The Good, The Bad, and The Ugly: My Initial Comments on the New Dessler 2011 Study

NOTE: This post is important, so I’m going to sticky it at the top for quite a while. I’ve created a page for all Spencer and Braswell/Dessler related posts, since they are becoming numerous and popular to free up the top post sections of WUWT.

UPDATE: Dr. Spencer writes: I have been contacted by Andy Dessler, who is now examining my calculations, and we are working to resolve a remaining difference there. Also, apparently his paper has not been officially published, and so he says he will change the galley proofs as a result of my blog post; here is his message:

“I’m happy to change the introductory paragraph of my paper when I get the galley proofs to better represent your views. My apologies for any misunderstanding. Also, I’ll be changing the sentence “over the decades or centuries relevant for long-term climate change, on the other hand, clouds can indeed cause significant warming” to make it clear that I’m talking about cloud feedbacks doing the action here, not cloud forcing.”

[Dessler may need to make other changes, it appears Steve McIntyre has found some flaws related to how the CERES data was combined: http://climateaudit.org/2011/09/08/more-on-dessler-2010/

As I said before in my first post on Dessler’s paper, it remains to be seen if “haste makes waste”. It appears it does. -Anthony]

Update #2 (Sept. 8, 2011): Spencer adds: I have made several updates as a result of correspondence with Dessler, which will appear underlined, below. I will leave it to the reader to decide whether it was our Remote Sensing paper that should not have passed peer review (as Trenberth has alleged), or Dessler’s paper meant to refute our paper.

by Roy W. Spencer, Ph. D.

While we have had only one day to examine Andy Dessler’s new paper in GRL, I do have some initial reaction and calculations to share. At this point, it looks quite likely we will be responding to it with our own journal submission… although I doubt we will get the fast-track, red carpet treatment he got.

There are a few positive things in this new paper which make me feel like we are at least beginning to talk the same language in this debate (part of The Good). But, I believe I can already demonstrate some of The Bad, for example, showing Dessler is off by about a factor of 10 in one of his central calculations.

Finally, Dessler must be called out on The Ugly things he put in the paper.

(which he has now agreed to change).

1. THE GOOD

Estimating the Errors in Climate Feedback Diagnosis from Satellite Data

We are pleased that Dessler now accepts that there is at least the *potential* of a problem in diagnosing radiative feedbacks in the climate system *if* non-feedback cloud variations were to cause temperature variations. It looks like he understands the simple-forcing-feedback equation we used to address the issue (some quibbles over the equation terms aside), as well as the ratio we introduced to estimate the level of contamination of feedback estimates. This is indeed progress.

He adds a new way to estimate that ratio, and gets a number which — if accurate — would indeed suggest little contamination of feedback estimates from satellite data. This is very useful, because we can now talk about numbers and how good various estimates are, rather than responding to hand waving arguments over whether “clouds cause El Nino” or other red herrings. I have what I believe to be good evidence that his calculation, though, is off by a factor of 10 or so. More on that under THE BAD, below.

Comparisons of Satellite Measurements to Climate Models

Figure 2 in his paper, we believe, helps make our point for us: there is a substantial difference between the satellite measurements and the climate models. He tries to minimize the discrepancy by putting 2-sigma error bounds on the plots and claiming the satellite data are not necessarily inconsistent with the models.

But this is NOT the same as saying the satellite data SUPPORT the models. After all, the IPCC’s best estimate projections of future warming from a doubling of CO2 (3 deg. C) is almost exactly the average of all of the models sensitivities! So, when the satellite observations do depart substantially from the average behavior of the models, this raises an obvious red flag.

Massive changes in the global economy based upon energy policy are not going to happen, if the best the modelers can do is claim that our observations of the climate system are not necessarily inconsistent with the models.

(BTW, a plot of all of the models, which so many people have been clamoring for, will be provided in The Ugly, below.)

2. THE BAD

The Energy Budget Estimate of How Much Clouds Cause Temperature Change

While I believe he gets a “bad” number, this is the most interesting and most useful part of Dessler’s paper. He basically uses the terms in the forcing-feedback equation we use (which is based upon basic energy budget considerations) to claim that the energy required to cause changes in the global-average ocean mixed layer temperature are far too large to be caused by variations in the radiative input into the ocean brought about by cloud variations (my wording).

He gets a ratio of about 20:1 for non-radiatively forced (i.e. non-cloud) temperature changes versus radiatively (mostly cloud) forced variations. If that 20:1 number is indeed good, then we would have to agree this is strong evidence against our view that a significant part of temperature variations are radiatively forced. (It looks like Andy will be revising this downward, although it’s not clear by how much because his paper is ambiguous about how he computed and then combined the radiative terms in the equation, below.)

But the numbers he uses to do this, however, are quite suspect. Dessler uses NONE of the 3 most direct estimates that most researchers would use for the various terms. (A clarification on this appears below) Why? I know we won’t be so crass as to claim in our next peer-reviewed publication (as he did in his, see The Ugly, below) that he picked certain datasets because they best supported his hypothesis.

The following graphic shows the relevant equation, and the numbers he should have used since they are the best and most direct observational estimates we have of the pertinent quantities. I invite the more technically inclined to examine this. For those geeks with calculators following along at home, you can run the numbers yourself:

Here I went ahead and used Dessler’s assumed 100 meter depth for the ocean mixed layer, rather than the 25 meter depth we used in our last paper. (It now appears that Dessler will be using a 700 m depth, a number which was not mentioned in his preprint. I invite you to read his preprint and decide whether he is now changing from 100 m to 700 m as a result of issues I have raised here. It really is not obvious from his paper what he used).

Using the above equation, if I assumed a feedback parameter λ=3 Watts per sq. meter per degree, that 20:1 ratio Dessler gets becomes 2.2:1. If I use a feedback parameter of λ=6, then the ratio becomes 1.7:1. This is basically an order of magnitude difference from his calculation.

Again I ask: why did Dessler choose to NOT use the 3 most obvious and best sources of data to evaluate the terms in the above equation?:

(1) Levitus for observed changes in the ocean mixed layer temperature; (it now appears he will be using a number consistent with the Levitus 0-700 m layer).

(2) CERES Net radiative flux for the total of the 2 radiative terms in the above equation, and (this looks like it could be a minor source of difference, except it appears he put all of his Rcld variability in the radiative forcing term, which he claims helps our position, but running the numbers will reveal the opposite is true since his Rcld actually contains both forcing and feedback components which partially offset each other.)

(3): HadSST for sea surface temperature variations. (this will likely be the smallest source of difference)

The Use of AMIP Models to Claim our Lag Correlations Were Spurious

I will admit, this was pretty clever…but at this early stage I believe it is a red herring.

Dessler’s Fig. 1 shows lag correlation coefficients that, I admit, do look kind of like the ones we got from satellite (and CMIP climate model) data. The claim is that since the AMIP model runs do not allow clouds to cause surface temperature changes, this means the lag correlation structures we published are not evidence of clouds causing temperature change.

Following are the first two objections which immediately come to my mind:

1) Imagine (I’m again talking mostly to you geeks out there) a time series of temperature represented by a sine wave, and then a lagged feedback response represented by another sine wave. If you then calculate regression coefficients between those 2 time series at different time leads and lags (try this in Excel if you want), you will indeed get a lag correlation structure we see in the satellite data.

But look at what Dessler has done: he has used models which DO NOT ALLOW cloud changes to affect temperature, in order to support his case that cloud changes do not affect temperature! While I will have to think about this some more, it smacks of circular reasoning. He could have more easily demonstrated it with my 2 sine waves example.

Assuming there is causation in only one direction to produce evidence there is causation in only one direction seems, at best, a little weak.

2) In the process, though, what does his Fig. 1 show that is significant to feedback diagnosis, if we accept that all of the radiative variations are, as Dessler claims, feedback-induced? Exactly what the new paper by Lindzen and Choi (2011) explores: that there is some evidence of a lagged response of radiative feedback to a temperature change.

And, if this is the case, then why isn’t Dr. Dessler doing his regression-based estimates of feedback at the time lag or maximum response? Steve McIntyre, who I have provided the data to for him to explore, is also examining this as one of several statistical issues. So, Dessler’s Fig. 1 actually raises a critical issue in feedback diagnosis he has yet to address.

3. THE UGLY

(MOST, IF NOT ALL, OF THESE OBJECTIONS WILL BE ADDRESSED IN DESSLER’S UPDATE OF HIS PAPER BEFORE PUBLICATION)

The new paper contains a few statements which the reviewers should not have allowed to be published because they either completely misrepresent our position, or accuse us of cherry picking (which is easy to disprove).

Misrepresentation of Our Position

Quoting Dessler’s paper, from the Introduction:

“Introduction

The usual way to think about clouds in the climate system is that they are a feedback… …In recent papers, Lindzen and Choi [2011] and Spencer and Braswell [2011] have argued that reality is reversed: clouds are the cause of, and not a feedback on, changes in surface temperature. If this claim is correct, then significant revisions to climate science may be required.”

But we have never claimed anything like “clouds are the cause of, and not a feedback on, changes in surface temperature”! We claim causation works in BOTH directions, not just one direction (feedback) as he claims. Dr. Dessler knows this very well, and I would like to know

1) what he was trying to accomplish by such a blatant misrepresentation of our position, and

2) how did all of the peer reviewers of the paper, who (if they are competent) should be familiar with our work, allow such a statement to stand?

Cherry picking of the Climate Models We Used for Comparison

This claim has been floating around the blogosphere ever since our paper was published. To quote Dessler:

“SB11 analyzed 14 models, but they plotted only six models and the particular observational data set that provided maximum support for their hypothesis. “

How is picking the 3 most sensitive models AND the 3 least sensitive models going to “provide maximum support for (our) hypothesis”? If I had picked ONLY the 3 most sensitive, or ONLY the 3 least sensitive, that might be cherry picking…depending upon what was being demonstrated. And where is the evidence those 6 models produce the best support for our hypothesis?

I would have had to run hundreds of combinations of the 14 models to accomplish that. Is that what Dr. Dessler is accusing us of?

Instead, the point was to show that the full range of climate sensitivities represented by the least and most sensitive of the 14 models show average behavior that is inconsistent with the observations. Remember, the IPCC’s best estimate of 3 deg. C warming is almost exactly the warming produced by averaging the full range of its models’ sensitivities together. The satellite data depart substantially from that. I think inspection of Dessler’s Fig. 2 supports my point.

But, since so many people are wondering about the 8 models I left out, here are all 14 of the models’ separate results, in their full, individual glory:

I STILL claim there is a large discrepancy between the satellite observations and the behavior of the models.

CONCLUSION

These are my comments and views after having only 1 day since we received the new paper. It will take weeks, at a minimum, to further explore all of the issues raised by Dessler (2011).

Based upon the evidence above, I would say we are indeed going to respond with a journal submission to answer Dessler’s claims. I hope that GRL will offer us as rapid a turnaround as Dessler got in the peer review process. Feel free to take bets on that. :)

And, to end on a little lighter note, we were quite surprised to see this statement in Dessler’s paper in the Conclusions (italics are mine):

These calculations show that clouds did not cause significant climate change over the last decade (over the decades or centuries relevant for long-term climate change, on the other hand, clouds can indeed cause significant warming).”

Long term climate change can be caused by clouds??! Well, maybe Andy is finally seeing the light! ;) (Nope. It turns out he meant ” *RADIATIVE FEEDBACK DUE TO* clouds can indeed cause significant warming”. An obvious, minor typo. My bad.)

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Ron Cram

Roy,
I am still not clear on how Dessler could be off by a factor of 10. Where exactly was his mistake?
Also, I’m surprised Dessler’s comment on his video that you didn’t use real data did not make your list of “The Ugly.” Any comment?

Fred from Canuckistan

Same actor, same music, better movie . . . . Kelly’s Heroes

Dr. Spencer: If there are MORE CLOUDS (which is our contention, caused by both feedback and the Svensmark mechanism), then Andy will see LESS LIGHT. And threrefore become MORE entrenched in his position. If there are LESS clouds, then he will see MORE LIGHT, but conclude that “warming” is still the trend (as that is what will happen with less clouds, wait..that’s “our side” of feedback). I don’t think we can win with Andy!

‘And, to end on a little lighter note, we were quite surprised to see this statement in Dessler’s paper in the Conclusions (italics are mine):
“These calculations show that clouds did not cause significant climate change over the last decade (over the decades or centuries relevant for long-term climate change, on the other hand, clouds can indeed cause significant warming).”’
I am not a geek or a maths guru, or a scientist of any kind, but this also made me smile. Did he really MEAN to say this? As to the article, it is as far as my very small brain can ascertain, a masterpiece! Your court I think, Mr. Dessler…now back to Flushing Meadow!

RobW

I will give 20:1 odds the turn around time is glacial. But I could be convinced to massage the numbers to 1.7:1
sorry couldn’t resist. Love your comments that go straight to the heart of the matter. Clouds are very important to climate.

KR

Dr. Spencer
With all due respect, I believe that your selection of only six of the fourteen models you evaluated, the six that (as it happens) maximize the difference between the model results and the observations, looks very bad. It has been my experience that if you show your hypothesis holds against the strongest counter-evidence, it’s going to hold up over the long term. You comparison, however, was to some of the weakest counter-evidence, and whether you like it or not, that gives readers a very poor impression of the work.
Add to that the fact that the three models that agree the most with the observations are those models that are noted to best match ENSO variations, which are (quite likely) the major cause of the temperature variations over the last decade, and your omission of those model results is even more puzzling.
At the very least you should have explained in your paper why you did not show the other eight model results you ran.
Regarding The Ugly, as you put it:
Most climate factors have possibilities of both forcing and feedback, including CO2, cloud cover, etc. However, the initiation of a change in climate is the forcing, caused by something other than relative temperature – insolation variations, CO2 levels, random cloud variations, etc. Even if Dessler is completely off base with his 20:1 difference between ocean heat redistribution and cloud effects, even if you are correct with ~2:1, you have still not shown any dominant effect of clouds over and above the ENSO heat redistribution. Certainly not in terms of long term effects, as you have posited no physical mechanism that could cause long term cloud changes. Without some mechanism, some reasons why, we have no reason to believe that variations plus or minus from temperature driven humidity and cloud cover will persist in imbalance long enough (10’s of years) to affect climate.
To be quite blunt, without such a physical mechanism overriding the water vapor cycle, your assertions of clouds as the forcing driving the ENSO are “Just So Stories”.

Dessler’s Paper should be henceforth referred to as The Dessler Flail.

eyesonu

Dr.Spencer, very well presented.
Thank you.
Sincerely,

Mike Bromley the Kurd

My synaesthesia is acting up. Hearing the GB&U theme, I suddenly smelled popcorn. Or, maybe it was the post……

TomRude

“When you have to shoot, shoot! Don’t talk.
Line from Tuco

NetDr

The violent reaction to this paper tells me that it has drawn blood.
If it were wrong then showing this to be true would be enough.
The libelous hyperbole just makes them look petty.

eyesonu

And the title with the associated format just “knocks my socks off”!

Bill Parsons

In one of Dessler’s video interviews (I can’t find the link right now), he insists that they can scarcely find a scientist ready to debate the issue with him. Well… (?) Any such public debate(s) would be a welcome complement to the recent papers, and certainly more productive than the pot shots being fired, and “the ritual seppuku of young academic Wolfgang Wagner”, as Steve McIntyre called it.

I guess you are going to get a lot of bets, so I will just comment on the conclusion. HUH????
They make a definitive statement, but qualify it by saying “maybe it has”? Sounds very wishy washy.

Michael Larkin

KR:
“as you have posited no physical mechanism that could cause long term cloud changes.”
But hasn’t Svensmark’s hypothesis provided this? And haven’t the CERN results so far begun to provide possible evidence for that?

richard verney

As soon as I read: “The claim is that since the AMIP model runs do not allow clouds to cause surface temperature changes, this means the lag correlation structures we published could are not evidence of clouds causing temperature change.” alarm bells rang loud.
I note that you state “While I will have to think about this some more, it smacks of circular reasoning.” I envisage that after you have reflected further upon this, you will continue to think that it is circular reasoning; so precisely what of significance does Dressler demonstrate?
It does appear that there is much in the Dressler paper that supports the root thrust ‘that models and observations are not in sync and that there is a divergence problem between models projections and reality’. This suggests either a problem with the models (most likely), or some unexplained errors in empirical data gathering/record keeping.
I look forward to reading your follow up paper.
ps, it would be ironic if Dressler has made an error in his paper which may give rise to him obtaining a reputation as a scientist requiring others to correct his work. I intend looking at the maths in more detail

Small typo in the equation: Tsfc should be (delta)Tsfc.

Disko Troop

An admirably restrained response considering the somewhat provocative statements in Daily Climate. Happily Dr Dessler released a video for the enlightenment of morons like me. Half way through it I wanted to put up my hand and ask to go to the toilet as I was beginning to feel sick, but no matter, I look forward to your forthcoming paper in GRL. Please don’t make a video. I hope Anthony Watts does not have to resign from his own blog for posting your response. (I’ll check with Kevin on the latest rules and get back to you!

Dr. Spencer, thanks for the quick response. I wasn’t sure how long it would take you. I’d personally like to thank you for showing all of the models. It proved my point that the rest were likely left out because it makes for a very ugly graphic and isn’t easy to discern what it is that you’d be trying to show.
Just so I’m clear, AMIP models don’t allow for clouds, even as feedback, to amplify or decrease temp changes? If so, this is another huge hit towards Dressler’s credibility and the alleged reviewers.
@KR What you are asking about is in the Bad section, (the 20:1vs2:1) not the Ugly. The Ugly section was reserved for the mischaracterization (lying about) the claims of SB11. And the obsession about how many models SB11 showed in their pretty picture.

John in NZ

It does not matter if Dessler’s paper is full of errors.
From now on, they will refer to Spencer and Braswell as being discredited.
It’s not about the science. It’s about the sound bites.

Nuke Nemesis

So where does CO2 and other greenhouse gases fit into this debate? How does human activity affect ENSO? Somebody, somewhere has to get the discussion back to fossil fuels or the message will get lost in a scientific discussion.

JeffC

so clouds (which are weather in my mind) and exist for short periods of time (individually and geographically) can effect long term climate but not short term climate … right …

Viv Evans

Thank you, from a non-geek with no pocket calculator, but who was quite amazed at dessler’s conclusion which you picked up.

glacierman

Another Aggie Joke to add to the list:
“These calculations show that clouds did not cause significant climate change over the last decade (over the decades or centuries relevant for long-term climate change, on the other hand, clouds can indeed cause significant warming).”
http://aggiejoke.com/

My concern is that the system works. If the system works then what goes through the system will work and so the science will be good.
But the evidence is that the peer review system is broken. And there is no better proof of that, than the way sceptic papers are repressed and pro papers get fast tracked and … really don’t seem to serve a purpose except to attack other people.

John in NZ says:
September 7, 2011 at 11:48 am
It does not matter if Dessler’s paper is full of errors.
From now on, they will refer to Spencer and Braswell as being discredited.
It’s not about the science. It’s about the sound bites.
========================================================
Enter the ever increasing sophistication of the average skeptic. It is true, many of your alarmist friends will consider S&B11 as refuted. However, this site and many other will amply provide you with the information necessary to dispute the claim. One of the things I’ve noticed, though there are exceptions, most skeptics have a much more intimate knowledge of various papers and the responses than alarmists.

Ron Cram

Roy,
Also, could you comment on the potential role of dimethyl sulfide in the debate on clouds? If I understand correctly, increased atmospheric CO2 will lead to more growth of dimethyl sulfide and so greater cloud condensation nuclei. The following abstract discusses changes in distribution, but there is also a change in quantity, correct? http://www.agu.org/pubs/crossref/2011/2011GL047069.shtml

KR:With all due respect, I believe that your selection of only six of the fourteen models you evaluated, the six that (as it happens) maximize the difference between the model results and the observations, looks very bad.
First off, has anyone actually shown that to be the case?
Second, it makes sense that he would choose the most and least sensitive.

richard verney

KR says:
September 7, 2011 at 11:25 am
////////////////////////////////////////////////////////////////////////////////////////////
You raise some points with respect to perception which may have some merit. However, I do not consider matters to be as clear as you suggest.
For example, with regard to the models not selected by S&B, if you look at the Dessler regression plot Fig2, whilst some of the models not used by S&B may have an impoved fit in the lag period 0 to + 7 months, you will note that many of the models not used have a worse fit in the lag period – 17 to – 5 months.
You criticize S&B for not having posited a physical mechanism that could cause long term cloud changes. There is no reason why S&B should put forward a mechanism. S&B are merely pointing out that models do not fit reality and reality could be driven by clouds.
In any case, it could all be due to natural variation in cloud formation/patterns which, as of yet, are not fully understood. For more than 20 years, I have considered the most obvious explanation for any real warming having actually taken place during the last century is clouds. Whilst there are many factors underlying their formation (some known, and may be understood to more or less degree, there are probably many factors which are presently unknown), essentially, clouds are chaotic and random.
We do not have adequate high resolution data of cloud cover to even begin to evaluate this. However, a general trend of less cloudiness (thereby allowing more solar radiance to impact the surface, particularly the oceans) lasting 150 years would not be surprising since one has to see such a trend against the backdrop of the entire period that Earth has had an atmosphere. If you toss a coin 7 times and it comes up heads on each occassion you may consider it weighted. However, it is quite conceivable to see such a run in a run of say ten million tosses, and it would not in any way look out of the ordinary and the coin would in this longer series be shown to have a 50/50 chance of coming up heads. 150 years is nothing in the context of the geological history of this planet, and it can be incredibly misleading to focus on short time periods and then seeking to extrapolate a trend.
ps. In my earlier comment, I referred to Dressler not Dessler (for which I am sorry).

Peter Dunford

Wagner made it clear that information brought to light from blogs, post publication, can discredit a peer-reviewed paper to the point that the peer-review process has been demonstrated to have broken down. Where does that leave the editor of GRL? Do we get another resignation? I suspect not.

Kevin Kilty

I tend to agree that using a model that does not allow cloud variations to impact surface temperatures to produce an argument against clouds as a source of surface temperature variations seems like circular reasoning.
I think what Dressler thought he was doing, and actually only he can say what he was thinking, is showing that the same lagged-correlation would arise without cloud variations, ergo cloudiness variations are not a cause of surface temperature variations. It seems to me one can look at this two ways. First, we often hear that correlation does not prove causation. It seems that correlation does not prove non-causation either–perhaps even more thoroughly.
Second, his logic seems to be not(A) then B is equivalent to (A) then not(B). Surely this is a fallacy.

What’s hilarious is that every model’s “projection” is the average of a bunch of runs with fiddled parameters, and the IPCC “consensus” projection is itself an average of these averages, EVERY ONE OF WHICH IS WRONG BY A LARGE MARGIN, and the daily temperature “averages” in the “raw data” are actually hi-lo temp mid-points (medians), not even weighted, and yet Dessler and supporting loons have the nerve to critique Spencer’s use of the 3 highest and lowest models?
Disingenuous witless hypocrisy, thy name is Climate Science.

KR

Michael Larkin“as you have posited no physical mechanism that could cause long term cloud changes.”
But hasn’t Svensmark’s hypothesis provided this? And haven’t the CERN results so far begun to provide possible evidence for that?

Svensmark’s work is very interesting (http://www.realclimate.org/index.php/archives/2011/08/the-cerncloud-results-are-surprisingly-interesting/), but GCR’s just don’t show a trend (up or down) that matches the changes in the climate over the last 50 years.
James Sexton
In reference to “The Ugly”, I was referring to causation (first cause of temperature change, clouds or ocean heat redistribution), although I did mention the different energy ratios. Sorry if I was unclear.
TallDave“KR:With all due respect, I believe that your selection of only six of the fourteen models you evaluated, the six that (as it happens) maximize the difference between the model results and the observations, looks very bad.”
First off, has anyone actually shown that to be the case?
Second, it makes sense that he would choose the most and least sensitive.

Unfortunately, that’s one of the key points in Dessler’s paper (http://wattsupwiththat.files.wordpress.com/2011/09/dessler_2011_grl.pdf). The best match models (GFDL CM 2.1, MPI ECHAM5, and MRI CGCM 2.3.2A) are the ones known to best match the ENSO, and they were not included despite being run by Spencer et al. That does not look good.

Andrew Harding

Roy, I congratulate you on the hard work that you have done to to question Dr Desslers science. I am normally vociferous on this website, but in this posting I am not going to comment. The reason for my lack of comment is because it is too technical for me. I do not want your hard work to indirectly criticised by warmists, because people like myself who are not climate scientists have made ill-informed comments that will be seized upon, quoted and ridiculed.
I will continue to read your future essays on the subject.

mckyj57

KR Wrote:
Even if Dessler is completely off base with his 20:1 difference between ocean heat redistribution and cloud effects, even if you are correct with ~2:1, you have still not shown any dominant effect of clouds over and above the ENSO heat redistribution. Certainly not in terms of long term effects, as you have posited no physical mechanism that could cause long term cloud changes. Without some mechanism, some reasons why, we have no reason to believe that variations plus or minus from temperature driven humidity and cloud cover will persist in imbalance long enough (10′s of years) to affect climate.
I think that long-term cloud changes could happen because of any number of factors. Isn’t that what the CLOUD experiment was aimed at?

Jeremy

Using the above equation, if I assumed a feedback parameter λ=3 Watts per sq. meter per degree, that 20:1 ratio Dessler gets becomes 2.2:1. If I use a feedback parameter of λ=6, then the ratio becomes 1.7:1. This is basically an order of magnitude difference from his calculation.

^^^ You have 1 equation and 3 unknowns. It is not clear here how you’re solving for that 20:1 unknown. Also, where was the number 3 arrived at?

Dayday

DirtyHarryreadmefile
I know what you are thinking , can I get this paper published in 5 days or can I get it published in 6, well to tell you the truth in all the excitement I kinda lost track myself but seeing this is about good science and could blow the head of your theory clean off, you have got to ask your self one question. Do I feel lucky? Well do you punk?

extremist

Why are so many of the “new results” showing the 0 time lag regression coefficients to be negative? Clearly, Dessler’s Fig. 2 shows that all but one are positive.
Some please explain. Are the datasets different? Does regression mean different things in the two papers? What’s going on?

eyesonu

As these comments are likely going to become very technically detailed discussions so I would like to make light one comment.
I thought that dihydrogen monoxide was going to kill us all, but now it may save the world. From the attributes to the death tolls from Irene, there were at least 5 that were directly attributed to those whom intentionally immersed / subjected themselves to dihydrogen monoxide. I did the same while the creeks were up, but I survived. Have to admit that I truly enjoyed the use of an excessive dose of dihydrogen monoxide! It was a real splash.

Gras Albert

Dr Spencer
I note your surprise regarding the peer review process’s failure to detect an apparently obvious and significant error in Dessler 2011.
I also note that Dessler thanks Evan, Fasullo, Murphy, Trenberth, Zelinka and A.J. Dessler for their useful comments.
Is it not equally surprising that such an august assembly* of renowned scientists in the field appear to have not commented on this issue?
* by the way, might I suggest that an appropriate collective noun for such an eminent group of climate scientists might be a ‘cloud’

ChrisM

“These calculations show that clouds did not cause significant climate change over the last decade (over the decades or centuries relevant for long-term climate change, on the other hand, clouds can indeed cause significant warming).”
But all the data sets (except GISS) show that there hasn’t been significant climate change in the last decade. Isn’t this Dessler just proving zero equals zero?

1DandyTroll

So, essentially, Dessler is claiming that the real world observation is not the representation of reality but that his models are.
I believe there’re quite the few pupils of the pharmacological self-study group in a number of insane asylums around the world that would agree if they were only allowed to leave the chemical compound. :p

Jeremy

KR says:
September 7, 2011 at 11:25 am
With all due respect, I believe that your selection of only six of the fourteen models you evaluated, the six that (as it happens) maximize the difference between the model results and the observations, looks very bad.

As you say, I would consider this a “just so” story until someone demonstrates that to be the case. Do the choices made actually maximize the difference between model results and observations? You need to provide some kind of evidence this is so, simply stating it doesn’t make it so. Dessler could have chosen to demonstrate this was so in his paper if he thought this was the case. He didn’t. That would at least suggest to me that it’s another piece of nonsense thrown at the wall to see if it sticks.

Add to that the fact that the three models that agree the most with the observations are those models that are noted to best match ENSO variations, which are (quite likely) the major cause of the temperature variations over the last decade, and your omission of those model results is even more puzzling.

It sounds like you are saying the models that account for ENSO show more agreement with the observations as presented by both SB11 and Dessler. When you consider: http://www.agu.org/pubs/crossref/2010/2010GL044888.shtml and the observations shown in the two papers in question it begs the question. Perhaps clouds have a part in determining ENSO and the models are simply a slightly flawed concept showing the right result. (as I recall it’s happened before)

As you say, it is going to take a cool head and probably a couple of weeks to fully address and deconstruct the Dessler paper. The mis-characterisation of your *bi-directional* hypothesis immediately raised red flags wrt. the objectivity of Dessler, as well as the peer review of his paper.
I have a limited understanding of “climate science” and current gaps, particularly wrt. characterising and quantifying cloud albedo (wrt. “energy budget”). I confess to being most aligned with Svensmark at present (which you don’t necessarily contradict in gross terms). Primarily, just want to say best wishes. Trenberth has further discredited himself with his petty actions and statements. Kudos for the way you have handled things over the last few days.

G. Karst

I hope that GRL will offer us as rapid a turnaround as Dessler got in the peer review process

How can they not? There is way too much focus, thanks to Wolfgang, for such shenanigans. Isn’t there? Or perhaps they regard such tactics as somehow heroic? I just find it all discombobulating. As someone said, let’s refill the popcorn bowl and await developments. We shall see what we will see! 🙁 GK

JFD

KR, you said above, “Certainly not in terms of long term effects, as you have posited no physical mechanism that could cause long term cloud changes.” I have no fish to fry in this hot grease but do believe that I can posit a physical mechanism that could cause long term cloud changes.
The world is currently producing a bit more than 1000 cubic kilometers of fossil water per year. Fossil water is from no or slow to recharge aquifers. This water, which is not in equilibrium with the hydrological cycle for one cycle, both heats the atmosphere as it changes energy regime from potential to kinetic then back to potential and increases the level of the oceans by 2.6 mm/year. Use of fossil ground water started in earnest around 1950 and increased as the world population increased until about 2000 or so when some decline started due to dropping water levels in the tube wells.
Much of the fossil water is used in evaporative cooling towers for electric power plants, refineries, chemical plants, gas processing plants etc. The cooling water removes heat from the processes and goes to the cooling tower where it flows downward as air is induced from the bottom through slats to cause evaporative mixing. The air, water vapor and aerosols leave the top of the tower at about 120F and 100% humidity plus the aerosols. The mixture is lighter than air so rises and eventually is cooled enough to condense into rain, giving up the initial latent heat which changed the potential energy into kinetic energy as specific heat when the kinetic energy is changed back to potential energy. It seems to me that cloud formation has to be a part of this physical process.
The other big use of fossil ground water is irrigation for food and fodder. This use is more sporadic/seasonal in nature but the evaporative cooling towers operate 24/7/365. However the fossil water used for irrigation does add to the level of the oceans.
Fossil water answers several questions about energy, ocean levels, global warming and sea level rises. 1000 cubic kilometers of new water added to the atmosphere each year is considerable. It accounts for more than the observable increase in atmosphere temperature, which leads me to believe that there is a “temperature relief valve” in the Tropopause. Simple partial pressures indicate that increasing carbon dioxide in the Troposphere causes water to be expelled into outer space.
JFD

HankH

Following KR’s comments above, What I see is the two of the models that more closely agree with the regression coefficient still exhibit a significant diverge in the phase relationship (lag) between model runs and satellite data. This causes me to question if they’re truly modeling reality or happen to be two models of the 14 that agree better for the wrong reasons. Statistically speaking two models of the 14 are going to agree better no matter how bad the entire ensemble gets it. That’s why I think that picking two or three models on the basis of a specific bias they represent in the data as KR suggests is an entirely wrong statistical approach and one clearly more likely to draw criticism from statisticians. After all, there’s a reason why there’s an ensemble of 14 models isn’t there? If one or two models are proven to be better consistently than all the others, then why do we continue to run the others and use them in key research as we do? Yes, we can play musical models and see which ones fit into chairs when the music stops but all you’re doing is finding a situational fit that may or may not lead to a valid analysis.
It seems obvious to me that there remains a clear divergence in phase in the general ensemble that can’t be substantially fixed up by singling out a few select models. Herein, I believe is Dr. Spencer’s point that deserves a better explanation than just hand waving and disparaging Dr. Spencer’s methodology.

Mycroft

DR Roy spencer
2) how did all of the peer reviewers of the paper, who (if they are competent) should be familiar with our work, allow such a statement to stand?
Answer because they know the effect it will have… to cast doubt, and no doubt one or two TEAM members have had their input or say.
good luck and best wishes with you reply paper

JFD says:
September 7, 2011 at 1:27 pm

Simple partial pressures indicate that increasing carbon dioxide in the Troposphere causes water to be expelled into outer space.
JFD

Whenever I’ve mentioned the open top of the atmosphere, and loss of mass and energy, I’ve been jumped on. What you describe makes great sense to me, a kind of evaporation of H2O, which is much lighter than CO2, O2, O3, N2, etc. There’s even a non-stop source of turbulence that would (IMO) facilitate this: the “Diurnal Bulge”, a 600-km high wave of atmosphere that tracks the sun about 2 hrs. lagging.
Anyhoo …