Climate Science Glossary

Term Lookup

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


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


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

Bluesky Facebook LinkedIn Mastodon MeWe

Twitter YouTube 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...

New? Register here
Forgot your password?

Latest Posts


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


Prev  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  Next

Comments 1251 to 1275 out of 1311:

  1. "What makes you think I haven't looked at those sources ..."

    If you had looked at them properly and with an open mind then you would have formed more specific and meaningful questions. That is why I think you have not looked at them. 

    The "control knob is easily debunked" is not a statement that is easy to engage with. 

  2. John Seers @1251

    I only asked how the current climate models show that humans are causing global warming — nothing more, nothing less.  How much more "specific" am I supposed to be?  It is these "sources" that are vague and not answering my question.  Frankly, I am very much disturbed by the fact that the climate science "experts" are using every scare tactic available to get nations to drastically cut CO2 emissions at a great economic sacrifice, yet none can give a straight answer as to how they used their models to conclude there is global warming and that humans are causing it.  Making your studies clear and traceable is an important part of doing good science, and it is not happening in the AGW community.


    [TD] At the top of the home page there is a big image labeled "Newcomers, start here." In the resulting "Welcome to Skeptical Science" page, look for the section "Good starting points for newbies." Click the links in that section.

  3. ClimateDemon @1252,

    Are you familiar with the United Nations Intergovernmental Panel on Climate Change? I ask because your comment @1252 only makes sense if you are not familiar with this organisation and its work. I would draw your attention to IPCC AR5 WG1 which reviews the science showing both that "there is global warming" and that "humans are causing it." I would draw your attention to Chapter 10 'Detection and Attribution of Climate Change:from Global to Regional' and, as you have show interest specifically in the role of CO2 in the global warming, also Chapter 5 'Information from Paleoclimate

  4. ClimateDemon - here is a challenge for you: register for our MOOC "Denial101x - Making sense of climate science denial" and work through the six weeks worth of lectures. You'll get a good understanding of the basics of climate science - including about models - and how/why these basics get regularly distorted. Once done, come back to the comment threads here with any clarifying questions you might still have.  But frankly, there shouldn't really be (m)any as what you keep asking here has been answered more than enough already - it's up to you to put in the effort to learn and understand.

    Here is the link to the MOOC:

  5. Climate Demon @ 1252

    For you to say you have asked a question and "nothing more, nothing less" is disingenuous. Comments like "the control knob is easy to debunk" say a whole lot more. 

    Others more knowledgeable than me have attempted to signpost you to more enlightening information but you think you are too informed to be bothered with that.

    I will give a partial answer to your no more, no less question. The question iteself shows you are not really clued up enough. Climate models do not provide proof humans are causing global warming. Climate models are a consequence of the scientists testing their theories against the data and evidence. They prove nothing in themselves. They are confirmation of what we think we know and help us feel we are on the right track. If we trust them enough we can use them for projections. Our trust grows over time as they are developed and used. (And as our computers get faster!)

    Models are one piece of evidence (not proof) of the consilience of evidences that add up to proof of AGW. That is evidence from many sources and lines of enquiry all point in the direction of AGW. 

    So, how much more specific can you be? A suggestion is you look through the references supplied (I recommend the Richard Alley lectures and his course) and then, (as you can simply debunk them Ha Ha), form a very specific question and work through it with the refutations you will get. You might learn something if you do it diligently.


  6. I'm trying to make sense of Climate Demon post at 1252 and it's difficult.

    This "they used their models to conclude there is global warming" is rather strange. The real situation is: the models suggest that global temperatures would rise under an increase in non-precipitable GHG scenario, accompanied by other phenomena like some decrease in stratospheric temp and changes in tropopause height, etc. Independently of models, multiple observations (tropospheric temps, sea surface temps, stratospheric temps, sea level, species movement upward and poleward, Arctic sea ice loss, etc) show without a doubt that there is global warming. These observations are what leads to the conclusion that there is global warming, not the models. They are, however, consistent with the expectations obtained from models when increased forcing from non-precipitable GHG are introduced. All this is in the original post.

  7. BaerbelW @1254

    I have seen some of the videos and other materials used in this course, and I highly doubt that you and the other faculty/staff members would want me in it.

  8. Well, I must thank you all for sending me such an impressive stack of references covering various aspects of arguing for AGW, most of which I have never heard about, and I will agree that as scientists, we must consider all available evidence on any issue before coming to a conclusion. I must also point out, however, that a chain is only as strong as its weakest link, and with AGW, the CO2 “control knob” is absolutely essential, yet it has never been proven. Without such a control knob, H2O vapor becomes the controlling as well as the strongest GHG, and in this case human contributions to temperature changes would be insignificant.

    In most of the peer-reviewed literature on climate change, existence of the control knob is simply assumed without references or supporting arguments. If references are given, I find they don’t explain the justification for the control knob either. The only paper I have found that even pretends to address this issue is the Lacis et. al. 2010 paper that I cited in a few earlier postings, although I have heard that other authors have made similar arguments. The problem, however, is that they make two false assumptions in setting up their model. First, they use a zero-dimensional model which assumes a single-temperature earth whereas temperatures on the real earth can vary by 50-60 degrees C over the surface. Second, they apply the Clausius Clapeyron equation to obtain the water vapor concentration. This equation assumes constant thermal equilibrium when in fact the earth is never in thermal equilibrium. Thus, there is no valid proof of the CO2 control knob effect.

    Unfortunately, since we cannot establish the existence of a CO2 control knob, all of those references you sent me are rendered meaningless.


    [DB]  Continuing to make things up is unhelpful.  Sloganeering snipped.

  9. ClimateDemon @1258,

    It appears you require your feed of information served up to you in the most readily consumable form.

    Lacis et al 2010 use a model. You say that model is "a zero-dimensional model which assumes a single-temperature earth."

    The model used was GISS ModelE. This model is a full-blown GCM. What you say about GISS ModelE is complete and utter nonsense.

  10. " Without the radiative forcing supplied by CO2 and the other noncondensing greenhouse gases, the terrestrial greenhouse would collapse, plunging the global climate into an icebound Earth state."

    Link to publication


    (BW) re-formatted the link

  11. ClimateDemon @1257

    Well, judging from your comments here, you'd provide ample examples for the students in our MOOC of how science denial can look like! Your contributions in the forum might therefore end up as actual case studies for them of what they'll encounter in real life! And who knows, you might still learn something - at least if you are prepared to really engage with the material and watch the expert interviews included in the course.

  12. Climate Demon @1258

    You have gone from "the control knob is easily debunked" to "absolutely essential" (for AGW) to "never been proven" to "simply assumed" to some waffle about zero-dimensional models to some mumbo-jumbo about Claudius Clapeyron to there is "no valid proof".

    You finish with a flourish. Everything is "rendered meaningless"

    It's a bit of a cop-out on your part, isn't it? Just make a list of random assertions, assert it is all meaningless and pat yourself on the back. 

    Sorry, you have to put more effort into it than that.

  13. Yes, Baerbel, ClimateDemon is a good example of denial because he's such a bad example. Even in his most recent post:

    • "...most of which I have never heard about..."

    ...but he still knows

    • "In most of the peer-reviewed literature on climate change, existence of the control knob is simply assumed ..."

    ...and he concludes

    • "...all of those references you sent me are rendered meaningless."

    So, he isn't aware of of much of what we pointed to, but knows that the entire field of climatology assumes things that they don't, and dismisses an entire field of science as "meaningless" even though he isn't aware of what it contains. Rinse, Repeat.

    It doesn't matter what is presented to him - without reading it, he knows it is all wrong.

    The Morton's Demon is strong in ClimateDemon.

  14. BaerbelW, I rather think that Climatedemon is like our old friend cosmowarrior/coolearth et al.  He/she struggles to comprehend information that is at odds with prior beliefs so would struggle in the course.

  15. MA Rodger @1259

    In Lacis et. al. (2010) the authors state:

    A clear demonstration is needed to show that water vapor and clouds do indeed behave as fast feedback processes and that their atmospheric distributions are regulated by the sustained radiative forcing due to the noncondensing GHGs. To this end, we performed a simple climate experiment with the GISS 2° × 2.5° AR5 version of ModelE, using the Q-flux ocean with a mixed-layer depth of 250 m, zeroing out all the noncondensing GHGs and aerosols.

    Now, the authors did not provide the input data they used, but they did say they performed a simple demonstration. Of course, I don’t know their definition of “simple”, but I believe it most likely would include a uniform temperature and zero fluid velocity and pressure gradients. Also, examining Figure 2, I see that one of the results of their ModelE runs is a single-value global temperature for each time point, which we already know is unrealistic. Although I am not familiar with ModelE, I do know a few things about GCMs in general, including the fact that the results of any such number crunching is highly dependent upon the initial conditions, many of which are unknown. This is what makes these models “tweakable” for purposes of hindcasting, but even that process is far from perfect. Although the ModelE demonstrations may well have produced valid results for the particular set of initial conditions chosen, they should not be regarded as “typical” output from the model.

    Therefore, my claim that the CO2 “control knob” has not been proven still stands.

  16. I would like to post this fun question to all of you AGW folks and anyone else interested in participating.  And who knows?  It may just resolve some confusion about the concept of thermal equilibrium.

    Suppose we have a planet similar to Earth, except that the temperature is everywhere uniform.  But like Earth, much of the surface is covered with water and the terrain outside of the water has varying elevations.  At the lower elevations the air is generally moist and there are lots of lakes and rivers, and at the higher elevations, the air is much dryer and the climate is much more desert-like.

    Question:  Is this planet in global thermal equilibrium?

  17. ClimateDemon @1266 , your question must necessarily include a pre-condition ~ How long can this planet maintain equilibrium?

    You propose an interesting hypothetical planet.  To have a uniform surface temperature, that would require it be evenly surrounded by a sphere of identical suns numbering 40 (better, 100 or more).  Unfortunately, the planet's central location would not be gravitically stable, and the planet would drift into one of the suns.  So the planet's evenly-distributed temperature would persist until shortly before impact.

    The unpleasant scenario would have to include the 40 (or 100) suns gravitically attracting each other, and converging to the original central location including the planet (unless the planet had moved some distance ~ owing to the chaotic & nonlinear wing-flapping of an especially powerful gravitic butterfly).

    The Clausius-Clapeyron Equation indicates that the planet's beautiful lakes rivers & oceans would rapidly enter a state of very low relative humidity . . . until reaching the plasma state [a state not describe by the C-C Equation, if I understand your earlier comments].

    (Moderators may care to remove this slightly Off-Topic post. )

  18. ClimateDemon @1265,
    Bar moderator intervention, you are of course at liberty to parade your ignorance here.

    What do you not understand about "GISS 2° × 2.5° AR5 version of ModelE"? Presumably all of it. (You might find this CarbonBrief article on GCMs useful in raising your understanding of GCMs to a less embarassing level.) And why would the values presented in the paper's Fig 2 throw any light on the complexity of the model used to generate them when, as the Fig 2 clearly states, they present "Global Annual Mean" data? Without there being more than one "globe", such a graph will only have "a single-value global temperature for each time point".

    As for your little speech about "inital conditions", perhaps you can give an example of which of these "inital conditions" could be "tweeked" to alter the fundamental finding of Lacis et (2010). (Remember this simple experiment is removing some 30Wm^-2 of greenhouse effect. Such a climate forcing, even without feedbacks, is enough to drop global average temperatures by far more that the last ice age achieved.)

    ClimateDemon @1266,
    I assume your cunningly crafted question is intended to show that a model of an Earth-like planet's climate in which "the temperature is everywhere uniform" would not capture the topological complexity of such a planet. As Lacis et al did not use such a model, your question is entirely misplaced.

  19. ClimateDemon:

    Since you seen keen on the concept, why don't you explain, in complete and unambigous terms, just exactly what you think you mean by "global thermal equlibrium".

    Unless you have a working definition of that phrase, you're just playing games, not doing science.

  20. MA Rodger @1268

    All right, so scrap the entire 1265 posting.  I never was very good at guessing games anyway.  If you go to the paragraph that starts near the top of the third column on page 357, however, you will see that the authors of the Lacis et. al. (2010) paper do in fact use that zero dimensional model with a single temperature earth to make some prediction on the sustainable amount of atmospheric water vapor in the example they were showing.  Their ModelE runs were for something else.

  21. ClimateDemon @1270:

    You mean where Lacis et al use the phrase "If the global atmospheric temperatures were to fall as low as TS=TE..."

    Clearly, you have no idea what Lacis et al are saying when they use the symbols TS and TE, even though they explain it in the second paragraph of the paper: "...mean surface temperature (TS = 288 K) and the global mean effective temperature (TE = 255 K)...

    That they describe a three-dimensional system by using mean values does not indicate they used a zero-dimensional model.

    Frankly, you have absolutely no idea what you are talking about.

  22. ClimateDemon, I will simplify Bob Loblaw's response to you. Here is a set of numbers: 8, 15, 3, 9, 4. Here is a "descriptive statistic" that summarizes the central tendency of that set of numbers, thereby making the set as a whole easier to understand for some purposes, by subsuming its details: The mean of that set is 7.8.

    Now look at my second sentence written above. Those five numbers still are there. They did not magically disappear merely because I typed their mean as "7.8." That ability is called "object permanence."


    [DB] The user in question has recused themselves from further participation in this venue.

  23. SpaceMan @1273,

    Your presence here may be limited (as the moderator response @1272 implies) but while you are here, the speculation set out by Lacis et al (2010) which talks of "TS=TE" and "the Clausius-Clapeyron relation" is part of an illustrative introduction to their employment of a full General Circulation model, such models being stacked full of 'dimentional' stuff. Are you with me so far? If so, that would be good, as that puts an end to your nonsense about them using zero-dimension climate models.


    [TD] Indeed, they are a sock puppet and have been removed.

  24. I have a few comments:

    1. These so called models, many of them, were made with public money.  Why has the public no access to play with the models?  For example, enter inputs (CO2 concentrations), and see what the predicted outputs (e.g.  temperature) are.   

    2. Where are these models, who programmed them, who owns them, who controls them, who maintains them, who checks them?

    3. From the best public models, what are the predictions the models are making?  Are these predictions published?  Can we compare future outcomes vs model predictions?  Do these models predict based on scenarios?   What percent of previous models been correct in their predictions?    Which accessible model is the best one, based on past predictions/forecasts vs. actual empirical data.  What are the current predictions of this model ?  Are these predictions contingent on certain scenarios, conditions and assumptions?  What are these?  Have these been documented, published and made public?  

    “What can be asserted without evidence can also be dismissed without evidence.”


    [DB] Sloganeering snipped.

  25. gzzm2013:

    1. The General Circulation Models (GCMs) can run only on supercomputers. (Well, they can run on lesser hardware in principle, but you'd need to wait years, decades, or centuries for results.) There are numerous dramatically simpler models used for teaching the principles, such as this one by Tim Osborn that you can play with as you requested. Tamino described a model you can play with, without needing a computer at all. Other evidence not involving computer models is abundant on this SkepticalScience site, and in a huge number of other sources, including a video by investigative journalist Potholer54.

Prev  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  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


(free to republish)

© Copyright 2024 John Cook
Home | Translations | About Us | Privacy | Contact Us