Environmental Engineering Reference
In-Depth Information
more complete simulations on longer time scales, once the ocean stops
taking up heat.
For the general circulation models listed in Table 8.2 of IPCC, Working
Group I, The Physical Science Basis (IPCC, 2007a), the equilibrium
Δ
T
2x
has a minimum of 2.1°C, a maximum of 4.4°C, and a median of 3.2°C. Even
the least sensitive model has a higher climate sensitivity than the idealized
calculations yield for basic clear-sky water vapor and lapse-rate feedback.
This is largely because the presence of clouds increases the basic black-
body plus water vapor feedback sensitivity to about 1.8°C even if clouds
do not change as the climate warms. This form of cloud effect is not con-
ventionally counted as a cloud feedback. It is more robust than feedbacks
due to
changing
clouds, because it is based on cloud properties that can be
verified against today's climate. This value, too agrees well among models
and is considered to be highly certain. Thus, the least sensitive IPCC models
correspond very nearly to cloud properties remaining fixed while warming
is amplified by water vapor feedbacks alone. The more sensitive models
are more sensitive primarily by virtue of having positive cloud feedback.
The spread in equilibrium climate sensitivity within the IPCC ensemble of
models is primarily due to differences in cloud feedback, and in particular
to the feedback of low clouds (Bony et al., 2006). Note that climate sensi-
tivity could only be lower than about 1.8°C if there are negative feedbacks
very different from those of any of the models, such as changes in upper
tropospheric or lower stratospheric water vapor, or changes in clouds that
are opposite to those expected.
It has long been recognized that a symmetric distribution of the uncer-
tainty in the strength of the feedbacks affecting climate sensitivity results in
a skewed distribution in the climate sensitivity itself, with a high probability
of large values (e.g., Schlesinger, 1986).
2
Roe and Baker (2007) attempt to
use this property to argue that it will be extremely difficult to eliminate the
significant possibility of very high climate sensitivities. However, there is
no a priori reason to expect the uncertainty in the strength of the feedback
2
This can be understood by noting that the climate sensitivity is proportional to 1/(1-f), where
f is the strength of the feedbacks, and is positive if the feedbacks are positive. If one starts with
the value f = 0.5, then increasing f by 0.25, say, increases the sensitivity by 100%, or a a fac-
tor of two. Decreasing f by the same amount decreases the sensitivity by only 67%. One can
also use Figure 3.1 to understand this result pictorially. Climate sensitivity is proportional to
the reciprocal of the slope shown in the figure, with the magnitude of the slope determined by
the strength of the feedbacks. A symmetric distribution of slopes does not result in a symmetric
distribution of climate sensitivity. A symmetric distribution might include zero slope with a
finite probability, resulting in infinite climate sensitivity, which, of course, is ruled out by the
observed stability of the climate system.
