William M. Briggs

Statistician to the Stars!

Response To Trenberth Over “Why Models Run Hot”

Kevin Trenberth

Kevin Trenberth

Update Be sure to come back on Sunday and see my wrap-up column.

A reporter from Nature who could not be brought to understand science was more important than fallacy or politics at least came out of his fog to ask a fellow scientist Kevin Trenberth to critique our “Why models run hot” paper. See this post for the details on this and other climate reporters. Here is Trenberth’s critique as given to me by the reporter (so God only knows if it’s accurate), followed by my response. Please at least read the penultimate response.

Very misleading opening:
IPCC does not make predictions: they have made scenario dependent projections and early projections in FAR were of just unrealistic GHG scenarios. The paper completely misrepresents IPCC in this regard.

Einstein said one should make a model as simple as possible but not simpler. There exist simple models, such as the MAGICC, that deal with a crude ocean as well as the land and response. These have proven useful in IPCC for interpolating global mean temperature between different scenarios. But such models have no hydrological cycle and are toys.

This model is even simpler. It has no recognition of land vs ocean and its distribution, or the atmosphere. It has no clouds or water vapor. It assumes a linear response to a forcing. Many of the past variations in climate are related to Milankovitch changes: the changes in the orbit of the Earth around the sun. There may be no change in radiative forcing but there can still be very large changes in climate: ice ages even. This is because of the distribution of the incoming radiation throughout the year and how it affects ice.
This model does not even handle that case. Yet it is applied over the past 800K years.

The model is then used to play toy games with a justification of some choices from IPCC.

A number of exercises are gone through to select some parameters but it is not easy to see what the tuning is to. Section 7 sets this up and ludicrously concludes there is no warming in the pipeline which is totally at odds with the heat capacity and response of the ocean. It also seems to be assumed for the scenarios (cf 8.3.2).

So there are a lot of “what if” statements without justification. For instance it is concluded in 8.4 that 74% of the warming since 1850 is anthropogenic whereas it seems likely that the value is greater than the observed value, because natural variability has recently suppressed warming at the surface.
It then goes on to take away another 0.6K because that is in the pipeline?

The paper ignores all of the literature related to the recent hiatus in warming related to small effects from missing forcings (mainly volcanoes) and natural variability, especially PDO and consequential burying heat in the ocean. Or that 2014 is warmest on record.

[1] “IPCC does not make predictions: they have made scenario dependent projections…”

This is false. Scenarios are projections are forecasts are predictions. All projection-slash-forecasts have the same form. They say, given this set of conditions, here is what the future will look like. If the conditions do not hold, then the forecast is not valid. The IPCC basically releases several forecasts, each with different conditions. To judge the efficacy of the forecasts, all we do is look for the conditions that obtained and then measure the forecast’s goodness.

As I’ve pointed out many times, simply saying that next year will be like last year beats the IPCC forecasts. In technical parlance, climate models don’t have (forecast) persistence skill (no matter how well they might fit or backcast past data). And that can only mean that the models on which the IPCC relies are busted, that the science is flawed in some way. The burden of proof is on the IPCC to discover why.

Side note: those who attempt to evade the force of a busted forecast, which logically implies an incorrect model or theory, often attempt refuge behind the “scenario” label. But it is a thin disguise.

[2] “[The Monckton et al. model] has no recognition of land vs ocean and its distribution, or the atmosphere…Many of the past variations in climate are related to Milankovitch changes: the changes in the orbit of the Earth around the sun…Yet it is applied over the past 800K years…The model is then used to play toy games with a justification of some choices from IPCC.”

Somehow, even though we go to great pains in the paper to admit the model is “irreducibly simple” and does not even pretend to capture all the physics of the climate, that it is simple is given as a criticism. We say, Our model is simple to which Trenberth replies Their model is simple! I’ve stared at this hard, and I guess the only thing I can take from it is that Trenberth agrees with us—Trenberth agrees with us—that our model is simple. Well then.

[3] “A number of exercises are gone through to select some parameters but it is not easy to see what the tuning is to…ludicrously concludes there is no warming in the pipeline which is totally at odds with the heat capacity and response of the ocean.”

There are two mistakes here, a trivial and an important one. I’ll save the important one because Trenberth makes the same mistake thrice (ocean heat capacity here, later “natural variability”, finally “hiatus”). The trivial mistake is where Trenberth claims he could not “see what the tuning is to” etc., possibly because he did not read the paper carefully, the most charitable explanation. I commend to him Section 5 “How does the model represent different conditions?”, which begins with the words “The simple model has only five tunable parameters…” And to Section 6 “Calibration against climate-sensitivity projections in AR4”, which begins with the words “To establish that the model generates climate sensitivities sufficiently close to IPCC’s value…” And to Section 7 “Calibration against observed temperature change since 1850”, which… Oh, you get the idea.

Trenberth was being lazy.

[4] “…a lot of ‘what if’ statements without justification…concluded in 8.4 that 74% of the warming since 1850 is anthropogenic…”

The “without justification” quip is more laziness on Trenberth’s part. The whole paper is nothing but justifications about why this or that will happen conditional on our simple model. Trenberth is thus complaining that we use our model to make statements about our model. Subtracting the bluster, what we have here is Trenberth agreeing with us again.

He would have a good complaint were he to say something like, “Their model implies X, but Y is true, therefore I reject their model.” And he would be right in rejecting our model, too. Why, that would be the same criticism scientists like myself make when rejecting IPCC models.

And, lo, Trenberth does try his hand at this excellent rebuttal, as we see next.

[5] “The paper ignores all of the literature related to the recent hiatus in warming related to small effects from missing forcings (mainly volcanoes) and natural variability, especially PDO and consequential burying heat in the ocean.”

Also recall his “heat capacity…of the ocean” and “natural variability” critiques. What Trenberth thinks is his most damning criticism is instead glaring proof that Trenberth, and many other scientists, have lost their way. I have pointed out, time and again, that you must not say “hiatus” or “natural variability” or anything else like that. “Natural variations” do not and cannot explain the “pause” (I beg you will read the link).

A physicist sets out to model the climate. To do so, he must incorporate whatever physics he thinks are meaningful or probative to why the climate does what it does. Make sense? The physicist then releases a forecast (or “scenario”) conditional on that model. If the observations and forecast do not match, the model is busted. Something is wrong with it. It is not right. It is wrong. It is in error. It is a bad model. I’m not sure how I can be clearer.

Trenberth and pals have released forecasts conditional on various models all of which fail badly. These models did not correctly capture the observations. They are therefore wrong. These models purported to explain the climate, and the climate just is “natural variability“, it just is heat capacity of the oceans, it just is cloudiness, it just is land use, it just is everything the climate is.

If you somehow reject this obviously true proposition, what do you think the climate is that these climatologists have been modeling?

What is happening is Trenberth is blaming the observations for failing to conform to his model. It is reality that is in error, not his theory. This is a special form of insanity encapsulated by the aphorism the love of theory is the root of all evil.

In our paper, we tried to show how a vastly simpler model than the kind Trenberth touts explains temperature better than more complex models. We know—as in know—that the complex models have something wrong with them. We know this because their forecasts do not match observations. What we did was to suggest a plausible explanation why this is so. Hey. We might be wrong. Assume we are. Assume our guess is invalid, our paper worthless, and that instead something else is wrong with Trenberth-style climate models.

Then it is still true that something else is wrong with Trenberth-style climate models! Would we call this, oh I don’t know, a travesty? His models do not suddenly become correct because we made a mistake. What a silly thing that is to imply.

And anyway, our model, simple as it is, sure does look better when compared against reality, no? Not that our model should be used for much except as a clue to climatologists where to look for their mistakes. Mistakes mistakes mistakes.

[6] “…2014 is warmest on record.”

Oh dear, oh dear. Oh no. Trenberth couldn’t have possibly meant to deceive a poor reporter with a statement he knew to be false. Could he? That would be unethical. And Trenberth is a scientist. Or maybe Trenberth, an expert in his field, just didn’t know that ridiculous claim was false? That also can’t be, because if it was, then he couldn’t be much of an expert. Let’s be nice and call this a prolonged typo.

99 Comments

  1. Please take pity on Trenberth, he suffers from hyperreality

    http://en.wikipedia.org/wiki/Hyperreality

  2. The download links on scibull don’t work (for me anyway). Anywhere else I can download it?

  3. The original paper, that is. Should have said that.

  4. If the observations and forecast do not match, the model is busted. Something is wrong with it. It is not right. It is wrong. It is in error. It is a bad model. I’m not sure how I can be clearer.

    Reminds me of this: https://www.youtube.com/watch?v=4vuW6tQ0218
    Guess which one is Briggs. Guess what the models are.

  5. It is interesting that Kokic, Howden and Crimp had only four factors in their “model” that showed 99.999% certainty that humans are causing global warming and I found no complaints about that. I guess it’s the conclusion and not the four factors that are really the problem.

    It appears that “what if” statements are also okay if you reach the right conclusion. So science now consists of reaching the same conclusion everyone who’s anyone reached. In other words, it’s not science anymore.

  6. I’m really enjoying your responses to these charlatans.

    The title of your paper was “Why Models Run Hot”, not “This is the new bestest physically realest model so come at me, bro”. The whole (I thought) point was to use a toy model to explain where model/reality disconnects are likely to come from.

    But if the critiques got the idea of the paper, they’d have to come to terms with the implications of failed predictions/forecasts. Lots of worldview protection going on these days…

  7. So science now consists of reaching the same conclusion everyone who’s anyone reached.

    Well, that pretty much IS the way my labs were graded in physics classes.

  8. First, Trenberth most likely did not read the paper or didn’t read carefully for any of a number of reasons. Maybe when a person becomes an authority ex cathedral statements are every bit as valid a carefully reasoned and supported argument.

    Second, Gary’s link to the Monte Python routine about the hiatus in Blue Norwegian Parrot activity is funny, but also apropriate. One of Langmuir’s ear marks of pathological science is the tendency toward ad hoc explanations of contrary observations.

    Third, I have been in and out of this argument over “climate change” for almost forty years, in fact it has been forty years since I heard a physicist speak at a colloquium about a few degrees of earth temperature locking all water in the atmosphere permanently. We still argue over essentially the same topics. No real progress toward resolution of a pressing scientific question must signal pathology of some sort. Certainly thirty years of no progress on cold fusion of the Fleischman/Pons variety suggests a small likelihood of it being true. And now to top it all off the original data are mangled. This is science in reverse.

  9. “The love of theory is the root of all evil. ” Too true.

    Julian Simon: The facts are fundamental.
    Garrett Hardin: The facts are not fundamental. The theory is fundamental.
    From a 1982 debate at UC Santa Barbara .

  10. re: “Certainly thirty years of no progress on cold fusion of the Fleischman/Pons variety suggests a small likelihood of it being true.” k. kilty

    You are ignorant of the literature of “cold fusion” as much progress has been made in the field.

    Dan Kurt

    p.s. I have no dog in the hunt, but I do follow the progress in the literature.

  11. When a model doesn’t match observations, they never do, what do you know?

    Think carefully
    When you compare the average temperature from a model with the average temperature constructed from
    Records what are you comparing and what do know when
    They don’t match
    Understanding that they can never match.

    Assuming you can reject the model might be over confident

  12. Steven Mosher, comparing calculations with observations is ok, if the observations are data that are not massaged and forced into an agreement with a model. See, for example, the Climategate stuff, articles McKittrick and McIntyre, and most recently, the fudging of temperature data from Paraguayan weather stations. And please don’t offer the excuse that the data massage methods follow prescriptions in “peer reviewed” articles. Peer Review is a farce in climate science journals, after the perversion of this process by evangelical warmists.

  13. Steven Mosher, another comment: if you mean’t to say that there will always be RANDOM error differences between model predictions and observations even if the model is “good”, of course one cannot disagree with that statement. On the other hand, if the difference are not random (and there are good statistical tests for that case), then one might well question the model. And I believe that most skeptics question the computer models not because the differences are there, but because the difference are not random–in short, the computer models for warmists do NOT predict trends.

  14. Briggs

    February 21, 2015 at 4:59 pm

    Mosher,

    “Understanding that they can never match.” This is, of course, false (a causal model never errs, for example). But what you probably meant was “They rarely match precisely for data of this kind”, which is true.

    Persistence also does not match precisely. But persistence is a better forecast.

    Meteorologists, as you know, routinely calculate skill scores and other verification measures of their models to help improve them. These are also published, and even boasted of because, again of course, weather predictions are gradually improving.

    Not so climatological models. They have no skill. I’m not even sure they have climate skill (as I defined it last week and which you saw) these last 20 years. I might be wrong about that. Have you a source which shows they do have it? Not hindcasting skill, which is for amateurs. Real skill, which is for pros.

    No. Climate models do not come as close to matching reality as much simpler models. Something is very wrong with them.

  15. Since Trenberth’s opening salvo was so ludicrous (arguing that some obscure semantic distinction between “forecast” and “prediction” had significance) he managed to shoot himself in the foot before he was able to take aim. And given the ridiculousness of his argument one wonders to what extent his claims and ideas get challenged within his inner circle. The rest of his argument seemed to be that he didn’t like the paper because it didn’t approach the climate prediction problem the way he thinks it should be approached — without of course addressing any of the papers arguments or any of the failings of his preferred approach.

    Mr Briggs’s rebuttal was devastating but then again he was shooting fish in a barrel. Had Trenberth engaged substatitively it very likely would have turned out badly for him. Hence lots of bluster and the tossing of red herrings was probably the best he could do.

  16. Sadly, the only thing that will appear in Nature will be Trenberth’s critique and not a single word of the rebuttal.

  17. Briggs

    February 21, 2015 at 6:54 pm

    DAV,

    You’re right. Nature never did anything with the letter I wrote them.

    They are lost, lost.

  18. Another example of biased reporting from that organ of doubtful credibility, the NY Times, libeling Soon.
    http://www.nytimes.com/2015/02/22/us/ties-to-corporate-cash-for-climate-change-researcher-Wei-Hock-Soon.html?&_r=0
    How long, O Lord, how long?

  19. DAV, that nature decided to do nothing with the rebuttal is not surprising at all. In the late 1990s a number of geophysicists were trying to recover long past climate from temperature logged in boreholes. The method involved is crap, and some of the effort, which the researchers described as Bayesian, made use of circular reasoning; but they produced a hockey stick and that seemed to be what was important. Maybe this was even before the one by Mann, I can’t recall any longer. I tried to respond to Nature and Science both of which had published versions of this work, with a brief argument about why the method probably could not resolve what was claimed. Science I recall seemed interested in my letter, then dropped it for unknown reasons. Nature declined to publish it after the authors said, in effect, I was wrong and they were right–hard to counter such a clever reposte.

    Some time later I was speaking to someone else in the geophysical community (heat flow research) who told me that almost all of them tried to convince the authors, privately, that their method and results were terrible. The research community were unwilling to criticize shoddy work in public even though they recognized it’s flaws. Yet they were also busy trying to keep valid criticism out of view of the public and allow the work to be printed. I broke off relationship with all these people, some of whom i’d known and collaborated with for twenty years. I have stayed with engineering ever since. It still makes me ill to ponder the whole episode.

  20. I should point out, though, that corruption in science is nothing new. The controversy involving Lord Kelvin, the geologist Perry, and Heaviside over the age of the earth resembles the present mess. Kelvin traded on his authority but was dead wrong about the age. He was dishonest about what the little data he could site actually meant. The community of geophysicists have since concocted a story that the old man was wrong merely because he didn’the know about radioactive decay. On the other hand Nature was willing to publish letters from all sides.

  21. Dan Kurt,

    Do you refer to the device that Andrea Rossi fabricated and had tested?

  22. If you use Twitter please communicate with this legislator – He tweeted:
    Dana Rohrabacher @DanaRohrabacher · Feb 20
    ” expect there to be congressional hearings into NASA altering weather station data to falsely indicate warming? & sea rise”

    Does anyone here have suggested candidates that would give good testimony?

  23. Let’s see. Rohrbacher has a Bachelors in History, Masters in American Studies. Why wouldn’t he be an appropriate Vice Chairman on the House Committee on Science, Space and Technology? I’m quite familiar with Congressman Rohrbacher, he represents my business partner in Congress (said partner lives in Huntington Beach, CA).

  24. @Bob,

    If you’re writing more than one paragraph to rebut one of Mosher’s haiku’s, you’re probably over thinking the point raised.

    “All models are wrong.” A claim that is either wrong itself or banal. Let’s say I’m building a long distance precision weapon for the military. I need to model the trajectory. Some things I need to figure out, like the vector, but we know how to do that. Then there are known unknowns. Will the weapon work in various wind conditions? Well I can try to solve that from first principles or do some empirical testing in wind tunnels. Now I’ve modeled the problem and I’ve calculated that given wind conditions of 1-n I can still hit my target? Then I try and I don’t hit my target. I check the wind conditions – no hurricane at the time – so I should have hit my target. I recheck my calculations for knowns and known unknowns. If they are all correct, I’m dealing with an unknown unknown. So my model is busted.

    Climate models also incorporate known unknowns. That’s the ‘chaos’ part of the model that they try to simulate. That’s the part of the model that has the expected error. That error is normal. But the error should be in a certain range. It can’t be so large that the model can’t predict anything useful. (Earlier generation climate models used to sporadically spin out of control and do things the real climate doesn’t, and some probably still do.) And this you must be able to quantify. And if you’re outside your expected error range, you’re now dealing with unknown unknowns. Or in other words, your model’s busted.

    This is what Mosher doesn’t seem to be able to understand. Or if he does, he’s never demonstrated that he grasps the distinction.

  25. As I’ve pointed out many times, simply saying that next year will be like last year beats the IPCC forecasts. In technical parlance, climate models don’t have (forecast) persistence skill (no matter how well they might fit or backcast past data). And that can only mean that the models on which the IPCC relies are busted, that the science is flawed in some way. The burden of proof is on the IPCC to discover why.

    Mr. Briggs,

    The naive estimator you mentioned in the above statement has no persistence skill at all. Just think about stock market. It doesn’t matter how many times you have pointed out. It is well known, though you might not know, that for data with trend, the naive estimator performs poorly.

    I understand that this post is written for deniers and conservative readers who probably don’t have technical backgrounds required. My dear long-time friend, why are you trying to discredit yourself by writing some incorrect claims or claims without demonstrations?

  26. Is anyone able to translate what JH might be talking about or is it just pure gibberish?

  27. Is anyone able to translate what JH might be talking about or is it just pure gibberish?

    He is using what climate models claim to prove, “there is an upward trend in average global temperature”, as a premise to his argument that the naive estimator is inappropriate for climate predictions.

    There are two problems with this: the logic is circular, and the conclusion still would not follow if the premise were even sound. It is certainly possible that the naive estimator could do a better job of predicting climate than other possible models when there is a trend present. It merely depends on how bad the other models are.

  28. swordfishtrombone

    February 22, 2015 at 9:26 am

    JH: “I understand that this post is written for deniers [note lazy use of insulting term] and conservative readers who probably don’t have [sic] technical backgrounds required.”

    You should be aware that numerous studies and opinion polls have established that in general, “deniers” have greater understanding of climate science and a higher level of educational attainment than believers.

    If asked twenty years ago to predict the temperature in 2015, I suspect that the public would have done a better job than climate modellers’ supercomputers. (Public answer: “About the same?”)

  29. John D: I believe JH is “she”, not he. Her use of the word “denier” makes clear she is not interested in the truth or actual discussions, as does the use of “conservative”. Her comments tend to be cryptic and she will not address actual questions, so there’s little point to actually asking anything, it just annoys her. References to the lack of actual degrees of readers are interesting since many her have technical degrees and some have PhDs. I have given up trying to engage someone who has no desire to actually discuss anything. It appears it takes too much time to actually defend what she writes (she did say this). This is, of course, based on my reading of her comments and others are free to disagree.

    It’s ignore the troll time again. Persistant things, aren’t they?

  30. Will N,

    I don’t expect you to know statistics and mathematics modeling at all. Whether you understand or not is not my problem, either. However, let me provide you some background information written for an introductory time series class – https://www.otexts.org/fpp/2/5. (Yes, it’s assumed that a PhD statistician would know the materials well.) The site contains basic, very basic materials and well-known examples. If you can comprehend the basic, good for you. If not, perhaps, it’s easier to believe the pseudoskeptic’s rhetoric.

  31. I would suggest from his own words that ‘JH’ is anything BUT your ‘long-time’ friend.

  32. Swordfishtrombone,

    It doesn’t matter to me what the opinion polls say. Don’t really care about politics in climate change. The fact is that the naive estimator doesn’t normally perform well for data with trend when fair comparisons are made. See the link I provide above. For math modeling, it’s more complicated.

    What is the global anomaly temperature 20 years ago? What is the one for 2014? It may be interesting to see what happens if one uses the data up to 1994 for modeling and those from 1995 to 2014 as a hold-out data set or test set for skill comparisons. In this case, the 1994 temperature is the naïve forecast for all the temperatures from year 1995 and 2014 (i.e., draw a horizontal line at 1994 temp anomaly.)?

    If you want to use the 2013 temperature as the naive forecast, a fair comparison requires one to run the model of interest using all the data up to 2013. But one can hardly make reliable conclusion using the result from one year.

    I am trying my best to repeat basics in statistics. I have always thought that one of the reasons we can be fooled is that we don’t know enough.

    And my writing in Chinese won’t help.

  33. Sheri,

    [i]t just annoys her.

    To me, that someone annoys me means I actually care about this person. In your case, it is not true.

    Yes, you should really ignore me. Please do yourself a favor!

  34. Otter, I know, I wonder whether I am a long-time friend too.

  35. John Dietl, but…. even Briggs agrees that there is an upward trend in the temp data. Of course, it merely depends on how bad the other models are! Thanks for showing that you get my points.

  36. JH: None of my comment was addressed to you. It was about you. Seriously, you are not that important. I was ignoring you.

  37. “Natural variations” do not and cannot explain the “pause” (I beg you will read the link).”

    Yes, they do, and your link isn’t convincing.

    For climate models to incorporate natural variability, they would have to know (obviously) how nature will vary in the future — what volcanoes will erupt and when, what ENSOs will occur (when and their magnitude), how will the sun’s irradiance change in the future.

    How is a modeler supposed to know what volcanoes will erupt in the next 10 years?

    Since the huge El Niño of 1998, there have been seven La Niña seasons (cooling effect), two of them strong, and four El Niño seasons (warming effect), with none of them strong. The predominance of La Niña conditions has tended to cool the surface. So have overlooked volcanic aerosols. So has a slightly weaker sun. And improved data models show there has been more warming that the traditional datasets (such as HadCRUT4) show.

    So how was a modeler in 2000 supposed to know the next 15 years would be dominated by La Ninas?

  38. As I remarked in a comment on another post, for Lent I’m giving up responding to individual comments on posts, but I would like to make a general point regarding agreement of “models” with “observations”. If the observational data is fudged/massaged/altered, then whatever agreement might be observed is meaningless. Link are given in a post on my blog, “Scientific Integrity: Lessons from Climategate” for someone to decide whether has been done by warmist academics (I refuse to call them scientists)
    http://rationalcatholic.blogspot.com/2015/01/scientific-integrity-lessons-from.html
    and in another blog to show that it is still being done, for example in Paraguayan weather stations
    https://notalotofpeopleknowthat.wordpress.com/2015/01/26/all-of-paraguays-temperature-record-has-been-tampered-with/
    And of course, the standard warmist orthodox reply, is that the data massage is done according to peer reviewed prescriptions. Peer Review, Shmeer Review–the peer review process has been perverted so much that in most climate journals it is a sham. Only orthodox opinions are allowed, as posts from this blog show.
    It is ironic that in a winter season where cold temperature records are being set one after another, that the warmists still proclaim their religious belief. And I as I say to my neighbor when I’m trying to chip the ice off my sidewalk, or shovel the foot of snow, “Where is global warming when we need it?”
    But of course, the response is, that’s only a local blip.

  39. “and in another blog to show that it is still being done, for example in Paraguayan weather stations”

    Bob, do you understand why the data is homogenized — what biases exist that need to be accounted for?

    How would you handle station breaks — when a temperature station fails and must be replaced by a different one, possibly of a different technology? When a station must be moved? When the time of observation changes?

    Are you aware the net effect of the raw data processing LOWERS the warming trend?

  40. “It is ironic that in a winter season where cold temperature records are being set one after another, that the warmists still proclaim their religious belief.”

    A healthy majority of the globe is right now at average temperature or higher. Alaska is especially hot at the moment. Go to this page, click on “Temperature Anomaly” and scroll down to the map at the bottom of the page:

    http://cci-reanalyzer.org/DailySummary/index_ds.php

    The globe just saw the 2nd warmest January since 1880, and February looks so far to be even warmer.

  41. How many times do you think you are going to have to tell me that what I am looking at is a wolf and not a chihuahua before you can get me to see a wolf?
    Hottest ever? No, it’s not a wolf and as long as you keep telling me the planet is warmer when it’s clearly not, I will ignore you. The insanity just keeps deepening.

    I did find an interesting comment on another website:
    Global Warming can cause cooling. Global Cooling can cause warming.
    This may be my new motto. Global Cooling and Global Warming become interchangable. Nifty!!

  42. Sheri wrote:
    “…as long as you keep telling me the planet is warmer when it’s clearly not.”

    What evidence and data are you using to conclude the planet is clearly not warmer?

  43. “So how was a modeler in 2000 supposed to know the next 15 years would be dominated by La Ninas?”

    Especially when a lot of the modelers were predicting “permanent” El Ninos and saying that global warming “causes” El Ninos.

    http://news.bbc.co.uk/2/hi/science/nature/25433.stm
    http://news.bbc.co.uk/2/hi/science/nature/76693.stm
    http://www.sciencedaily.com/releases/1999/01/990111180607.htm

    This reminds me of a complaint I once heard from some naïf in the marketing department. “How are we supposed to know what the customers are going to want next year?”

  44. all:
    There’s an interesting article on the American Thinker : “Studies in Comparative Theology–The Hidden Imam versus Hidden Heat”
    http://www.americanthinker.com/blog/2015/02/studies_in_comparative_theology_hidden_imam_versus_hidden_heat.html
    Let’s pray for the conversion of Islamic terrorists, evangelical greens and warmists, and evangelical atheists.

  45. I’m going to violate my vow to correct contrary to fact statement (have to go to Confession tomorrow):” Are you aware the net effect of the raw data processing LOWERS the warming trend?”
    go to the link in my previous comment and you’ll see that the alteration gives a temperature rise, rather than cooling.

  46. Bob Kurland wrote:
    “go to the link in my previous comment and you’ll see that the alteration gives a temperature rise, rather than cooling.”

    It does for these few stations in Paraguay. But there are thousands of others around the world that go into calculating the global average, plus sea surface temperatures. The next effect of these adjustments is a lower global warming trend, according to Zeke Hausfather, who a data analyst at the BEST project at Berkeley that was formed (by Richard Mueller) specifically to take a new look at temperature records (they found the same results as everyone else).

    https://twitter.com/hausfath/status/564921572096348160

    Stephen Mosher works with Zeke — these guys have been all through the data over the last several years. They wrote some blog posts explaining why these adjustments are scientifically necessary and valid, such as

    http://judithcurry.com/2015/02/09/berkeley-earth-raw-versus-adjusted-temperature-data/

    Kevin Cowtan made this video that explains why the Paraguay adjustments are made and why Christopher Booker is wrong:

    https://www.youtube.com/watch?v=qRFz8merXEA

  47. If you believe the links in the last comment, there is a bridge in Brooklyn that is for sale..

  48. If you believe the links in the last comment, there is a bridge in Brooklyn that is for sale.. fudging data is fudging data, no matter how much one tries to euphemize that process with terms like “equalization”.

  49. David Appell @ February 22, 2015 at 12:37 pm

    “Natural variations” do not and cannot explain the “pause” (I beg you will read the link).”

    Yes, they do, and your link isn’t convincing.

    The problem you have is that, if natural variations can explain the “pause”, then they can also explain the previous rise.

  50. John M: Yes, not everything said about climate science is true. Nor in physics, biology, chemistry, mathematics, or….

  51. and by “fudging” I mean any process that does not show the untreated data and that gives a uniform change in the direction of the desired result to the untreated data. Here are two relevant quotes:
    “The Scientific Method is a wonderful tool as long as you don’t care which way the outcome turns; however, this process fails the second one’s perception interferes with the interpretation of data.” Christina Marrero
    and
    “…if you’re doing an experiment, you should report everything that you think might make it invalid—not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you’ve eliminated by some other experiment, and how they worked—to make sure the other fellow can tell they have been eliminated.” Richard Feynman
    In the case at hand “experiment” might be replaced by data display.

  52. “fudging data is fudging data, no matter how much one tries to euphemize that process with terms like “equalization”.”

    It’s called “homogenization,” not equalization. And it’s not fudging data, it’s processing the data to remove biases and make it useful. It’s routinely done in all kinds of science.

    Bob, you still haven’t said — how would you correct for station breaks, if you’re trying to build a long-term time series?

  53. David Appell,

    Since the subject at hand is the accuracy of the climate models, and since you offered up the excuse that the poor modelers were blind-sided by the La Ninas, no comment on the delicious irony that many of those same modelers were confidently predicting endless El Ninos?

    They weren’t just wrong, they were wrong is such a way that your lame “how were they supposed to know” looks just plain silly.

  54. Bart wrote:
    “The problem you have is that, if natural variations can explain the “pause”, then they can also explain the previous rise.”

    They can if and only if there is evidence for them in the past. Modelers have done historical calculations with only natural factors, and they cannot explain modern warming. But their models do with anthropogenic + natural factors. See Figure TS.9 (p 60) in the IPCC 5AR WG1 Technical Summary
    http://ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_TS_FINAL.pdf

  55. David Appell @ February 22, 2015 at 3:12 pm

    This is an argument from ignorance, and self-contradictory on its face.

    If they do not know the “natural factors” of the present, how can they “know” the natural factors of the past?

  56. So the models for the most part missed the warming from 1910 to 1945, miscalculated the rate since 2000, but somehow magically matched the warming with all those El Ninos in the 80s and 90s almost perfectly.

    Just lucky I guess.

  57. Appel, this once I will reply to you by name: you’re quite correct I have no idea how to account for “station breaks”. But since the primary data isn’t adequate, then why should one believe data massaging methods that give a uniform answer in the direction desired by warmists (see the quotes in my comment above), an answer contrary to tropospheric satellite measurements, that are independent of weather stations?
    And with this last remark, I’m out of here until April 4th.

  58. John, as far as I can tell only one scientist, Russ Schnell, said El Nino would be permanent “in a few years, or a decade or so.” That was wrong. I don’t see that he wrote any papers about it:

    http://www.esrl.noaa.gov/gmd/staff/Russell.C.Schnell/

    Many others have wondered if global warming will increase the frequency or intensity of El Ninos, and as far as I see there is no conclusion about that yet, though it’s a worthy topic of investigation.

  59. Bottom line: there is no indication from the temperature record that anything is happening which wasn’t laid in well before humans could have been having any impact. The temperature record is dominated by a long term trend and a ~60 year cyclical phenomenon which have been in evidence for well over a century. Nothing is changing, nothing is accelerating, relative to that long established pattern.

  60. Bob: The warming we’re seeing is serious — 10 to 15 times faster than when the Earth left its last glacial period. Sea level is rising 15 times faster than it did in the 5000 years before the Industrial Revolution.

    So the question of global warming is serious. So we need to find all the data and observations and clues we can to answer the question of how can can it get.

    In climate science you don’t get the data you want, you have to use the data you can get. Homogenization is a way of utilizing historical data that certainly isn’t perfect. But if you wait for perfect data it all be over before you can say anything. Simply throwing up your hands and saying “I don’t know” doesn’t cut it when the implications of warming are so significant.

    If you looked seriously into how to use historical temperature data, I bet your solution would be very much like homogenization, if not exactly it. That was why the BEST project was created by Richard Muller, who was skeptical going in. They analyzed all the data they could find; they found the same result as everyone else:

    “The Conversion of a Climate-Change Skeptic”
    By RICHARD A. MULLER
    Published: July 28, 2012
    http://www.nytimes.com/2012/07/30/opinion/the-conversion-of-a-climate-change-skeptic.html

    “CALL me a converted skeptic. Three years ago I identified problems in previous climate studies that, in my mind, threw doubt on the very existence of global warming. Last year, following an intensive research effort involving a dozen scientists, I concluded that global warming was real and that the prior estimates of the rate of warming were correct. I’m now going a step further: Humans are almost entirely the cause.”

  61. John M: There was not supposed to be a major effect from La Ninas. CO2 was THE driver and the correlation plots all proved it. Saying anything could overcome CO2 was heresy–until something did. Now you hear it all the time. (Ever wonder why in the graphs of the past there is no cooling due to La Ninas but now there is? Same for El Ninos. In the past, they were irrelevent or they were fudge factors. Either way, they could not overcome CO2.)

    Michael H: Excellent point!

  62. Bart wrote:
    “The temperature record is dominated by a long term trend and a ~60 year cyclical phenomenon which have been in evidence for well over a century. ”

    Natural cycles don’t create energy; energy must be conserved over the cycle. So where is all the cooling occurring that must necessarily be offsetting the warming we’re seeing — warming of the surface, of the lower troposphere, of the ocean?

  63. John M wrote:
    “So the models for the most part missed the warming from 1910 to 1945, miscalculated the rate since 2000, but somehow magically matched the warming with all those El Ninos in the 80s and 90s almost perfectly.”

    Looking at the figure TS.9 I referred to above, models track the 1880-1945 warming fairly well, within about 0.1-0.2 C.

    IPCC 5AR WG1 Technical Summary, Figure TS.9a p 60
    http://ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_TS_FINAL.pdf

    They do an even better job of tracking it since 1960, up until about 2000 when they are too high. This is the time when we’ve had overall La Nina conditions, some volcanic eruptions, and a slightly weaker Sun.

  64. Sheri wrote:
    “There was not supposed to be a major effect from La Ninas.”

    Not sure where you got that idea, and you didn’t cite any science. As long as I’ve been following climate science people have said the ENSOs can cause up to +/-0.2 C temperature swings in a few years. Since anthropogenic warming rate now is about +0.2 C/decade, a large La Nina can mask part of that. Several can mask it longer.

  65. With temperature adjustments:
    Paul Homewood is looking at GISS temperature sets, I believe.
    Judith Curry is looking at BEST temperature sets.

    These are not the same and the adjustments are not made in the same way on each set. BEST is based on an algorithm. GISS appears to be manual.

    It is said repeatedly that the adjustments don’t affect the data. So why are adjustments made? The data does not need adjustment, obviously.

  66. Sheri wrote:
    “Ever wonder why in the graphs of the past there is no cooling due to La Ninas but now there is? Same for El Ninos.”

    Since you never show any evidence, I looked it up. There were strong La Ninas in 1973-74 and 1975-76. As measured by GISS, the global temperature fell 0.23 C from 1973 to 1974, and 0.11 C from 1975 to 1976.

    Your claim about El Ninos is also wrong. The huge El Nino of 1997-98 saw GISS temperatures go up +0.16 C in a year. That was the last strong El Nino we’ve had.

  67. David Appell is of the opinion that the models do a good job from 1910 to 1945.

    A picture is worth a thousand words.

    http://tinypic.com/view.php?pic=2ltmxrc&s=8#.VOpENLd0w3E

    Next, David Appell will explain to us how his eggs this morning revealed an image of Elvis.

  68. Sheri wrote:
    “BEST is based on an algorithm. GISS appears to be manual.”

    Wrong. (Also, unbelievable — there are thousands of temperature stations.) From the GISTEMP FAQ:

    Why are some current station records different from what was shown before 2012?
    A. UK Press reports in January 2015 erroneously claimed that differences between the raw GHCN v2 station data (archived here) and the current final GISTEMP adjusted data were due to unjustified positive adjustments made in the GISTEMP analysis. Rather, these differences are dominated by the inclusion of appropriate homogeneity corrections for non-climatic discontinuities made in GHCN v3.2 which span a range of negative and positive values depending on the regional analysis. The impact of all the adjustments can be substantial for some stations and regions, but is small in the global means. These changes occurred in 2011 and 2012 and were documented at that time.

    To recap, from 2001 to 2011, GISS based its analysis on NOAA/NDCD’s temperature collection GHCN v2, the unadjusted version. That collection contained for many locations several records, and GISS used an automatic procedure to combine them into a single record, provided the various pieces had a big enough overlap to estimate the respective offsets; non-overlapping pieces were combined if it did not create discontinuities. In cases of a documented station move, the appropriate offset was applied. No attempt was made to automatically detect and correct inhomogeneities, assuming that because of their random nature they would have little effect on the global mean.

    After October 2011, NCDC added no more data to GHCN v2, so GISS used its replacement GHCN v3.1 as the base data. One of its differences from GHCN v2 is that multiple records are replaced by a single record, obtained by using for each month the report from the highest ranked source without applying any offsets when switching from one source to another. The resulting discontinuities are handled by NCDC when creating the adjusted version. Since the multiple records used by the GISS procedure no longer were available, GISS switched to using the adjusted instead of the unadjusted version of GHCN v3.1.

    http://data.giss.nasa.gov/gistemp/FAQ.html#q216

  69. “A picture is worth a thousand words.
    http://tinypic.com/view.php?pic=2ltmxrc&s=8#.VOpENLd0w3E

    That’s (part of) the IPCC figure I referred to. The largest variance between model and observations is about 0.3 C from 1880-1940. How good does it have to be? And remember, this was a time before satellites, so there was not good data on volcanic aerosols (besides major eruptions, a constant aersol background is often assumed) or total solar irradiance (comes from proxies).

  70. David Appell @ February 22, 2015 at 3:36 pm

    “Natural cycles don’t create energy…”

    Non-scientific people really shouldn’t try to sound scientific. They end up producing word salad.

    Natural cycles are phenomena reflecting the storage and release of energy. Cooling occurs during the storing phase, warming during the release phase. Hence the word “cycle”.

  71. David Appell @ February 22, 2015 at 4:20 pm

    It does not matter how good it is. Consistency is not proof. A plane crashing is consistent with engine fire, yet not all plane crashes are the result of engine fire. Asserting that an engine fire occurred on the basis of the plane crashing is the logical fallacy of affirming the consequent.

  72. I feel like I’m beating up on a special needs child. Over and out.

  73. David Appell:

    “How good does it have to be?”

    Well, clearly, until the models can deal with things like the PDO and other ocean oscillations, they are going have problems. If you are going to overfit a model to a period with a lot of El Ninos, don’t whine when it falls apart when the El Ninos stop. The lack of fit from 1910-1945 is diagnostic of the models being incapable of dealing with the PDO and AMO.

    And Trenberth has been all over the “Global Warming/El Nino” link.

    “One respected climate scientist who has gone out on a limb about the global warming-El Niño connection is Kevin Trenberth, a climatologist at the National Center for Atmospheric Research in Boulder, Colorado. He thinks that El Niño may function as a kind of pressure release valve on the tropics. In an era of global warming,”

    http://www.pbs.org/wnet/savageseas/weather-side-elnino.html.

    Please don’t tell me that was “only” a media report. As a journalist, I would think you’d have more pride than that.

  74. A word of caution when engaging with cranks such as Appell. No counter argument will ever change his mind. He can be debunked a thousand times but will be putting the same argument forward on some other blog the next day. He will lie and cheat with his arguments, sources and numbers, typically by excluding caveats, cherry picking or using invalid statistical techniques, if he thinks he can get away with it, so as to prove the “deniers” wrong. And if he could stab all of the people who attend this forum in the eye and get away with it, he would. Because he has nothing but utter contempt for people who oppose his end-of-the-world-is-coming view. (He sees himself as a saviour within this world view.) So think carefully before engaging with him. He will endlessly flood every topic with his comments if he thinks anyone is paying attention to what he has to say. As with most cranks, nothing is more desirous than attention, whether positive or negative.

  75. The most effective thing you can do to someone like Appell is agree with him. Then he has nothing to discuss. Of course, you can’t lie, but you can often find something that he says that is valid and concentrate on that. Or you can just ignore him. Either works. He’s been here before and I have no doubt he’ll be back again. As Will noted, there is no convincing a true believer of the error of their ways, so if that’s your goal, you will not succeed.

  76. Sheri wrote:
    “As Will noted, there is no convincing a true believer of the error of their ways, so if that’s your goal, you will not succeed.”

    I am convinced by data. Unfortunately you never provide any, which leads me to think your position isn’t based on the science, but on something else.

  77. Briggs

    February 22, 2015 at 6:31 pm

    Hey Appell, tried any good FOIAs lately?

  78. John M wrote:
    “Well, clearly, until the models can deal with things like the PDO and other ocean oscillations, they are going have problems.”

    Why? Climate models calculate equilibrium climate sensitivity — the warming expected after the system has come back to equilibrium. Over that time, PDOs and AMOs and ENSOs average out to close to zero, and volcanic effects drop out because they’re temporary.

    Climate models can’t do accurate short-term (~decades) predictions, for two reasons:
    1) no one knows what natural variabilty will happen in that time , and it well may not average to zero
    2) the initial state isn’t known. Climate models don’t solve a PDE initial state problem, they solve a boundary value problem. There are simply too many unknowns about any initial state, even now, especially for (1) manmade aerosols, and (2) deep ocean dynamics (current flows). Modelers don’t start their program at the year 1990 or 1900 or 1880 or such; the models are “spun up” from hundreds of years earlier under the applied (current) forcings (which are known for GHGs, but not so well for aerosols) they reach an equilibrium state. Then the forcing changes are applied as time goes by until the system comes back again to an equilibrium state.

    But if you know how to generate the PDO or AMO in a model, the world is waiting to hear. It will require data we don’t now have (deep ocean, though the deep Argo program will help), and probably grid sizes we can’t now obtain due to computing limitations.

    “If you are going to overfit a model to a period with a lot of El Ninos, don’t whine when it falls apart when the El Ninos stop. ”

    Models aren’t “fit” with ENSOs, because, again, no one knows when they will happen in the future.

    “The lack of fit from 1910-1945 is diagnostic of the models being incapable of dealing with the PDO and AMO.”

    Define “lack of fit.” Tell us what fit is needed instead.

    “Please don’t tell me that was “only” a media report. As a journalist, I would think you’d have more pride than that.”

    Please show me the papers that conclude El Nino will soon be permanent. I didn’t even see that Russ Shell wrote any.

  79. Will: Looks like those tipping point citations hit a nerve, huh?

  80. Sheri,

    I think reading those sorts of posts have some limited value if you’re at all curious about current activist talking points. It’s just pointless to engage with them. The latest of their ideas doing the rounds is that more Antarctic sea ice = global warming and colder temperatures/ more snow = global warming. There is not even peer reviewed speculation behind this. They are purely invented stories stated as scientific facts. The logical disconnect is now insurmountable. In one post on another blog Appell hand waved mid tropospheric warming as unimportant because “nobody lives in the mid troposphere. ” Then in his very next post demanded that the true metric for global warming should be deep ocean temperature. Now, it’s not like he wrote one post, forgot what he wrote, and a few days or weeks later he thought up the second claim. These two posts *followed* each other. These people have so compartmentalized their thinking that they now hold mutually contradictory arguments in their heads simultaneously and recognise no conflict. That’s why debate with them has moved beyond rational exchange. That’s the downside of the internet. In the good old days they would just attend their UFO meetings and nobody would know what they were up to. These days they publish their agenda everywhere, and especially in places that have the lowest tolerances for nonsense.

  81. Briggs

    February 22, 2015 at 6:47 pm

    Appell,

    You go get ’em tiger. If you don’t have facts, obfuscation often works.

    And limit your comments. Put them all in one. Else I will have to put you into moderation.

  82. Bart commented:
    “Natural cycles are phenomena reflecting the storage and release of energy. Cooling occurs during the storing phase, warming during the release phase. Hence the word “cycle”.”

    That’s equivalent to what I said. So where was all this energy stored in the cool phase of the cycle? And where is the evidence that shows some place cooling (of about -1/2 W/m2) as the cycle has gone into its warm phase?

    We’ve had surface warming since 1880. That’s over two of your purpoted cycles. The ocean heat content (top 2000 meters) has been going up since the late 1960s., and shows no sign of slowing down. (Just the opposite.)

    http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT/

  83. Will: I mostly agree with you. However, I actually read very little of what Appell writes. If I happen to notice a line or two and feel like writing a comment I do. Otherwise, I don’t care. I’m afraid some are just too far off the scale for much reading. While it does tell me the current activist talking points, I tend to run into them on virtually every blog about global warming (except the very few that are science only). It seems all the believers use the same points over and over and over. Holding contradictory beliefs is easy for them. Like warming causes cooling.

  84. Following Sheri’s lead, I guess I can agree with Appell that climate scientists are not to be believed when they talk to the media.

  85. david appell:
    “The globe just saw the 2nd warmest January since 1880, and February looks so far to be even warmer.”
    really?
    do you seriously maintain that we know, with any degree of certainty that “the globe”
    saw its warmest january since 1880? really?
    the world laughs at you innumeracy and idiocy.
    now, what will you do threaten me?

  86. “your” effing typos.

  87. It is with deep sadness we note the passing of the Null Hypothesis in climate science. Born about 1925, Null has had a long and distinguished career testing the significance of an immense variety of theories and conjectures. In particular, Null brought to science a realization of the medical injunction to “First do no harm,” by not claiming the truth of a hypothesis without clear evidence. Unfortunately, in recent years Null fell into declining health, contracting a serious case of consensus from which Null never fully recovered. Finally, when complications set in from natural variability and other signs of “bad data,” Null finally expired. In lieu of flowers, Null’s estate asks that you donate to the statistician of your choice.

  88. It makes me sad to se how Kevin Trenberth completely misses the point. I guess a much more reasonable problem with the article to point out would have been the low g argument. Made a more complete comment on that on the post about the original article. http://wmbriggs.com/post/15095/

  89. David Appell @ February 22, 2015 at 6:48 pm

    The ~60 year cycle accounted for the run up in temperatures in the latter third of the 20th century. Take that away, and the leftover long term trend is not large enough to be of any particular concern. The upswing of the natural ~60 year cycle created the trend which produced the alarm, which was now obviously overwrought.

    Furthermore, the long term trend itself has been in evidence for over a century, well before humans could have caused it, so you have to take that out, too – it is probably simply a partial glimpse of an even longer cycle. Once you take that out, you have very little left that could be human induced at all.

    Relax. Take a pill, if you need to. There’s nothing in the record to get excited about.

  90. “It makes me sad to se how Kevin Trenberth completely misses the point.”

    I doubt he misses the point, but rather it’s not to his advantage to address it.

  91. Appel, you, Trenbarth, Gillis, et al are ignoring then point of the paper. The.Models.Suck. Hope that helps.

  92. Briggs wrote:
    “Briggs emphasized that “if you don’t remember anything else from this radio program listen to this: If you have a theory and that theory makes bad predictions, that theory is in error…Climate forecasters have made, for decades, lousy predictions. They are therefore in error…”

    Yet again, CLIMATE MODELS DO NOT MAKE PREDICTIONS. Constantly claiming otherwise either shows you don’t understand climate models (or, say, financial models), or you aren’t representing them honestly.

    Secondly, even if the models *are* wrong, that hardly exonerates CO2, which, let’s face it, is what contrarians really want. Climate changes due to GHGs are among the BEST known parts of the models, because they can be calculated from fundamental physics. (Though the very complicated band spectrum of the molecules means the calculations can only be done by computer.) It’s the feedbacks where the issues lie, and since they come after GHG warming starts, they will show up after it. Some of them take decades to centuries to show. We are just getting started into AGW….

  93. ““Understanding that they can never match.” This is, of course, false (a causal model never errs, for example). But what you probably meant was “They rarely match precisely for data of this kind”, which is true.”

    No I meant exactly what I wrote.

    But amuse me. Pick any model you like of the physical world. Any aspect, anything you like. Use the model. Make a prediction. Then we will go and observe. Let me know when the difference is zero.

  94. “No. Climate models do not come as close to matching reality as much simpler models. Something is very wrong with them.”

    You need to answer the question I asked. I will rephrase it for you so you wont go off on tangents

    When a model of the physical world makes a prediction and that prediction does not match observation. What do you know?

  95. I congratulate those who found the Monckton et al. paper pellucid. However, when I personally first started to read the paper, I put it down because of frustration with what seemed to be left unstated.

    The simple-model equation does indeed seem simple. For the benefit of anyone who is still interested, I’ve written it in R.

    f = 0, CRat = 2, C_0 = 1, C_t = 1, q = 1, r = 1, k = 5.35){
    # A stab at coding the simple model described in Monckton et al.,
    # "Why models run hot: results from an irreducibly simple climate model"
    # dF: Monckton et al.'s delta F, i.e., forcing due only to increased CO2 concentration
    # L_inf: Monckton et al.'s lambda sub infinity
    # L_0: Monckton et al.'s lambda sub zero
    # CRat: Ratio of Monckton et al.'s initial CO2 concentration to their final CO2 concentration
    # C_0: Monckton et al.'s initial CO2 concentration
    # C_t: Monckton et al.'s final (time t to infinity) CO2 concentration
    #
    # Caution: This routine permits user to supply inconsistent argument sets,
    # and it assigns priority among inconsistent arguments somewhat arbitrarily
    # A typical call supplies only the feedback srgument f, possibly as a vector,
    # in response to which the routine returns, inter alia, the so-called
    # equilibrium climate sensitivity as dT.

    if(missing(dF)){
    if(missing(CRat) & !missing(C_0) & !missing(C_t)){
    CRat = C_t / C_0;
    }
    dF = k * log(CRat);
    }
    if(missing(L_inf)){
    if(missing(G)){
    if(missing(g)){
    if(missing(f)) return("f is missing");
    g = L_0 * f;
    }
    G = 1 / (1 - g);
    }
    L_inf = L_0 * G;
    return(list(df = df, dT = dF * r * L_inf / q, L_0 = L_0, L_inf = L_inf));
    }
    list(dF = dF, dT = dF * r * L_inf / q, L_inf = L_inf);
    }

    MoncktonModel(f = c(1.0, 1.5, 2.2))
    # $dT
    # [1] 1.685608 2.181375 3.708337
    #
    # $L_0
    # [1] 0.3125
    #
    # $L_inf
    # [1] 0.4545455 0.5882353 1.0000000

    But the paper’s discussion of the transience fraction is hard to sort out.

    The part that raised the most questions for me was the transience-fraction part, §4.8. Its Table 2 is described as “derived from” the GeraldRoe paper, but it’s not clear how that derivation occurred. Table 2 is not consistent with a simple application of Roe’s Equation 29, which would seem to leave only eyeballing his Figure 6. Yet the correspondence between feedback values and temperature values as a function of time is not immediately apparent there. How did Mockton et al. get their Table 2?

    In that connection, how were the values in Table 4 obtained from Table 2? Presumably there was some kind of interpolation, but it would aid understanding to make that more explicit.

    It’s not clear how the §7 statement that “the 0.6 K committed but unrealized warming mentioned in AR4, AR5 is non-existent” was arrived at. That section refers to Table 4, which shows that the values computed for the model result from multiplication by a transience coefficient r_t, supposedly taken from Table 2. The r_t values 0.7, 0.6, and 0.5 respectively given in Table 4 for f values 1, 1.5, 2.2 suggest that in fact the central estimate leaves (1 – 1/0.6) * 0.8 = 0.53 K of warming yet to be realized. What am I missing?

    Less important, there may be some way to interpret the §8.3.2 passage, “Also, in electronic circuits, the singularity at g_inf = +1, where the voltage transits from the positive to the negative rail, has a physical meaning,” but I haven’t been able to envision the “transits” part. I’m told that a g value of +1 has a meaning for a portion of the amplifier’s operating regime, but the amplifier tends promptly to leave that regime, possibly clamping its output to one or the other rail, or, depending on delays in the feedback, possibly causing it to oscillate. So an explanation of how the “voltage transits from the positive to the negative rail” would be helpful.

    I’m fairly sure that the paper has a valid point regarding the failure of AR5 to reduce the equilibrium-sensitivity range. But the lacunae in the transience-fraction discussion make that issue hard to assess.

  96. Joe Born: Thank you for posting the R code. I am still working through the paper and you have raised some interesting questions. Just wanted to let you know some are still reading and appreciate your comment.

  97. Sheri: I appreciate the feedback.

    An unfortunate feature of blog discussions is that they have usually moved on before plodders such as I have found the time to give technical matters serious consideration. In this case I commented anyway because many critics had faulted the paper for lack of code, I happened to have written some, and there was a small chance that someone else would still be reading and could possibly use it.

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