Enciclopédia da Energia Natural   CPMA.COMUNIDADES.NET
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Enciclopédia da Energia Natural CPMA.COMUNIDADES.NET


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should be postponed until more informa-
tion is gathered and the uncertainty is lessened. Charles Kolstad
examined these issues by modeling the tension between the
irreversibility of climate damage and the greater knowledge
gained from postponing action.
Several authors have endorsed greater investment as a result
of the high uncertainty associated with climate change. Quig-
gin argued that the concavity of utility functions associated
with risk aversion and the likely convexity of damage functions
related to climate change suggest greater intervention in the
face of uncertainty. Stern has also argued that great uncertainty
should provoke a larger policy response, although many of the
methods used to support his findings in The Stern Review have
vocal critics includingNordhaus, Dasgupta, RobertMendelsohn,
and John Weyant. Francesco Bosello and Chen Chen used
an adapted version of Nordhaus\u2019 DICE model (Regional
Dynamic Integrated Model of Climate and the Economy)
to examine the relative merits of mitigation and adaptation
in light of catastrophic and spatial uncertainty. They found
that both kinds of uncertaintymakemitigationmore appealing
relative to adaptation. Weitzman has taken a slightly different
view, arguing that great uncertainty does not necessarily favor
mitigation or adaptation but instead suggests that the optimal
strategy is to invest in research aimed at decreasing the uncer-
tainty itself. This is an excellent point, although it is difficult to
determine to what extent further research is capable of dimin-
ishing the uncertainty of climate change in a timely manner.
Resolution that occurs after environmental irreversibilities
have been reached, and large economic damages assured, is
of limited value.
It is unambiguously beneficial to decrease the uncertainty
associated with the six aforementioned areas of climate change
analysis. While doing so is costly, due especially to the unique
and challenging nature of the problem, the high stakes may
warrant the price. The resultant policy implications (does one
invest more or less, and what form should the investment
take?) of finding some degree of uncertainty resolution are
Thin tail
Fat tail
1.2
\ufffd10\u20133
1
0.8
0.6
0.4
P
ro
b
ab
ili
ty
0.2
0
4 4.5 5 5.5 6 6.5
Standard deviations from mean
7 7.5 8 8.5 9
Figure 4 Example of fat- and thin-tailed distributions, magnified.
Climate Change and Policy | Dealing with the Uncertainty About Climate Change 35
unclear, which is as it should be. If one already knew what to
do, resolving the uncertainty would not be so important.
See also: Allocation Tools: Bayesian Decision Theory and Climate
Change; Environmental and Natural Resource Economics: Decisions
Under Risk and Uncertainty; Ethics, Economics, and Decision Rules for
Climate Change; Managing Catastrophic Risk; Climate Change and
Policy: Carbon Cap and Trade; Carbon Offsets; Carbon Taxes; Climate
Change and Food Situation; Double Dividend; Economics of Forest
Carbon Sequestration as a Climate Change Mitigation Strategy;
Intergovernmental Panel on Climate Change (IPCC); International
Climate Treaties and Coalition Building; Markets/Technology
Innovation/Adoption/Diffusion: Technological Change and
Climate Change Policy; Microeconomics: Forest Management and
Climate Change; Spatial Management of Renewable Natural Resources;
Political Economy: Political Economy of International Environmental
Agreements; Theoretical Tools: Carbon Leakage; Discounting;
Option Value and Precaution.
Further Reading
Andronova N and Schlesinger M (2001) Objective estimation of the probability density
function for climate sensitivity. Journal of Geophysical Research 106(D19):
22605\u201322611.
Annan J and Hargreaves J (2006) Multiple observationally based constraints to estimate
climate sensitivity. Geophysical Research Letters 33: L06704.
Arrow K (1951) Alternative approaches to the theory of choice in risk-taking situations.
Econometrica 19: 404\u2013437.
Borghans L, Heckman J, Golsteyn B, and Meijers H (2009) Gender differences in risk
aversion and ambiguity aversion. Journal of the European Economic Association
7(2\u20133): 649\u2013658.
Bosello F and Chen C (2010) Adapting and mitigating to climate change: Balancing the
choice under uncertainty. 159 Note Di Lavoro, Fondazione Eni Enrico Mattei.
Ceronsky M, Anthoff D, Hepburn C, and Tol R (2005) Checking the price tag on
catastrophe: The social cost of carbon under non-linear climate response. ESRI
Working Paper Number 392.
Ellsberg D (1961) Risk, ambiguity, and the savage axioms. Quarterly Journal of
Economics 75(4): 643\u2013669.
Forest C, Stone P, and Sokolov A (2006) Estimating PDFs of climate system properties
including natural and anthropogenic forcings. Geophysical Research Letters
33: L01705.
Forest C, Stone P, Sokolov A, Allen M, and Webster M (2002) Quantifying uncertainties
in climate system properties with the use of recent observations. Science
295: 113\u2013117.
Forest C, Webster M, and Reilly J (2004) Narrowing uncertainty in global climate
change. The Industrial Physicist 10: 20\u201323.
Forster P and Gregory J (2006) The climate sensitivity and its components diagnosed
from earth radiation budget data. Journal of Climate 19: 39\u201352.
Frame D, Booth B, Kettleborough J, et al. (2005) Constraining climate forecasts: The
role of prior assumptions. Geophysical Research Letters 32: L09702.
Gregory J, Stouffer R, Raper S, Stott P, and Rayner N (2002) An observationally based
estimate of the climate sensitivity. Journal of Climate 15(22): 3117\u20133121.
Harvey L and Kaufmann R (2002) Simultaneously constraining climate sensitivity and
aerosol radiative forcing. Journal of Climate 15(20): 2837\u20132861.
Hegerl G, Crowley T, Hyde W, and Frame D (2006) Climate sensitivity constrained by
temperature reconstructions over the past seven centuries. Nature 440: 1029\u20131032.
Hoffert M and Covey C (1992) Deriving global climate sensitivity from paleoclimate
reconstructions. Nature 360: 573\u2013576.
Hope C (2006) The marginal impact of CO2 from PAGE2002: An integrated assessment
model incorporating the IPCC\u2019s five reasons for concern. The Integrated
Assessment Journal 6(1): 19\u201356.
Intergovernmental Panel on Climate Change (IPCC), Mastrandrea M, Field C, Stocker T,
et al. (2010) Guidance Note for Lead Authors of the IPCC Fifth Assessment Report
on Consistent Treatment of Uncertainties.
Intergovernmental Panel on Climate Change (IPCC), Rosenzweig C, Casassa G, et al.
(2007) Assessment of observed changes and responses in natural and managed
systems. In: Parry ML, Canziani OF, Palutikof JP, van der Linden PJ, and
Hanson CE (eds.) Climate Change 2007: Impacts, Adaptation and Vulnerability.
Contribution of Working Group II to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change, pp. 79\u2013131. Cambridge: Cambridge
University Press.
Kerr R (2004) Three degrees of consensus. Science 305: 932\u2013934.
Knight F (1921) Risk, Uncertainty, and Profit. Boston, MA: Houghton Mifflin.
Knutti R, Stocker T, Joos F, and Plattner G-K (2002) Constraints on radiative forcing
and future climate change from observations and climate model ensembles.
Nature 416: 719\u2013723.
Kolstad C (1996) Learning and stock effects in environmental regulation: The case of
greenhouse gas emissions. Journal of Environmental Economics and Management
31: 1\u201318.
Mendelsohn R (2008) Is the stern review an economic analysis? Review of
Environmental Economics and Policy 2(1): 45\u201360.
Morgan M and Keith D (1995) Subjective judgements by climate experts. Environmental
Science and Technology 29: 468A\u2013476A.
Murphy J, Sexton D, Barnett D, et al. (2004) Quantification of modeling uncertainties in
a large ensemble of climate change simulations. Nature 430: 768\u2013772.
National Academy of Sciences (1979) Carbon Dioxide