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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

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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 501 to 525 out of 903:

  1. Relevant to this discussion on skill/validation of models is Hargreaves 2010
  2. Scaddenp brought me here to answer his question, so here I am. I said that extraordinary claims require extraordinary evidence. Sccadenp asks "Sorry, what is extraordinary about the claims of climate theory?" Here are two examples: "And that is what is at stake: our ability to live on planet Earth, to have a future as a civilization." Al Gore, An Inconvenient Truth. "On the long run, if this [increase in greenhouse gases] continues for centuries, that's it for all the species on this planet." John Hansen, The Runaway Greenhouse Effect (YouTube video) I call these claims extraordinary and I expect an extraordinary amount of model validation before I accept the consequences, which are also extraordinary. And, for hearing too many failed season-long forecasts from our Canadian chief meteorologist, I do not believe a minute that we understand all there is to understand about the physics of climate. Read this for fun: Balmy winter takes climate experts by surprise
    Response: Regarding your last paragraph, you need to understand that weather is not climate. See Scientists can’t even predict weather
  3. Perhaps, Manny, if these are indeed "claims of climate theory", as you propose, you could furnish us with the references in the peer-reviewed literature where either of these claims are made. I contend that you can't do this, as the first claim is made by a politician in a film, and the second is a personal opinion by (James) Hansen in a youTube video. See if you can find either statement in the published literature or in the IPCC reports. What you will find in the published literature: extensive discussions of empirical evidence documenting the causes and impacts of climate change, with uncertainties attached; discussions, with evidence and uncertainty, of how sensitive our climate is to change (e.g. 2C-4.5C warming per doubling CO2); discussion of model representations of the climate system, with assessment of their strong and weak points. Models validate the core propositions of our theory of climate very well. Seasonal weather forecasts are an irrelevant distraction, being both notoriously unreliable and bearing precious little in common with climate modelling. I wonder why 'skeptics' would wish to conflate the two?
  4. "I call these claims extraordinary". Why? Would "firing off our entire nuclear arsenal at once might lead to mass extinctions", or "a 10km asteroid impact, will lead to mass extinctions" be extraordinary claims? I would say no - both a consistent with known science. The context for that original quote and its basis from Laplace, refer to ideas that are in breach of all known science. The denialist community is making the extraordinary claim that modifying our atmosphere with a known radiative gas is somehow, in defiance of quantum mechanics and laws of thermodynamics, not going to result in a warming climate. The question over model skill is whether they are better than predicting the future than a naive assumption.(eg that man cant affect climate). The models demonstrably have that skill. Instead, Manny, you seem prepared to bet the future on the basis that known physics is wrong. I rather doubt you make similar bets against in science in other spheres (eg what you Dr tells you). Would this be because you perceive that any solution would violate your political ideals?
    Response: TC: Text edited to change all capitals into bolded. The comments policy applies for everyone.
  5. Manny's argument, if it can be called one, cuts both ways. Here is an extraordinary claim: We can burn fossil fuels without regard to our impact on the global environment. Where is the extraordinary evidence that supports this extraordinary claim? Or do we just carry on with business as usual, on the sole basis of 'that's what we've always done'? Particularly when we know without question that our actions do indeed impact the environment in both directions - see ozone, smog, the Black Triangle, the Clean Air Act, Asian brown clouds, etc.
  6. Continued from here In other words, Clyde has no evidence what so ever, only conjecture and assumption. A question for you, Clyde: Which would you find more believable as a climate modeler, a climate scientist, or rather team of scientists, who are also competent at building a computer model of the physics and chemistry of the coupled land-ocean-atmosphere system, or an expert at computer modeling who knows absolutely nothing about the underlying physics and chemistry of the coupled land-ocean-atmosphere system that is being modeled? (Why should they, they are not climate scientists, they're computer modelers, while practically all physical scientists work intensively with computers.) And why did you fail to consider that climate scientists work with actual computer modelers when developing climate models, as I suggested, before leaping to defend your assertion that climate scientists have no expertise in the use of computers?
  7. Jim Eager 506# I've never seen any credit given to computer modelers. Would you want heart surgery done by a doctor who has performed say 100 successful operations or by a doctor who has used a computer to project/predict how to do the operation? Would you bet your life on the future global warming projections/predictions coming from computers? I read a few other blogs. As i said earlier the science is above my head. I know enough to understand a failed prediction. Do you want me to post the links to the failed predictions/projections? From my brief time of reading this blog Rodger Pielke Sr is not one of the favorites around here. Why doesn't somebody ( you if your qualified) refute his claims on climate model predictions/projections? I'm not saying Rodger is right or wrong. He has an open challenge to prove him wrong & nobody has taken him up on it. He admits when he is wrong. He had to eat crow after a discussion he had with dana1981. You can input all the physics & chemistry you want into a computer. Doesn't mean what comes out is accurate. Have a nice day
  8. "heart surgery done ... by a doctor who has used a computer to project/predict how to do the operation?" What nonsense. Medicine uses computer imaging, based on models of how the body interacts with magnetic fields, sound and/or radiation. Oil exploration uses computer modeling based on seismic techniques. Is there a car or airplane that can function without a computer? Why is climate science held to the false standard that 'computer models don't work'? "You can input all the physics & chemistry you want into a computer. Doesn't mean what comes out is accurate." No, but it does mean that we can eliminate things that can't be verified by models. We can eliminate the idea that climate change is purely natural.
  9. Clyde, what on earth makes you think modelling teams dont include heavy-duty modelling folk? As to "failed predictions" that pick up off blogs, there are a couple of things to check. First, check the source of the prediction. The usual denialist stuff is make claims about a prediction that are not actually made and since its a straw man, (take note of error bars) then its easy to demolish. All models are wrong, but some predictions are far more robust than others. A converse page of robust model predictions together with papers that do the prediction and papers that confirm it can be found here Second, modellers usually judge models by skill. Ie the ability of models to make better predictions than some simpler method (ie that nothing is changing). Climate models have no skill for instance at decadal-level predictions. This is common "skeptic" ploy. As to Piekle, perhaps you should follow the discussion with the modellers at Realclimate? In short, you cannot make naive comparisons of models and observations. If you still think there is clear case of model "being wrong" supported by papers, then by all means post links.
  10. Clyde: What is your definition of a "computer modeler"? On what basis do you claim that any particular "climatology expert" is not knowledgeable about computer modeling, and how would this affect the work that they are doing? I think that you are creating a strawman "computer modeling expert", in a futile attempt to pretend that climatologists can't do "computer modeling". Many climate modelers have physics and mathematics in their background, and at least one I know personally works in a mathematics department. I would consider myself to be a "climatologist", and I have written "climate models" (microclimate) from scratch. My background is physical geography, but - I have studied numerical methods, including finite difference solutions to partial differential equations. - I have coded numerical solutions to radiative transfer, atmospheric turbulent heat transfer, and soil thermal diffusion problems. - I know from study and experience the issues related to floating-point arithmetic, and how to avoid them. - I have coded the required root-finding procedures for complex, non-linear systems. - I wrote my first computer program before I took my first computer course, and before most people had a clue what "Computer Science" was (or would be). I never took a second computer course, but I have written serious code in three different languages, simple code in a few more, and can read read quite a few more than that. And I know that "Computer Science" students often don't get exposed to half the stuff that I have learned that is necessary to do "climate modeling" correctly. - my first numerical programming was done on punch cards, fed into a mainframe computer. I've been doing programing for almost 35 years. What else would I need in my background to convince you that I know enough about "computer modeling"? I seemed to convince my PhD thesis examining board that the modeling work I did was valid - and that board included an engineer that asked me why I used a secant root finding method instead of Newton-Raphson, and a physicist that said that when he read my thesis he discovered a field of study that he could have been very happy doing instead of physics. I agree that the science is above your head. It doesn't have to stay that way if you are willing to learn. Start by giving me your definition of "computer modeler", and what makes you think that people doing climatology aren't capable of it...
  11. Clyde: you said "I know enough to understand a failed prediction. Do you want me to post the links to the failed predictions/projections? Please do so, but keep in mind that here at SkS you will be expected to back your position up with references to real scientific literature (not just blog posts). Before you start to post your own stuff, though, you may want to review the series of posts found using the Lessons from Predictions search item. There is a button that will do this search for you near the top left of the SkS page (just above "Most Used Climate Myths").
  12. Last comment for now... Clyde: if you want to see why the name of Pielke Sr. gets the reaction it does here, read the discussions available here, where he has participated in some comment threads, and there have been numerous blog posts commenting on his arguments. Note that Pielke Sr. does not seem to allow comments at his own blog, so it isn't easy to engage in a discussion with him about them. I've already done some searching for you (the search box is in the upper left corner of the SkS page). You can try reading these blog posts and discussions: Pielke Sr and scientific equivocation: don't beat around the bush, Roger Response to Roger Pielke Sr. One-Sided 'Skepticism' Chasing Pielke's Goodyear Blimp SkS Responses to Pielke Sr. Questions Pielke Sr. Agrees with SkS on Reducing Carbon Emissions Pielke Sr. and SkS Disagreements and Open Questions Pielke Sr. and SkS Warming Estimates Pielke Sr. and SkS Dialogue Final Summary Pielke Sr. Misinforms High School Students
    Response: (Rob P) Removed dead link
  13. Just on the RC discussion you might like to look at this comment and surrounding context.
  14. Clyde, you appear to be attempting to make a case against climate science (or at least, echoing Dr Pielke Sr's case) on the basis of its use of computer models to project future states of the climate. This is likely to be an exercise in futility on your part. As I intimated on the Bob Carter thread, the mainstream scientific position on climate is the result of an intertwining web of: (1) Physics & chemistry theory (ranging from quantum-mechanic radiative properties of IR-trapping gases, to the physics of blackbodies, to the chemistry of ocean buffering of CO2, to many other strands of theory besides); (2) Lab or computer experiment (starting with Tyndall's experiments demonstrating the atmospheric IR-trapping gases and confirming the atmospheric IR-trapping 'greenhouse' effect all the way to the elaborate atmosphere-ocean-surface coupled models of the present); (3) Empirical observation (the surface, satellite & sea surface temperature datasets, measured ocean heat content, measured crysophere melt, shifting wind currents & atmospheric cells, shifting animal & plant distribution, and so on). It it this intertwining of these various strands of evidence which has led to the formation of the generally-accepted scientific consensus on climate change, as expressed by the IPCC, the US NAS, the UK Royal Society, and virtually every major national, transnational, or intranational scientific organization. Even supposing you could chip away at the reliability & accuracy of computer models, you would still have an enormous task ahead of you to knock down enough of the theory, experiment & observation supporting the mainstream consensus to cause a substantial re-think.
  15. Clyde asks: "Would you want heart surgery done by a doctor who has performed say 100 successful operations or by a doctor who has used a computer to project/predict how to do the operation?" This is an obviously bogus analogy. Heart surgery is performed routinely these days, so it is easy to find heart surgeons who have performed 100 successful operations. However climatology as a field is only a couple hundred years old and it takes at least 30 years worth of observations to get a clear picture of what the climate is doing, thus there is no climatologist that has made 100 successful (independent) predictions of future climate. Sadly observations of future climate are not available at the current time, so projections based on computer simulations are the best tool we have at the moment for exploring the consequences of a given course of action (or inaction). If Clyde has a better solution, then lets hear it. BTW, if computer simulations were of no value, then one would ask why computer simulation is widely used in training surgeons?
  16. Clyde wrote: "I've never seen any credit given to computer modelers." How would you know this? What, exactly, is your definition of a computer modeler? What is your expertise in determining who is a competent computer modeler? "Would you want heart surgery done by a doctor who has performed say 100 successful operations or by a doctor who has used a computer to project/predict how to do the operation?" Your analogy actually better applies to you. It seems you would trust the expert modeler who has no understanding of the physical climate than the climatologists who actually study the real climate. Where do you think climatologists working with computer modeling learn enough about the the physics and chemistry of the real climate to model it? "Would you bet your life on the future global warming projections/predictions coming from computers?" Yes, I would and I am. Would you bet yours, or more telling, your children's and your grandchildren's lives on going forward with business as usual without understanding the possible impacts of tampering with the atmosphere and greenhouse effect and ocean chemistry and without bounding the probability of those impacts by modeling them? "Do you want me to post the links to the failed predictions/projections?" Do you mean failures like successfully predicting... ... that global mean temperature would warm, by about how fast, and by about how much ... the rising of the tropopause and the effective radiating altitude ... that the troposphere would warm while the stratosphere would cool ... that night time surface temperatures would increase more than daytime temperatures ... that winter surface temperatures would increase more than summer temperatures ... that higher latitudes would warm faster than temperate and equatorial latitudes (polar amplification) ... that the Arctic would warm faster than the Antarctic because the two poles are physically and geographically quite different ... the magnitude (~0.3 C) and duration (~two years) of the aerosol cooling caused by the 1991 Mt. Pinatubo eruption ... that modeled hindcasts for Last Glacial Maximum sea surface temperatures was inconsistent with the paleo evidence, and then better paleo evidence showed that the models were right ... a trend significantly different and differently signed from the UAH satellite temperature record, and then a bug was found in the UAH satellite data ... a tropospheric temperature trend significantly different and differently signed from the balloon radiosond temperature record, and then it was found that the thermometers used on the balloons were not properly shielded from direct sunlight ... the ~4% increase in absolute humidity as the atmosphere warms (water vapor feedback) ... the increase in both number and intensity of record high temperature events ... the increase in both drought intensity and intense precipitation events ... the response of southern ocean winds to the ozone hole ... the northward expansion of Hadley cell circulation ... the expanded range of hurricanes and tropical cyclones, poleward movement of storm tracks, and the increase in average cyclone & hurricane energy intensity It's "failures" like these that give me confidence that the models are useful. Not that they are right, but useful.
  17. And, finally, Clyde, remember that any claim you make contrary to these computer models must be based on a model itself. It may be your intuition, or it may be someone else's computer model, but it's still a model. Unless, of course, you give voice to thoughts which have no rational origin, and I don't think you'd admit to that (or your admission wouldn't mean anything if it were true). Thus, just saying "models suck" is not good enough. You need to be able to defend your own model (or the model you currently accept) against the IPCC's model set, or you're just barking loudly without any teeth.
  18. Ben Santer has an interesting lecture where he discusses climate modeling HERE. Santer states that no model is perfect, they're good but not perfect. He says that some models are better than other models, but ensembles of the models is better than any given model. And they also find that ensemble models that are weighted for the better individual models perform even better than that. And you have to realize, the models are not being put out there without checking them against empirical results. They, in fact, are tested against actual results, but as Dikran says, it takes a long time to test the models against the broad, long term climatic response to forcing. What I think is going on in the media and the blogs is, it's a meme that plays on people's lack of understanding of a complex science. It's the "hey, they can't even predict the weather next week" idea, which is a completely false analogy. So, people get the idea that climate change is all based on models and models don't even work. It's the mother of all red herrings in the climate debate.
    Response: TC: I think Clyde has more than sufficient responses to his comments now. Any further responses before he responds would by "dogpiling", and hence in contravention of the comments policy. In order to to avoid overwhelming Clyde with weight of respondents rather than weight of argument, I also request that only Bob Loblaw and Jim Eager respond to his future posts, unless they wish to deffer to some other person.
  19. I appreciate all the help everybody is giving. I can't reply to everybody. Thanks to the moderator who has ask the "dogpiling" be kept down. Bob Loblaw 510 Which is harder/more complicated - Writing code for GCM or writing HTML codes for a website?
  20. Bob Loblaw 512 I have no idea if Pielke Sr is right or wrong when he issued the challenge. All i know is if anybody has taken him up on it he hasn't posted least not yet. The link below is not the challenge (I'll try to find it later) but has several peer reviewed papers casting doubt on predicting future climate based on computer models. Read more here. I've read articles that Kevin Trenberth has a theory where the "missing heat" went. Another example of the models not being very accurate. How can you just a model[s] that missed 10 years of heat? My first try with the hyperlink deal. Hoping this works.
  21. Jim Eager 516 I guessing if you had a peer reviewed paper you would give credit to all who helped in writing of the paper IE any folks who had been computer modelers by trade. My definition of a computer modeler would be somebody who's primary job was making computer models. I might have more trust in the models if i knew the scientist running them had expertise in computer modeling. So yes i would prefer the scientist give the data they want modeled to somebody who's primary job is computer modelling. No i wouldn't bet my life on computer model predictions. My using the betting of life is not a good thing to do IMO. My apologies to all. (-Snip-)
    Response: [DB] Off-topic snipped.
  22. Sorry about the post above. More evidence the computer models are not good at predicting future climate change. One minor "type O" & things come out wrong.
  23. Well, since Clyde refuses to acknowledge all the things that climate models have gotten right, and that they are useful for understanding how climate behaves in the present and will behave in the future, or that scientists can even be competent climate modelers, and is now directing people to Jo Nova's site to support his argument, as per the moderator's request I hereby defer my right of reply to anyone else wishing to waste their time continuing the discussion with him.
  24. Clyde, your (now deleted) Arctic comment has been responded to on a more appropriate thread.
  25. Clyde#521: "I might have more trust in the models if i knew the scientist running them had expertise in computer modeling." How do you know they do not have such expertise - or do not have available those who do? It would appear you missed this model quality-check from the Intermediate version of this argument. If your argument with computer models is that 'scientists don't know how to program,' that song is old and tired. I suggest you look here or here. If your argument is 'you can't trust a computer model,' I suggest you look here to see how computer models impact medicine and here to see how pervasive computer models are. If you distrust modeling so much, be prepared to give up a lot of what we now take for granted as part of our 'quality of life.'

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