cc: jfbmitchell@meto.gov.uk
date: Fri, 09 Jul 1999 12:03:50 -0400 (EDT)
from: JMitch3572@aol.com
subject: chapter13review-j.mitchell
to: tar13@meto.gov.uk

Dear Chapter 13 authors
I attach some comments on your first draft- I hope they are useful.
With best wishes
JohnMitchell



Review of first draft of chapter 13 of the IPCC TAR

General comments
This is a good first draft- it reasonably short, well laid out, mostly easy 
to read and generally to the point. It also sticks well to the assessment of 
methodology of producing scenarios, not scenarios per se. I would urge the 
authors to resist embellishing the chapter. I had some difficulty with the 
approach in section 13.5.1.6

Specific comments
Section 13.1.1
I found this section hard to read- long convoluted sentences, unnecessary and 
numerous qualifiers, and a slightly odd choice of words.
eg lines 128-132
"for example, most future climate change scenarios include the characteristic 
of increased tropospheric temperature (except in some isolated regional and 
physical circumstances) and that particular condition is one in which most 
climatologists have most confidence (I.e. believe to be the most 
plausible)(Schneider et al,1990)"
which means (I think)
"For example, most scenarios include increased surface temperature as this 
the change climatologists think most plausible"

line 381 could reference Cubasch et al, 1994, Mitchell et al, 1999

Section 13.3.4
Another advantage of the using the latest period is that impacts are 
evaluated with respect to present (i.e. the present status of the parameter 
being impacted) and not to a period some period in the past.
A disadvantage is that every ten years or so, the baseline moves, and new and 
old studies become less compatible. If the rate of climate change 
accelerates, then this will become more of a problem.

Section 13.4.1
There is a philosophical problem here- is one really gaining any skill by 
downscaling?
It is not just that the model's level of skill is restricted to much larger 
scale than that of a grid point. Even with a perfect model, the scale at 
which the model is skilful is quite limited, (see Stott and Tett, 1998(?)), 
because of internal variability. 
Regional models and MOS methods may help to some extent by allowing for 
mesoscale effects, particularly those due to orography and changes in surface 
type. However, even if the GCM is skilful at its gridscale, the impacts 
modeller must remember that downscaled fields are plausible rather than 
necessarily more skilful.

line 685
Statistical downscaling relies on the availability of long, good quality 
timeseries of the appropriate climatological data. Hence there are regions of 
the globe where one would struggle to implement this approach.

Lines 858-861 Leave the assessment of changes in ENSO to chapter 9. For the 
purpose of this discussion it is sufficient to state that we have little 
confidence in the predicted changes for ENSO- some models do predict an 
increase in frequency, and this could be incorporated in scenario development.

871-874 Again, this should be based on chapter 9. If chapter 9 doesn't cover 
this adequately, then help them.

Section 13.5.1
There is also an uncertainty form getting from concentrations to forcing (eg 
the indirect aerosol effects)
I presume signal to noise ratios means sampling uncertainty.

931-5 I think this repeats what was said earlier in the chapter.



Section 13.5.1.6
I wasn't quite sure where this was leading- may be I misread the sign posts- 
I think the issues are

I think for impacts the things of interest are Tf and changes in the 
distribution of T" which together are needed to evaluate extreme events.

The control distribution of T" (orTf/T") is of interest from the point of 
view "will we notice the any differences?"

Models give Tf +T" - (or Tf +T"/(n)**0.5 from an ensemble of n) and so do not 
give a clean estimate of Tf. 

One point is that many studies to date have used data where T" is comparable 
to Tf because of the short meaning period. Giving the standard deviation of 
T" can help impact scientists to assess the signal to noise ratio of their 
changes, and hence ignore insignificant changes.

Another problem is that even with a long control run, it is not simply 
possible to add the distribution of T" estimated from the long control to the 
estimated Tf from a model run to get the mean and spread, because Tf will be 
contaminated by T".

Another issue is using ensembles for a non-linear impact- the mean of the 
impacts for each ensemble is a better measure than the impact of the mean 
climate change.

1034 scale dependant, AND dependant on what variable is used.

1042- 1044 This is more to do with uncertainty in the response to forcing 
and, if included, should got there. Averaging across models as a way of 
improving accuracy has no scientific basis and is highly controversial. If 
models all have the same sort of error, then this will not work. If the model 
errors are smaller than the level of internal variability on the timescale of 
interest, then this will work as one is effectively increasing the "noise" 
ensemble size.

1203ff  There is no easy answer to this. There is some comfort in having a 
reasonable simulation of present day climate, particularly in and around the 
region of interest. As noted , having neighbouring sea-ice/snow cover in the 
right place, and the correct positioning and seasonal movement of the 
rainbelts affecting the area of interest is  obviously a good idea. But as 
noted in chapter 9, one can vary parameters in a model which have little 
effect on present day climate, but alter the sensitivity to climate change. 
This implies a good simulation of present day climate is not a sufficient 
condition for accurate simulation of climate change- the chapter should note 
this. (It is even possible that a model with a poor simulation of present day 
climate could provide a more accurate simulation than one which has a good 
simulation of present climate-  if it contains a better representation of the 
dominant feedbacks) However, it is difficult to validate the feedbacks.

1294 albedo (or does snow have a high albino?)

1301 -1313 update and harmonise with sea-level chapter-let them do the 
assessment.



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