3.5.2.3. Use of Climate Model Outputs
The most common method of developing climate scenarios for quantitative impact
assessments is to use results from GCM experiments. Most estimates of impacts
described in this report rely on this type of scenario. GCMs are three-dimensional
mathematical models that represent physical and dynamical processes that are
responsible for climate. All models are first run for a control simulation that
is representative of the present-day or preindustrial times. They have been
used to conduct two types of "experiment" for estimating future climate:
equilibrium and transient-response experiments. In the former, the equilibrium
response (new stable state) of the global climate following an instantaneous
increase (e.g., doubling) of atmospheric CO2 concentration or its
radiative equivalent, including all GHGs, is evaluated (Schlesinger and Mitchell,
1987; Mitchell et al., 1990). Transient experiments are conducted with
coupled atmosphere-ocean models (AOGCMs), which link, dynamically, detailed
models of the ocean with those of the atmosphere. AOGCMs are able to simulate
time lags between a given change in atmospheric composition and the response
of climate (see TAR WGI Chapter 8).
Most recent evaluations of impacts, as reflected in this report, are based on
scenarios formed from results of transient experiments as opposed to equilibrium
experiments.
| Table 3-5: Catalog of GCM experiments
used to develop scenarios applied by impact studies referenced in this report.
Columns show the acronym of the modeling center; the common model acronym
found in the impacts literature; a code for the model experiment; reference
number for the experiment from Chapter 8, WGI
TAR; main reference sources; type of experiment (EQ = equilibrium; TRS
= transient with simple ocean; TRC = transient cold start with dynamic ocean;
TRW = transient warm start with dynamic ocean); increase in CO2-equivalent
concentration; effective climate sensitivity [equilibrium warming at CO2-doubling
from AOGCM experiments (see Chapter 9, WG
I TAR); in some cases this differs from climate sensitivities cited
elsewhere derived from atmosphere-only GCMs]; and availability from IPCC
Data Distribution Centre. |
 |
| Center |
Model |
Expt |
WG I |
Reference |
Type |
Forcing |
dT2xCO2(°C) |
DDC |
|
| CCCma |
CCC |
a
|
—
|
McFarlane et al. (1992) |
EQ
|
2 x CO2
|
3.5
|
—
|
| |
CGCM1 |
b
|
6
|
Boer et al. (2000) |
TRW
|
1% a-1
|
3.6
|
X
|
| |
|
|
|
|
|
|
|
|
| CCSR/NIES |
CCSR-98 |
c
|
5
|
Emori et al. (1999) |
TRW
|
1% a-1
|
3.5
|
X
|
| |
|
|
|
|
|
|
|
|
| CSIRO |
CSIRO |
d
|
—
|
Watterson et al. (1997) |
EQ
|
2 x CO2
|
4.3
|
—
|
| |
CSIRO-Mk2 |
e
|
10
|
Gordon and O'Farrell (1997) |
TRW
|
1% a-1
|
3.7
|
X
|
|
|
|
|
|
|
|
|
|
|
|
DKRZ
|
ECHAM1
|
f
|
13
|
Cubasch et al. (1992)
|
TRC
|
IPCC90A
|
2.6
|
—
|
|
|
ECHAM3
|
g
|
14
|
Cubasch et al. (1996)
|
TRW
|
IPCC90A
|
2.2
|
X
|
|
|
ECHAM4
|
h
|
15
|
Roeckner et al. (1996)
|
TRW
|
IPCC90A
|
2.6
|
X
|
| |
|
|
|
|
|
|
|
|
| GFDL |
GFDL |
i |
-- |
Wetherald and Manabe (1986) |
EQ |
2 x CO2 |
4.0 |
— |
| |
GFDLTR |
j |
-- |
Manabe et al. (1991) |
TRC |
1% a-1 |
4.0 |
— |
| |
GFDL-R15 |
k |
16 |
Haywood et al. (1997) |
TRW |
1% a-1 |
4.2 |
X |
| |
|
|
|
|
|
|
|
|
| GISS |
GISS |
l
|
—
|
Hansen et al. (1983) |
EQ
|
2 x CO2
|
4.2
|
—
|
| |
GISSTR |
m
|
—
|
Hansen et al. (1988) |
TRS
|
1.5% a-1
|
4.2
|
—
|
| |
|
|
|
|
|
|
|
|
| NCAR |
NCAR |
n
|
—
|
Washington and Meehl (1984) |
EQ
|
2 x CO2
|
4.0
|
—
|
| |
NCAR1 |
o
|
28
|
Washington and Meehl (1996) |
TRW
|
1% a-1
|
4.6
|
X
|
| |
|
|
|
|
|
|
|
|
| OSU |
OSU |
p
|
—
|
Schlesinger and Zhao (1989) |
EQ
|
2 x CO2
|
2.8
|
—
|
| |
|
|
|
|
|
|
|
|
| UKMO |
UKMO |
q |
-- |
Wilson and Mitchell (1987) |
EQ |
2 x CO2 |
5.2 |
-- |
| |
UKHI |
r |
-- |
Haarsma et al. (1993) |
EQ |
2 x CO2 |
3.5 |
-- |
| |
UKTR |
s |
-- |
Murphy (1995) |
TRC |
1% a-1 |
2.7 |
-- |
| |
HadCM2 |
t |
22 |
Mitchell and Johns (1997) |
TRW |
1% a-1 |
2.5 |
X |
| |
HadCM3 |
u |
23 |
Gordon et al. (2000) |
TRW |
1% a-1 |
3.0 |
X |
|
|
|