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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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How reliable are climate models?

What the science says...

Select a level... Basic Intermediate

Models successfully reproduce temperatures since 1900 globally, by land, in the air and the ocean.

Climate Myth...

Models are unreliable

"[Models] are full of fudge factors that are fitted to the existing climate, so the models more or less agree with the observed data. But there is no reason to believe that the same fudge factors would give the right behaviour in a world with different chemistry, for example in a world with increased CO2 in the atmosphere."  (Freeman Dyson)

At a glance

So, what are computer models? Computer modelling is the simulation and study of complex physical systems using mathematics and computer science. Models can be used to explore the effects of changes to any or all of the system components. Such techniques have a wide range of applications. For example, engineering makes a lot of use of computer models, from aircraft design to dam construction and everything in between. Many aspects of our modern lives depend, one way and another, on computer modelling. If you don't trust computer models but like flying, you might want to think about that.

Computer models can be as simple or as complicated as required. It depends on what part of a system you're looking at and its complexity. A simple model might consist of a few equations on a spreadsheet. Complex models, on the other hand, can run to millions of lines of code. Designing them involves intensive collaboration between multiple specialist scientists, mathematicians and top-end coders working as a team.

Modelling of the planet's climate system dates back to the late 1960s. Climate modelling involves incorporating all the equations that describe the interactions between all the components of our climate system. Climate modelling is especially maths-heavy, requiring phenomenal computer power to run vast numbers of equations at the same time.

Climate models are designed to estimate trends rather than events. For example, a fairly simple climate model can readily tell you it will be colder in winter. However, it can’t tell you what the temperature will be on a specific day – that’s weather forecasting. Weather forecast-models rarely extend to even a fortnight ahead. Big difference. Climate trends deal with things such as temperature or sea-level changes, over multiple decades. Trends are important because they eliminate or 'smooth out' single events that may be extreme but uncommon. In other words, trends tell you which way the system's heading.

All climate models must be tested to find out if they work before they are deployed. That can be done by using the past. We know what happened back then either because we made observations or since evidence is preserved in the geological record. If a model can correctly simulate trends from a starting point somewhere in the past through to the present day, it has passed that test. We can therefore expect it to simulate what might happen in the future. And that's exactly what has happened. From early on, climate models predicted future global warming. Multiple lines of hard physical evidence now confirm the prediction was correct.

Finally, all models, weather or climate, have uncertainties associated with them. This doesn't mean scientists don't know anything - far from it. If you work in science, uncertainty is an everyday word and is to be expected. Sources of uncertainty can be identified, isolated and worked upon. As a consequence, a model's performance improves. In this way, science is a self-correcting process over time. This is quite different from climate science denial, whose practitioners speak confidently and with certainty about something they do not work on day in and day out. They don't need to fully understand the topic, since spreading confusion and doubt is their task.

Climate models are not perfect. Nothing is. But they are phenomenally useful.

Please use this form to provide feedback about this new "At a glance" section. Read a more technical version below or dig deeper via the tabs above!

Further details

Climate models are mathematical representations of the interactions between the atmosphere, oceans, land surface, ice – and the sun. This is clearly a very complex task, so models are built to estimate trends rather than events. For example, a climate model can tell you it will be cold in winter, but it can’t tell you what the temperature will be on a specific day – that’s weather forecasting. Climate trends are weather, averaged out over time - usually 30 years. Trends are important because they eliminate - or "smooth out" - single events that may be extreme, but quite rare.

Climate models have to be tested to find out if they work. We can’t wait for 30 years to see if a model is any good or not; models are tested against the past, against what we know happened. If a model can correctly predict trends from a starting point somewhere in the past, we could expect it to predict with reasonable certainty what might happen in the future.

So all models are first tested in a process called Hindcasting. The models used to predict future global warming can accurately map past climate changes. If they get the past right, there is no reason to think their predictions would be wrong. Testing models against the existing instrumental record suggested CO2 must cause global warming, because the models could not simulate what had already happened unless the extra CO2 was added to the model. All other known forcings are adequate in explaining temperature variations prior to the rise in temperature over the last thirty years, while none of them are capable of explaining the rise in the past thirty years.  CO2 does explain that rise, and explains it completely without any need for additional, as yet unknown forcings.

Where models have been running for sufficient time, they have also been shown to make accurate predictions. For example, the eruption of Mt. Pinatubo allowed modellers to test the accuracy of models by feeding in the data about the eruption. The models successfully predicted the climatic response after the eruption. Models also correctly predicted other effects subsequently confirmed by observation, including greater warming in the Arctic and over land, greater warming at night, and stratospheric cooling.

The climate models, far from being melodramatic, may be conservative in the predictions they produce. Sea level rise is a good example (fig. 1).

Fig. 1: Observed sea level rise since 1970 from tide gauge data (red) and satellite measurements (blue) compared to model projections for 1990-2010 from the IPCC Third Assessment Report (grey band).  (Source: The Copenhagen Diagnosis, 2009)

Here, the models have understated the problem. In reality, observed sea level is tracking at the upper range of the model projections. There are other examples of models being too conservative, rather than alarmist as some portray them. All models have limits - uncertainties - for they are modelling complex systems. However, all models improve over time, and with increasing sources of real-world information such as satellites, the output of climate models can be constantly refined to increase their power and usefulness.

Climate models have already predicted many of the phenomena for which we now have empirical evidence. A 2019 study led by Zeke Hausfather (Hausfather et al. 2019) evaluated 17 global surface temperature projections from climate models in studies published between 1970 and 2007.  The authors found "14 out of the 17 model projections indistinguishable from what actually occurred."

Talking of empirical evidence, you may be surprised to know that huge fossil fuels corporation Exxon's own scientists knew all about climate change, all along. A recent study of their own modelling (Supran et al. 2023 - open access) found it to be just as skillful as that developed within academia (fig. 2). We had a blog-post about this important study around the time of its publication. However, the way the corporate world's PR machine subsequently handled this information left a great deal to be desired, to put it mildly. The paper's damning final paragraph is worthy of part-quotation:

"Here, it has enabled us to conclude with precision that, decades ago, ExxonMobil understood as much about climate change as did academic and government scientists. Our analysis shows that, in private and academic circles since the late 1970s and early 1980s, ExxonMobil scientists:

(i) accurately projected and skillfully modelled global warming due to fossil fuel burning;

(ii) correctly dismissed the possibility of a coming ice age;

(iii) accurately predicted when human-caused global warming would first be detected;

(iv) reasonably estimated how much CO2 would lead to dangerous warming.

Yet, whereas academic and government scientists worked to communicate what they knew to the public, ExxonMobil worked to deny it."

Exxon climate graphics from Supran et al 2023

Fig. 2: Historically observed temperature change (red) and atmospheric carbon dioxide concentration (blue) over time, compared against global warming projections reported by ExxonMobil scientists. (A) “Proprietary” 1982 Exxon-modeled projections. (B) Summary of projections in seven internal company memos and five peer-reviewed publications between 1977 and 2003 (gray lines). (C) A 1977 internally reported graph of the global warming “effect of CO2 on an interglacial scale.” (A) and (B) display averaged historical temperature observations, whereas the historical temperature record in (C) is a smoothed Earth system model simulation of the last 150,000 years. From Supran et al. 2023.

 Updated 30th May 2024 to include Supran et al extract.

Various global temperature projections by mainstream climate scientists and models, and by climate contrarians, compared to observations by NASA GISS. Created by Dana Nuccitelli.

Last updated on 30 May 2024 by John Mason. View Archives

Printable Version  |  Offline PDF Version  |  Link to this page

Argument Feedback

Please use this form to let us know about suggested updates to this rebuttal.

Further reading

Carbon Brief on Models

In January 2018, CarbonBrief published a series about climate models which includes the following articles:

Q&A: How do climate models work?
This indepth article explains in detail how scientists use computers to understand our changing climate.

Timeline: The history of climate modelling
Scroll through 50 key moments in the development of climate models over the last almost 100 years.

In-depth: Scientists discuss how to improve climate models
Carbon Brief asked a range of climate scientists what they think the main priorities are for improving climate models over the coming decade.

Guest post: Why clouds hold the key to better climate models
The never-ending and continuous changing nature of clouds has given rise to beautiful poetry, hours of cloud-spotting fun and decades of challenges to climate modellers as Prof Ellie Highwood explains in this article.

Explainer: What climate models tell us about future rainfall
Much of the public discussion around climate change has focused on how much the Earth will warm over the coming century. But climate change is not limited just to temperature; how precipitation – both rain and snow – changes will also have an impact on the global population.


On 21 January 2012, 'the skeptic argument' was revised to correct for some small formatting errors.

Denial101x videos

Here are related lecture-videos from Denial101x - Making Sense of Climate Science Denial

Additional video from the MOOC

Dana Nuccitelli: Principles that models are built on.

Myth Deconstruction

Related resource: Myth Deconstruction as animated GIF

MD Model

Please check the related blog post for background information about this graphics resource.

Fact brief

Click the thumbnail for the concise fact brief version created in collaboration with Gigafact:

fact brief


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Comments 1276 to 1291 out of 1291:

  1. gzzm2013:

    2. Numerous groups of researchers all over the world create and run climate models, which intentionally differ from each other to provide consilience in the evidence. Scroll down in this page in the RealClimate site for a list of links to just a few of the model's web sites, where you will find the information you asked for. The most prominent, though certainly not only, organized effort to create and compare multiple models is CMIP--Coupled Model Intercomparison Project. The most recently completed version of that multimodel project is CMIP5. CMIP6 is in progress. There is a summary of the degree of independence of the most prominent models, in this RealClimate post. More fundamentally, you need to learn better what "model" means in this context; Steve Easterbrook's post is a good summary. Getting at the root of your questions, watch Steve's TEDx talk.

  2. gzzm2013:

    3. I'm not going to waste my time answering these questions, when you have not bothered to read the post on which you are commenting. I suspect your questions are merely rhetorical--actually, that's dignifying them too much. I suspect you are just drive-by ranting. Please do prove me wrong, by posting more specific questions that reveal you have done at least basic reading already.

  3. RealClimate has posted its 2021 comparison of models to observations.

  4. Recommended supplemental reading:

    If scientists can create a new way to predict climate change – making it as accurate as, say, forecasting the weather – it would help people make everyday decisions: how high to build a sea wall or what crops to plant.

    Meet the team shaking up climate models by Doug Struck, Environment, The Christian Science Monitor, Jan 22, 2021

    Note: This is a very well-researched and well-written indepth article.  

  5. Eclectic:

    In his Politics, Aristotle believed man was a "political animal" because he is a social creature with the power of speech and moral reasoning: Hence it is evident that the state is a creation of nature, and that man is by nature a political animal.

    To think that the IPCC is not political is naive at best.  The United Nations Security council is formed by the victors of WW2, nations that have been colonial empires and empires.  They are great exporters of weapons and they have financed the United Nations.  

    You cannot analyze the science of climate change without questioning its funding, motives, mechanisms, governance and who is not sitting at the table, and who is not represented. 


    [DB] Off-topic snipped.

  6. Dayton

    1. So you are saying that because those models are to be run on expensive computers they cannot be accessed by the general public.  Why can't the public enter the input to the model, send it to the operators, then get the output of the model?  Is the public not paying for the models?   Every model has inputs and outputs.  Its that simple.  Can you list what are the input parameters of the best model?  And what are its output parameters?   Are the models too busy with experts entering inputs on them all the time that there is no time for the public to use what they paid for?   Can things not be explained in plain English?  Someone very smart said that if you can't explain it to a 6 year old you don't understand it yourself.   

  7. Dayton

    2 and 3. So let's put it this simply, let us draw an analogy.  Many so called sciences like economics claim that they have economic "models" , which model complex systems, but the fact remains that the economics science is not able to predict the next global financial crisis in magnitude or timing or nature.   


    Yet people are claiming that the climatic models are reliable and can actually predict future climate (but long term trends only).   I would like to hear from the best model, you chose it, name it, locate it, say who programmed it, who maintains it, who financed it (the onus is on the claimant, not me) and say what is the sea level (however they define it) in year 2025, 2030, 2035, 2040, and so on until year 5000.  Also change in global temperature (however they define it, give the formal unchanging definition).   We of course don't know what the sun is going to do, or volcanoes.   So the prediction is contigent of factors that are unforeseable, so the predictions are a function of different combinations and series and progressions of multivariable values.   I want to see the data.  Should not be hard for a proven theory, right? 

      4.  New topic.  Where is the proof that CO2 is driving the climate and not a third exogenous variable, like solar energy.   Please post the evidence that proofs undeniably this supposed fact.  Remember that correlation does not mean causation. 


    [TD] Regarding your new question #4, see the post “CO2 is main driver of climate.” Post any comments on that topic, in the thread off of that post. Your comments about that topic are off topic in this thread, and further off topic comments will be deleted.

  8. gzzm2013: Your two responses to me show that you have not bothered to read any of the material I linked for you. That behavior of refusing to engage in actual back and forth conversation is called "sloganeering" and is prohibited by the policies of this site, which you need to read. 

  9. Dayton

    Your argument is a red herring to distract from the fact that you won't answer my questions.  The material you offer does not address directly the questions.  The onus is on the claimant to produce the evidence.  I don't have to produce anything. I am simply questioning the claims. 


    [BL] "Just asking questions" as a rhetorical ploy does not cut it here. You must be willing to learn - and willing to put an effort into learning.

    There is an immense amount of reference material discussed here and it can be a bit difficult at first to find an answer to your questions.  That's why we recommend that Newcomers, Start Here and then learn The Big Picture.

    I also recommend watching this video on why CO2 is the biggest climate control knob in Earth's history.

    Further general questions can usually be be answered by first using the Search function in the upper left of every Skeptical Science page to see if there is already a post on it (odds are, there is).  If you still have questions, use the Search function located in the upper left of every page here at Skeptical Science and post your question on the most pertinent thread.

    All pages are live at SkS; many may be currently inactive, however.  Posting a question or comment on any will not be missed as regulars here follow the Recent Comments threads, which allows them to see every new comment that gets posted here.

    Comments primarily dealing with ideologies are frowned upon here.  SkS is on online climate science Forum in which participants can freely discuss the science of climate change and the myths promulgated by those seeking to dissemble.  All science is presented in context with links to primary sources so that the active, engaging mind can review any claims made.

    Remember to frame your questions in compliance with the Comments Policy and lastly, to use the Preview function below the comment box to ensure that any html tags you're using work properly.

  10. Gzzm @1282 ,

    thank you for replying to Tom Dayton, who, I gather, was inclined to bet that you yourself were simply one of those "timid-but-angry" commenters who make a drive-by comment . . . and are never seen again here, owing to their strange psychological make-up.

    Gzzm, clearly you are made of sterner stuff and wish to add some rational intelligent points to the online discourse.  And it's never too late to begin in earnest !

    In reply to your point /4.   [in brief because off-topic]  :-

         4.  Where is the proof ... CO2  ... variable like solar energy ...

    Alas, Gzzm, this is "off-topic" here at this thread.  You will find the evidence you ask for, at the Top Left of this page, via  MOST USED Climate Myths number 2  "it's the sun"  . . . or the other thread recommended by the Moderator.    Indeed, your education would be greatly enhanced by you reading through at least the first half-dozen Myths in their Original Post form [basic thru advanced ] .   And as has already been suggested, please read the OP of this thread here (which you appear to have omitted from your things-to-do-first  list.)

    Back on topic, Gzzm, with the models are unreliable  ~ I can recommend some later reading for you, for the counter-arguments which can be found on the WattsUpWithThat  blogsite.   At WUWT  the view is that all the scientists' models have subsequently proven to be completely wrong . . . and therefore all climate science is wrong.

    Gzzm, you may not have heard of WUWT  , or perhaps you have been warned to avoid it because of its strong tendency to promote half-baked science (or disproven science) and even more to repeatedly  promote rubbish which is "Not Even Wrong".   But fear not, Gzzm ~ among the pig-swill there, you may occasionally find a pearl or two from genuine scientists like Nick Stokes.   Alas, Stokes does not appear there often . . . likewise there are a few other scientific minds to be found in the WUWT  comments columns, but few and rare, because they generally get driven out of WUWT  by the editors/censors.  (Or perhaps these scientific minds get tired of the incessant torrents of mindless vitriol they receive at WUWT  .)

    Nevertheless, Gzzm, the WUWT  blogsite is a fascinating exhibition of logical fallacies and intellectual insanity.  An excellent guide to What Not To Do  with one's brain.   Most interesting of all, is the huge amount of anger  there, underlying the flakey thinking and political extremism and lack of human compassion.

    Gzzm, I have the strong impression that you yourself may be able to enlighten me about the deepest psychiatric basis of the sheer anger in these disparate "contrarian" minds.  Some of it may be a genetic personality-type anger in all or most of the denialists, but there may well be one or more other factors.   Your own insight would be welcome !  (But please reply on a more appropriate thread.)


    [BL] Please leave moderation to the moderators.

    Discussing the character of people's behaviour at other blog sites is not helping this discussion.


  11. Eclectic

    Your reply at "Eclectic at 16:08 PM on 24 January 2021"

    Constitutes a series of ad-hominem attack fallacies... no substance.

    Waiting to hear direct responses to the questions I have raised from others as I am not going to bite on these attacks. 


    [BL] You are continuing to refuse to engage in honest discussion.

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

    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.

  12. [deleted]


    [BL] Moderation complaints deleted.

    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 or off-topic posts. 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.

  13. Any model that requires calibration is wrong; there are an infinite number of models for a system with more than 6 or 7 in interdependant variables can be backtested with 100% coorelation yet differ in future predictions.   So, all the models show is the bias of the modeler.  It's non-sense to claim any model of the climate is accurate.    Basically, the model must work without any calibration or the results simply reflect the bias of the modeler.   Humanity may have increased the amount of CO2 in the atmoshere; but, humanity has simply no idea what the impact will be.


    [BL] Link activated.

    The web software here does not automatically create links. You can do this when posting a comment by selecting the "insert" tab, selecting the text you want to use for the link, and clicking on the icon that looks like a chain link. Add the URL in the dialog box.

  14. robnyc987:

    You have made several empty assertions without evidence.

    All models require some level examination between model outputs and observations, and all models undergo modification to improve their ability to match observations. That is good science.

    You will need to provide some sort of definition for what you call "calibration" before anyone will take your criticism seriously.

    Where do you get "6 or 7" from, and what is the basis for your claim that 6 or 7 variables is enough for "100% correlation"? It sounds like you think all models are purely statistical fits to data. If this is what you think, you are wrong. If you think that hind-casting models can be 100% accurate with only a few variables, you are wrong.

    Your assertions of nonsense, working without calbration, bias and "no idea" are all just rhetorical waffling.

    Of what relevance is a link to economic models  to a discussion about climate models? The link refers to one case of a geophysical oil field model. Over-fitting a model - even one that is physically-based - is poor science, but that does not mean that every model is over-fitted and suffers the same problems. You will need to come up with an example of a climate model that is over-fitted if you want to be taken seriously.

    If you do not understand the difference between statistical models and physically-based models, then you are woefully uninformed.

    By the way, we know all models are "wrong" in that they are incomplete - but they can be useful.

    You may have no idea, but the science of climatology does. Try reading and learning. Start with the blog post you are supposedly commenting on. If you continue to comment, I suggest that you actually respond to specifics in the blog post at hand. Comments need to be on topic, not just meaningless rants.

  15. Bob Loblaw @1289,

    The paper that fuelled the 2011 Scientific American item linked @1288 is presumably Carter et al (2005) 'Our calibrated model has poor predictive value: An example from the petroleum industry' [ABSTRACT] which may provide the argument for "6 or 7 in interdependant variables" preventing model calibration although likely this is no more than a different version of the famous Fermi quote:-

    “I remember my friend Johnny von Neumann used to say, with four parameters I can fit an elephant, and with five I can make him wiggle his trunk.”

    However, this Fermi quote concerns "arbitrary parameters" and what Carter had in mind when he says "As far as I can tell, you'd have exactly the same situation with any model that has to be calibrated," isn't defined. But this 2011 Scientific American quote of Carter (I don't see an earlier statement of it) has occasionally been used by denialists to suggest the same calibration situation affects climate models. Of course GCMs do have a big challenge with calibration but I don't think it is down to the number of independent variables. There are many physical measures that can be used to callibrate the processes within GCMs, which is probably why they can (collectively) demonstrate useful predictive qualities. (The graphic is from this 2021 RealClimate post.)

    RealClimate GCM performance 2020

  16. MAR:

    This all hinges on what is meant by "calibration", and whether or not the parameters in a model are arbitrary.

    Wiktionary defines "calibrate" as "To check or adjust by comparison with a standard." When discussing climate models, this implies that there is some adjustable parameter (or seven) or input that can be varied at will to create a desired output.

    There are many problems with this argument [that climate models are "calibrated" to create a result]:

    • What are we calibrating for? A global 3-d climate model has thousands (if not millions) of outputs. Global mean surface temperature is one simple statistical summary of model output, but the model has temperatures that vary spatially (in 3-d) and temporally. It also has precipitation, humidity, wind speed, pressure, cloud cover, surface evaporation rates, etc. There are seasonal patterns, and patterns over longer periods of time such as El Nino. All of these are inter-related, and they cannot be "calibrated" independently. Analyzing the output of a GCM is as complex as analyzing weather observations to determine climate.
    • How many input parameters are devoid of physical meaning and can be changed arbitrariiy? The more physcially-based the model is, the fewer arbitrary parameters there are. You can't simply decide that fresh snow will have an albedo of 0.4, or open water will evaporate at 30% of the potential evapotranspiration rate, just because it makes one output look better. So much of the input information is highly constrained by the need to use realistic values. All these have uncertainties, and part of the modelling process is to look at the effect of those uncertainties, but the value to use can be determined independently through measurement. It is not a case of choosing whatever you want.

    So, robnyc987's claim that you can achieve 100% accuracy by "calibrating" a small set of parameters is bunkum. If climate models are so easy to "calibrate", then why do they show variations depending on who's model it is? Or depending on what the initial conditions are? That variability amongst models and model runs indicates uncertainty in the parameters, physics, and independent measurements of input variables - not "calibration".

    Perhaps robnyc987 will return to provide more explanation of his claim, but I somehow doubt it.

  17. Back to basics, concerning Christy's popular graph:

    He states that the data is of the bulk atmosphere.

    Are 102 model runs also for the bulk atmosphere, or are they for the surface?

  18. sailingfree @1292,

    The GCM models cover the entire climate system so it is up to the analyst creating a graph what part of the modelled climate system he takes data from for his comparison.

    The problem with Christy is that he is rather too enthusiastic about demonstrating his denialism and so makes a very poor job of his comparisons.

    RealClimate provide comparisons of model output with temperature data including global & tropical TMT data and have also provided a critique of Christy's efforts.

  19. MA,Thanks.

    I'll look at RealClimate.   So did Christy use model predictions for the "bulk atmosphere?

  20. sailingfree:

    To add to what MA Rodger said about climate models, analyzing the output from a three-dimensional general circulation model is about as complex as analyzing climate observations - maybe even more so.

    Think about the number of locations world-wide where we have measurements of surface temperature, humidity, wind speed, precipitation, radiation, etc. Then add in upper air, oceanic, ground temperature opservations, etc.

    Then think about how sparse some of those observations are - how much of the globe is not well-measured.

    Then think about things that are not routinely measured - vertical motions, cloud water content, spectral (wavelength-dependent) radiation. The list goes on.

    ...and then realize that a 3-d climate model is calculating all those things on an ongoing basis (minute by minute, hour by hour), at a 3-d set of points covering the entire globe.

    Comparing the model to observations can be done where the two types of data match, and commonly involves some sort of statistical summary (of both the model output and the real-world measurements).

    I don't know what Christy means by "bulk atmosphere". My guess would be that he is averaging over the entire vertical profile, but I consider Christy to be such an unrelaible source that I don't want to spend valuable time trying to figure out what he means.

  21. sailingfree @1294,

    You ask "Did Christy use model predictions for the bulk atmosphere?"

    He says he does.

    It is not easy to be sure what Christy "uses" as he is not a reliable researcher. In specific cases it would/should be possible to see what he says he is "using" and then compare the numbers he "used" with what he says. But this is not always a trivial task and Christy's public statements are not considered of the slightest scientific importance by those best positioned for this task. So they mainly ignore them. But note the issue of modelled tropical tropospheric temperatures (which is real) is being addressed with, for example Vergados et al (2021) or Po-Chedley et al (2021).

    You mention @1292 the "102 model runs", so a specific case of data use (although Christy happily reuses his grand finding oblivious to any errors it contains). The prime-time appearance of "102 model runs" was presumably Christy's testimony to the U.S. House Committee on Science, Space & Technology 2 Feb 2016 and in this case Christy's use of data has been questioned more than once but this is technical enough for even climatologists to trip over this task (as the correction within yet another RealClimate posting illustrates). What is perhaps most telling in this situation is the silence of John H Christy who thus acts more like a troll than a proper scientist who would be expected to defend his position by resolving any doubt on the matter.

    Christy's misleading graphs

    So on these graphics we see John Christy saying he uses "Global Bulk Atmospheric Temperature, Surface to 50,000ft" and also 'Global' and 'Tropical' "TMT Temperature Variations"  (which actually go a bit higher than 50,000ft). The TMT satellite data is a statistical sample of emissions from a great swathe of altitudes, even up into the stratosphere where it is cooling due to AGW.

    MSU weighting functions The RSS browser tool with the correct choice of 'Channel' and 'Region' shows a TMT Tropical trend of +0.145ºC/decade. This compares with the UAH TMT Tropical trend of +0.09ºC/decade. Christy's assessment of model data puts the comparable model trend at +0.214ºC/decade although the model assessment presented by the RealClimate critique linked above gives a model trend of +0.19ºC/decade.

    This +0.214ºC/+0.19ºC isn't a massive difference but this and the visual trickery employed by Christy has resulted in a film (actually a 7 minute YouTube video).

    Christy latest wheeze is to brandish yet another fun-with-figures graphic (below) which compares TMT data (measured from surface up to 70,000ft with differing strength) with a small layer of the modelled atmosphere (roughly from 30,000ft to 40,000 ft). Presumably this is because the denialists require redder meat with the passing years.

    Chrisiy's latest nonsense.

  22. To follow-up again on MA Rodger's excellent description, two things to note:

    1. Satellite data are not a measurement of atmospheric temperature. Satellites measure radiation. To transform the radiation data into an estimate of temperature requires some sort of model. A detailed atmospheric radiation transfer model. To call the results "observations" is playing loose with the term, although it is a common use of the term.
    2. In the last diagram that MA Rodger provides, note the expression "the models and observations are not from the same physical system". As MAR notes, the results from the climate models are an average of the entire atmosphere from the surface to 70,000 feet (>20km). The "observations" (Christy's model conversion of the satellite data) cover the pressure range from 300 to 200 hPa, which is roughly from 30-40,000 feet (9km to 12 km). That the two are "not from the same physcial system" is known prior to doing any statistical analysis.

    Christy's "analysis" takes two things that are known to be different, and tries to make it look like the difference disproves some aspect of climate theory.

  23. Oldengine is a retired engineer, not a scientist.  I love watching scientists argue over how many angels can dance on the head of a pin.  But this has become tiresome and dangerous.  The accuracy of the measurement of CO2 in the atmosphere is "good enough" to take action now.  My ASHRAE handbook from 1977 shows the CO2 content of "average air" was less than 300 ppm.  Now it's over 400 ppm (+/- whatever).

    Don't you all see what you are doing.  We (The big "we", as in all humanity) are driving towards a stone wall at more than sixty miles an hour and we are not taking our foot off of the accelerator.  It doesn't matter if the speedometer is calibrated in MPH or furlongs per fortnight.  It doesn't matter if we are actually going 58 mph or 62 mph.  We have to step on the brake now.  Paralysis by analysis will result in the end of life as we know it.

    FYI - I think we should be building 500 thorium salt fueled nuclear reactors (50 to 100 MW each) right now and ordering another 500 tomorrow.


  24. Oldengine,

    I very much understand how you feel. I used to teach the weather and weather data sessions in the groundschool part of a pilot training program. Back then, CO2 content was still around 300ppm. The fact that it increased to 400 is a geological scale event that happened in a geological blink of an eye. There is no natural explanation for this whatsoever. 

    The reason why this thread is so long and convoluted is the never-ending insistence of some to protect the power of certain industries. In that effort, they deploy an infinity of vacuous arguments, all of which have to be dismissed meticulously by the reality based crowd. Meanwhile, they have no problem remaining free of the very strict standards they demand of others, with arguments ranging from grotesque as shown by basic physics, to downright mendacious. They seldom, if ever, argue in good faith.

    I actually trend to agree on many of your points. I hope the reactor being built in Wyoming will pan out and show itself as a viable tool. The efforts toward fusion energy should increased tenfold. Coal burning on an industrial scale should be phased out as quickly as possible. Terrestrial transportation should be electrified to the best extent possible. All possible avenues to minimize emissions in agriculture practices should be explored and implemented. Buildings should undergo retrofitting work, new ones should have appropriate certification standards. Fossil fuels use should be reserved to situations where alternatives are not possible or practical, like aviation, which presents unique challenges in terms of weight and energy density, but where efforts to find ways for the future have increased significantly in the past 15 years.

  25. Out today ~ date 19 March 2022 ~ a new YouTube video

    by science journalist PotHoler54

    Describing multiple errors with Dr Roy Spencer's [Christy and Spencer] UAH satellite system's tropospheric temperature measurements, errors made over several decades.

    In short : Spencer's predictions wrong, and model predictions right.

    Not exactly news ~ except I myself had not realised how greatly Spencer's fundamentalist religious beliefs had given a severe bias to his thinking.

    (Moderator ~ I'm not sure if there is a better thread for this post.)

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