Monday, 10 January 2000: 2:30 PM
Chris E. Forest, MIT, Cambridge, MA; and M. R. Allen, P. H. Stone, and A. P. Sokolov
We present a method for estimating uncertainties in climate
predictions by comparing the modeled response to prescribed forcings
over the 20th century against climate observations for that period.
To determine these constraints, we use the MIT 2D climate model
(Sokolov and Stone,1998) in conjunction with results from the Hadley
Centre's coupled atmosphere-ocean general circulation model (A-OGCM),
HadCM2. The MIT 2D model is a zonally-averaged version of a 3D GCM
and was shown to accurately reproduce the global-mean transient
response of any coupled A-OGCM through appropriate choices of the
cloud feedback and the effective rate of diffusion of heat into the
deep ocean. Vertical patterns of zonal mean temperature change
through the troposphere and lower stratosphere also compare favorably
with those generated by 3-D GCMs. We compare the height-latitude
pattern of temperature changes as simulated by the MIT 2D model with
observed changes, using climate change detection diagnostics, which
yield an objective measure of model-observation goodness-of-fit (via
the noise-weighted residual sum of squares, see Allen and Tett
(1999)). For purposes of comparison, the forcings and fingerprint
were chosen to match those used in Allen and Tett (1999), which
follows Tett et al. (1996). The MIT model permits one to
systematically vary global model parameters and determine how the
goodness-of-fit with observations depends on these factors. Three
such parameters are the cloud feedback (i.e. the model's climate
sensitivity), rate of mixing of heat into the deep ocean, and the net
direct radiative forcing by anthropogenic aerosols. This would not be
possible with a coupled A-OGCM, owing to the computational
requirements and lack of structural flexibility. Hence, we varied
climate sensitivity from 0.4 K to 6.2 K, global-mean ocean diffusivity
from 0.0 cm
2/s to 160.0 cm
2/s, and the
anthropogenic aerosol forcing from -1.5 to +0.5 W/m
2.
For a fixed aerosol forcing at -0.5 W/m2, two sets of model parameters are rejected, with a
chosen confidence level, as being inconsistent when the model response
is compared with observations. The first corresponds to high climate
sensitivity and low heat uptake by the deep ocean; the second
corresponds to climate sensitivity less than ~1 K for all values of
ocean heat uptake. When the aerosol radiative cooling is increased,
these rejection regions retain their shape but shift to compensate for
the decrease in the net radiative forcing.
Thus, to obtain matching temperature changes, either a higher climate
sensitivity or a reduced ocean heat uptake are required for the same
changes in greenhouse gas concentrations. When we turn off the
anthropogenic aerosol forcing, we still find that simulations are not
inconsistent with observed temperature changes. Although high climate
sensitivities combined with low ocean heat uptake can now be rejected
more strongly, we still reject regions with climate sensitivity less
than ~1 K for all values of ocean heat uptake. This contribution provides an
efficient framework for interpreting detection and attribution results, and it estimates quantitative uncertainty bounds for
both physical properties and forcings of the climate system that are important for
future climate predictions.
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