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.)
Ged says:
September 9, 2011 at 12:07 pm
Ged quotes @KR
“The three models among those best known for reproducing ENSO are the closest to the observational data”
Ged writes:
“KR, that means nothing. It doesn’t matter if it seems like it’s close. Until you do a statistical test, it means -nothing scientifically-. It could look close, but be significantly off, and thus NOT a reflection of reality what so ever.”
Right on the money, Ged.
Ged writes:
“Finally, another point I’ve been trying to make and which you keep ignoring, is that SB11′s point was to show that model climate sensitivity did not conform close to observations. Do you see that? That was the point, and that is what was illustrated.”
Ged correctly identifies the topic and conclusion of Spencer’s paper. Spencer’s paper is about climate sensitivity. Spencer does not address some other aspect of the models. Spencer’s argument does not depend on differences among the models.
KR, I know you wish that Spencer had written a different paper with a different topic but he did not. Maybe you should write the abstract for that different paper and see if you can get Spencer to write the paper.
tallbloke: my reflection “Dessler states he will change sentences of his paper. However, he is not allowed to do that at this stage. Scientific statements cannot be changed without another roud by reviewers…” does not mean I do not see positive aspects in the development of the story. I just would like to remark that it would be fine if the peer review process remained as neutral as possible:
a) exceptionally fast tracks should be avoided or they should be offered on both sides;
b) when a paper is conceived as a response to a previous paper, the author of that paper should be involved in the review process;
c) changes in the scientific statements should be approved by editor and reviewers.
Dessler, for instance could ask the editor to send the paper for a further review and esplicitely involve Dr. Spencer in the process. Dr. Spencer could than publically state his role in the new review…
This, in my opinion, could help to restore trust in the review process…
A question for anyone.How much more heat does a cloud e.g. a thunder head deliver into the upper atmosphere than a regular clear air thermal of the same size?
Ged
“Think again too at what it means if climate sensitivity is not the correct factor for matching a model to reality.”
Let’s be a bit more precise here. This means that climate sensitivity is not the correct factor for matching models to variously lagged 10 year temperature variations, in a period dominated by strong ENSO effects.
Spencer’s work should have relevance to very short period (months?) climate response, but not to mid-term or equilibrium climate sensitivity. That takes decades (~30 years) of data. In fact, given the change in CO2 over that period, I believe the expected GHG driven temperature change would be on the order of 0.13 degrees C/decade – very difficult to pull out of seasonal signals.
I do agree on the lack of statistical significance testing on both Spencer and Dessler – I would prefer much better analysis. I will point out, however, that Dessler at least included the 2-sigma ranges on the temperature data estimates, which gives a somewhat better idea of how close the models came.
“SB11′s point was to show that model climate sensitivity did not conform close to observations”
Unfortunately, what SB11 showed is that model climate sensitivity did not conform or correlate (plus or minus, as the mid-range sensitivity models are closer) to observations of 10 year temperature variations. Which is hardly surprising, as climate models are intended to look at long term average behavior, not short term variations with chaotic elements such as the ENSO. That’s one of the reasons you run ensembles of models with varied conditions, and look at the average behaviors as they simulate the evolution of the climate.
Spencer’s test is inappropriate for drawing the conclusions he has so publicly made.
Ah, James, I now agree with you. Thanks for those extra words.
In my perception, we have convinced enough of the general public that climate science as it stands is untrustworthy, to turn the scales. But five key groups remain to be convinced: the politicians, the ruling academics, most greenies, the media, and the Team.
* Politicians – and the heads of the academic institutions, see only the surface and don’t understand that whereas some areas of science are ok enough, climate science has been dangerously corrupted.
* Academia is too calcified and insulated to call for the return of the lost integrity. IMHO their time for shakeup will come but they haven’t yet become corrupt enough.
* Rank-and-file greenies choose the “proofs” that support their feelings and therefore don’t want to know that Climate Science has become corrupt.
* The media will follow anything that titillates their paymasters enough.
* The Team will perhaps never acquiesce – but the strangleholders like Jones and Trenberth and Mann could be moved sideways – so long as there isn’t a Club of Rome fiat to replace them all with clones. I still sense the Team, and others like Bob Ward and Fiona Fox, are puppets.
So yes, the tide may have turned, but the war is not yet won.
@KR:
Isn’t climate just an average of the weather over a period of time? If increased cloudiness goes from months into years, it’s not climate change? How long a period does something happen to occur before it’s climate change and not weather? What’s the generally accepted time frame? Not months, not years, not one decade, but more than two?
@KR
“Let’s be a bit more precise here. This means that climate sensitivity is not the correct factor for matching models to variously lagged 10 year temperature variations, in a period dominated by strong ENSO effects.”
You’d be making a point, if we weren’t trying to validate the behavior of computer models made by Man. If the models do not act correctly on the scale of 10 years, solely based on climate sensitivity parameters; then the models can be said to not reflect reality and thus not be useful even in the long term.
The idea that, even if they fail on 10 year spans trying to model the basic physics, models can somehow be right on 30 year or longer spans, is quite a fallacy. If the model accurately reflects the underlying reality, it’ll be significantly correct in its behavior and predictions at 10 years, 30 years, 100 years, or 1 year. That’s the whole point of the model.
If sensitivity parameters cannot match 10 year variations, they cannot be given confidence for any amount of time, as they are flawed at the fundamental level. This is what SB11 and even Dressler’s reply have shown. This was a very important result; as now we know we need to make better models, do we not? And there in, science has advanced, as well as our understanding of the basic underlying physics behind our climate system. Something absolutely vital for any time span of predictions.
Also, 2 sigmas do not tell you much significantly, other than the spread of the variance. All you need are a few very far off outlayers from your mean to give you a wide 2 sigma, which would overlap with another data set with very far out outlayers. But, that doesn’t say they are significantly similar at all! Just that your data is messy.
In short, I don’t see ANY statistical tests being done, no real analysis that would give us vital scientific info. I feel this is a fundamental problem, and more rigor is necessary on everyone’s parts who aren’t doing their quantitations to verify theory with reality. C’est la vie.
Nuke Nemesis – “How long a period does something happen to occur before it’s climate change and not weather? What’s the generally accepted time frame?”
The generally accepted time frame in the climate field appears to be 30 years.
If you look at the statistics of year-to-year temperature changes, and see how long before the standard deviation stabilizes (one measure for ‘long enough’) it flattens at about 45 years. Variations such as ENSO (one of the most important), where heat moves in/out of the oceans, tend to cancel out over about 20-25 years.
Some people (like Tamino) have performed multiple regression analysis, attempting to separate out ENSO, volcanic activity, solar levels, and the annual cycle, and have shown separability and a discernible trend over shorter periods (~10 years), but given the interactions between various forcings I personally consider that a pretty weak conclusion.
So – 30 years is considered climate, 10-15 years is variations, months are seasons, days to weeks are weather (where initial condition models used by meteorologists can make reasonable predictions).
I would have thought Nuke Nemesis that a measurement of the entire planet from thousands of different locations via satellite would be an example of our climate even on a daily basis but I seem to have been mistaken!
This commotion has established a new paradigm for analysis of scientific papers. From this time forth, any new pronouncements by ‘the Team’ will be scrutinized by myriad wizened eyes.
Woe be to the deceivers.
Edicts from the puppet masters will be lost in the winds of change.
Luther Wu says:
September 9, 2011 at 3:02 pm
This commotion has established a new paradigm for analysis of scientific papers. From this time forth, any new pronouncements by ‘the Team’ will be scrutinized by myriad wizened eyes.
Woe be to the deceivers.
Edicts from the puppet masters will be lost in the winds of change
——————-
Luther Wu,
Poetic. That last line. Thank you.
Where the heck is kim?
John
@Lucy Skywalker says:
September 9, 2011 at 1:15 pm
“Ah, James, I now agree with you. Thanks for those extra words.
In my perception, we have convinced enough of the general public that climate science as it stands is untrustworthy, to turn the scales. But five key groups remain to be convinced: the politicians, the ruling academics, most greenies, the media, and the Team.”
Hah, do not misstake those groups who probably do know but do not care due to the agenda they’re riding. The “ruling academics” and the “Team” do know but don’t care for the sole reasons that boils down to money. Those two groups have never had as much money to throw around before.
The media is run by money and populism so both can sway media.
Politicians, pfft, lefty politician it should be, but even if they understand they only work to further their own agenda, which is based upon greed of power and money, but if they have to choose they choose money.
Politician in general is easily brought to heels you just vote on the most sensible rational people who run for office. Of course it helps to point out that the other folks are socialists and the socialists was during the 20th century the sole cause for the wars and mayhem and mass murders.
The greenies, well they’re fanatics and extremists just like right wing or left wing socialists, so even if they understand they won’t acknowledge because that would be breaking rank from their ideology, and that almost never happens because like the socialists and the talibans no matter how evil the ruler or the cause or the consequences the idea must be upheld at all cost (or else suffer the even more fanatical and extremists). Greenies are nothing but neo communists and they’re as extreme as their counter part the neo nazis.
Dictators and their authoritarians, kings and queens and their royalists, and every kind of socialists are the only ones in EU that went to war to commit mayhem and murder. Yet they all complain on democratic capitalists even though none has ever started any war or committed genocide within EU.
Lucy Skywalker says:
September 9, 2011 at 1:15 pm
—————–
I agree with your thoughts and will thus expand with some of mine.
I hope that ‘climate science’ will take a serious turn for the better as a result of the issues tackled the past several days. It could not have gotten worse.
I have heard the expression “I wouldn’t trust that bastard in a shithouse with a muzzle on his face” and perhaps that could be interpreted in the plural with regards to the CAGW crowd. But they may have some or possibly many within their ranks that, deep in their souls, don’t buy the CAGW hype but are not strong enough to stand on their own two feet.
For the weak or intimidated it may seem better to just go with the flow, which is CAGW. These people are not leaders and should never hold leadership positions. The leaders of this scheme need to be rooted out, but how do you determine those who are just followers from those who are of the fanatical state or simply profiteers? I think it may take a complete purge of the ranks. One thing to remember is that all employed were looking for a job when they got the one they have now, so the net result is that they will have lost nothing that they didn’t have to start with. They can now endure the same economic challenges that the CAGW policies have pushed on to the rest of society. Their views may then change.
Those whom have questioned the CAGW meme show an open mind and should be considered for future contribution within the ranks. However a claim that “I was already here first” is not reason for inclusion. You can’t tweak a corrupt program. It needs to be replaced with a better one with non-corrupted components. Where will these come from? I don’t know, as the corruption has spanned a generation. The first start will need to be academia. Where will those replacements come from? An entire generation has been corrupted. But it has got to start somewhere. I, like many others, waited until the writing was on the wall and then it was late, but better to give the benefit of the doubt than to jump the gun so to speak.
CAGW has become a big ugly monster now and is going to be tough to kill, but the fall
will be loud and clear. Do you hear the rumble? Are you part of the lost generation? Now is the time to take a stand.
Ged – “The idea that, even if they fail on 10 year spans trying to model the basic physics, models can somehow be right on 30 year or longer spans, is quite a fallacy. If the model accurately reflects the underlying reality, it’ll be significantly correct in its behavior and predictions at 10 years, 30 years, 100 years, or 1 year. That’s the whole point of the model.”
That’s really not true, Ged. It depends on what kind of model you are talking about.
Weather predictions are done with initial value models, attempting to predict how the weather will evolve over the next few days to weeks. Given the non-linear interrelations of weather, any error or imprecision in initial conditions, or averaging over space or time, means that the weather will in reality deviate from the prediction after a while, limiting how far you can predict it.
Climate models, on the other hand, are boundary condition models, where you look at how the average values will change based on boundary conditions such as conservation of energy. They are generally run repeatedly with small variations in their initial conditions, simulate how the weather _might_ evolve over time, and based upon limits such as how fast energy moves in/out of the atmosphere, oceans, etc., try and predict the _average_ conditions over time. Variations like the ENSO, which are +/- shifts in where energy is located in the climate, average out over time, so even simple zero dimensional models that don’t attempt to replicate ENSO can provide some predictive power (if the boundary conditions are correct) over longer terms. But climate models are lousy at predicting whether it’s going to rain in Topeka next week – that’s a different question.
The mid-range of a few months to 10 years, where ENSO and seasonal effects lie, is actually the most difficult to predict and where a lot of research is occurring now.
—
As an analogy:
* You could model traffic on the Los Angeles freeway system with initial values, the speed of each car at the starting time, engine powers, the aggressiveness of each driver, etc., and make short term predictions of how traffic will behave over the next couple of hours. After that your model will fall apart.
* You could also model traffic based on boundary conditions such as population levels, employment conditions, lane sizes, and planned changes to on/off ramps over the next few years, and from that predict _average_ traffic a decade out. But that model won’t tell you about the traffic next Tuesday.
Different models, different predictive ranges.
—
Finally, as to statistics – I couldn’t agree more, both Spencer and Dessler could use better numeric analysis in their papers. But that doesn’t mean either paper is without value.
OK, RE: mixed layer – to be fair my commentary was based on dives here in CA. Admittedly in the equatorial waters the mixed layer probably extends down to near 700m. But in terms of a global mean or weighted mean, I seriously doubt it.
—————-
Lucy Skywalker and James Sexton,
Climate science, to me, is the result/symptom of a broader problem in Western Civilization. The broader problem is philosophic systems based on support of man’s rational nature are in fundamental battle with philosophic systems inimical to man’s rational nature. So, as we counter the impact of climate science irrationalism we should do so in a broader context which will enable us to efficiently stomp the next iteration of irrationalism when it crops up after the climate pseudo-science. The next pseudo-science will always crop up, ad infinitum.
This is an eternal philosophical battle. Vigilance forever is required.
John
GRL state about papers in press:
“Papers in Press is a service for subscribers that allows immediate citation and access to accepted manuscripts prior to copyediting and formatting according to AGU style. Manuscripts are removed from this list upon publication.”
The AGU Authors Guide states: “Once the figures pass technical requirements, your final figures and text will be combined into
a PDF file that is placed on the journal’s Papers in Press page. Papers in Press is a service for subscribers that
allows immediate citation and access to accepted manuscripts prior to copyediting and formatting according to
AGU style.”
The Publishing Guidelines state:
“An author should make no changes to a paper after it has been accepted. If there is a compelling reason to make changes, the author is obligated to inform the editor directly of the nature of the desired change. Only the editor has the final authority to approve any such requested changes.”
As the changes suggested by Dessler are greater than “copyediting and formatting” it seems the paper must be withdrawn and a new version submitted and reviewed. Any comment?
So when is the GRL editor going to resign and send an apology to Roy Spencer?
An Optimal Definition for Ocean Mixed Layer Depth
Journal of Geophysical Reasearh, July 2000
http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA480229&Location=U2&doc=GetTRDoc.pdf
Flip on down to page 10. Nice graphs (by season) on right of mean MLD.
It’s about 50 meters average across seasons. At least according to a published study.
Dessler’s using 300m as I recall. Sounds like he’s making up his own definitions for things to suit his agenda. FAIL
I also posted the below comment on BH.
—————–
It just doesn’t matter what a scientist’s politics, ethics, sexual preferences, religion and favorite colors are.
Look at a scientist’s work product and in course of analysis any bias can be seen. If bias is found, then a correction is made. That is the scientific process. That means through its process science just doesn’t care what a scientist’s politics, ethics, sexual preferences, religion or favorite colors are.
I find the recurring fixation on Spencer’s theology to be bigoted and prejudiced. I would think that it is quite common for scientists to have theological views. So what? What is going on, do I see the beginning of the formation of a new agenda for a Politically Correct climate science police enforcing atheistic scientists only? What is next persecuting scientists for liking the color pink?
John
SteveSadlov says:
September 9, 2011 at 12:22 pm
“700m for the mixed layer? Wow! My own personal experience (from deep diving) is, you start to get into the realm of 10 deg C water at something between 20 and 30m, and into the 6 deg C realm down around 50m, and after that you have the transition into true abyssal uniformity.”
The definition of the mixed layer is the upper ocean layer where there is very little temperature change with increasing depth. The starting point is 10 meters to isolate it from skin effects at the surface.
Reference the JGR paper I linked in previous comment.
Dessler is now calling 700 meters the mixed layer? Seriously?
Both him and the pal-reviewers need to take Oceanography 101. I did. I got a 4.0 grade in it too. And I read the entire textbook for it in one weekend, didn’t go to a single class, and just showed up for mid-term and final exams because most of it I already knew just because I’ve been a science nerd since kindergarten.
700 meters is near the bottom of the thermocline and about 650 meters below the mixed layer.
The GRL editor should resign for letting that be published and write a letter of apology to Roy Spencer. I mean that’s how it’s supposed to work in science journals now, right? Or do I detect a double standard at play here? /sarc
John Whitman says:
September 9, 2011 at 4:00 pm
…“This is an eternal philosophical battle. Vigilance forever is required.”
John
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We change the world when we change our habits of thought.
I’m new as to the peer review process so this is very interesting. I never imagined that an editor could be held to such a high degree of responsibility and ethics.
Is the current editor the one who accepted the first version of Dessler? Has already resigned? If so, will the new editor need to resign later? If he hasn’t resigned yet, why not? Are editors a dime a dozen?
All of this is like a dream / nightmare to someone. I’m losing sleep trying to follow it all.
John Whitman says:
September 9, 2011 at 4:40 pm
Well said. Objecting to a scientist’s work because of his religion is simple bigotry. It is no less morally wrong than objecting to a person because of his skin color.