yohe March 3, 2004 CIS oƒ HDGC Carnegie Mellon

2 CIS oƒ HDGC Carnegie Mellon Context Don’t send money. Not asking for CLAs or Las Send ideas, and work… » Here is the State of the Process as it Begins!

3 CIS oƒ HDGC Carnegie Mellon New Components - WGII Chapter 1 – Assessment of Observed Changes » Methods in Detection and Attribution (first order causality) » Larger Scale Aggregation and Attribution (second order causality) Chapter 2 through 16 – Sectors and Regions Chapter 17 – Assessment of Adaptation Options, Capacity, Opportunities, Constraints and Practice » Methods and Concepts (vulnerability, resilience, etc.) » Current Practices (risk management, variability, etc.) » Assessing Adaptive Capacity (generic and specific, links to development) » Enhancing Adaptation (technologies, adaptive learning, etc.)

4 CIS oƒ HDGC Carnegie Mellon More New Components in WGII Chapter 18 – Inter-relationship between Adaptation and Mitigation » Implementation and determinants of capacity » Objectives – reducing sensitivity, exposure; dealing with risk » Scale issues, etc. Chapter 19 – Key Vulnerabilities (TAR 19) Chapter 20 – Perspectives on Climate Change and Sustainability » Adaptation with multiple stresses » Risk and hazard management » Aggregate impacts versus sub-regional and local » Uncertainties

5 CIS oƒ HDGC Carnegie Mellon Chapters 18 & 20 Their purpose is to address the current state of knowledge about how the impacts of climate change and climate variability (with and perhaps without adaptation) might complement or impede processes of sustainable development in the face of multiple non-climatic stressors? Neither will serve as executive summaries of the contribution of Working Group II to the Fourth Assessment Report. Rather, they will focus attention on new knowledge since the Third Assessment Report on the interface between climate issues and development strategies.

6 CIS oƒ HDGC Carnegie Mellon A Story Line for Their Contribution Fundamental results from the TAR lead to concerns about global vulnerabilities to multiple stressors. A regional focus can reveal the implication of vulnerabilities on development, access to resources and equity. Paying systematic attention on the determinants of adaptive capacity can reveal the implication of development, access and equity on vulnerabilities. Current inadequacies in our ability to produce global portraits of net impacts are profound.

7 CIS oƒ HDGC Carnegie Mellon Review of pertinent material in the Third Assessment Report The capacity to adapt varies considerably across regions, countries, and socioeconomic groups. It varies even more significantly from location to location within regions and countries. Adaptations are most frequently inspired by variability and extreme events and not by long- term secular changes. Least developed countries are likely to be the most vulnerable to climate change, climate variability, and the effects of other stressors.

8 CIS oƒ HDGC Carnegie Mellon Opportunities and Challenges The determinants of adaptive capacity correspond well with precursors for sustainable development. Sustainable development and adaptation to climate change and climate variability are both constrained by the weakest underlying determinant or precursor. The key to integrating climate and development issues lies in understanding how systems cope with climate variability and other shorter-term stressors that impede steps toward sustainable development.

9 CIS oƒ HDGC Carnegie Mellon Recall the Determinants of Adaptive Capacity Availability of adaptation options Availability and distribution of resources Stocks of human and social capital Ability of decision makers to » Assume responsibility » Process information » Separate signal from noise Access to risk spreading mechanisms Public perception – attribution and responsibility

10 CIS oƒ HDGC Carnegie Mellon Fundamental Conclusions from the TAR - Chapter 18 “Current knowledge of adaptation and adaptive capacity is insufficient for reliable prediction of adaptations; it is also insufficient for rigorous evaluation of planned adaptation options, measures and policies of governments” (pg 880 or WGII Report) Vulnerability is a function of exposure and sensitivity; and both can be influenced by adaptive capacity All of these are path dependent and site specific

11 CIS oƒ HDGC Carnegie Mellon Anticipated Uncertainties, Gaps and Knowledge Needs at the End of AR4 Current knowledge is still insufficient for reliable predictions of adaptations across the globe (some regions and sectors, particularly in developed countries, have been adequately analyzed). Current knowledge is still insufficient for rigorous evaluation of planned governmental adaptations (options, measures or policies) across the globe (some regions and sectors, particularly in developed countries, have been adequately analyzed). Current knowledge is still insufficient for sustaining credible global portraits of impacts cum adaptation along any given climate scenario.

12 CIS oƒ HDGC Carnegie Mellon Uncertainties, Gaps and Knowledge Needs, continued Global integrated assessment efforts cannot yet adequately reflect net impacts of even gradual and predictable climate change. Researchers should not necessarily tie their analyses explicitly to global climate scenarios; climate scenarios can inform their analyses by framing a range of not-implausible futures. Looking at simultaneous vulnerability to multiple stresses can provide insight into how adaptation might be most efficiently mainstreamed into programs and policies that have been designed to alleviate problems of more immediate concern.

13 CIS oƒ HDGC Carnegie Mellon Uncertainties, Gaps and Knowledge Needs, continued Climate variability and extreme events become priority problems quickly, and so it might be possible to mainstream adaptation in these arenas most effectively; but adequate analysis of an adaptation problem does not necessarily translate into adequate management. Current knowledge can support analyses of the joint efficacy of mitigation (stabilization scenarios, for example) and adaptation for some regions and sectors.

14 CIS oƒ HDGC Carnegie Mellon Some Working Hypotheses Countries where the effects of climate change on development, access to resources, and equity measures are largest tend to be the same countries where adaptive capacity is the weakest. Stronger evidence now exists that developing countries are most vulnerable to climate change, climate variability, and other stresses because the effects of these stresses on weak determinants of adaptive capacity are the largest.

15 CIS oƒ HDGC Carnegie Mellon Some Working Hypotheses, continued Working Group II can rigorously assess the joint the effectiveness of mitigation and adaptation for some regions, sectors, and/or systems where regional advantages in knowledge can be exploited. Working Group III should not yield to the temptation of using scattered local and regional estimates of climate impacts net of adaptation to produce unsubstantiated global portraits along specific scenarios whose regional manifestations are fraught with enormous uncertainty and thus highly suspect.

16 CIS oƒ HDGC Carnegie Mellon A Result from the Scoping Meeting The synthesis of adaptation and mitigation is located in Working Group II……… » This is the point of Chapter 18 WE NEED SOME LITERATURE TO REVIEW! HELP WANTED

17 CIS oƒ HDGC Carnegie Mellon A Perspective from the TAR Climate related damages that can be avoided by mitigation are the benefits of that mitigation Credible calculations of the benefits of mitigation must therefore recognize the potential that adaptation (autonomous and planned) could reduce damages and therefore the benefits of mitigation.

18 CIS oƒ HDGC Carnegie Mellon Support for that Approach The environmental economics literature – optimal intervention assumes efficient evasive activity The finance literature – calculates risk premia net of diversifiable risk thereby assuming efficient diversification

19 CIS oƒ HDGC Carnegie Mellon More from the TAR Adaptation may or may not reduce damages significantly » SLR examples from developed coastlines (work on the US developed coastline shows significant cost savings from adaptation; corroboration in subsequent global coverage by Nichols and friends) » SLR examples from low-lying islands (Atoll states work by Adger shows abandonment only option to SLR, but earlier significant stress from other sources)

20 CIS oƒ HDGC Carnegie Mellon Including Adaptation can be Critical It follows that adaptation cannot be ignored in any credible calculation of the benefit side of mitigation » It passes the Lave test (factor of two) » But we are not sure where, when and how.

21 CIS oƒ HDGC Carnegie Mellon Two Asides from Neil Adger What can be attributed to SLR when atoll states are more vulnerable to extinction in the near term from internal development paths? How much mitigation would be forthcoming if the COP of the UNFCCC did not know which 5 of the 180+ members were facing extinction?

22 CIS oƒ HDGC Carnegie Mellon A Potentially Unsettling Conclusion Asking for estimates of the economic value of mitigation might be wrong question. Thinking about mitigation in the context of a cost- benefit framework might be the wrong approach … …at least for a while… … This is why it is good that it is in WGII

23 CIS oƒ HDGC Carnegie Mellon A Risk-based Approach can Accommodate the Synthesis Thinking about both mitigation and adaptation as tools to reduce the risk of troublesome, intolerable, etc… climate change makes them complements rather than substitutes, and we are out of the bind of simply cataloging “win-win” options. Mitigation is then a means of hedging against bad outcomes measured, net of adaptation, in terms of the likelihood of crossing critical thresholds. Adaptation is then a means by which systems can expand their coping ranges or delay their contraction.

24 CIS oƒ HDGC Carnegie Mellon The Cost Side The cost side of mitigation (thought of as a risk- reducing tool whose outputs are measured in terms of a vector of impacts) is one of cost-effectiveness; i.e., minimizing the cost of achieving certain objectives. The cost side of adaptation (thought of as a risk- reducing tools whose outputs are measured in terms of the likelihood of crossing thresholds) is one of opportunity cost informed by understanding how the determinants of adaptive capacity help or impede adaptation.

25 CIS oƒ HDGC Carnegie Mellon Decision-makers’ Context Their job is to assess the relative opportunity costs of achieving specific risk reductions. Double causality is required to assess the effectiveness of mitigation. Single causality is sufficient to assess adaptation; but not in a synthetic approach. Uncertainty becomes the reason for contemplating policy rather than the reason for contemplating delay.

26 CIS oƒ HDGC Carnegie Mellon Can Science Support this Approach? Will there be Literature to Assess? Recent MIT work (Webster, et. al., “Uncertainty Analysis on Climate Change and Research Policy Response”, Climatic Change, 2003) produces distributions of temperature change associated with a specific concentration threshold and translates that into SLR possibilities (at least for 2100, but could produce transcients).

27 CIS oƒ HDGC Carnegie Mellon Will there be Literature? Recent Schneider work (See OECD Workshop on the Benefits of Climate Policy and forthcoming special issue of Global Environmental Change) produces distributions of an extreme event (THC shutdown) conditional on » natural variables (climate sensitivity, etc…) » policy-related variables (the discount rate in an otherwise informed optimization exercise).

28 CIS oƒ HDGC Carnegie Mellon Will there be Literature? Roger Jones (See OECD Workshop on the Benefits of Climate Policy and forthcoming special issue of Global Environmental Change) : links site specific thresholds to adaptation and climate variables » SLR illustration with the likelihood of crossing critical thresholds at specific years » Episodes of coral bleaching and mortality with the likelihood of crossing critical ocean temperature thresholds at specific years

29 CIS oƒ HDGC Carnegie Mellon The Implicit Scheme to Gain Access to Considerations of Mitigation Temperature (climate variable) distributions → Impact (vector) distributions → Frequency of crossing critical thresholds Adding adaptation assesses the potential of changing the thresholds [or the correlation between temperature (climate variable) and impact]. Contemplating mitigation tracks changes in the temperature (climate variable) distribution

30 CIS oƒ HDGC Carnegie Mellon Sea Level Rise is a Great Example – As Usual Distributions of temperature change support distributions of SLR. Local subsidence combines with this to produce distributions of local SLR. Distributions of impacts (inundation, salt-water intrusion, vulnerability to coastal storms, etc….) follow from local modeling links to SLR. Adaptations are obvious (protect or not; set-back rules, etc….) Mitigation effects distributions of temperature and SLR trajectories.

31 CIS oƒ HDGC Carnegie Mellon A Second Approach – Not Implausible Futures Not-implausible futures produce ranges of impacts across which adaptations must cope. The key on the adaptation side is to look for robust responses that handle many possible futures. The link to mitigation follows from changes in not implausible futures. The key on the mitigation side is to look at the effect on the range or timing of futures across which robustness might be measured.

32 CIS oƒ HDGC Carnegie Mellon A New Example – Flooding in Bangledesh Strzepek has calibrated a hydrologic model of the Ganges and Brahmaputra rivers to COSMIC output to produce trajectories of maximum monthly flow; critical variables include Monthly precipitation and temperature (winter months) in highlands (determines timing and significance of snowmelt) Strzepek has also calibrated the likelihood of various degrees of flooding to maximum flows

33 CIS oƒ HDGC Carnegie Mellon Preliminary Results – 684 Scenarios

34 CIS oƒ HDGC Carnegie Mellon Representative Scenarios

35 CIS oƒ HDGC Carnegie Mellon An Alternative View of the Representative Scenarios

36 CIS oƒ HDGC Carnegie Mellon The Likelihood of Severe Flooding

37 CIS oƒ HDGC Carnegie Mellon The Likelihood of Moderate Flooding

38 CIS oƒ HDGC Carnegie Mellon The Likelihood of Modest Flooding

39 CIS oƒ HDGC Carnegie Mellon Efficacy of Protecting Against Modest Flooding Only

40 CIS oƒ HDGC Carnegie Mellon Efficacy of Protecting against Modest and Moderate Flooding

41 CIS oƒ HDGC Carnegie Mellon Decrease in the Likelihood of Modest Flooding with Moderate Protection

42 CIS oƒ HDGC Carnegie Mellon Adding Mitigation Track the representative scenarios with mitigation imposed to achieve some sort of stabilization target. Track the differences in the likelihood of flooding, the efficacy of protection, and the necessary timing – would protection be more effective (because peak flows are lower) or would the timing of the benefits change (forward or backward in time)? QUESTION: STABILIZE WHAT?

43 CIS oƒ HDGC Carnegie Mellon Multiple Stabilization Options: Two Examples Limit concentrations – temperature uncertainty persists, particularly with 5% to 10% of the tail of the cumulative probability distribution at 9 degrees or more. Limit temperatures – produces significant uncertainty about the cost of compliance. Implementation uncertainty – the ability to achieve the target and/or effect midcourse corrections contingent on measuring something and understanding causality.

44 CIS oƒ HDGC Carnegie Mellon In Any Case – One Way Forward Analysis of mitigation should focus on cost- effectiveness, the ability to make mid-course corrections, and implementation uncertainty. Analysis of adaptation should focus on understanding the roles played by the various determinants of adaptive capacity and the antecedents of robust options.

45 CIS oƒ HDGC Carnegie Mellon A Two Way Street Adaptation must be included in any assessment of what may or may not be accomplished by mitigation in terms reducing the likelihood crossing critical impact thresholds. The degree to which mitigation complements adaptation in reducing those likelihoods must be explored with full recognition of associated uncertainties in the outcome of mitigation.