Climate Change 2014
Mitigation of Climate Change
Working Group III Contribution to the
Fifth Assessment Report of the
Intergovernmental Panel on Climate Change
6.3 Climate stabilization:
Concepts, costs and implications for the macro economy, sectors and technology port folios, taking into account differences across regions
6.3.2 Emissions trajectories, concentrations, and temperature in transformation pathways
Seiten 438 - 440
6.3.2.6 The link between concentrations, radiative
forcing, and temperature
The assessment in this chapter focuses on scenarios that result in
alternative CO2eq concentrations by the end of the century. However,
temperature goals are also an important consideration in policy discussions. This raises the question of how the scenarios assessed in
this chapter relate to possible temperature outcomes.
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One complicaton for assessing this relationship is that scenarios can follow different concentration pathways to the same end-of-century goal (see Section 6.3.2.2), and this will lead to different temperature responses.
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A second complication is that several uncertainties confound the relationship between emissions and temperature
responses, including uncertainties about
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the carbon cycle,
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climate sensitivity, and
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the transient climate response (see WG I, Box 12.2).
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This means that the temperature outcomes of different concentration pathways assessed here (see Section 6.3.2.1) are best expressed
in terms of a range of probable temperature outcomes (see Chapter
2 and Section 6.2.3 for a discussion of evaluating scenarios under
uncertainty).
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The definition of the temperature goals themselves
forms a third complication. Temperature goals might be defined in
terms of the long-term equilibrium associated with a given concentration, in terms of the temperature in a specific year (e. g., 2100), or
based on never exceeding a particular level.
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Finally, the reference
year, often referred to as Ôpre-industrialÕ, is ambiguous given both
the lack of real measurements and the use of different reference
periods.
Given all of these complications, a range of emissions pathways can be seen as consistent with a particular temperature goal
(see also Figure 6.12, 6.13, and 6.14 below).
Because of the uncertain character of temperature outcomes,
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probabilistic temperature information has been created for the scenarios in the AR5
database that have reported information on at least CO2, CH4, N2O and
sulphur aerosol emissions.
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Several papers have introduced methods for
probabilistic statements on temperature increase for emission scenarios
(Meinshausen, 2006; Knutti et al., 2008; Schaeffer et al., 2008; Zickfeld
et al., 2009; Allen et al., 2009; Meinshausen et al., 2009; Ramanathan and
Xu, 2010; Rogelj et al., 2011).
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For this assessment, the method described
by Rogelj et al. (2012) and Schaeffer et al. (2014) is used, which employs
the MAGICC model based on the probability distribution of input parameters from Meinshausen (2009) (see also Meinshausen et al., 2011c).
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