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parameters, in particular
, may be time-dependent 3 , which serves no
purpose if we do not specify what they vary in relation to. This is how
[BOE 05] consider that climate sensitivity is dependent on the level of
forcing. Such a dependence in relation to the variables
λ
G
uu or T G
therefore implies nonlinearity, to be processed as such, or to be integrated in
an LTI approximation.
,
,
u
1
2
3
is what it is. Excepting incoherence, it is
constant. There are as many reasons to enlarge it as there are to reduce it. It
is, above all, very uncertain, whether globalized in a reduced EBM, or
distributed through a large-scale GCM.
Ultimately, the coefficient
λ
G
G will
unfortunately be individually inaccessible using the observation of
input/output data. Only the transmittance G ( s ) can be identified along with
sensitivities in the form of ratios
In the context of identification, the coefficients
and
λ
α
,
α
,
α
1
2
3
α
α
α
1
2
3
. This does not
S
=
,
S
=
,
S
=
1
2
3
λ
λ
λ
G
G
G
prevent us from taking advantage of the fact that static sensitivities S i are in
the same ratio as radiative forcing coefficients
, but to increase to three
α
i
G , it would be necessary to have prior knowledge of one or other of
the four parameters. Unfortunately, as will be seen in Chapter 5, there is not
one of these which physical knowledge allows us to determine a priori with
enough accuracy.
and
λ
α
i
4.4. Dynamic parametrization
The above formulation of equilibrium sensitivities can be found, at one
level or another, in all climatic energy balance models. It is also implicitly
3 AR4, end of paragraph 8-8-2: The obtained best-fit climate sensitivity estimates differ for
various reasons from other estimates that were derived with alternative methods. Such
alternative methods include, for example, regression estimates that use a global energy
balance equation around the year of atmospheric CO 2 doubling or the analysis of slab ocean
equilibrium warmings. The resulting differences in climate sensitivity estimates can be
partially explained by underscore in many of the AOGCM runs. Furthermore, tuning results
of a simple climate model will be affected by the model structure, although simple and other
default parameter settings that affect the simple model transient response.
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