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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 1301 to 1311 out of 1311:

  1. @Eclectic #1300

    The argument answering the question "Which is a more reliable measure of global temperature: thermometers or satellites?" is a better fit for Peter Hadfield's latest video. Which is why I added it as a "further viewing" note at the bottom just now.

  2. Although it does not have a place for comments or responses, readers of this discussion who are curious about Roy Spencer's work may also wish to read the information on this page:

    As usual, Desmog also tracks him:

  3. Bob Loblaw @1302  -  thank you.  It is a while since I looked at the background info on Dr Roy Spencer.  The SkS  info on him is from 2012, and the Desmog info goes up to 2017.   ( I do see Spencer's UAH  monthly chart always gets featured on the WUWT  blogsite, and draws many comments of a vacuous sort.  Other global temperature charts get little mention there . . . and oceanic warming is almost tabu. )

    Spencer has to keep backstepping from his original position of total AGW denial (including the "minimal warming" assertion).   And he has stepped even further back since 2017, and is now admitting (quietly) that it is possible the majority of modern warming comes from manmade GH gasses.

    No such admission from that other celebrated contrarian climatologist Dr Judith Curry.   On her blog [ClimateEtc] her latest article, posted 17 March, titled:  "A 'Plan B' for addressing climate change"  . . . is classic Curry vagueness.  The reader risks almost drowning in discursive verbiage ~ which in essence kind of boils down to:  We should be doing nothing to counteract Global Warming because it is all too difficult (and too mild) and should probably be given a priority way, way below all the other problems that we face in this world.      (And of course we cannot tackle more than one problem at a time.)

  4. BaerbelW @1301  -  thank you for adding the latest Potholer54 video to the bottom of the article "Which is a more reliable measure"  [linked @1301].    Potholer54's video is 20 minutes long, and (unusually for him) contains only a few humorous remarks.

    But I think it is a neat summary of of Dr Spencer's ongoing error-making in measuring AGW's increase  ~ and shows how Spencer has gradually changed from a scientific black sheep, into merely a dark gray sheep.

    Potholer54 puts Spencer's history into perspective ~ and I find the PH54 videos a very useful source for arguments against denialists.  And always useful to be able to quote Spencer's own evidence against  denialists !

    Noteworthy :-  Potholer54's new video has scored 22,000 views in its first 24 hours.

  5. Regarding models, the explanation is good, especially about whether or not a model is good or not.

    My observation: Are these the same models that for the last 40 years (Since I was in high school.) that predicted global warming before it predicted global cooling before blaming any and all weather on climate change driven by man's activity?

    Are these the same models that for the last 40 years have predicted global coastal flooding, sinking island, the extinction of polar bear, penguins and increasing deserts and that man has only 8-12 years to survive?

    I make these observations to prove that is seems there are NOT any good models, based on a proven, accurate track record, that can be called "good".


    [PS] You appear to be engaging in strawman arguments - ie making claims about what science has said that are not true. You can find details of how well past predictions have done in "Lessons from Past Predictions" series. Broecker's 1975 model holding up pretty well.  See here for the "Scientists predicted cooling" myth.  If you dispute this, then please provide 1/ a link the scientific prediction you think was mistaken, and 2/ link to evidence that it is wrong.

  6. MichaeISF @1305 , you sound a bit confused.

    Climate models (for estimating future climate changes) base their predictions on the observed (and projected) rise in CO2 levels.

    The CO2 level has continued to rise (observed fact).  The world is warming (observed fact).   Consequently, sea level is rising (observed fact) ~ so some increased flooding of coasts is occurring, and will get worse as a matter of course.   (Unless you think the higher sea level is due to more polar bears staying in the water.)

    Have you any evidence that "cancels" the facts?

  7. MichaelSF:

    The direct answer to your question would have to be "I don't know", because most of the "predictions" that you claim have been made by "climate models" bear very little resemblance to the predicitons from climate models in the scientific literature.

    If you want us to believe that such "predictions" actually exist, you are going to have to provide scientific references where the "climate models" are described and the "predictions" made.

    Once you actually provide some sort of detail, it may be possible to answer your question. Until then, you're just engaging in rhetoric (meaning #2)

  8. If climate models are accurate then why are they constantly being updated or improved?   Assuming there's even a logical answer to that question, how are scientiests certain that the "improved" versions of the models are actually improved?   None of the climate catastrophes predicted during the past 50 years ago have come to pass (see "False Alarm: How Climate Change Panic Costs Us Trillions, Hurts the Poor, and Fails to Fix the Planet" by Bjorn Lomborg) so why is the scientific community convinced it is correct now given it's history of failing to make accutrate climate predictions?  

  9. JohnCalvinNYU:

    I"m really not sure just what definition of "accurate" you are using. If you are expecting it to be "perfect", then prepare to be disappointed. Science (and life in general) does not produce perfect results. Any scientific prediction, projection, estimate, etc. comes with some sort of range for the expected results - either implicitly, or explicitly.

    You will often see this expressed as an indication of the "level of confidence" in a result. (This applies to any analysis, not just models.) In the most recent IPCC Summary for Policymakers, the state that they use the following terms (footnote 4, page 4):

    Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high, and typeset in italics, for example, medium confidence. The following terms have been used to indicate the assessed likelihood of an outcome or result: virtually certain 99–100% probability; very likely 90–100%; likely 66–100%; about as likely as not 33–66%; unlikely 0–33%; very unlikely 0–10%; and exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%; more likely than not >50–100%; and extremely unlikely 0–5%) are also used when appropriate. Assessed likelihood is typeset in italics, for example, very likely. This is consistent with AR5. In this Report, unless stated otherwise, square brackets [x to y] are used to provide the assessed very likely range, or 90% interval.

    So, the logical answer to your question of why models are constantly being updated or improved is so that we can increase the accuracy of the models and increase our confidence in the results. Since nothing is perfect, there is always room for improvement - even if the current accuracy is good enough for a specific practical purpose.

    Models also have a huge number of different outputs - temperature, precipitation, winds, pressure - basically if it is measured as "weather" then you can analysis the model output in the same way that you can analyze weather. A model can be very accurate for some outputs, and less accurate for others. It can be very accurate for some regions, and less accurate for others. It can be very accurate for some periods of geological time, and less accurate for others. The things it is accurate for can be used to guide policy, while the things we have less confidence in we may want to hedge our bets on.

    Saying "none of the climate catastrophes predicted in the last 50 years" is such a vague claim. If you want to be at all convincing in your claim, you are going to have to actually provide specific examples of what predictions you are talking about, and provide links to accurate analyses that show these predictions to be in error. Climate models have long track records of accurate predictions.

    Here at SkS, you can use the search box (upper left" to search for "lessons from past climate predictions" and find quite a few posts here that look at a variety of specific predictions. (Spoiler alert: you'll find a few posts in there that show some pretty inaccurate predictions from some of the key "contrarians" you might be a fan of.)

    As for Lomborg: very little he says is accurate. Or if it is accurate, it omits other important variables to such an extent that his conclusions are inaccurate. I have no idea where I would find the article of his that you mention, and no desire to spend time trying to find it. If that is your source of your "none of the climate catastrophes" claim, then I repeat: you need to provide specific examples and something better than a link to a Lomborg opinion piece.

    There have been reviews, etc. posted here of previous efforts by Lomborg, such as:

    ...and Lomborg has a page over at DesmogBlog.

    In short, you're going to have to do a lot better if you expect to make a convincing argument.

  10. Lomborg today sounds more like Fox News & Tucker Carlson.

    That's a slight exaggeration, JohnCalvinNYU  ~ but Lomborg's ideas seem to be wandering further away from common sense . . . almost like he's getting all his information from the Murdoch media empire.

    John, please widen your education.  Avoid Fox and suchlike propagandists.

  11. I frequently point freinds to this excellent site, and hope you can make a minor change for the sake of readers' convenience. That would be to add a "last page" or "latest comment" button to the bottom of the comments pages.

    I am motivated, so I am willing to scroll through the whole article, scroll through the comments to the page bottom, and click on the last listed page. But repeating that four more times to get to comment 1310 on page 53 is getting tiresome.

    An alternative is to sort the list of comments from latest to oldest.

    Thank you for considering this change.


    [PS] Thanks for the suggestion. I have passed it on to the technical team. 

    [BL] That partially relates to a bug discovered previously, where the "what page is this on?" link in Recent Comments assumes 50 comments per page, but blog posts such as "CO2 is Saturated" only have 25 comments per page. As a result, when you try to follow the link on Recent Comments, you end  up on a page only half way to where you expect to be.

    As a work-around until we fix the bug, you can see a "page" number in the link. You can edit that manually.

    For example, the last link to "CO2 is Saturated" on the Recent Comments page (now #81) is from MA Rodger, and the link is as follows:

    ...but his comment is actually #668  on page 27:

    Since the comment in question is not on page 14, following the first link puts you on page 14 (not a specific comment). Changing the page number to the second link gets you to the correct comment.

    In this case, seeing page 14 in the incorrect link could be page 27 or 28 for the correct link. But at least you can narrow it down. The correct page will be either {wrong page x 2} or {wrong page x 2} -1.


  12. I'm interested in comments about this Youtube channel's climate deception and denial, especially this video and Roy Spencer's comment about models being wrong. 1:34


    [BL] Link activated. Remember: you need to turn the text into a link using the little "link" icon on the "Insert" tab. Select the text you want to display (which can be different from the URL), click on the link icon, then add the URL in the dialog box.


  13. Eddie:

    I have not watched the video you linked to, but this SkS repost of a RealClimate blog post discusses how Spencer has gotten things wrong in the past:

    Comparing models to the satellite datasets



     [Note that the proper link to the correct page for this comment on its proper thread is as follows:]

  14. Thanks for the reply.

    I believe that Spencer's contrarian views go back a long way in the denial business. Potholder54 on Youtube ( does a lot of work on climate evidence and deniers. He's a geologist and creates helpful videos.

    What disturbs me, and the motivation for my post is his following. I'm just nosing about it; it's mental health, reality check thing.

  15. Bob Ludlow, I'm concluding my Spencer search via Real ClimateReview of Spencer’s ‘Great Global Warming Blunder’ to "cdesign proponentsists-the case against "Intelligent Design" and it's not even five in the morning. I mentioned Potholder54 because I believe that I first heard Spencer's name in one of his videos. Now I know, and the redirection to "cdesign proponentsists" and climate change deniers, deceivers sheds more light. I hope I have not transgressed boundaries on SS with this post. I also wonder if RealScience's copyright applies to copying text and posting it on Youtube. I better ask first. Regards

  16. EddieEvans @1314,
    The 3-minute video clip linked @1312 in turn referrs to this blogpost by Spencer. The agrument put forward by Spencer is that the summer trend in AGW over the contiguous USA 1973-2022 as measured by NOAA is +0.26ºC/decade, a value he confirms with his own analysis of temperature records (although Spencer also suggests this result may be impacted by the presence of that fantastical archipelago 'The Urban Heat Islands' even though his analysis fails to note their location within the contiguous USA).
    Spencer then compares this US summer trend with that of 36 modelled trends** and finds a bit of a mismatch. The models are all showing far more warming for this particular measure according to Spencer. If correct (and that is a big 'if' because Spencer is involved), these modelled trends are sitting in the range +0.28ºC/decade to +0.72ºC/decade and averaging perhaps +0.45ºC/decade.
    And so Spencer concludes:-

    Given that U.S. energy policy depends upon the predictions from these models, their tendency to produce too much warming (and likely also warming-associated climate change) should be factored into energy policy planning. I doubt that it is, given the climate change exaggerations routinely promoted by environment groups, anti-oil advocates, the media, politicians, and most government agencies.

    This all seems a bit of a leap into the realms of purile nonsense rather than the sort of stuff a grown-up climatologist should be doing. I note in Spencer's comment thread somebody says they "checked NOAAs summer temperature for Europe 1975-2022 and got 0.53 deg.C/decade." So if there is "far more warming" showing in these models, for Europe that modelled warming must show a steep trend indeed.
    ** Spencer doesn't explain his analysis of these models but points to this web engine which might have done it for him, or confused him enough to make his blunderful grand finding. A quick go on the web engine for Tas & SSP2-4.5 (as per Spencer) yields a summer global land model average of +0.33ºC/decade which is pretty close to the NOAA NH summer land average trend (1973-2020) of +0.31ºC/decade.

  17. MA Rodger - - Thanks for the information. For the record, I'm still learning to navigate SS.

    FYI: My chief goal, however useful, aims to make more information available on Youtube; I'd like to add your post to a growing project on climate deniers on one of my Youtube channels, "Climate Deception."  Interestingly, my hobby with climate deception dovetails with climate damage, and global warming simplified. Although the global warming simplified project lags because it's hard to simplify beyond NASA's Climate Kids.  So, I think I'm going to post the difficult reading on it too. I'm old and this is my most useful activity as it turns out. Regards.

  18. EddieEvans is justified to question Roy Spencer's work. And I agree with MA Rogers that Spencer's claim that 'what he claims to have discovered about climate models should alter (govern) US Energy Planning Policy development and action' is bizarre.

    I do not believe it is necessary to get into the details of what Spencer did. The real question is: How is the 'summer trend in average surface warming of the contiguous USA' relevant to US Energy Planning? The likely answer is "It Isn't relevant".

    The rate and total ultimate magnitude of human global warming impacts is the concern. And US Energy Planning needs to be aligned with the USA responsibly leading the rapid ending of harmful impacts (because the USA undeniably led the creation of the problem and is still a per capita leader of the increase of the problem).

    Also, it is unlikely that the sea level rise impacts on the USA, or many of the other climate change impacts on the USA, are altered by what the models indicate as the 'trend of Summer surface average temperature in the contiguous USA from 1973 to 2022' vs NOAA data. And "What about the Fall or Winter or Spring values?"

    This apperas to just be Spencer 'doing his thing' - creative development of attempts to be misleading about climate science to delay the development of the understanding of, and delay the development of popular support for, the need to rapidly end the harm done by fossil fuel use and other harmful human pursuits of benefit.

    Actually, this recent bit about how the models appear to overstate the rate of warming of the 'Summer values' of the contiguous USA is rather weak compared to many of Spencer's 'more subtle distortions and misleading claim-making'.

  19. Eddie et al (comments 1314-1417)  on Spencer's video and blog post.

    Thanks, MAR, for the link to Spencer's blog post. I followed his link to the NOAA data source, and looked at the numbers. If I grab the June, July, and August monthly values (the standard climatological "summer"), I get the same results: about 0.26C/decade. That checks out. A few things that Spencer does not mention:

    • The overall trend is not particularly linear.
    • The r2 value is rather low.
    • The standard error on the slope esitmate is 0.04 C/decade.

    Here is a graph of the data:

    Continental US Temperatures

    The uncertainty on the trend covers some of the model range he provides in the blog post. Two sigma range places the observed trend between 0.17 and 0.35 C/decade.

    The model trends also include a level of internal variability. The observations follow a specific pattern of "unforced variations" related to cycles such as El Nino, etc., while individual model runs and models will have different patterns within a specific model run. Over shorter periods, and smaller areas, you need to consider this in making any comparisons. For models, they often get an "ensemble mean" of many runs with different variability - but the observations are still a "single roll of the dice" that can fall anywhere in the range of the collection of model runs and still be consistent with the models.

    I see that you have already found the Great Global Warming Blunder post at RealClimate. They also have a couple of other relevant posts:

    This one talks about how unforced variability affects model runs.

    This one talks about things to consider in comparing models and observations.

    Tamino's blog is also a useful place to look whenever statistical stuff comes up. In this post, he points out several aspects of the use of the continental US for data. He covers the non-linearity of trends, the variations in trends in different parts of the US, and points out that the continental US represents 1.6% of the global area (ripe for cherry picking).

    In general, Spencer tends to get more wrong than he gets right.

    P.S. The preferred abbreviation for SkepticalScience is SkS (for obvious reasons).

  20. Thanks for responding to my page comment.

    A question, and forgive my for not reading all 1.3 k comments: Re: Christy's chart for the Senate hearings: Is he doing apples to apples or not? i.e, What is "Global Bulk Atmospheric Temperature", and is that at the altitude of the 102 CMIP-5 models that he shows? Thanks in advance.

  21. sailingfree:

    I presume you are asking about the Christie graph in the blog post? The image is actually an animated graphic, but on the intermediate tab you can see additional static images from the animation.

    You can also click on the graphic to load this page, with more explanation:

    On that page you can get a higher-resolution copy of the first annotated image:

    ...but to address your question, the Christie graphic talks about surface to 50,000 feet. That is a pressure of about 115 mb.

    On this blog post, there is a chart of weighting functions for satellite measurements:

    Satellite weighting functions

    As you can see, the satellite temperatures represent a non-uniform weighted response at different altitude, so proper weighting of other sources is required for a valid comparison. In addition, the processing of satellite radiation data into temperatures is complex, and explains much of the differences between different satellite sets (which is not shown by Christie, as mentioned in the annotations for the figure).

    Without knowing details, Christie may or may not have done a proper weighting - but the other problems with his graph (as noted in the annotations in the blog post image) are not a good indication that he can be relied on.

  22. Bob Loblaw @ 1321.

    Thank you so much for info on Christy's "Bulk Atmosphere". Are the 102 CHIMP-5 models for a similar altitude, or are they for near the surface? i.e, apples or oranges compared to his oranges?

  23. sailingfree:

    The models are three-dimensional, so they give temperature in a three-dimensional grid of latitude/longitude/altitude. To get a "global" average from 0 to 50,000 feet, you'd need to average in all three dimensions.

    To compare to the satellites, the vertical averaging of model data would need to be a weighted average, using the same weighting function as the satellites.

  24. sailingfree @1322,

    The four 'corrections' to Christy's senate presentation presented in the gif in the OP above are originally set out within this RealClimate post. While that post makes no mention of problems with the averages presented by Christy (eg apples being compared with oranges), I am a bit sceptical of Christy's Global graphics given the graphed 'correction' in that RealClimate post.

    The RSS TMTv4 plotted in the 'correction' would not have been available in Feb 2016 (it was a month later) so Christy's 'Ave 3 satellite datasets' plotted as 'squares' would presumably be UAH TMTv5.4, RSS TMTv3.3 & NOAA STAR. While the divergence between model & satellite data in Christy's Tropical graphic appear to match, the Global divergence seems 'stretched' in the Christy version relative to the 'corrected' version. Thus scaling the graphics gives Christy showing +0.47ºC divergence while the 'corrected' version shows just +0.39ºC for just RSSv3/UAH, a value which presumably would be even smaller (+0.36ºC) if NOAA STAR as plotted in the 'correction' is the third 'satellite dataset'.

    I think this is probably Christy plotting his averages with more carelessness than would be expected from a genuine researcher rather than it being an 'apples-&-oranges' thing.

  25. This is new information related to the video by Spencer mentioned by EddieEvans @1312 and comments about it since then.

    Roy Spencer has a November 19th 2022 blog posting titled "Canadian Summer Urban Heat Island Effects: Some Results in Alberta".

    In the conclusion Spencer says:

    "The issue is important because rational energy policy should be based upon reality, not perception. To the extent that global warming estimates are exaggerated, so will be energy policy decisions. As it is, there is evidence (e.g. here) that the climate models used to guide policy produce more warming than observed, especially in the summer when excess heat is of concern. If that observed warming is even less than being reported, then the climate models become increasingly irrelevant to energy policy decisions."

    That is very similar to the wording by Spencer included in the comment by MA Rodger @1316. It appears to be Spencer's "New Trick" - seeking any bits of data evaluation to make-up a claim about model inaccuracy that is then claimed to mean that "Energy Policy" should be less aggressively ending fossil fuel use.

    And the introduction of this blog post by Spencer makes it pretty clear he has made this line of investigation, evaluation and claim-making regarding "Energy Policy" his new focus.

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