Learning and climate change |
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| Authors: | Brian C O'Neill Paul Crutzen Arnulf Grübler Minh Ha Duong Klaus Keller Charles Kolstad |
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| Institution: | 1. International Institute for Applied Systems Analysis , A-2361, Laxenburg, Austria;2. Watson Institute for International Studies, Brown University , Providence, RI, USA;3. Max Planck Institute for Chemistry , Mainz, Germany;4. School of Forestry and Environmental Studies, Yale University , New Haven, USA;5. CIRED/CNRS , Paris, France;6. Pennsylvania State University , Pennsylvania, USA;7. Donald Bren School of Environmental Science and Management , UC Santa Barbara, USA |
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| Abstract: | Abstract Learning—i.e. the acquisition of new information that leads to changes in our assessment of uncertainty—plays a prominent role in the international climate policy debate. For example, the view that we should postpone actions until we know more continues to be influential. The latest work on learning and climate change includes new theoretical models, better informed simulations of how learning affects the optimal timing of emissions reductions, analyses of how new information could affect the prospects for reaching and maintaining political agreements and for adapting to climate change, and explorations of how learning could lead us astray rather than closer to the truth. Despite the diversity of this new work, a clear consensus on a central point is that the prospect of learning does not support the postponement of emissions reductions today. |
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| Keywords: | Learning Uncertainty Climate change Decision analysis |
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