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Adaptation in an Uncertain World - Detection and Attribution of Climate Change Trends and Extreme Possibilities


  • Xiyue Li

    () (The Brattle Group)

  • Gary Yohe

    () (Department of Economics, Wesleyan University)


We offer results from an artificial simulation exercise that was designed to answer three fundamental questions that lie at the heart of anticipatory adaptation. First, how can confidence in projected vulnerabilities and impacts be greater than the confidence in attributing what has heretofore been observed? Second, are there characteristics of recent historical data series that do or do not portend our achieving high confidence in attribution to climate change in support of framing adaptation decisions sometime in an uncertain future? And finally, what can analysis of confidence in attribution tell us about ranges of “not-implausible” extreme futures vis a vis projections based at least implicitly on an assumption that the climate system is static? An extension of the IPCC method of assessing our confidence in attribution to anthropogenic sources of detected warming allows us to offer an answer to the first question. We can also identify characteristics that support an affirmative answer to the second. Finally, we offer some insight into the significance of our attribution methodology in informing attempts to frame considerations of potential extremes and how to respond.

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  • Xiyue Li & Gary Yohe, 2018. "Adaptation in an Uncertain World - Detection and Attribution of Climate Change Trends and Extreme Possibilities," Wesleyan Economics Working Papers 2018-008, Wesleyan University, Department of Economics.
  • Handle: RePEc:wes:weswpa:2018-008

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    adaptation; detection; attribution; uncertain; climate change;

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