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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Side topic from the Spencer-Dessler discussion, but relevant to the most recent posts:
For those claiming we haven’t affected CO2, see the century-resolution rate of CO2 changes here: http://farm6.static.flickr.com/5123/5304093969_dc21d0f5d1.jpg
KR:
At September 12, 2011 at 7:09 pm you say;
“actual scientific discussion on this thread pretty much stopped >150 posts ago.”
No. You, R Gates and John B started snowing this thread with propaganda some >150 posts ago then several – including me – responded by refuting your nonsense with referenced, peer reviewed scientific information.
The problem is that you (and other warmists) would not notice science if it could and did hit you on the head with a 5 lb hammer.
Richard
R. Gates says:
Some new science will have to emerge to explain all the rise in ocean heat content and global temperatures. At least some of the rise in these parameters cannot be currently explained by any other mechanism other than the forcing brought about by anthropogenic greenhouse gases. So, tell me when we’ll get a new science related to explain all the full cause of the 20th century and early 21st warming, and I’ll tell you when the AGW theory can be abandoned.
I’m sick and tired of such stupid remarks. This is a ridiculous argument from ignorance …, it must be one or the other and if it isn’t CO2 induced warming it must NOT be CO2 warming and as there clearly is a warming effect of CO2 it must all be CO2. Voodoo claptrap!
No wonder people are turning away from your argument in droves particularly the scientifically literate people who are so influential in public opinion on science.
CO2 warming can be expected to produce around 0.5 to 1C warming per doubling of CO2 (if we are able to double CO2 given the state of the economy). That only explains a fraction of the (apparent) warming in the 20th century. To suggest the rest must also be CO2 and then make up positive feedbacks to invent a way to make the models fit the temperature is in my opinion fraud as there is no justification and plenty of evidence against it. In particular solar activity is now almost certainly responsible for a large chuck. Natural variation from other sources is bound to make up another substantial chunck. And last and not least is the clear and obvious instrumentation errors for which Anthony deserves a lot of credit for exposing.
As I said. This argument that we must “explain all the full cause of the 20th century” is claptrap. A doctor doesn’t look at healthy patient and say: “ooohhh I’m not certain why their temperature is a fraction of a degree higher, I’ve got to find out why? Common sense, tells us we only need to investigate where there is a real problem. The question is not “what caused all the 20th century climate variation”, but “is there a problem“? And the answer most certainly is that there is virtually no sign whatsoever that raised levels of CO2 are causing any significant problem which we do not ordinarily tolerate. Humans have cut down vast swathes of forest for agriculture. Even at its worst, the effect of the minuscule amount of CO2 is not going to be anything near as bad as the impact humans already have on the environment. That is not to say we shouldn’t try to act if there are particularly eco-systems that may be affected, but it certainly does not mean wrecking the whole western economy based on bad science, jumped political views and a hang wringing self-deluding group who think that somehow their bad conscience about burning fossil fuels means the rest of should go without.
Regarding Energy and “Climate Change”.
There has never been a comprehensive independent scientific review of any IPCC report by a member government or by an official audit body. Nonetheless, the following five events, drawn from a much larger group of happenings, have demonstrated to all the political nature of the IPCC and its scientific advisers, and greatly damaged the credibility of the organisation as a source of accurate policy advice on climate change:
In
December, 2008, 103 scientists, including 24 Emeritus Professors, wrote to the Secretary General of the United Nations about what they saw as the unsubstantiated, alarmist projections of warming by the IPCC, concluding that the “approach of curbing CO2 emissions is likely to increase human suffering from future climate change rather than to decrease it – because attempts to drastically cut CO2 emissions will seriously slow development”.
In November, 2009, the leaking of the “Climategate” papers drew public attention to the malfeasant way in which scientists at the Climatic Research Unit, University of East Anglia, undertook their research on the IPCC’s global temperature record;
During 2010, a group of more than 40 Fellows of the Royal Society of London insisted on a revision of the Society’s (formerly alarmist) statement on global warming; the revised document acknowledged, inter alia, that ”It is not possible to determine exactly how much the Earth will warm or exactly how the climate will change in the future …”.
In February this year, 36 leading US scientists wrote an open-letter to Congress in which they disagreed with the IPCC’s conclusions, citing 678 peer-reviewed references in support; and
Also this year, a large group of members of the American Physics Society described the IPCC account of climate change as an “international fraud, the largest we have ever seen”.
It is clear, therefore, that large groups of highly qualified, professional persons exist who reject both the IPCC’s dangerous global warming paradigm, and also the need for government action to reduce carbon dioxide emissions
““These calculations show that clouds did not cause significant climate change over the last decade”…
Climate change over the last decade? I thought we have been endlessly lectured that you can’t measure ‘climate change’ over a period as short as 10 years?
———————–
R. Gates,
Thank you for your response on the uncertainty of ice core proxies of CO2.
I will continue our discourse after a delay while I am on a business trip.
If I do not pick up with you again on this thread then I will do so on another thread in the near future.
A heads up on my thoughts regarding the total uncertainty of ice core proxies: 1) ice cores inherently have physical phenomena causing very long term smoothing of CO2 results and 2) there are statistical problems with ice core data sets that are very similar to those found by McShane and Wyner (2010) for the proxies for temperature.
John
John Whitman says:
September 12, 2011 at 11:41 am
R. Gates says:
September 12, 2011 at 11:00 am
John,
If you read the referencies that R. Gates cites, I think you will conclude that he doesn’t have the basic knowledge to understand what you are asking or is deliberately trying to misslead you to support his biased beliefs. The “uncertainty ranges” he has given you are the best guesses of the researchers as to the accuracy of their measurements and has nothing to do with site to site variations or even variations in the time estimates that can range from around 100 to over 3000 years. Read my analysis and come to your own conclusions. Just click on my name.
Hi
Some please explain. Are the datasets different? Does regression mean different things in the two papers? What’s going on?
Thanks
KR says:
September 12, 2011 at 7:12 pm
KR, I’m pleased you linked to that “hockey stick” graph. It is a good illustration showing that the ice core CO2 data are not good proxies for atmospheric concentrations. In this case where rates of change are being compared, the differences in time resolution is the factor that produces the hocky stick. The time resolution for the ice core data varies from around 100 years near the surface to over 3000 years at depths. Compare that to atmospheric measurements with resolutions that can show annual variations in rates of change. It makes no since to compare averages over 3000 years with averages for one year. The long term averages will never reveal the relative rapid swings that we observe.
Fred H. Haynie
I linked that _century_ resolution graph for the specific purpose of comparing recent CO2 levels to ice core samples, which have varying resolutions.
The Siple ice core (Taylor 2003, http://icebubbles.ucsd.edu/Publications/siple22ka.pdf) shows decadal sampling over the last 2000 years, overlapping with the recent direct instrumental record. Andersen 2004 (http://homepages.ulb.ac.be/~desamyn/NATURE02805_published-version_09-09-04.pdf), has 50 year sampling data going back over 100kY. Luthi 2008 (http://www.nature.com/nature/journal/v453/n7193/full/nature06949.html) shows data going to 800kY with the coarsest resolution being 570 years – not as good as the recent data, but far better than the 3kY you quote. And the roughly 70-80 (depending on local conditions) firn solidification that averages out values, if applied to the instrumental record of the last 150 years, still shows the recent excursion in CO2 change rates.
A century time resolution for CO2 deltas (hence matching instrumental data to the ice core averaging caused by compaction and bubble isolation) is more than sufficient for comparisons to ice core data. Results? No evidence for CO2 levels over 290 in the last 800kY, no evidence whatsoever for rates of change in CO2 within an order of magnitude of what’s happened over the last 150 years.
“The long term averages will never reveal the relative rapid swings that we observe.” – Funny thing, though, the rapid swing shown in the graph I linked is a swing in a long term (100 year) averages.
Sorry, mis-typing in the last post. “And the roughly 70-80 (depending on local conditions) firn solidification that averages out values” needs the additional word year – that’s about how many years of CO2 get averaged while the ice compacts.
To KR,
The links you cite for time resolution of ice core samples is for delta D not CO2. The high resolution data for Greenland can detect seasonal changes because they are thin slices. They have to extract trapped air with small amounts of CO2 from much longer samples in order to get enough air to measure. On top of that, they do not make measurements on every meter of the ice core. Samples may be taken up to 50 meters apart. Take a look at some of the depth/CO2 raw data. Another factor to consider is that the estimated values for time have error ranges that increase with depth. I stick with my assessment.
We have sampling at 50 year intervals for the last 100kY, as per Andersen. Even the Vostok cores (perhaps the worst case, for earliest periods) represent averaging over only a couple of hundred years (http://books.google.com/books?hl=en&lr=&id=lhzK1-woaiQC&oi=fnd&pg=PA407&dq=vostok+ice+core&ots=Ok0OPci_0p&sig=dF1KHSvGdlnOWJpqJiubXw3Ui-o).
I still have to disagree. Century-level averages should be sufficient to test the hypothesis. Although, if you want, you can take that linked graph, average it over 200 or even 500 year periods, and the recent CO2 delta will still be unique.
Results? No excursions of CO2 at current levels at any time in the last 800kY, appeals to natural variation notwithstanding.
After I initially commented I clicked the -Notify me when new comments are added- checkbox and now every time a comment is added I get four emails with the same comment. Is there any method you possibly can take away me from that service? Thanks!
[why not go to “manage Subscriptions” at the bottom of the email? . . that usually get’s my stuff sorted out.]