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Is there a case against human caused global warming in the peer-reviewed literature? Part 2

Posted on 9 November 2011 by Jim Powell

Science advances through the peer-reviewed primary literature. Peer-review is not perfect, but it is the best system humans have invented for uncovering and correcting errors. In science, the truth will out.

Part 1 of this series of posts introduced a database of more than 115 climate skeptics and the peer-reviewed papers each has published as recorded in the Web of Science. The database is located here. I have now added the journal for each publication. You will find the papers organized by journal here.

Some conclusions emerge from reading this set of abstracts, and in some cases the entire paper, which can be done in an hour or two.

  1. 70% of those listed have no scientific publications that deny or cast substantial doubt on global warming. This list includes such outspoken and media-promoted skeptics as Joe Bastardi, Freeman Dyson, Bjorn Lomborg, Christopher Monckton, Jo Nova, Ian Plimer, Matt Ridley, and S. Fred Singer. Why don't they write up their argument and submit it to a scientific journal?   


  2. None of the papers provides the “killer argument,” the one devastating fact that would falsify human-caused global warming. The best they can do is claim that sensitivity is low, which they have been unable to substantiate and which much evidence contradicts. If as the skeptics claim, human-caused global warming is wrong, why can’t they show it is wrong? 


  3. None of the papers explains the observed, concomitant rise in fossil fuel emissions, atmospheric CO2, and global temperatures. Attempts in some papers to blame the the sun are falsified because as temperature has risen, solar activity has remained about the same, or even declined. 


  4. The skeptics have no better theory, or indeed any theory, to explain all of the observational evidence of man-made global warming.


  5. Many papers, particularly the earlier ones, suggest improvements in the IPCC’s procedures, in the way temperature data are collected, etc. They imply that once those improvements have been made, the case for human-caused global warming might be weakened. Instead that case has grown stronger.  


  6. A true scientific skeptic must be prepared to change his or her mind as new evidence comes in. But as far as I am able to tell from these papers, in spite of the continuing rise in global temperature; heat records; extreme weather of all sorts; melting glaciers, ice caps, and sea ice; sea level rise; migrating species, and the like, no skeptic who wrote in the first half of the 1990s has since accepted human-caused global warming. To be a climate skeptic is to remain a skeptic. 


  7. Richard Muller says, "The skeptics raised valid points and everybody should have been a skeptic two years ago. And now we have confidence that the temperature rise that had previously been reported had been done without bias.” To me, this makes him a skeptic. See this other quotes here.  But his publication of the BEST results may indicate that we should no longer consider him one. 


  8. In a 1990 paper, Professor Richard Lindzen of MIT argued that because the observed global temperature rise to that year had been less than predicted, the sensitivity of global temperature to rising CO2 must be less than expected. Therefore, he wrote in 1990, “The current state of our understanding of climate hardly justifies a consensus over the response of climate to the small increase in downward flux caused by a doubling of CO2.” In spite of all the evidence mentioned in item 6, 21 years later, in a paper titled, “On the observational determination of climate sensitivity and its implications,” Lindzen and Choi conclude, “The results imply that the models are exaggerating climate sensitivity.” In that 21 year period, atmospheric CO2 concentration rose from 354 to 389 ppm and the global mean temperature anomaly rose from about +0.2 to about +0.6°C. Moreover, if the sensitivity is as low as Lindzen has been saying for more than two decades, what caused the observed temperature rise? 


  9. Skeptics feel no compunction about making emphatic statements on subjects far afield from their expertise, in some cases, literally. Astrophysicists write about polar bears; those with no expertise in computer modeling denounce  climate models.

These peer-reviewed papers by skeptics offer no reason to doubt that global warming is real, caused by humans, and dangerous. Despite ample opportunity, climate skeptics have failed to present any coherent alternative to the theory that carbon emissions are the primary driver of observed warming. That is why 100 national and international scientific organizations have issued statements accepting human-caused global warming, and not a single such organization has issued a statement of denial. 

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Comments 1 to 50 out of 56:

  1. "The skeptics have no better theory, or indeed any theory, to explain all of the observational evidence of man-made global warming."

    That is such an important point. Science doesn't work by criticizing arguments and trying to deny the evidence, but by building and testing competing theories. "Skeptics" don't have any consistent theory that explains all the data. Moreover, in order to deny each piece of evidence, they eventually get into contradictions (as documented here: http://www.skepticalscience.com/contradictions.php).
    Another important point, IMHO, is that global warming is not some kind of surprising feature of our world that we need to come up with explanations for. Global Warming was a prediction, an expected consequence of dumping billions of tons of CO2 to the atmosphere.

    Speaking of contradictions; one minor quibble. Point 6 end with "To be a climate skeptic is to remain a skeptic" but point 7 you state about Muller that "we should no longer consider him one"
    Besides, I don't think I agree with point 6. There are "skeptics" that changed their mind. Michael Shermer comes to mind; he wasn't "sold" on the idea of climate change but some years ago he ended accepted reality. While I accept that your characterization applies to many "skeptics", I don't think is fair to generalize.
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  2. Just reading Steven Pinker's Better Angels and he uses the quote:

    "Those who can make you believe absurdities can make you commit atrocities."
    —Voltaire

    That'll be why these people work so hard on the absurdities .. to promote the atrocity of inaction.
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  3. Yes, as you point out, the skeptic attempts to blame the Sun are falsified.

    But the other main claim of the skeptics is also falsified, and this falsification does not seem to get a lot of press, and this falsification is this:

    The skeptics deny what mainstream peer-reviewed climate science has to say on the greenhouse gas activity of non-condensing greenhouse gases like CO2 as forcers and water in the atmosphere as an amplifier (feedback). And so those that admit that the Sun's output has not changed enough to cause all or almost all the recent warming say that essentially only less reflected light has caused all or almost all of the recent warming. (Note that the claims of Svensmark and Spencer et al. with respect to cosmic rays or oceans or clouds ultimately reduce to the claim that essentially only less reflected light has caused all or almost all of the recent warming.)

    There is a book that is partially available online as a Google e-book
    "Solar activity and earth's climate"
    by Rasmus E. Benestad, who obtained a Ph.D in physics from Atmospheric, Oceanic & Planetary Physics at Oxford University. (He is one of the many real climate scientists who contribute at RealClimate.) Go to page 176. We read, "Any mechanism involving the albedo implies strongest response in the daytime temperature. Observations, on the other hand, suggest a reduction in the diurnal temperature range where the night-time temperature has increased more than the daytime temperature (Houghton et al., 2001). According to Svensmark's hypothesis, the warming is due to the reduction in Earth's albedo (reflected light), and therefore a long-term reduction in the low-level planetary cloud cover appears to be inconsistent with the observations."

    That is, what Benestad says above is simply a polite way of saying that the reduction in the global diurnal temperature range where the global night-time temperature has increased more than the global daytime temperature strongly falsifies the skeptic hypothesis that essentially only less reflected light has caused all or almost all of the recent warming. That is, if CO2+H2O greenhouse gas activity is as weak as the skeptics claim and the warming is entirely or almost entirely due to less reflected light, then there is nothing to keep enough heat from escaping out into space at night globally to avoid a global diurnal temperature range increase such that the global daytime temperature increases faster than the global nighttime temperature. But the opposite has been happening.

    And note that this falsification of the skeptic claim that essentially only less reflected light has caused all or almost all of the recent warming is a strong falsification. That is, even though a constant global diurnal temperature range would suffice to falsify the skeptic claim, a decreasing global diurnal temperature range strongly falsifies it. And depending on its rate of decline and on whether this rate of decline is changing and how it is changing, one could argue that this falsification is not just strong but very strong or even very, very strong.

    How do skeptics deal with the fact of the falsification of their denials of what mainstream peer-reviewed climate science has to say on greenhouse gas activity? They deal with it in two ways: They either ignore it or they try to use *local* phenomena to try to refute fact about *global* phenomena. That is, on the latter point, they try to use the fact that there has been an increase in the diurnal temperature range in some *local* climates to try to argue against the fact that the *global* diurnal temperature range has decreased. But since this is all about *global* climate and not about the climate of only cherry-picked parts of the planet, this attempt is just an embarrassment to those skeptics who try this.

    By the way, if a skeptic tries to say that increased water in the atmosphere by itself with no or almost no forcing from non-condensing greenhouse gases like CO2 will save the day for the skeptic denial of what mainstream peer-reviewed climate science says about these non-condensing greenhouse gases, then consider this: The equations in physics providing the calculations that fit reality on this one are where? Answer: Nowhere. Everyone in the skeptic community who does not try to confront this problem in some meaningful way (like Svensmark) know full well that they cannot even begin to make the numbers work to their favor on this one, and so rather than embarrass themselves trying to make the numbers work to their favor they elect to just ignore this problem when confronted with it.
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  4. If your going to use data collected from satalites and ground based units then you nead to at least understand these processes
    (-Snip-)
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    Moderator Response:

    [DB] Please do not link-dump without providing context for why you are providing the links and what the reader can be expected to take away from the reading of the links.  You provide neither in this case, so the links have been snipped.

    As an FYI, you presume that the author doesn't understand the processes behind integrating satellite and ground-based measurements.  That is a false presumption.

    Edit:  Please note that a subsequent comment of yours to this was deleted due to multiple violations of the Comments Policy.

    Please take the time to thoroughly acquaint yourself with it in order to fully comport your comments with its strictures.  Understand that, by commenting at this site, moderation is an implicit condition accepted by the person commenting when posting a comment.  Thanks in advance for your understanding and compliance.

  5. Just got the current issue of Scientific American. In the article "A Formula for Economic Ca laity" the author, David H. Freedman, makes a comment about modelling, and referring to climate science he says" Omitting a key variable seems egregious, but scientists do it all the time....That is a problem for climate science, Colander says, where models often have no terms to account for the effects of clouds. " Clouds control 60 percent of the weather, and models usually ignore them," he notes, "When you can't model a factor that has that kind of influence on the outcome, you have to use a lot of judgment in whether to believe the results.""
    I am very much an amateur with respect to this, but this quote seems to throw more doubt on the models than is justified.
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  6. jim - this is plain flat out wrong. Where on earth do you suppose he got that idea?

    Some info on treatment of clouds in models can be found here.
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  7. jimb @5, if that is what David Freedman says, he is simply wrong. Outrageously so. He may be confused by the fact that clouds are not a single variable. Rather they effect both incoming SW radiation both by reflection, scattering and absorption, and outgoing LW radiation by absorption and emission. How clouds effect these factors depend on their altitude and type. Climate models also track convection and latent heat transfer, important factors often associated with clouds. So, looking at a global circulation model it would be hard (indeed) impossible to point to a single variable and say "that is clouds", but the effect of clouds is integral to operation of the models.
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  8. jmorpuss - you seems to be under the misapprehension that GHGs affect radio-frequency radiation or that radiowaves affect climate. This is not supported by data.
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  9. jimb#5: "David H. Freedman, makes a comment about modelling, and referring to climate science he says"

    Here's another take on the Freedman article:

    Freedman builds off a 2005 paper (pdf) by earth scientist Jonathan N. Carter et al. from a conference on Sensitivity Analysis of Model Output; the paper's titled "Our Calibrated Model has No Predictive Value: An Example from the Petroleum Industry". The SciAm article starts with this geophysical model, draws conclusions about economic models, and mentions climate models not at all.

    The model in the Carter paper is a petroleum reservoir; the model has difficulty reproducing actual production results. Freedman concludes:

    "That financial models are plagued by calibration problems is no surprise to Wilmott--he notes that it has become routine for modelers in finance to simply keep recalibrating their models over and over again as the models continue to turn out bad predictions. ... But in finance they just keep on recalibrating and pretending that the models work."

    What does this have to do with climate science? Here's the big insight:

    No matter what the application (economics, geology/geophysics, climate modelling, etc) a simple axiom applies to computer models: garbage in, garbage out.

    Only one response to that is worthwhile: "Wow."
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  10. WG1 Section 8 is quit plain when referring to models. They do not have preditive ability.
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    Response:

    [DB] "WG1 Section 8 is quit plain when referring to models.  They do not have preditive ability."

    Yes, it is plain.  And it plainly says the opposite of your assertion.  So substantiate your assertion.

    http://www.ipcc.ch/publications_and_data/ar4/wg1/en/faq-8-1.html

    http://www.ipcc.ch/publications_and_data/ar4/wg1/en/ch8s8-4-11.html

  11. Camburn @10, I'm going to call you on that. Your claim is so contrary to the general tenor of the comments in section 8 that I cannot see how you came to that conclusion. What is more, chapter 10 repeatedly uses climate models to make projections, ie, because they are presumed to have predictive power. Therefore I must conclude that your claim is in direct contradiction of the IPCC WG 1 report.

    In fact, it is so far in contradiction of the report that, if you do not produce the quote where Chapter 8 of the IPCC AR4 WG 1 report says that models have no predictive power, I will have to conclude that your statement is a flat out lie.
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  12. #10, Camburn, do you have evidence for your claim? In AR4 WG1, Section 8 is to do with the construction and evaluation of climate models, in 8.1.1: "In climate change simulations, on the other hand, models are used to make projections of possible future changes over time scales of many decades and for which there are no precise past analogues. Confidence in a model can be gained through simulations of the historical record, or of palaeoclimate, but such opportunities are much more limited than are those available through weather prediction.

    Without getting into the semantics of projections vs predictions, we can see that Section 8 does not support a view that "they do not have predictive ability". We then have a whole section, Section 10, on "global climate projections".
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  13. Tom & Sky, Camburn has said many an outrageous thing in his time commenting here since September 2010. But he also has had time to be fully aware of the consequence for the egregious transgression he has just committed here.

    So let us await an answer, on the off-chance that all of us have missed something in the relevant text that Camburn can enlighten us on.

    But if no answer is given - or more obfuscation - then that will be sufficient for resolution to then follow.
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  14. #9 muoncounter-Thanks for the link to the online article, which, as you noted, does not refer to climate science- not sure why he included the quote from David Colander re clouds and climate science- in the print edition that I received today the paragraph I referred to left me with the impression that he accepted the assertion that climate models were leaving out a key variable. Maybe I just read too much, or too little, into it.
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  15. jimb#14: "the impression that he accepted the assertion that climate models were leaving out a key variable."

    There's a fairly extensive discussion of modeling on this thread.
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  16. Tom:
    I don't have time today, but within 48hrs I will pull the quote from WG1 Section 8 concerning the predictive power of the models.
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    Response:

    [DB] Please do not post any other comments in that 48 hour window until you have found the actual quote you referenced.  Or concede that you simply fabricated the quote.

  17. Camburn @16, I would have thought for such a strong, and surprising claim, the quote would have to be very familiar to you, and hence producible by you in just a few minutes. Afterall, it takes just a few minutes for me to quote the AR4 WG1 chapter 8 as saying:

    "There is considerable confidence that climate models provide credible quantitative estimates of future climate change, particularly at continental scales and above. This confidence comes from the foundation of the models in accepted physical principles and from their ability to reproduce observed features of current climate and past climate changes. Confidence in model estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). Over several decades of development, models have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases."

    (FAQ 8.1, my emphasis.)

    And:

    "The atmosphere-ocean coupled climate system shows various modes of variability that range widely from intra-seasonal to inter-decadal time scales. Successful simulation and prediction over a wide range of these phenomena increase confidence in the AOGCMs used for climate predictions of the future."

    8.4, my emphasis.)

    These, along with Skywatcher's quote (@12) from 8.1.1 directly contradict your assertion. Why then the delay in correcting your blatant falsehood.
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  18. Eschenbach questioned the predictive power of models using his model of the GISS-E model: http://wattsupwiththat.com/2011/05/14/life-is-like-a-black-box-of-chocolates/
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  19. Eric- From reading just that article, I wonder if Eschenbach ever built a computer simulation of anything....anything at all. I have....and if you tried to do what he did to climate models to my reactor model systems you'd get garbage out. In fact sometimes I wonder if that's what some clients of mine did, deciding that they could shortcut some work and not pay me. They blew up the plant.
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  20. Camburn:

    " I will pull the quote from WG1 Section 8 concerning the predictive power of the models."

    I think he meant to say "I'll quote mine WG1 ..."

    Camburn, if you don't supply a quote in full context I think people will be disappointed in you.
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  21. Eschenbach's result appears to match GISS-E and also validates CO2 warming as implemented by GISS-E (using HITRAN results). What it does not do (his major complaint) is model or "predict" natural variations.
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  22. Eric @21, if that is Eschenbach's concern (natural variability not predicted), then the game is given away on his method by Steve McIntyre of all people, who describes his "target" as "An ensemble of GISS Model E global temperatures is used as a target."

    The ensemble is of course the average (mean) of a large number of runs. Because natural climate variations, which do appear in the individual runs, do not all occur at the same time and strength, the cancel each other out in the ensemble mean. Consequently only known forcings will effect the ensemble mean, even though natural variability is modeled in any given model run.
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  23. Eric #18: "questioned the predictive power of models using his model of the GISS-E model:"

    Isn't that an inherent contradiction? 'I do not believe in models so I will use a model to show that.'
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  24. mouncounter, not contradictory since he purposely built a model with limitations that matched GISS-E; with the caveat as Tom points out that it matched the average of a large number of runs. The runs contain natural variation presumably with the same statistical properties as measured natural variation. The mean of all the runs is what I would call the prediction. Eschenbach showed that the prediction was simple. His inference that the model is therefore simplistic is disputed by Tom. Either way, an individual run is likely not a valid "prediction" of reality even with real world initial conditions (chaos gets in the way).
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  25. Your data base of peer reviewed papers appears to be highly incomplete. You show David Douglass having only one paper. When I search Web of Science for "Douglass D" only one climate paper comes up. But if I search for "Douglass DH" I get 17 climate papers.

    I'm not suggesting that these papers are correct. Many will recall the 2008 smackdown with Realclimate http://www.realclimate.org/index.php/archives/2008/10/tropical-tropopshere-iii/

    Another problem: when I click on a name in your database, nothing happens.
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  26. Eric#24: "The runs contain natural variation presumably with the same statistical properties as measured natural variation. The mean of all the runs is what I would call the prediction."

    Granted that each run has its natural variation, containing an element of pseudo-randomness. An ensemble of these models will average out this randomness and thus your 'prediction' - a mean - will appear simple. That's not a good way to see if models model natural variation -- by design.

    Tom C makes the same point.

    One must conclude that there is no basis in this experiment for saying that models are inaccurate predictors. By the nouveau logic we hear these days, that means they are accurate.
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  27. Eric-224 1) Isn't this off-topic for this thread?
    2- This is what Eschenbach says he is doing

    . In other words, we may be able to find a simple function that provides the same output as the black box.

    This isn't a model. It's mathturbation. There's no physics in it. You can't validate CO2 or anything with it. Suggests to me that you don't have a clue...precisely the naive target of a (-Snip-) such as Eschebach.
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    Response:

    [DB] While I can certainly sympathize with the thought process & the emotion, please substitute euphemisms such as "fake skeptic" or dissembler for the snipped text.

    In Eric's defense, he has previously demonstrated a capacity for understanding some of the many complexities of climate science, so let us please grant him the benefit of the doubt in this instance of perhaps not having put a lot of time into reading & comprehending his linked blog post.

  28. Eric:
    Let's look at the structure of Eschenbach's argument. It has the following form:
    Premise 1: The ensemble average response of climate models to forcings is linear. (Evidence: multiple pages of blog postings, graphs, and excel spreadsheets).
    Premise 2: Climate is non-linear. (Evidence: "Me, I find the idea ... a risible fantasy).
    Conclusion: Climate models are unrealistic.

    I think Eschenbach has unintentionally committed a rhetorical sleight-of-hand, by his preoccupation with his first premise. His mistake in his second is a variant of the confusion of weather and climate. Just because the internal variations of the system are chaotic and non-linear, doesn't mean that the response of the equilibrium state to external forcing must also be so.

    With a little more research, he could have saved himself all of the calculation. Climate scientists have know about this for years, and have written about it extensively. See Held's Simplicity of the forced response, the IPCC TAR which used a more sophisticated version of this approach for its centennial projections, and this recent paper.
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  29. Dave123, on your #1, yes it is off topic except for how to define what models "predict". On #2, I agree with the explanation by Kevin C that the complexities of a model can be simplified to a linear function as lots of model runs are averaged. The relevant point to this thread is that models predict the climate response to natural and manmade forcings when multiple runs of the model are averaged. They don't "predict" natural variations, but can demonstrate various possible natural variations from run to run.
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  30. Eric (skeptic) @29, your claimed "relevant point" is false.

    The multi-run mean is not the only prediction made by climate models. A second prediction is in fact the standard deviations of the variability between each individual run. That standard deviation predicts the variability from year to year due to natural variations in the climate system. Consequently, any prediction of future temperatures (for a given future forcing scenario) by a model is properly given as the multi-run mean plus the standard deviation of all runs.

    The reason models must give future predictions in this form is because some aspects of climate are chaotic. We cannot reasonably hope to predict this far in advance whether 2050 will be an El Nino year, or a La Nina. But we can predict a range of temperatures such that, if it is an El Nino the temperature will be at the top of that range, while if it is a La Nina it will be near the bottom.

    Clearly Eschenbach's method cuts the second part of the prediction out of the equation. Having excluded the model predicted natural variability from his discussion, he then complains that the models make no prediction about natural variability.
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  31. Quotes from Third Assessment:

    IPCC Chapter 14, 14.2.2.2, Working Group 1, The Scientific Basis

    Third Assessment Report: “In sum, a strategy must recognise what is possible. In climate research and modeling, we should recognize that we are dealing with a coupled nonlinear chaotic system, and therefore that long-term prediction of future climate states is not possible.”



    I will say that my memory was wrong in that I thought this quote was in AR4, it was AR3.

    AR4: 8 8.2

    Nevertheless, models still show significant errors. Although these are generally greater at smaller scales, important large-scale problems also remain. For example, deficiencies remain in the simulation of tropical precipitation, the El Niño- Southern Oscillation and the Madden-Julian Oscillation (an observed variation in tropical winds and rainfall with a time scale of 30 to 90 days). The ultimate source of most such errors is that many important small-scale processes cannot be represented explicitly in models, and so must be included in approximate form as they interact with larger-scale features. This is partly due to limitations in computing power, but also results from limitations in scientific understanding or in the availability of detailed observations of some physical processes. Significant uncertainties, in particular, are associated with the representation of clouds, and in the resulting cloud responses to climate change. Consequently, models continue to display a substantial range of global temperature change in response to specified greenhouse gas forcing (see Chapter 10).
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    Response:

    [DB] It has already been pointed out how thoroughly wrong you were.  Links were given documenting model uncertainties and model skill both.  Your continuance in this endeavor now falls to bluster and reflects poorly on you.

    Thank you for at least acknowleging your error.  However it is noted that you also not only fail to withdraw the statement but attempt to continue to prosecute what now clearly amounts to agenda: discrediting climate models by whatever means necessary.

    Therefore, please note that posting comments here at SkS is a privilege, not a right.  This privilege can and will be rescinded if the posting individual continues to treat adherence to the Comments Policy as optional, rather than the mandatory condition of participating in this online forum.

    Moderating this site is a tiresome chore, particularly when commentators repeatedly submit offensive, off-topic posts or intentionally misleading comments and graphics or simply make things up. We really appreciate people's cooperation in abiding by the Comments Policy, which is largely responsible for the quality of this site.
     
    Finally, please understand that moderation policies are not open for discussion.  If you find yourself incapable of abiding by these common set of rules that everyone else observes, then a change of venues is in the offing.

    Please take the time to review the policy and ensure future comments are in full compliance with it.  Thanks for your understanding and compliance in this matter, as no further warnings shall be given.

  32. 31, Camburn,

    Your summation of what AR four said:
    They do not have preditive ability.
    is no where near the same as what you found in AR three:
    ...that long-term prediction of future climate states is not possible.
    But more importantly, you have taken that statement grossly out of context.

    Specifically, the section is discussing the fact that computing needs as models become more intricate (i.e. finer and finer grid layouts with more detailed simulation of physical processes) were in danger of outstripping available computing power:
    These considerations must also recognise that the potential predictive capability will be unavoidably statistical, and hence it must be produced with statistically relevant information. This implies that a variety of integrations (and models) must be used to produce an ensemble of climate states. Climate states are defined in terms of averages and statistical quantities applying over a period typically of decades (see Chapter 7, Section 7.1.3 and Chapter 9, Section 9.2.2).
    This also reflects a basic aspect of climate modeling, which is that there are multiple future paths and no one is necessarily correct. The solution is to use ensembles... multiple runs which will produce an average prediction of climate change, with error bars.
    Ensemble integrations yield estimates of the variability of the response for a given model.
    Then comes your quote:
    In sum, a strategy must recognise what is possible. In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible.
    Which is followed by:
    The most we can expect to achieve is the prediction of the probability distribution of the system's future possible states by the generation of ensembles of model solutions. This reduces climate change to the discernment of significant differences in the statistics of such ensembles.
    Which, when coupled with your statement, shows that it doesn't at all say what you want people to infer that it means. This is a simple description of the fact that multiple iterations are needed to produce a range of predictions rather than one specific, perfect prediction.

    By way of analogy, imagine that I write a program that attempts to predict heads and tails in 1000 coin tosses. By your logic, I am unable to write such a program because I could never possibly, with any degree of certainty, predict the exact sequence of heads and tails that will actually come to pass. I can, however, run such a simulation multiple times and give good estimates, with ranges, of the likelihood of a certain number of heads and tails by the end of the run -- a prediction "defined in terms of averages and statistical quantities."

    You, sir, are quoting statements out of context and playing games with words. I would put forth that you have failed to prove your case, and are still required to openly and publicly retract your statement.
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  33. Interested readers can find the text of AR3 here, and look at the section presented by Camburn by following the links to section 14.2.2.2. Balancing the need for finer scales and the need for ensembles.
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  34. I have known Julia ever since she was at UNI. She is part of a cohort of rational people in our current Government that believe in rational science. The opposition has and is still scratching and biting like a wild animal. Their alternative plan is to pay for the CO2 pollution with taxpayers money! Sound familiar? Bert
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  35. Sorry the previous post was meant to go in the relevant blog. Bert
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  36. @ Bert. Well according to the brainiacs on the Opposition Benches, CO2 is not only colourless & odourless-its now apparently *weightless* as well ;-).
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  37. Camburn:

    "...that long-term prediction of future climate states is not possible."

    In simple terms, they can't predict the weather far out in the future.

    Predicting the weather is much like, as Sphaerica says, trying to predict the exact sequence of heads vs. tails in a 1000 coin toss sequence.

    This says nothing about being able to predict how many heads vs, tails we expect, with error bounds, if the coin is fair (or, for that matter, if it's not, if we can figure out how to model the unfairness).

    Climate vs. weather. Camburn vs. reality.
    0 0
  38. On the other hand, with no computational effort at all (but using a very simple mental model), I was able to successfully predict that camburn was going to quote mine ...
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  39. 1. I recommend that all read section 8 again.
    2. My impression of section 8 is that there is confidence in the output of the models concerning termperature because this is simple physics.
    3. The confidence of precip, soil moisture, clouds etc is not there because there is either not enough computation power, or it is not well enough understood to model at this time.
    4. WG1-3 is quit plain in what models can do. WG-4 shows that the models have improved but still lack certainty in large areas that affect climate.
    As far as multiple model runs and picking the middle as a result. Being the models do not do well with clouds, hydro, etc which do affect not only weather, but clmate as well, the outputs of the models should be in question. AS it is right now, it is a best guess. Kinda like flipping a coin.

    So as far as predictive power? In my opinion, given the variables at present with present understanding, I will stand by my statement.

    As far as the future of models? I would hope that within 5 to 10 years that the items addressed in section 8 will be better understood which will result in more certainty of the results.
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  40. 39, Camburn,

    You're making stuff up.

    Anyone who chooses to can go read it for themselves. Hopefully, they'll read it to understand it, rather than to try to find in it what they'd like to read.

    You have been demonstrated to have fabricated your position on what AR4 does and does not say about models. Your own opinion on this is of little value.

    As far as "within 5 to 10 years"... you do realize that the report was written, um, 5 years ago?
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  41. Camburn,

    Your impressions and opinions do not count for much, neither do mine for that matter. What counts are facts and observations.

    You distorted and misrepresented the IPCC's assessment reports because of your confirmation bias. That is not how science is done.

    Now, the favourite crutch of the "skeptics" are the models, well, we can also learn a heck of a lot about the climate system from paleo data, and they show that the system is quite sensitive with a climate sensitivity for equivalent forcing to doubling of CO2 resulting in a warming of >2 C. And we will easily double CO2 on our current path, perhaps even trebling or quadrupling it.

    Your claim that "AS it is right now, it is a best guess. Kinda like flipping a coin" is simply ludicrous. But I can understand that if that is your personal belief how you are having reconciling it with the science and our current understanding of the climate system.
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  42. Sphaerica:
    I am not making stuff up and I can only encourage everyone to read Section 8.

    As far as 5 to 10 years, I am talking from present.

    Let's move this discussion to a models thread if there is one.
    0 0
    Response:

    [DB] Take it to the Models are unreliable thread.

  43. Albatross:
    I agree, my opinion is my opinion. I use the outcomes of the models to try and make long term business decissions. In doing so, I evaluate what is credible and what is not, as presented in AR4 by looking at the shortcomings as well as the confidence levels.
    I do appologize for representing something my memory failed me on in quoteing AR3 rather than AR4. That was a mistake of credibility on my part.
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  44. Camburn#43: "a mistake of credibility on my part. "

    Isn't your bigger mistake the fact that you are basing your 'models are unreliable' case on this one section of some very long documents? Documents that contain, as both Sphaerica and Tom Curtis quoted, statements that models are indeed reliable? Some call that 'quote-mining;' others might call it 'cherrypicking.'

    BTW the models thread is 'Models are unreliable,' #6 on the thermometer at the upper left of every SkS page.
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    Response:

    [DB] Agreed.  Any further discussion of models, as Camburn has persisted in, is OT here and should be taken to the Models are unreliable thread.

  45. I've read the entire report a couple of times and some chapters more. How you can misconstrue section 8 like that is beyond me, but sure, I would definitely encourage any skeptic to read the entire IPCC.
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  46. Jim, have you seen the list of "peer reviewed" papers at

    http://www.populartechnology.net/2009/10/peer-reviewed-papers-supporting.html

    they claim 900+ peer reviewed papers dissenting on climate change. Looking down the list, some are published in such recognised climate journals as "Iron & Steel Technology" and "Missouri Medicine", some date back to the 1980s, and others are by the likes of Michaels and McKitrick, Pielke x2, etc. One or two are listed as simply "submitted", i.e. not yet peer reviewed at all. I'd be very interested in your take on these, and it might be a useful resource to add obscure papers to your database
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  47. G'day monkey, take a look at this evaluation and following links.
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  48. The following is an even better evaluation of Poptech's little list :

    Meet The Denominator


    More here and here.

    Basically, that list is worthless and only the most desperate would ever bring it up.
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  49. I don't like that 'denominator' argument. The denominator isn't actually the number of US science grads - it's the number of people who were asked to sign the Oregon petition who would have signed the opposite petition.
    0 0
  50. 46 monkeyorchid

    For an alternative take on 'Consensus' discussion in general, and popdreck's list in particular, may I recommend the new video from climate skeptic Barry Bickmore.. being a scientist who spent a lot of time feeling there was no consensus.
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