Climate Science Glossary

Term Lookup

Enter a term in the search box to find its definition.

Settings

Use the controls in the far right panel to increase or decrease the number of terms automatically displayed (or to completely turn that feature off).

Term Lookup

Settings


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.

Home Arguments Software Resources Comments The Consensus Project Translations About Support

Twitter Facebook YouTube Pinterest MeWe

RSS Posts RSS Comments Email Subscribe


Climate's changed before
It's the sun
It's not bad
There is no consensus
It's cooling
Models are unreliable
Temp record is unreliable
Animals and plants can adapt
It hasn't warmed since 1998
Antarctica is gaining ice
View All Arguments...



Username
Password
New? Register here
Forgot your password?

Latest Posts

Archives

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)

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 proved 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. For example, here’s a graph of sea level rise:

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. Climate models form a reliable guide to potential climate change.

Mainstream climate models have also accurately projected global surface temperature changes.  Climate contrarians have not.

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

A 2019 study led by Zeke Hausfather 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."

There's one chart often used to argue to the contrary, but it's got some serious problems, and ignores most of the data.

Christy Chart

Basic rebuttal written by GPWayne


Update July 2015:

Here is a related lecture-video from Denial101x - Making Sense of Climate Science Denial

Additional video from the MOOC

Dana Nuccitelli: Principles that models are built on.

Last updated on 9 September 2019 by pattimer. 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.

Update

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

Myth Deconstruction

Related resource: Myth Deconstruction as animated GIF

MD Model

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

Comments

Prev  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  Next

Comments 626 to 650 out of 787:

  1. cruzn246...  What you say might be interesting if it were based on any facts.  

    Do you think for even two seconds that the many thousands of scientists who work on climate issues have not considered the relative forcing of solar vs GHG's?  

    Global Mean Radiative Forcings

  2. The image from the link above:

  3. cruzn...  Please look again at the chart I linked to before.  It clearly shows that there is a low LOSU (level of scientific understanding) related to solar.  But that doesn't mean it could be absolutely anything.  Still the likely range solar forcing is a fraction of GHG forcing, which has a high LOSU.  

    You do realize, of course, we have satellites which are measuring solar variation, and you were even quoting radiative forcing figures, data that comes from those satellites.

  4. cruzn246:

    "Tell me why it has essentially stopped warming just when the solar torch let up?"

    See the SkS climate myth #2 "it's the sun".  The first graph does not support your statement above.  Also, what do you mean, specifically in @628 when you say "it has stopped warming". Specifically what do you mean when you say "it".

    Finally, I think it is a strech to imply that the modelers and those that utilize them to aid in understanding climate change "think they have it all figured out". However, you sound like that. And in my opinon have much less of a leg to stand on in your assertions.

    Response:

    [DB] Please note that cruzn246 has an extensive history of sloganeering and trolling in this venue.

  5. (-snip-).

    Response:

    [DB] Please comport yourself with this site's Comments Policy.  In it you will note under the Sloganeering section that if you wish to differ with established science, you will need to bring reputable evidence to support that chosen differing.  Mere assertion, as has been your wont, fails to rise to that burden of proof.

    Sloganeering snipped.

  6. cruzn...  I think you'll actually find that people here are willing to entertain contrarian ideas, but you have to be able to substantiate your position far better than you're currently doing.

    Just because you think something is obvious does not make you automatically correct.  As the moderator is saying, you must back your claims with actual science and research.

  7. Kishoreragi, to add to Michael's comment: that is the way general circulation modeling is done. The Earth itself is one big experiment, and it has been well-demonstrated that the minor variables vary within certain ranges and rarely, if ever, end up leading global or even regional climate by the nose long enough to significantly alter major elements of general circulation. There is a strong tendency to regress to the mean, and the mean is driven by the major elements of the climate: continental drift, orbital variation, vulcanism, solar output, collision with significant extra-terrestrial objects, and, now, artificial enhancement of the greenhouse effect. Everything else is a feedback: something that reacts but is unlikely to change on its own -- biosphere (with rare exceptions), snow/ice albedo, ocean carbon cycle, clouds, water vapor, natural greenhouse effect, etc. Feedbacks vary and are integrated in different ways, but they regress to the mean of net forcing, with minor temporal variations driven primarily by ocean thermal capacity.

    Thus it's a little inaccurate to describe the climate system as comprised of components that vary but are all of equal or near-equal power in shaping the future of the system. And, in addition to the major forcings, modeling does take into account many of the major and minor feedbacks. Of course, in the short-term (months to years), the interplay of major and minor feedbacks can produce significant but temporary anomalies, but the resonance of those anomalies across the long-term trend is ultimately insignificant. Arctic sea ice (ASI) is a great example. ASI is never, with all forcings stabilized, going to vary strongly and consistently to the extent that a glacial cycle is initiated. Only orbital or solar variation (or a one-timer) can do that (partially through the mechanism of snow/ice albedo feedback).

  8. Given that climate models can closely approximate past climate, I'd think the onus is on 'skeptics' to show some reason why we should assume that they will not be equally accurate for future climate.

    Just saying, 'there are too many factors involved to ever model climate' doesn't cut it given the established reality of models which already do successfully match past climate. Heck, we even know most of the causes of short term variation... such that if you plug major volcanic eruptions, variations in solar output, ocean cycles, and other such 'unpredictable' factors into model runs of past climate they then match not only the long term trends, but even the short term fluctuations around the trends. That's shockingly accurate for something which is supposedly 'impossible'.

  9. kishoreragi at 17:00 PM on 18 September 2013 9 (found in What's causing global warming? Look for the fingerprints)

    Your “a forest is like a climate model” analogy would benefit if you could identify the critical variables omitted from the models or issues with how climate models utilize them.

    Yes, there are a lot of different animals moving around in a forest. Yes, modeling everything going on in a forest would require understanding how sensitive each thing is to changes in each other thing. But it’s not a valid analogy to just list some of the different things going on in a forest, and then jumping straight to the insinuation that climate models omit critical features. In short, you don’t provide any solid rational that climate models are not useful with respect to predicting changes in climate.

    Response:

    [JH] Thank you for responding to kishoreragi on this thread. 

  10. Roger D

    I don't want to go predict big things right away with incomplete models, but I want to eloborate what I wanted to inform here.

    I have given this analogy because there is a need to understand each and every animal (here it is physical process) is related (friendly/hostile, here for climate, how processes are intricately mixed- diminishing/strengthening) on forest variables (We can choose any variable here) on specific part of forest(Any region of the world). So that little by little, we can understand about the comple forest and their inter-relation.

    My main point is that the science has progressed much further, but in wrong path. The simple fix for this is to make the system simple and see the intricacies among the processes, leaving the comparision with observations, on regional climate variables so that in the FAR future, we may be in a position to see the BIG picture like AGW without hesitation from anybody (skeptics/supporters) and with clear understanding. As far as I understand(ofcourse I am still reseach student), there is no other way as climate system super complex !!!

  11. kishoreragi, you only need to model every conceivable input if you need to know every conceivable output... which isn't the case. To take your forest example, if the goal of the model is to determine how the forest will grow then the actions of deer and bears are largely irrelevant... they might impact a tree here and there, but they are not going to change the overall growth pattern of the forest. Instead, you are going to look at weather, human logging, beavers, and other factors which can actually have a significant impact.

    Ditto climate models. No, they cannot possibly model every individual cloud and gust of wind... but there is absolutely no reason they would need to, because those things are not going to impact the overall climate trends.

    Again, you do understand that climate models already work, right? They can successfully model the past and even the relatively primitive climate models in use 30 years ago produced results consistent with the past 30 years. You are arguing that something which has been done, cannot be done. You're wrong before you even get started.

  12. Thank you all for reading my views and their valuable comments/suggestions.

    CBDunkerson, thank you for your valuable comment on my analogy, and insights into climate modeling. I understand that climate models work. I have been trying to study precipitions but, I felt, with supervisor's advise, like I was cheating science because model resolution is coarse and cloud physics is not yet well understood. Hence, I have changed my thought to study other variables. May be climate models worked for few variables even before 30 years but, climate is not of those few and rest of them won't work even 21st century. May be you are looking at those few variables(I agree with you here) but, I always see other side with completely different view to progress further.

    I will try to correct myself (that is why I have been focusing on literature from all corners) before get started my research as well begun is half done !!! I am off on this thread. Thank you all !!!

  13. kishoreragi - I think what you are overlooking is that there is an approriate level of detail for studying anything. Details below the scale of GCM's are parameterized, treated as blocks that have known (as in, tied to observations) responses to inputs, and that physically based parameterization works just fine for global and regional level modeling. 

    More detail would be needed if you wanted to look at microclimates and the chances of a particular bush getting wet during a closely timed rain shower. But that's not the level of study for GCM's, and if subscale responses are reproduced well a GCM will give a fine answer at the scale it is actually studying. 

    These models aren't looking at the level of individual trees and gusts - hence they just don't need to simulate at that level to get a good answer for the regional/global scales studied. 

  14. I just saw "Overestimated global warming over the past 20 years", by Fyfe, Gillett and Zwiers in Nature Climate Change, Vol 3, Sept 2013, page 767. They contend that the divergence of models and observation is statistically significant. In trying to rationalize the discrepancy it seems to me that they don't consider the possibility that atmosphere-ocean heat transfer coupling methodology (particularly below several hundred meters depth) in the models may not yet be up to par. 

    What is the SkS take on this article? 

  15. tcflood's source in pdf, in case SkS can't access it by other means.

  16. @tcflood it looks like there was indeed less warming over the period 1997-2012 than the models predicted, however, what "skeptics" often fail to mention is that "the surface warming trend from 1993 to 2007 was significantly higher than projections." See here for more information: http://www.abc.net.au/environment/articles/2013/09/27/3857704.htm

  17. @jsmith.  Thanks for the response. I read somewhere that many of the GCMs actually do produce ENSO episodes but that the timing of their appearance (as in nature) is chaotic. If modeling results are reported as an average of many models, wouldn't the effect be to remove the ENSO effects thereby insuring some departures of observation from the models when real ENSOs would occur? So, hypothetically, if there were some way to trigger an episode at the same time in all the models, the match between models and observation might be much improved. I don't pose this as a realistic modeling strategy, but rather as an accurate and effective counterargument to this common cavil in the denier echo chamber?  

    Also, the denier rant that called my attention to the above-cited paper said Zwiers is a vice chair of the IPCC. I infer from your comment that he is nonetheless a skeptic. The paper certainly reads like he is.   

     

  18. tcflood "wouldn't the effect be to remove the ENSO effects thereby insuring some departures of observation from the models when real ENSOs would occur? "

    Essentially true. See for instance the graph here. Forcing ENSO in model to match what happens is somewhat like Kosaka and Xie did. See discussion here.

    Comment from Mike at RC on Zwiers.

    "[Response: Francis is a top-rate scientist of the highest integrity. I strongly suspect that he has been misquoted and mischaracterized quite a bit lately. -mike]

  19. Further to Zwiers. Any good scientist is a skeptic - a real one. Fake skeptics are only skeptical about things they disagree with and will swallow any kind of junk uncritically if it supports their notions.

  20. "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."

    So if we look at the past 30 years we should get the climate trend. According to skepticalscience's trend calculator from 1983 to 2013 the earth's temp has increased by 0.17 C per decade (GISTEMP moving average 12 months). Since CO2 has risen at about a linear rate since 1980 (according to: http://www.esrl.noaa.gov/gmd/ccgg/trends/), is it reasonable to predict a best guess rise of 1.7C from decades (1990 - 2000) to (2090 - 2100)? This would point to the low scenario from IPCC 2007, which has a best guess of 1.8C.

  21. Engineer, the issue is estimating climate sensitivity is non-linear feedbacks. Decreasing ice and increasing methane emissions would be two examples. Models attempt to build these influences in whereas linear extrapolation does not. 

  22. @ Scaddenp,

    Of course, but I thought climate sensitivity can be considered constant for small changes in temp. ∆T = k * 5.35*ln (C/C0), where k is climate sensitivity. I graphed 5.35*ln(C/C0) and it looks approximately linear in the range for C: (275 ppm, 550 ppm) and C0=275ppm. Is climate sensitivity not supposed to be considered constant even for small changes in temp?Thanks.

  23. But you would only expect temperature rise to be linear if transient climate sensitivity was same as equilibrium climate sensitivity. Emperical determinations of ECS suggest it is reasonably robust over quite a temperature range. However this is an observation, not an assumption.

  24. You would also need to separate out the other forcings at play if trying to establish k by simple fits. I would recommend Chpter 10 of the newly out AR5 WG1 which has a section on estimation of TCS and ECS, along with references to the papers which attempt this from various observational sets. The section of estimation from the instrumental record looks like it would interest you most.

  25. I have a friend of a friend who is a physicist.  He is ~not~ an AGW denier; he does however have objections to models as he claims they are used in climate science.  He fears that, to quote him:

    Where are the studies of model sensitivity to variations in the way any given model fixes up non-conservation of mass and/or energy? Every model I have looked at in detail has non-conservative processes, and they are always fixed up by hand at the end of each time step. This is a very bad thing. and I have yet to find any study on the sensitivity to the various choices one might make as to how to do this.

    I suggested he post this question himself, but since he didn't feel it worth his time (which, I pointed out, is maybe why, though ignorant myself, I shouldn't take his objection too seriously), I told him I'd post it and see what people had to say.  If this question doesn't explain his position clearly enough, I have some longer expositions of it I can post as well.

Prev  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  Next

Post a Comment

Political, off-topic or ad hominem comments will be deleted. Comments Policy...

You need to be logged in to post a comment. Login via the left margin or if you're new, register here.

Link to this page



The Consensus Project Website

THE ESCALATOR

(free to republish)


© Copyright 2022 John Cook
Home | Translations | About Us | Privacy | Contact Us