Appendix 9.1: Tuning of a Simple Climate Model to AOGCM Results
The simple climate model MAGICC (Wigley and Raper; 1987, 1992; updated in Raper
et al., 1996) was used in the SAR to make temperature projections for various
forcing scenarios and for sensitivity analyses. The justification for using
the simple model for this purpose was the models ability to simulate AOGCM
results in controlled comparisons spanning a wide range of forcing cases (for
example SAR Figure 6.13). The approach used in this report differs from that
in the SAR. Thus the upwelling diffusion-energy balance model (UD/EB) model
is not used here as a stand-alone model in its own right but instead it is tuned
to individual AOGCMs and is used only as a tool to emulate and extend their
results. In this way, a range of results is produced reflecting the range of
AOGCM results. The tuning is based on the CMIP2 data analysis of Raper et al.
(2001b). The validity of the tuning is tested by comparisons with AOGCM results
in the DDC data set and, where available, with recent AOGCM results using the
SRES scenarios. By using such simple models, differences between different scenarios
can easily be seen without the obscuring effects of natural variability, or
the similar variability that occurs in coupled AOGCMs (Harvey et al., 1997).
Simple models also allow the effect of uncertainties in the climate sensitivity
and the ocean heat uptake to be quantified. Potentially, other simple models
(for example, Watterson (2000), Visser et al. (2000)) could be used in a similar
way.
The first step in the tuning process is to select appropriate values for the
radiative forcing for a CO2 doubling parameter, F2x, and
the climate sensitivity parameter, T2x. In the SAR, F2x=
4.37 Wm-2 was used, as given in the 1990 IPCC Assessment (Shine et
al., 1990). This value, which did not account for stratospheric adjustment and
solar absorption by CO2, is now considered to be too high (Myhre
et al., 1998). These authors suggest a best estimate of 3.71 Wm-2;
model-specific values are used here (see Table 9.A1).
The effect on global mean temperature and sea level change of using lower values
of F2x has been investigated by Wigley and Smith (1998). The lower
F2x values result in slightly lower temperature projections. Different
definitions and methods of calculation of model climate sensitivity are discussed
in Section 9.3.4.1. Here the effective climate sensitivities
based on the last twenty years of the CMIP2 data are used.
| Table 9.A1: Simple climate model parameter
values used to simulate AOGCM results. In all cases the mixed-layer depth
hm=60m, the sea ice parameter CICE=1.25 and the proportion of the upwelling
that is scaled for a collapse of the thermohaline circulation is 0.3, otherwise
parameters are as used in the SAR (Kattenberg et al., 1996; Raper et al.,
1996). |
 |
| AOGCM |
F2x (Wm -2)
|
T2x (°C)
|
 T
+(°C) |
k(cm2s-1)
|
RLO
|
LO and NS (Wm-2 °C-1)
|
|
| GFDL_R15_a |
3.71*
|
4.2
|
8
|
2.3
|
1.2
|
1.0
|
| CSIRO Mk2 |
3.45
|
3.7
|
5
|
1.6
|
1.2
|
1.0
|
| HadCM3 |
3.74
|
3.0
|
25
|
1.9
|
1.4
|
0.5
|
| HadCM2 |
3.47
|
2.5
|
12
|
1.7
|
1.4
|
0.5
|
| ECHAM4/OPYC |
3.8
|
2.6
|
20
|
9.0
|
1.4
|
0.5
|
| CSM 1.0 |
3.60
|
1.9
|
-
|
2.3
|
1.4
|
0.5
|
| DOE PCM |
3.60
|
1.7
|
14
|
2.3
|
1.4
|
0.5
|
|
Having selected the value of F2x and T2x appropriate
to a specific AOGCM, the simple model tuning process consists of matching the
AOGCM net heat flux across the ocean surface by adjusting the simple model ocean
parameters following Raper et al. (2001a), using the CMIP2 results analysed
in Raper et al. (2001b). Sokolov and Stone (1998) show that when using a pure
diffusion model to match the behaviour of different AOGCMs a wide range of diffusion
coefficients is needed. The range here is much smaller because a 1-D upwelling
diffusion model is used and changes in the strength of the thermohaline circulation
are also accounted for. A decrease in the strength of the thermohaline circulation
leads to an increased heat flux into the ocean. In the UD/EB model a weakening
of the thermohaline circulation is represented by a decline in the upwelling
rate (see SAR). The rate of sea level rise from thermal expansion for a collapse
in the thermohaline circulation in the UD/EB model is tuned to match that which
occurs for an induced collapse in the GFDL model (GFDL_R15_a) control run. An
instantaneous 30% decline in the UD/EB model upwelling rate gives rates of sea
level rise comparable to that seen in the GFDL model over a period of 500 years.
Thus a 30% decline in the UD/EB model upwelling rate represents a collapse in
the thermohaline circulation. For the individual models the rate of decline
in the strength of the thermohaline circulation relative to the global mean
temperature change is based on the CIMP2 data and is specified by the parameter
T+. It should
be pointed out that the processes in the UD/EB model that determine the heat
flux into the ocean are not necessarily physically realistic. Raper and Cubasch
(1996) as well as Raper et al. (2001a) show that the net heat flux into the
ocean in the UD/EB model can be tuned to match that in an AOGCM in several ways,
using different sets of parameter values. Nevertheless, if the UD/EB model is
carefully tuned to match the results of an AOGCM, and provided the extrapolations
are not too far removed from the results used for tuning, the UD/EB model can
be used to give reasonably reliable estimates of AOGCM temperature changes for
different forcing scenarios. The thermal expansion results are less reliably
reproduced because thermal expansion is related to the integrated heat flux
into the ocean. Errors therefore tend to accumulate. In addition, the expansion
depends on the distribution of warming in the ocean. Nonetheless, the simulation
is adequate for comparison of scenarios.
Other parameters in the UD/EB model are adjusted in order to correctly simulate
the greater surface temperature change over the land relative to the ocean as
shown to a varying degree in different AOGCM results. The land-ocean, Northern-Southern
Hemisphere temperature change contrasts are adjusted by parameters that govern
the contrast in the land-ocean climate sensitivity and the land-ocean exchange
coefficients. The specific parameter values used for the different AOGCMs are
given in Table 9.A1.
