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Roy Spencer's paper on climate sensitivity

What the science says...

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Spencer's model is too simple, excluding important factors like ocean dynamics and treats cloud feedbacks as forcings.

Climate Myth...

Roy Spencer finds negative feedback

"NASA satellite data from the years 2000 through 2011 show the Earth's atmosphere is allowing far more heat to be released into space than alarmist computer models have predicted, reports a new study in the peer-reviewed science journal Remote Sensing. The study indicates far less future global warming will occur than United Nations computer models have predicted, and supports prior studies indicating increases in atmospheric carbon dioxide trap far less heat than alarmists have claimed." (James Taylor)

Climate scientists have identified a number of fundamental problems in Spencer and Braswell's 2011 study which wrongly concludes that the climate is not sensitive to human greenhouse gas emissions.  One of the main problems with the paper is that it uses Roy Spencer's very simple climate model which we've previously looked at in slip up.

This simple model does not have a realistic representation of the Earth's oceans, which are a key factor in the planet's climate, and it also doesn't model the Earth's water cycle.  One key aspect in the Earth's temperature changes is the El Niño Southern Oscillation (ENSO), which is a cycle of the Pacific Ocean.  Spencer's model does not include ENSO, and he assumes that ENSO responds to changes in cloud cover, when in reality it's the other way around.

There are some other key problems in the paper.  It doesn't provide enough information for other scientists to repeat the study.  When two other climate scientists (Kevin Trenberth and John Fasullo) tried to replicate its results as best they could with the information provided, they found quite different results (see the Advanced version of this rebuttal for further details).  Spencer and Braswell's conclusions also only seems to work using the satellite data set they chose, but Trenberth and Fasullo found that using other data sets also changes their results.

Trenberth and Fasullo also found that when using a few different climate models, the one which replicated the observed data best was the one with a climate more sensitive to greenhouse gases, which directly contradicts Spencer and Braswell's conclusion that the climate is not sensitive to greenhouse gases.

It's also worth noting that the journal which published Spencer and Braswell's paper does not normally publish climate science research.  This may explain how the paper made it through their peer-review system with so many problems.  In the end, Trenberth and Fasullo find that the Spencer and Braswell study has no merit. 

  • The model it uses is far too simple to accurately represent the Earth's climate
  • The paper doesn't provide enough information to replicate their results
  • Their results depend on using one particular data set
  • They assume that ENSO responds to cloud cover changes, when in reality, the reverse is true
  • The study's conclusions are incorrect and unsupportable

UPDATE 3 Sep 2011: Wolfgang Wagner, has stepped down as editor-in-chief of the journal Remote Sensing. Wagner concluded the Spencer's paper was "fundamentally flawed and therefore wrongly accepted by the journal". More here...

Last updated on 1 August 2011 by dana1981.

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Comments 26 to 50 out of 80:

  1. Uncle Ben#25, While I appreciate the continued double-quoted shout-outs, I am not sure they contribute to productive discussion. If you are curious as to the origin of my login name here, I do indeed count muons (in my spare time). "You do understand that the technique displayed in Spencer's plots has not been seen before in this field." No. Others have tried to prove their misconceptions by looking at short term changes alone (notably, that year-to-year changes in atmospheric CO2 were supposed to show a natural source). Tamino did an excellent analysis of this type of mistake (which Spencer made as far back as 2008): He’s based his estimation of climate sensitivity on time spans which are so brief that feedback (in the usual sense) in the climate system doesn’t have time to operate! If you eliminate feedback (in the usual sense) from consideration, you’re not going to get a realistic estimate of climate sensitivity. After some searching, a graph similar to the one you describe as so revolutionary is shown here: -- source In this graph, many 'segments' are indeed parallel. But what does that signify? Rather than declare that 'Mother Nature is trying to tell us something,' look at the graph itself. In a plot of change in flux vs. change in temperature, we are looking at derivatives. What is the significance of the slope of a derivative in this context, except as a very effective means of removing the longer term trend? A derivative, after all, is a high-pass filter. And in climate contexts, high frequency equates to noise. Note: If this is not the type of graph you are describing, my apologies. There are numerous criticisms of Spencer's method, both on the source page for the graph above and on the RealClimate review of Spencer's blunder. At the minimum, Spencer somehow equates global radiation to ocean-only temperature change, presents (without saying so) a very short time span of data and emphasizes monthly variation (which of course, obscures the longer period terms). To make matters worse, Spencer's own words betray a certain lack of scientific objectivity: I find it difficult to believe that I am the first researcher to figure out what I describe in this book. Either I am smarter than the rest of the world’s climate scientists–which seems unlikely–or there are other scientists who also have evidence that global warming could be mostly natural, but have been hiding it. So let us lose the Galileo references, the 'witchhunt' fears and the appeal to 10 minute exercises. Let us lose the proclamations of Nobelity (which seem to be prevalent only on the pages of WUWT). I do agree that we must always be on the alert for hints of paradigm change. But this wasn't it.
  2. Uncle Ben wrote:
    Then see if, among the scattered connection lines, it jumps out at you that half of them are all parallel. It doesn't take a linear regression to estimate their common slope as about 6.0 (dashed line).
    Uncle Ben, humans are very good at seeing patterns, because that's a crucial survival skill. It is such an important survival skill that humans are biased toward seeing patterns in samples of data even when those patterns do not exist in the population of data from which those samples are drawn. That was a good bias in our evolutionary history, where usually there was a low cost of acting on the basis of perceived patterns that are not really in the population, compared to the high cost of failing to act due to not recognizing patterns that really are in the population. For example, a shrub rustling could indicate a bear. Changing course to avoid that shrub has the slightly negative expected value of missing whatever food might be in that shrub (low probability of there being more food in that shrub than elsewhere, low value of food in that shrub versus elsewhere, even if it is in that shrub). In contrast, not changing course has a large negative expected value (fairly low probability of being killed by bear, but very expensive cost if true). The inferential statistics that you so casually dismissed are crucial tools for mitigating those biases in judgment based on visually detecting patterns. All that long ago was well established in the empirical science of judgment and decision making. For example, Tversky and Khaneman (1971) called it "belief in the Law of Small Numbers." They found it existed even among 84 scientific research psychologists all of whom had extensive training and experience to avoid that bias. So I'm not picking on you, I'm simply pointing out how difficult it is to counteract that bias. You can't really avoid that bias, because it's a core part of being human. Instead you must acknowledge the bias's existence and consciously override your instinct despite what your gut is telling you. There are some utterly reliable examples of judgment and decision problems whose correct answer violently disagrees with people's gut, to the extent that when I try to force my gut to match my head, I literally start to feel nauseous despite my years of training as a decision researcher. I find that fascinating. I suspect you, too, will find it fascinating, so here are some links to get you started; I suggest dipping in to the references on these pages, especially the peer-reviewed publications, instead of stopping after reading just these particular pages: the clustering illusion in the Skeptic's Dictionary, the clustering illusion in Wikipedia (remember, don't just trust Wikipedia--read the referenced papers), and apophenia in Wikipedia (I'm not at all suggesting you suffer from apophenia; I'm linking there because it has a wide range of references relevant to a particular judgment bias.) Being disciplined in doing that overriding of your gut is a big part of scientific training in fields that inherently have messy data. Perhaps the scientific field from which you are now retired had relatively tidy data and so does not require so much vigilance against that bias. But you need to recognize that your expertise in one narrow field of science does not transfer to all other areas of science.
  3. @muon counter I suspected that you are a physicists from your username. The Tamino reference is quite interesting. Thanks. He does not seem to accept that the slope on the dH/dt vs dT represents inverse sensitivity. I thought that was well accepted. He complains that a mere 8 years is too short a time to measure feedback. Doesn't that depend on how fast the feedback is? Feedback to the heating of the ocean, if any, is certainly quite slow. That is why what I have called the curly parts curly. Ocean currents are affected chaotically by many things on the way to equilibrium. But it is certainly helpful to have the usual (non-time-connected) plots recognized as showing points that are certainly not at equilibium, and in that case there is no reason to expect a proportionality between rate of heating and temperature. But the heating of air by warm water is quick. The ratio of specific heats of air and water is quite small. That is why the segments are straight. So the 8 years of data are plenty for the feedback of cloud effects. The parallel segments measure the (inverse) sensitivity at equilibrium between rate of heating by oceans of the atmosphere. Of course, the reason for using the brief span of satellite data is that we have the dH/dt data and the time of measurement. The temperature data inferred earlier is informative for temperature, but we cannot estimate the forcings that caused it. This makes it hard to infer sensitivity. Regarding ice ages and sensitivity, here we are talking about feedback of a different kind. Feedback to albedo is certainly strong and positive. @Tom Dayton Some decisions require statistics and some do not. If you measure each line slope, you can do the statistics and find the std. deviation. But some things are actually obvious. If you look at the plots in the Blunder book, you will see. In physics, the half-serious view of statistics is, if you need statistics to make your point, improve your experiment. That one has tongue in cheek, but there is some truth to it. I have taught statistics and have examples where they are needed.
  4. 28, Uncle Ben, Your worshipful attitude towards Spencer is wholeheartedly unskeptical. Especially when the flaws are so obvious. Muoncounter has already quoted the single most important fact, from Tamino:
    He’s based his estimation of climate sensitivity on time spans which are so brief that feedback (in the usual sense) in the climate system doesn’t have time to operate! If you eliminate feedback (in the usual sense) from consideration, you’re not going to get a realistic estimate of climate sensitivity.
    That's it, right there. What Spencer has done is equivalent to proving that you aren't aging by demonstrating that you weren't more prone to illness after a week of elapsed time. It's meaningless. When you add to that the other problems with his report, the whole thing is a waste of time (have you read the criticism above? Why do you put so much effort into lauding him without addressing those criticisms?).
  5. 28 - Uncle Ben A couple of things. In tamino's post he exactly equates sensitivity as the inverse of the slope and derives, via the method, and says; "estimated climate sensitivity is 1/1.553 = 0.644 K/(W/m^2), very close to the true value 0.667 K/(W/m^2)." What's the problem with that? Did you read the article? If not, shame, because his commentery on Spencer's error relates closely to your insight: "the half-serious view of statistics is, if you need statistics to make your point, improve your experiment". As you clearly know, that is said because statistics is only important if your are dominated by statistical or systematic errors. A better experiment could reduce the former (more data) or the latter (less measurement errors). Now, as I read it, it is exactly Tamino's point that if you look to closely (to short a time scale) you will be dominated by the systems internal dynamics. as he says "He’s based his estimation of climate sensitivity on time spans which are so brief that feedback (in the usual sense) in the climate system doesn’t have time to operate!" I'm pretty sure if you read Taminos post as a statistician (indeed, as one statistician to another!) rather as attacker/defender of some bit of work; you will see his insight.
  6. Uncle Ben, you did not explicitly confirm or deny that the graph shown by muoncounter above @26 is the type of graph to which you refer. Could you please do so. Could you also do the same for the following graph: Quite frankly, your discussion to date has been essentially meaningless because you have not provided an example of the graph which is central to your case. Without your explicitly providing such a graph, or explicitly acknowledging some example, you give the impression of intentionally keeping the center piece of your discussion carefully hidden to avoid criticism.
  7. @Sphaerica 29 and Les 30. (Complaint about only 8 years of data) Friends, you would not say this if you had been able to read my response to muon counter at 28. (1) Three seconds is enough time to measure audio feedback in an auditorium. (2) One month is enough time to measure temperature feedback from ocean currents to the lower atmosphere. (3) One year is surely not enough time to achieve equilibrium to the solar heating of the top layer of ocean. @Tom Yes, this is kind of plot I have been talking about. I have been reluctant to post copies of the plots for fear of copyright violations. My motives were fear, not craftiness. :-) (How we suspect each others motives! But the answer to suspicion is openness. I have nothing to gain by trying to fool anyone. My personal interest is in chasing skirts.) This plot is a little harder to recognize than the one Tamino published, but you can still distinguish the straight parts from the curly parts.
  8. "I find it difficult to believe that I am the first researcher to figure out what I describe in this book." -- Dr. Roy Spencer If his "discovery" were valid, why did he publish it in a book? Science is published in science journals. "Either I am smarter than the rest of the world’s climate scientists--- which seems unlikely--- or there are other scientists who also have evidence that global warming could be mostly natural, but have been hiding it." --- Dr. Roy Spencer Fallacy of false dichotomy. (Dr. Spencer's statement is identical to ones some Creationists have made.) There are other explanations: 1) Spencer could be mistaken; 2) Spencer could have cherry-picked his data. 3) Spencer is so incompetent that he just accidentally left out of his study all of the evidence that refutes his desired conclusion. It seems hyper unlikely to me that Spencer accidentally left out more than half of the data available, and accidentally excluded the best of the data---- which, if he (they) had left in, would have shown his conclusion about climate sensitivity wrong. If I had done this in high school the teacher would have graded my paper an "F," and then castigated me for lying.
  9. 32 - Ben. I did read your post - clearly, better than you read Taminos! which clearly demonstrates which resolutions are appropriate to demonstrate compliance with known science and when the data is being mis-analyses. I've no doubt you've had experience, when teaching, if people finding features due to oversamplung... Again I plead with you to use your statistics insight!
  10. @les 35 Les I am willing to try to answer your questions regarding Taminos post. I found a list of complaints as follows: "Spencer does it “without going into the detailed justification” by: ■Ignoring data from polar areas, where most of the climate change has occurred.(1) ■Comparing global radiation data to ocean temperatures.(2) ■Pretending that 7 years of satellite data is a sufficient time span for climate analysis (try 30 years).(3) ■Restricting his plot to just month-to-month variation.(4) ■Using only monthly temperature changes that were greater than 0.03°C.(5) ■Ignoring decades of independent empirical studies that conclude that climate sensitivity must be somewhere between 2.3 to 4.1°C.(6) ■Sweeping away the 0.6°C warming over last 100 years as natural (therefore a similar estimated rise for this century must also be natural).(7) ■Ignoring the reality check that ice ages are impossible if CO2 sensitivity is as low as he declares.(8) "What does Dr. Spencer end up with? I mean besides the WUWT comments declaring him a shoo-in for a Nobel Prize. He ends up with an artificial statistical correlation with no physical explanation to support it." And I remember among his 3 posts titled 'Spencers errors" I think in which he claims that the ratio of two derivatives means nothing, IIRC. It is this last that I commented on and responded to, but three long posts are too much to search through without printing the out. If you can send me a link, it would help. His name does not appear on these posts, so I am relying on the words of commenters that they are Taminos. Am I mistaken? Among the bullet points, I have already rebutted some. Would you let me know which bother you the most and I will try to answer, if I can. You can refer to them by number.
  11. 32, Uncle Ben,
    (1) Three seconds is enough time to measure audio feedback in an auditorium.
    Irrelevant.
    (2) One month is enough time to measure temperature feedback from ocean currents to the lower atmosphere.
    That's not a feedback, that's simple heat transfer.
    (3) One year is surely not enough time to achieve equilibrium to the solar heating of the top layer of ocean.
    Why? Because you say "surely"? Your answer he is completely nonsensical. You also dodged my last questions. Have you read the criticism above? Why do you put so much effort into lauding him (Spencer) without addressing those criticisms?
  12. UncleBen#32: There are some problems with your feedback analogies. 1. 'Three seconds is enough time' to identify audio feedback - audio frequencies are in the 100s to 1000s of hz. A few seconds represent 100s to 1000s of samples, which is indeed sufficient. However, seven years of monthly data = 84 samples at best; from the figures presented above, it is not clear how many of these are responding to the supposed small feedback. That raises a significant possibility for aliasing. 2 and 3 are both unsubstantiated assertions on your part. If you wish to play by the rules of this house, provide references for your claims. As to your 'rebuttals' thus far, permit me to say, I have not seen any convincing evidence other than your assertions. That we are even discussing a study based on monthly changes in a climate science context already places this entire idea on thin ice. However, it would be helpful if you would focus on the objections you deem #6, 7 and 8; these are substantial - and have not been rebutted.
  13. Uncle Ben @ 18 says:
    I am astonished at how little attention has been directed at this novel contribution. To me, that is worth a Nobel Prize.
    That raises two interesting questions:
    • In what field of endeavour should he be awarded the prize?
    • What are the criteria for earning a Nobel?
    As to the first question, I am guessing the nomination would be in the field of physics, but could it be literature on the basis that Spencer's hypothesis is in the form of an imaginative, published document? (The Nobel prizes are in the fields of physics, chemistry, peace, physiology or medicine, and literature; there is an additional prize, the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel.) For the second question, one source I looked at quoted from Nobel's will:
    The whole of my remaining realizable estate shall be dealt with in the following way: the capital, invested in safe securities by my executors, shall constitute a fund, the interest on which shall be annually distributed in the form of prizes to those who, during the preceding year, shall have conferred the greatest benefit on mankind. The said interest shall be divided into five equal parts, which shall be apportioned as follows: one part to the person who shall have made the most important discovery or invention within the field of physics; ...
    As can be seen, the important criterion is to bring a great benefit upon mankind, through an important discovery or invention. This is where it gets sticky for Spencer: it would have to be proved that he had made an important discovery and that it brought a great benefit to mankind. If his hypothesis were correct, it would certainly be important, but would it bring a great benefit? I suggest that that would depend upon how it changed the progress of our civilisation, or the welfare of our population. Arguably, if Spencer had proved that the Earth is not warming, then it could be said that a monetary benefit would accrue in the form of wealthy nations not having to reduce their CO2 emissions and a psychological benefit would accrue in the form of the removal of significant worry for those who currently accept the theory of AGW. Would that be enough to justify a Nobel? I am not qualified to judge. On the other hand, if Spencer's hypothesis has been demonstrated to be junk science and if his paper does not have great literary merit, we can save the Nobel committee the trouble of deciding these questions. I guess it is up to his followers to nominate his work for a prize and see what happens. Perhaps Anthony Watts could start the ball rolling, as Spencer supporters seem fairly thick on the ground at his blog.
  14. Uncle Ben @32, thankyou. In light of your response, I want you to consider the following graph derived by the same means, but using a different data set to that shown in my post 31: If you recall, in your post 5, you wrote:
    "Not much calculation is needed, in fact. If you take the trouble to look at his plots, you will see that the straight-line segmenmts are numerous, parallel, and obvious. It is quite convincing. It is their slope which gives the sensitivity to dH/dt."
    This closely parallels a suggestion by Spenser:
    "Note the linear striations in the data that are approximately parallel to the feedback specified in the model simulation indicated by the dashed line. This potentially explains the linear striations seen in Figure 3a as a reflection of the net feedback operating in the climate system on intraseasonal time scales."
    Given this, do you agree that the slope of "linear striations" in the graph above (approximately parallel to the red line) also "give the sensitivity"?
  15. Tom 39, that is a curious plot. If it refers to a system like the ones we have been discussion, I can't imagine what process creates the bowing out of the nearly vertical lines. Assuming that the horizontal axis represents temperature and the vertical axis represents rate of heating, it is clear the temperature is being affected by something else and heating has almost no effect. Doug 38 You refer to Spencer's hypothesis. To my way of thinking, he has put forward no hypothesis. Feedback is the question of the century. Previously one could not measure feedback without including solar forcing. Spencer has discovered how to separate feedback from forcing in satellite data and has used it to measure the sensitivity of feedback to solar heating. He did it by utilizing periods of time when clouds were heated more by some non-radiative forcing, such as ocean currents, than by the sun. That eliminated the sun from the forcing leaving only the feedback radiation. What hypothesis do you refer to?
  16. 40, Uncle Ben,
    Spencer has discovered how to separate feedback from forcing in satellite data...
    No, he hasn't. Repeating it as often as you can does not make it so.
    He did it by...
    No, he didn't. He didn't succeed. His logic was grossly flawed, and your tacit and uncritical acceptance (acceptance? praise and worship is more like it) is singularly unconvincing. Your arguments to date amount to nothing more than "Spencer is great" and "I like what he said."
  17. Uncle Ben @ 40, you ask:
    What hypothesis do you refer to?
    Earlier in your comment, you claimed:
    Spencer has discovered how to separate feedback from forcing in satellite data and has used it to measure the sensitivity of feedback to solar heating.
    Until Spencer's 'discovery' has been reviewed and validated, I regard it as only an hypothesis. Clearly, from comments here and elsewhere, there is a weight of scientific analysis suggesting that Spencer is wrong. In other words, Spencer's science is not yet independently supported. When there is a weight of scientific analysis that supports his claim, I will elevate it from hypothesis to theory. Does that sound fair?
  18. Uncle Ben @40, let me assure you that the x-axis represents temperature anomalies in degrees K, the y-axis represents TOA net radiative flux anomalies in W/m^2, just as in the previous figure shown by me, and as in the figure shown by muoncounter @26. Further, just as in the previous figure I showed you, radiative flux is the only source of heating (something which is not true in the figure muoncounter showed). Therefore based on the reasoning you stated in 5, and which is the foundation of your case, the slope of the lines which approximately parallel the red line must "give the sensitivity". If they do not, then you must provide a reason for the exception or admit the counterexample refutes your theory.
  19. 35 - Ben "I am willing to try to answer your questions regarding Taminos post" I don't recall asking you any questions regarding that post other than how could you say that tamino denies dH/dt vs dT represents inverse sensitivity when he says explicitly that. You did not respond to my correction (which, itself could be wrong, and if so you could say why). I'm doubtful...
  20. Les, (44), my reply was that the post I referred to was not signed, and I relied on commenters to say who wrote it. It may have been someone else. You may be right.
  21. Uncle Ben#40: "He did it by utilizing periods of time when clouds were heated more by some non-radiative forcing, such as ocean currents, than by the sun." That's quite a trick! If the figures posted above are representative of this great work, where are the gaps between monthly observations that represent months when the sun was doing the heating? As far as 'heating clouds by some non-radiative forcing,' that mechanism needs a bit more substantiation. FYI: tamino's analysis was linked here.
  22. Uncle Ben - You have now been pointed to multiple issues with Spencers work. These criticisms include some peer-reviewed papers: Dessler 2011 - "It is also shown that observations of the lagged response of top-of-atmosphere (TOA) energy fluxes to surface temperature variations are not evidence that clouds are causing climate change." Trenberth et al 2011 - "...some efforts have been shown to contain major errors and are demonstrably incorrect. ...cloud variability is not a deterministic response to surface temperatures...many of the problems in LC09 have been perpetuated..." They also include Taminos analysis, comments here, and the noteworthy problems in many of Spencers works with basic statistics. If you continue to hold to Spencers work without considering or addressing these issues, I would have to suspect you are suffering from confirmation bias.
  23. 45 - Ben. Ummm, ahhh... eh? Anyway. I had thought, with your history in statistics etc. maybe some detailed discussion... I'll leave it at that.
  24. muon counter 46 KR @ 47 Many thanks for the link to the part of Tamino's treatise that you find most relevant. The beginning is quite clear, something that Spencer might have written. He supports the importance of speed of the process being discussed, including the fact that warming of air by ocean surface is fast and warming of ocean by the sun is slow. Where he diverges from Spencer is his undertaking to compute the sensitivity of the composite process from the jagged line. He says that to take the slope of just the jags is an error if you want to measure the sensitivity of the entire system to radiative forcing. My understanding is that Spencer is looking for the sensitivity of temperature to the feedback from CO2, which is what Hansen and others blame for the total strength of global warming. Since the effect of feedback from CO2 warming does not involve the slow process of ocean waming, it is quick, as acknowledged by Tamino. That is why the use of the slope of the jags is not a mistake but is added information. In Spencer's plots, showing short-term effects, the curvy parts show the ocean surface not in equilbrium. That is why one does not attempt to fit them with straight lines. The critics are right that to include everything in these short-term plots would be a mistake. But the parts of the plots that Spencer uses are straight, which indicates that the cause of the change happens quickly, reaching equilibrium in weeks, not years. So I think Tamino is correct up to the point where he objects to the use of the jags.
  25. There are three commonly used definitions of climate sensitivity. The slowest is the Earth System Sensitivity. The Earth System Climate Sensitivity is the change in temperature for a given forcing once equilibrium has been reached for all feedbacks including slow feedbacks. As slow feedbacks include the melting of ice sheets (with a time scale of thousands of years) and the equilibriation of atmospheric and deep ocean CO2 concentrations (time scale in the hundreds of years), ESCS measures sensitivity in the long term. More commonly used is the Charney Climate Sensitivity, which is the temperature reached for a given forcing after equilibrium is reached including all fast feedbacks, but no slow feedbacks. "Fast feedbacks" include such things as the watervapour feedback (time scale to equilibrium of days), changes to the cryosphere excluding ice sheets ie, snow and sea ice (time scale to equilibrium - decades) among a host of others. The short term climate sensitivity is the Transient Climate Responce, which is defined as:
    "The transient climate response is the change in the global surface temperature, averaged over a 20-year period, centred at the time of atmospheric carbon dioxide doubling, that is, at year 70 in a 1% yr–1 compound carbon dioxide increase experiment with a global coupled climate model. It is a measure of the strength and rapidity of the surface temperature response to greenhouse gas forcing."
    (My emphasis) So even the most rapid of the commonly defined measures of climate sensitivity is a response over decades. But by fiat, Uncle Ben declares that "... effect of feedback from CO2 warming does not involve the slow process of ocean waming ...". From that he concludes that measuring the sensitivity to only those processes which reach equilibrium in a matter of days measures the Charney Climate Sensitivity which is known to take decades, indeed up to a century or more, to reach equilibrium. It is amazing what absurdities you can believe when you allow yourself to use false premises asserted by fiat anytime they are needed.

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