Learning about climate change and implications for near-term policy
Climate change is an issue of risk management. The most important causes for concern are not the median projections of future climate change, but the low-probability, high-consequence impacts. Because the policy question is one of sequential decision making under uncertainty, we need not decide today what to do in the future. We need only to decide what to do today, and future decisions can be revised as we learn more.
In this study, we use a stochastic version of the DICE-99 model (Nordhaus WD, Boyer J (2000) Warming the world: economic models of global warming. MIT Press, Cambridge, MA, USA) to explore the effect of different rates of learning on the appropriate level of near-term policy. We show that the effect of learning depends strongly on whether one chooses efficiency (balancing costs and benefits) or cost-effectiveness (stabilizing at a given temperature change target) as the criterion for policy design. Then, we model endogenous learning by calculating posterior distributions of climate sensitivity from Bayesian updating, based on temperature changes that would be observed for a given true climate sensitivity and assumptions about errors, prior distributions, and the presence of additional uncertainties. We show that reducing uncertainty in climate uncertainty takes longer when there is also uncertainty in the rate of heat uptake by the ocean, unless additional observations are used, such as sea level rise.
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- Baehr J, Keller K, Marotzke J (2007) Detecting potential changes in the meridional overturning circulation at 26°N in the Atlantic. Climatic Change, Published online: 10 January 2007 DOI 2010.1007/s10584-10006-19153-z
- Church JA, Gregory JM, Huybrechts P, Kuhn M, Lambeck K, Nhuan MT, Qin D, Woodworth PL (2001) Changes in sea level,’ Chapter 11. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Climate change 2001: the scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, p 881Google Scholar
- European Council (2005) Presidency conclusions. European Council, BrusselsGoogle Scholar
- Folland CK, Karl TR, Christy JR, Clarke RA, Gruza GV, Jouzel J, Mann ME, Oerlemans J, Salinger MJ, Wang S-W (2001) Observed climate variability and change,’ Chapter 2. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Climate change 2001: The Scientific Basis Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, p 881Google Scholar
- Forest CE, Stone PH, Sokolov AP (2006) Estimated PDFs of climate system properties including natural and anthropogenic forcings. Geophys Res Lett 33(L01705):1–4Google Scholar
- Keller K, McInerney D (2007) The dynamics of learning about a climate threshold,’ Climate Dynamics, in review, available at: http://www.geosc.psu.edu/~kkeller/publications.html
- Keller K, Kim S-R, Baehr J, Bradford DF, Oppenheimer M (2007) What is the economic value of information about climate thresholds? Chapter in: Integrated Assessment of Human Induced Climate Change, Chief Editor: Michael Schlesinger, Cambridge University Press, pp. 343–354Google Scholar
- Manne AS, Richels RG (1995) The greenhouse debate: economic efficiency, burden sharing and hedging strategies. Energy J 16(4):1–37Google Scholar
- Nordhaus WD (1994) Managing the global commons: the economics of climate change. MIT Press, Cambridge, MA, USAGoogle Scholar
- Nordhaus WD, Boyer J (2000) Warming the world: economic models of global warming. MIT Press, Cambridge, MA, USAGoogle Scholar
- Nordhaus WD, Popp D (1997) What is the value of scientific knowledge? An application to global warming using the PRICE Model. The Energy J 18(1):1–45Google Scholar
- Oppenheimer M, O’Neill B, Webster MD (2008) Negative learning’ climatic change. Clim Change, (in press) DOI 10.1007/s10584-008-9405-1
- United Nations (1992) Framework Convention on Climate Change. International Legal Materials 31:849–873Google Scholar
- U.S. Senate (2007) The low carbon economy act. Senate Draft Proposal. http://energy.senate.gov/public_new/_files/END07842_xml1.pdf
- Webster MD (2002) The curious role of “learning” in climate policy: should we wait for more data? Energy J 23(2):97–119Google Scholar