Environmental Engineering Reference
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to be symmetric, especially when one considers observational constraints,
such as those that are provided by paleoclimates, that constrain the equi-
librium climate response directly rather than by constraining the strengths
of feedbacks. Hannart et al. (2009) have highlighted the implications of the
arbitrary assumptions regarding uncertainty in Roe and Baker's analysis.
Chapter 6 contains a brief discussion of paleoclimatic constraints consistent
with the range of equilibrium sensitivities in Table 3.1
Perturbed physics ensembles, notably Stainforth et al. (2005), do show
that there are physical mechanisms that can operate in climate models,
which yield climate sensitivity well above the top of the IPCC range em-
ployed in Table 3.1. Such ensembles do exhibit a distribution of climate
sensitivity with a fat tail skewed toward high values, much as one would
expect from assuming a symmetric and broad uncertainty distribution in the
total feedback strength. In perturbed physics ensembles, it is typical to admit
members to the ensemble only if they pass through a “keyhole” requiring
that the basic climate of that member is realistic enough to serve as a basis
for predicting the future. If the keyhole is made too wide, it can allow un-
realistic behaviors to pass through. This is evidently the case for the many
of the anomalously high climate sensitivity cases seen in Stainforth et al.
(2005), which require a very unrealistic moistening of the upper troposphere
and lower stratosphere (Sanderson et al., 2008; Joshi et al., 2010). It cannot
unequivocally be ruled out that some unknown future climate state could
trigger the onset of such behavior of water vapor, but there is no good basis
at present for evaluating the prospects that this might happen. As another
example, working with an alternative model, Yokohata et al. (2005) illustrate
how simulation of the Pinatubo eruption provides evidence against a version
of the model with equilibrium sensitivity as high as 6K.
Our choice to emphasize the CMIP3/AR4 model range is based on the
judgment that these models have been analyzed most fully by the research
community, thanks in large part to the open archive created by the World
Climate Research Program's Couple Model Intercomparison Program and
the Department of Energy's Program for Climate Model Diagnosis and In-
tercomparison ( http://www-pcmdi.llnl.gov/ ). The description of this range
of equilibrium sensitivity in the CMIP3 models as “likely” is consistent with
the conclusions of the review of Knutti and Hegerl (2008), which attempts
to take into account observational constraints as well as model results.
In interpreting future climate impacts based on Table 3.1 it is impor-
tant to keep in mind that these do not necessarily represent worst possible
cases, even if defensible physical mechanisms leading to higher climate
sensitivity have not yet been identified. Our judgment is that the likelihood
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