from: Sarah Raper <sraperatXYZxyz-bremerhaven.de>
subject: my zero draft for CH10
to: Tom Wigley <wigleyatXYZxyz.ucar.edu>
At the end of this email please find my zero draft for ch10. I would
much appreciate it if you would look through it. I have reviewed
literature since the TAR and how that reflects on what we did in the
TAR, and outlined what might be done in the AR4.
It's only zero draft and likely most of it won't stay but it does set
the tone for where we are going so its quite important for that.
It is already about 3/4 the length of what I am allowed!
PS will have some space for forcing in Collin's section.
10.5.2 Range of responses from different scenarios.
The TAR projections with a SCM presented a range of warming over the
21st Century for all the SRES scenarios. The construction of the TAR
Figure 9.x was pragmatic. It used a simple model tuned to AOGCMs that
had a climate sensitivity within the long-standing range of 1.5 - 4.5
advocated by the IPCC. Models with CS outside that range were discussed
in the text and allowed the statement that the presented range was not
the extreme range indicated by AOGCMs. The figure was based on a single
anthropogenic forcing estimate for 1750 to 2000, which is well within
the range of values recmommended by TAR ch 6, and is also consistent
with that deduced from model simulations and the observed temperature
record (TAR ch 12.). To be consistent with TAR Ch 3. climate feedbacks
on the carbon cycle were included. The resulting range of global mean
temperature change from 1990 to 2100 given by the full set of SRES
scenarios is 1.4 to 5.8 degC.
Since the TAR several studies have examined the TAR projections and
attempted probabilistic assessments. Allen et al, 2001 show that the
forcing and SCM tunings used in the TAR give projections that are in
agreement with the observationally constrained probabilistic forecast
(Allen et al. 2000), reported in TAR ch x, stating that under the IS92a
scenario anthropogenic warming is likely to lie in the range 0.1 deg to
0.2 degC over the next few decades.
As noted by Schneider (2001), Jones (2000) and Moss and Schneider
(2000), giving only a range of warming results is potentially
misleading unless some guidance is given as to what the range means in
probabilistic terms. Wigley and Raper (2001) interpret the warming
range in probabilistic terms, accounting for uncertainties in
emissions, the climate sensitivitiy, the carbon cycle, ocean mixing,
and aerosol forcing. They give a 90% probability interval for 1990 to
2100 warming of 1.7 deg to 4.9 degC. As pointed out by Wigley and Raper
(2001), such results are only as realistic as the assumptions upon
which they are based. Key assumptions in this study were; that each
SRES scenario was equally likely, that 1.5 to 4.5 corresponds to the
90% confidence interval for the CS, that carbon cycle feedback
uncertainties can be characterised by the full uncertainty range of
abundance in 2100 of 490 to 1260 ppm given in the TAR. The aerosol pdf
was based on the uncertainty estimates given in the TAR together with
constraints based on fitting the SCM to observed global- and
Several studies have used observational constraints to determine the
range of likely future climates under specific emissions scenarios.
Because CS is only weakly constrained by the observations Knutti et al
(2002) admit higher warming for the specific scenarios studied compared
to the TAR SCM projections. However, when they also constrain CS to be
in the range 1.5 to 4.5 deg C they get results consistent with the
those of the TAR. Stott and Kettleborough 2002 bypass the need to
specify the CS and scale scenarios on the assumption that a model that
over- or under-estimates the response by a ceratin fraction now will
continue to do so by a similar fraction in the future. They give
probabilistic results for specific emissions scenarios which admit
higher warming than given in the TAR.
Stott and Kettleborough 2002 mention that the reduction of SO2
emissions in the SRES scenarios in the latter half of the century
increases the uncertainty range consistent with past observations.
However, Wigley and Raper 2001 with their method, report that the 21st
C decline in SO2 emmissions leads to a reduction in the effect of the
very large present-day uncertainty range in aerosol forcing on future
Webster et al. (2003) use the probabilistic emissions projections of
Webster et al.(2002) which consider present uncertainty in SO2
emissions, and allow the possibility of continuing increases in SO2
emissions over the 21st C, as well as the declining emissions
consistent with SRES. Their main results give a CS pdf not unlike that
used by Wigley and Raper (2001) but for aerosol forcing their pdf gives
substantially smaller forcings compared to both Wigley and Raper (2001)
and Knutti et al. (2002). This is likely to be a compensatory effect
because they did not explicitly consider natural forcings. Since their
climate model pdfs were constrained by observations and are mutually
dependant the effect of the lower present day aerosol forcing on the
projections is not easy to determine but there is no doubt that their
projections tend to be lower where they admit higher SO2 emissions.
Only the first of these studies (Wigley and Raper, 2001) considers the
effect of carbon cycle feedbacks. None of the studies consider abrupt
changes which are examined in another section.
The aim of this section is to bring together information on emissions
scenarios from WGIII, on forcings from Chapter 2, on the carbon cycle
from Chapter 7, on attribution from chapter 8, and on model assessment
in Chapter 9, together with the AOGCM responses examined in this
chapter and to make projections with simplified models that are
consistent with that information.
There will be a figure 10.x1 comparable to TAR Figure 9.14, so that the
new projections can be compared to the old. Observational constraints
will be considered at least for the near term using information from
Chapter 8 (attribution).
As well as the SRES scenarios there may be new information from WGIII,
with the possiblility of probabilistic and longer-term scenarios. It is
likely that Chapter 2 will provide probabilistic forcings. In TAR
Figure 9.14 a climate feedback on the carbon-cycle was included. We
will seek the latest information on the strength of this feedback and
its uncertainties from Chapter 7. These uncertainties will be
concatenated where possible in probabilistic form to produce a new
presentation of results in Figure 10.x2 (SCM) and Figure 10.x3 (EMIC,
possible contribution from Knutti). It may be necessary to have an
additional figure showing longer-terms scenarios (Figure 10.x4).
The SCM will be tuned to emulate the AOGCMs using the PDMCI AR4 AOGCM
modelling exercise data. For Figure 10.x1 the climate sensitivities
will be the AOGCM effective climate sensitivities at the time of CO2
doubling and the ocean heat uptakes in the SCM will match those of the
AOGCMs in the 1% CO2 increase experiment. Figures 10.x2 and 10.x3 may
present results based on pdfs of the climate sensitivity and other
Probabilistic temperature projections do not give true probabilities of
occurrance but are conditional on the assumptions made in their
construction. To convey this it may be wise to present more than one
set of probabilistic projections, using for example different pdfs for
the climate sensitivity (cf Box on pdfs of climate sensitivity).