Subject: Chapter 13 review
Date: Fri, 23 Jul 1999 19:52:44 +0100
Cc: email@example.com, firstname.lastname@example.org
COMMENTS ON CH. 13 (SCENARIOS) FROM TOM WIGLEY
(Page and line numbers are from the May 14 zero order draft.)
Dear contributors to Ch. 13,
Here are my comments on your chapter. I think you all know me
well enough that you will not be offended by my occasional
bluntness. The chapter needs a lot of work (not surprisingly),
but it has at least touched most of the bases. It suffers from
a lack of overview perspective, making the detail hard to wade
through. I was disturbed by the lack of credit given to
MAGICC/SCENGEN, since this software already addresses many of the
key issues that arise in scenario development.
Apologies for not proof reading this. By the time I got to the
end of typing it, I'd had enough.
Page 3 (lines 86-89) : Critically, this information doesn't give
a full assessment of uncertainties.
3 (110-115) : Sentence too long.
3 (117) : State 'illuminate uncertainty' earlier, since this
is a primary purpose of, e.g., MAGICC/SCENGEN.
3 (118) : 'indeterminate' is far too strong.
4 (124-125) : Not clear.
4 (155) : What is 'integrated assessment'? Define and/or
5 (170) : Clumsy grammar.
5 (171-172) : Silly! Scenarios per se do not have ANY uncertainty
associated with them, by definition. They are, however, a very
(if not the most) useful tool for assessing and quantifying
uncertainties. For example, a primary purpose of MAGICC/SCENGEN
is to quantify uncertainties. Major text revision is needed to
clarify this point.
Part of the problem here is that the boundary between scenarios
and predictions/projections is indistinct (as is the distinction
between predictions and projections -- this too needs to be
clarified). One could argue that 'scenarios' developed using
MAGICC/SCENGEN are actually better predictions of some aspects
of future climate change than any O/AGCM results. Certainly,
'scenarios' based on scaling are much more than just scenarios
as defined here -- they are true predictions, based on some
assumed scenario (this is the correct word here!) for future
Substantial work is required to the present text to clarify
these issues -- they are the crux of the matter.
5 (178-179) : Note earlier that scenarios (a word I will continue
to use even though it may be inappropriate in many cases)
usually define CHANGES in climate. They are not, in these
cases, 'scenarios', but 'scenarios of change'. Strict (i.e.,
absolute) scenarios are then constructed from them by adding
the changes to a baseline climatology. This needs to be
explained up front.
5 (187) : Delete '(and art)'. This is a derogatory term, likely
to be misinterpreted/misrepresented.
6 (220) : Comma after 'scenarios'. The text contains many
stylistic and grammatical errors (the most common being the
failure to isolate parenthetical clauses). I will assume that
someone with a better grasp of grammar will catch all these
at some stage, so I will not comment further on them.
6 (225+) : A critical item missed here is inter-variable
consistency. Later, consistency between climate and CO2 is
mentioned; but there is no mention of consistency between, e.g.,
temperature and precipitation, etc. This is a major issue!
7 (257) : Instrumentally-based analogue scenarios were first
introduced by Wigley et al. (Nature, 1979). Credit should be
given. Also, the USDOE 'State of the Art (sic)' reports (1985)
and the Bolin et al. SCOPE report (1986) both review this and
other methods. This reviews should be cited.
7 (267-268) : What does 'extrapolating ...' mean?
7 (296) : Wigley et al. (1979) should also be cited here.
8 (306) : Nevertheless, they may do a better job of getting the
inter-variable correlations 'right' than GCMs!
8 (315) : Delete 'questionable'. This word is entirely unnecessary
here. More importantly, the authors need to be more careful in
their choice of words, since there are many critics out there who
will be looking for things that can be taken out of context,
misinterpreted, or misrepresented.
8 (344-345) : Control run? So what? This is only relevant if the
control is used in scenario development. This raises the issue
of 'Definition 1' versus 'Definition 2' for defining climate
change (a terminology introduced by Santer et al., 1994, JGR).
(Later, this difference is attributed to Cubasch et al., but
it was first clearly enuncited by Santer et al.) The difference
is whether or not one subtracts the control from the perturbed
result. More needs to be said about this. It is often assumed
that subtracting the control will remove any spurious drift in
the perturation experiment. This, of course, is clearly wishful
thinking, both a priori, and as shown by Raper and Cubasch (1996).
Basically, there is no way to reliably remove drift in a
perturbation experiment; which makes it all the more important
to have drift-free models. Flux adjustments do not necessarily
remove drift -- just look at some of the ECHAM control-run
results. There are some very important issues here, central to
the use of O/AGCMs in scenario generation. They need better
coverage. More is said later, but this is still inadequate.
9 (357) : Yes, they can be different, but so what? The issue is
whether the differences are statistically significant. To my
knowledge, no one has addressed this issue properly.
9 (358) : I'm sure (at least I hope) you don't mean 'observed'.
The issue is the difference between the equilibrium PATTERNS
of change and the MODELLED (NOT 'observed') transient patterns
9 (to 361) : You've missed the most inportant point! The advantage
of an equilibrium result over an O/AGCM result is that the
former is pure signal.
9 (to 376) : The Definition 1 versus Definition 2 issue is relevant
9 (379) : Please don't propogate garbage. The issue here is
natural internally generated variability. There is no need for
such variability to be chaotic, so you should eschew use of
9 (to 387) : I presume here that you are talking about O/AGCMs.
You should not use just 'GCM' -- you must be specific. Also,
you've missed some vital points: the natural internal variability
problem (i.e., output is signal plus noise -- noted elsewhere,
but must be stated here); and the model-specific natureof the
10(399) : Please give credit to the first work on this (Santer
et al., 1990). I should point out that this was actually my
10(404-406) : Totally unclear.
10(420-421) : Poor wording. Should be '.. to which changes are added'.
10(423) : Delete 'appropriate'.
10(429) : Insert 'based' after 'period'.
10(431) : 'weather generators' comes as a non sequitur here. In
any event, you haven't said what they are!
10(435-437) : So what? The issue is what period one is measuring the
impacts from. In most cases it will be some nominal 'present-day',
so the baseline climatology must refer to the same period.
Whether or not the period has some sulphate effect in it is
10(437-438) : What garbage. See above.
11(448-450) : More garbage -- think about it! The reason 1990 is
not so useful as a reference 'period' is because the impacts
variable is probably not adequately definable over a single
year. You have really messed up this issue.
11(460) : Yet more garbage! Given what I have tried to explain
above, it is ludicrous to consider daily data as part of the
baseline climatology. The impacts variable may require daily data
from a baseline period in order to define ITS reference level
(but probably not), but this is NOT the same thing. Either all
this is very badly worded, or you don't know what your doing.
11(468) : No!! Think about it!
11(470) : No!! This is NOT the reason.
11(473) : No!! Not 'observed' (which is past or present), but
11(482-483) : Duplication.
12(to 492) : This is a very confused paragraph.
12(497-499) : Wrong. For upper air, their is a major paper by Santer
et al. (JGR, 1999), which also touches on some surface issues.
There are also a number of papers by Trenberth that are relevant.
12(507) : Again, introduction of an undefined term/concept
12(510) : At last, mention of changes. Sadly, it is inappropriate
here, since this is NOT the reason.
12(514) : Why should this Figure be here?
12(518) : Wrong. As a scenario, this could be justified. You are
confusing scenario (as you have defined it, which I have already
criticized) with prediction/projection.
12(521) : See above.
12(525-527) : This is the Def. 1 vs Def. 2 issue. However, you have
the history and motivation wrong.
12(527-531) : Wrong. This issue has nothing to do with cold start vs
warm start; it is to get over the drift problem (which it fails
12(537) : Not 'especially'; mor appropriate may be 'but only'.
13(543) : 'were'; grammar!
13(543-545) : Not clear.
13(552-553) : Not clear.
13(579-581) : So what? Given your definition of scenario, this
14(594) : Why use 'perceived'?
14(604) : This issue was first raised by Kim et al. (1987?).
It was first addressed in a credible manner by Wigley et al.
14(606) : 'appending' is a ridiculous word to use. Try 'adding'.
14(608) : 'often' to 'usually'.
14(613) : 'appended' to 'added'.
14(616) : 'appended' to 'added'.
14(617) : 'appended' to 'added'.
14(627,628) : Please cite the key initial papers by Kim et al. and
Wigley et al.
15(635,636) : Clumsy sentence.
15(638) : Isn't the word 'physical' usually used? The process
does not just involve dynamics.
15(642-648) : Mention of 1-way vs 2-way nesting needed here.
15(657-659) : You have failed to mention the most important reason
for using LAMs, orography/topography.
16(667) : Please cite the key initial papers by Kim et al. and
Wigley et al.
16(673) : 'predict and' to 'predictand'.
16(679-683) : Once again, you fail to mention the main advantage;
viz. that statistical downscaling involve real-world data and
so ensures that inter-variable relationships are realistic. Of
course, these relationships may change; but LAMs don't even get
the correct relationships for the present.
16(703)-17(716): These are VERY important results. They need far
17(720) : In Australia? Or anywhere for that matter.
17(723-724) : See, e.g., Wigley (1999 - Pew report- and material
17(725) : 'mulitple'?
17(730-732) : Not clear.
17(739-740) : This sentence sounds stupid. Rephrase.
17(744) : You cannot say 'most areas' and then cite only
17(748) : The first clear exposition of this is in the oft-cited
paper by Wigley (Nature, 1985). See also later paper in Climate
17(755-756) : I disagree. Both methods have strengths and weaknesses.
18(770) : At last! A definition of 'weather generators'.
18(778-779) : Unclear.
18(798) : What means 'more definitive'?
18(803) : "Wilk's" to "Wilks'".
18(805) : Hence, the work is irrelevant in the present context.
Delete irrelevant text.
19(to 821) : Most of the agriculture studies dealing with the
effects of variability changes are flawed since they fail to
separate the low-frequency effect of induced changes in
winter soil moisture levels from the specific effect of
within-growing-season variability changes.
19(826-839) : Since this should refer back to lines 823,824,
this whole section amounts to a giant non sequitur.
20(880) : One could be much stronger than this. The use of
high spatial resolution information is more than just
'warranted', it is absolutely essential. However, there is
another approach that you have failed to mention at all.
This is 'upscaling' of the impacts model. There is some
relevant work on this in papers by Jarvis and McNaughton
(and vice versa). Another related approach is the direct
modelling of spatial patterns of agricultural yield (as
in work by Wigley and Tu Qipu, which relates yield patterns
to climate patterns). Presumably one could apply a similar
approach to direct modelling of river flow. These approaches
complement the rather boring direct approach of downcsaling,
and they may well circumvent some of its problems.
20(898) : Under this comes: model errors; sensitivity
uncertainties; aerosol forcing uncertainties; lag uncer-
tainties, regionalization versus global-mean uncertainties.
21(905) : lesser or greater than what??
21(916) : 'adequacy' is not the right word; hoe about
21(928) : I disagree. Re-analysis data for precipitation are
simply not good enough, and precipitation is the key variable
in most impact areas. Also, in the regions where scenario
data are most needed, real observational data are available.
Re-analyses largely provide useful new data in regions where
data are not needed. The authors seem not to have thought
21(to 931) : There are two papers by Wigley (conference
proceedings, edited by Hanisch) which address the issue of
the relative magnitudes of different sources of uncertainty
in global-mean projections (emissions, aerosol forcing,
carbon cycle, other trace gases, climate sensitivity).
These papers are singularly relevant to this section.
21(939) : Actually, the range for total emissions is from
7.9 to 29.0GtC/yr. For fossil CO2 emissions, the range is
6.5 to 28.8GtC/yr.
21(943) : Not just 'time-dependent evolution', but anything
that has a specific time attached to it.
22(948) : The reference to Alcamo et al. here seems either
perverse or ignorant. Recall that the topic is CLIMATE
scenarios. In this context, MAGICC/SCENGEN is FAR better
suited to exploring the consequences (right down the line)
of emissions 'uncertainties'.
22(959-960) : MAGICC/SCENGEN already does this at the global-mean
level. Furthermore, at least three O/AGCMs have fully embedded
sulphur cycles already.
22(968) : 'specifications' is the wrong word. These things
are NOT 'specified'.
22(970) : 'determine' to 'have'
22(972) : See also Wigley's Pew report (1999).
22(974-976) : Not straightforward? This really is utter garbage.
In MAGICC/SCENGEN, this is extremely easy and straightforward.
22(985) : Ah ha! The 1-way/2-way nesting issue surfaces at last!
22(989-990) : See above.
23(999) : Actually, this issue was first raised in Santer et al.
(1990). It has also been addressed in papers by Wigley and
Palutikof (probably before anyone else).
23(1010-1011): The wording here is not quite right.
23(1022) : First done in Santer et al. (1990).
23(1030) : If one assumes stable patterns, which has been shown
to be okay for the CO2 component of change, then the SNR problem
can be minimized by using changes over a long time interval.
23(1033) : This average response method was alluded to in
Santer et al. (1990). It was first implemented in ESCAPE and
later in MAGICC/SCENGEN. A good illustration of the method,
including some relevant discussion of it, is given in the
Wigley Pew report (1999). One of the critical aspects of this
method (which is not even mentioned here!) is that the results
must be normalized by the global-mean temperature before
24(1040) : Is this the ACACIA program run out of NCAR? This
program was established some years ago, and it would be
extremely confusing if there were two programs with the same
24(1047) : Not 'a few', but many -- CMIP1.
24(1060) : 'rations' to 'ratios'.
24(1060-1062): Not clear.
24(1073) : What means 'non-standard forcing'? In my view, something
like IS92a forcing would be 'standard', whereas 1% compound CO2
is 'non-standard' (i.e., unrealistic and artificial).
24(1076-1078): Really? Why? I think this statement is wrong. There
are a number of ways to determine SNR values from a single O/AGCM
run. (Note the continuing confusing use of 'GCM', instead of
24(1085) : I don't think 'uncertainties' is quite the right word
here. Input emissions scenarios, which are scenarios in the
strict sense of the word, do not directly address uncertainty
issues (although they can, with some trepidation and a not-
inconsiderable amount of ingenuity, be used to define
uncertainties). By the way, as far as I can see, the only
scenario development method/software that does address the
input and uncertainty issues is MAGICC/SCENGEN.
25(1090) : Again, these are not the most appropriate references.
Key references are Santer et al. (1990), and papers on ESCAPE
25(1093) : What means 'annotation' here?
25(1102) : Actually, it was my idea.
25(1105,1106): No! The key assumption is actually linear superposition.
This is the way that SO4 effects are handled. There are a number
of papers that show that this assumption works well for
temperature, and a paper by Ramaswamy and Chen in GRL that shows
that it works also for precipitation. The tricky thing for this
variable would be to prove statistically that it doesn't work.
Given the SNR, it would be very difficult to reject the null
hypothesis that P(A)+P(B)=P(A+B), where A,B are the forcings
and P(.) is the response pattern.
25(1108) : Plus numerous other papers.
25(1112,1113): This is very galling. The method may have been used
in IMAGE, but they got it from ESCAPE, which goes back to
Santer et al. (1990). MAGICC/SCENGEN pushes the idea as far
as is possible. Schlesinger's COSMIC does things quite
similarly tp MAGICC/SCENGEN. (Schlesinger was a co-author of
the Santer et al. paper.)
25(1115) : Not clear.
25(1122) : All you can say here is 'may not hold', not 'probably
does not hold'. Indeed, there are reasons to expect it to hold
25(1123) : Could begin new paragraph with 'Uncertainties'.
25(1123,1124): I think this statement is categorically wrong. MAGICC/
SCENGEN incorporates SO4 influences, as does COSMIC. There is
no evidence at all that the uncertainties are thereby amplified.
Indeed, there is evidence to the contrary (e.g. Penner et al.,
1997). Idle and unsupported speculations like this do nobody
25(1124,1125): I suspect you argument here would have to hinge on
the possible spatial effects of a THC slowdown or shutdown.
If so, say so. But, if this is the case, you must also note
that the latest non-flux-corrected O/AGCMs do not show these
major THC changes, and scaling approaches may well work out
very well for these situations, even in stabilization cases.
Please avoid jumping to unsubstantiated conclusions.
25(1125) : I refereed this paper, and I judged it to be an
appalling display of ignorance. It should not be cited.
26(1134) : Why is this Figure here?
26(1138) : Ah ha! At last the normalization issue. This must
come much earlier.
26(1144-1147): This is simply wrong. It is true that Ramaswamy and
Chen dreamed up a case with big hemispheric-scale responses
but little global-mean response, but this was totally
unrealistic. In all cases that I have looked at, using the
method employed by MAGICC/SCENGEN and COSMIC, this is simply
NOT a problem.
26(1147,1148): Again, this is just WRONG!
26(1150+) : Again, this is my idea, and it was first implemented
in MAGICC/SCENGEN. Please give credit where due.
26(1156-1159): Isn't this ALWAYS the case. In other words, the
scaling method is almost universally applicable and useful.
26(1159-1162): I do not think this has been proven.
26(1164,1165): There are other methods, too.
26(1172) : Oh come on! Scaling handles MANY types of uncertainty
(perhaps all), not just 'one type'.
27(1181) : 'documented' to 'quantified'?
27(to 1185) : etc., etc.
27(1193) : MAGICC/SCENGEN allows the user to consider this issue
by providing data on global precipitation pattern correlations.
Indeed, this software was the first to consider this issue (in
spite of the Whetton and Pittock paper cited on line 1199).
27(1198-1201): Very clumsy text.
27(1203-1204): This is an issue we considered years ago in developing
ESCAPE and MAGICC/SCENGEN. The trouble with judging a model on
its regional performance is one of statistical significance.
It is much easier to get a good regional result by chance than
to get results that are good globally.
27(1208-1211): Very clumsy text.
27(to 1214) : You have failed to mention a key issue. Is model skill
in simulating present-day climate a reliable indicator of its
skill in predicting future climate change? There is no evidence
to support this idea, although it does sound a priori reasonable.
You must at least raise the issue.
28(1227) : Cite Morgan and Keith (1995) here.
28(1231) : This is a critical point. It needs more emphasis.
28(1235+) : What about inter-variable consistency? This needs to
28(1236) : 'the manifold' to 'possible'.
28(1239) : Insert 'give' after 'chapters'.
28(1252) : Not clear.
28(1255) : So what? It is almost certainly irrelevant unless the
CO2 changes are bigger than anything anticipated, or unless there
are nonlinear effects associated with THC changes (which looks
28(1257) : 'mimics'? You must be joking! How about 'approximates'?
28(1262) : 'equal' (grammar).
28(1262,1263): How can smart people like this make such an elementary
29(1280,1281): This does not seem to be an appropriate reference.
29(1282) : 'albino' to 'albedo'.
29(1294) : This sea level consistency issue was first addressed
by Wigley and Raper (Warrick et al. sea level book). It is,
of course, avoided in MAGICC/SCENGEN.
29(1295) : 'dependable' to 'dependent'.
29(1295-1301): A giant red herring! Maybe some ignorant people
produced inconsistent scenarios like this years ago, but the
issue was also resolved years ago. All you need to say is that
comprehensive software suites avoid these naive problems.
Concentrate on the strengths of existing methods/software;
don't reraise issues that were solved long ago.
29(1305-1308): Another misleading red herring, that fails to reflect
the current state of the science. Global-mean responses to
aerosol forcing CAN be used to drive regional patterns. This
is just what is done in MAGICC/SCENGEN and COSMIC.
29(1310,1311): Not clear.
29(1314) : Delete 'scenario'.
29(1318) : 'to daily' to 'in daily'.
30(1329,1330): 'stimulated new techniques' Oh yeah? The MAGICC/SCENGEN
method has not changed in 7 years, and it still represents the
state of the science.
30(1332,1333): True, but you have not explained them very well. Could
you not have a summary Table that lists the strengths and
weaknesses of the various methods, including the direct use of
O/AGCM output. This would have helped you a lot in planning
and structuring this chapter. It can still help in revising it;
and be useful to readers.
30(1336-1339): Not clear.
30(1342) : You have mentioned this before, but you have failed
to tell us what it is or given any example. A mention alone is
30(1344) : What means 'semi-formal'. I thought it was a dress
30(general) : A crucial need for scenarios (and for simple models)
is to expand the range of cases covered by O/AGCMs.
* Dr. Sarah Raper *
* Climatic Research Unit *
* University of East Aglia *
* Norwich *
* NR4 7TJ *
* Tel. + 44 1603 592089 *
* Fax. + 44 1603 507784 *