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

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How reliable are climate models?

What the science says...

Select a level... Basic Intermediate

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

Climate Myth...

Models are unreliable

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

At a glance

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

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

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

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

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

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

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

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

Further details

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Exxon climate graphics from Supran et al 2023

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

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

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

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

Printable Version  |  Offline PDF Version  |  Link to this page

Argument Feedback

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

Further reading

Carbon Brief on Models

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

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

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

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

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

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


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

Denial101x videos

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

Additional video from the MOOC

Dana Nuccitelli: Principles that models are built on.

Myth Deconstruction

Related resource: Myth Deconstruction as animated GIF

MD Model

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

Fact brief

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

fact brief


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Comments 1176 to 1200 out of 1331:

  1. @ ClimateDemon 1173

    Thank you for your response. I have a background in Operations Research developing and using models and simulations for other disciplines. This is partly why the models used for climate change predictions are of interest to me. I see that parts of your comment has been censored but my understanding is that AOGCM climate simulation models are in fact used to generate long-term predictions which in turn are used to justify carbon taxes and regulations. This is why I am challenging the validity of the models.

    I think I’m posting in the correct article which states the science is:
    “While there are uncertainties with climate models, they successfully reproduce the past and have made predictions that have been subsequently confirmed by observations.”

    So I am trying to understand what are these uncertainties as well as how well these models hindcast by acquiring an understanding of and hands on use of these AOGCM. I was looking for a university course that teaches this subject to climate researchers.

    You threw me off course by stating that models that accurately predict climate change are a set of differential equations because I haven’t seen that courses in differential equations or even calculus for that matter are course requirements for degrees in atmospheric sciences. So my questions are how are climate researchers taught to use and evaluate these models? And what course can I take that teaches the models that are used to generate long-term predictions which in turn are used to develop public policy?

    Thank you again for your help.

  2. Climate models are around 0.5 million line of code created by discipline experts for each of the climate processes. Starting from scratch to write your own is somewhat ambitious. Note that they are not statistically based so I am skeptical that a background in stats or operations research would help you much. The background requirement is numerical solution to systems of partial differential equations. No shortage of courses of these.

    I cannot comment on US university or course, but going into serious atmospheric sciences here would be based on undergraduate degree in physics and maths. The numerical solution of systems of partial differential equation is specialist area of mathematics - numerial analysis. Our institute (geology/geophysics) typically has mathematicians, programmers and subject specialists working together on problems of this kind of class.

    I still think predicting the base level of future isnt that hard. If surface irradiation increases, then surface gets warmer. The complicated bit is by how much will feedbacks magnify that effect. (Equilibrium Climate Sensitivity) And yes, predictions of future are based  are done by AOGCMs. However, there are also paleoclimate constraints on climate sensitivity. Too crude compared to models but good enough to cause serious concern. Again, the WG1 report is good place to find the papers on emperical constraints on climate sensitivitiy.

  3. @scaddenp 1177

    Thank you for your response. I don’t know what an AOGCM computer model looks like under the hood which is why I am looking for a university course on them. I have a minor in math, I took differential equations, I’ve taken Physics in Engineering school, I’ve not only written computer code but in my career I’ve project managed the creation of multi-million dollar IT systems. I wasn’t planning on writing a half million lines of code but I haven’t seen anything yet that would make me believe I would be in over my head working with an AOGCM model. But I haven’t been successful finding a way to actually work with one.

    I am somewhat confused by your comment. I would think there would be a plethora of courses on climate modeling otherwise how would all of the climate scientists learn how to construct and evaluate them? We have legions of climate researchers at the EPA, who taught them?

    I understand the paleoclimate approach but I am specifically interested in understanding the more sophisticated AOGCMs, specifically their fidelity on climate sensitivity. I’ve gone through the WG1 report and read the results and conclusions. But there are scientists who disagree with their conclusions. To understand the competing arguments I’m trying to educate myself on the models they are using and how they are used. I thought that taking a university course on the subject would be a good approach but not finding one I am stuck. How do the climate researchers at the EPA get the knowledge of which expert and model to believe? What course would they take?

    Thank you again for your help.

  4. Deplore_This: You are finding few courses because you are looking too narrowly for courses labeled specifically "Climate Modelling." As scaddenp explained, there are many components of GCMs, and they are used also independently from GCMS. Also, GCMS use theories, models, and computer code from multiple sub-disciplines.

    So nearly any course you take in atmospheric science will give you some knowledge about GCMs. If you try to take a course specifically about GCMs, you will need to have that prerequisite knowledge in order to gain the insight you say you want to gain. Just look at the Penn State meteorology course list, for example. In addition to the Modelling the Climate System course you wrote is "no longer offered," are many other courses that include solidly relevant knowledge for climate models. (By the way, universities do not offer all listed courses in every academic period. So that course unlikely is discontinued, because unlikely they would list it at all. It might happen to not be offered right now when you want it.) Just one example is course METEO 520: Geophysical Fluid Dynamics, whose prerequisites are vector calculus and differential equations.

  5. Deplore_This: Your own description of your background makes it sound like you are unlikely to benefit much from a specialized course in climate modeling, due to your lack of the prerequisite knowledge. So again I urge you to take some other courses, or if you really are dead set on diving into specifically GCMs (versus other types of models and theories), then get a textbook. Before you even attempt to write code for a GCM, or even look at the code of a GCM, experiment with the easier to use human-computer interface of the EdGCM project, whose underlying GCM is the actual GISS Model II GCM. If you want to look at the code of that underlying GCM, you can get it here.

  6. Deplore_This: The very first thing you might do is take Module 4: Introduction to General Circulation Models, from the Earth in the Future series.

  7. Deplore_This: Tim Osborn has an excellent web page Climate Models for Teaching.

  8. @Dayton 1179, 1180, 1181 and 1182

    Thank you for your responses. All of the other courses that reference GCM's that I've seen don't give me the opportunity to get under the hood of the models and determine for myself how they work. Your suggested Module 4: Introduction to General Circulation Models How Good are GCM's? is a perfect example. So is Tom Osborn's page. There are explanations but there is no way I can hands on understand the nuances of the models and confirm their observations.

    My objective is to understand the models themselves. I apologize in advance if this sounds rude but I really don't care what your opinion is concerning whether I have the sufficient prerequisites to take a course in this subject. Quite candidly, you're wasting your time trying to steer me in a different direction. I know where I want to go and I'm smart enough to determine if I meet the prerequisites for a particular course and to negotiate any shortfall with the school. My question is very simple, do you know of any course that is comparable to Penn State's METRO-523?

    Thank you again for your help and I apologize if I am being too coarse.

  9. Deplore_This: Clearly you are not actually interested in learning anything.

  10. @Dayton 1184

    That’s not very nice or respectful. I thought this was a scientific community. Please just answer my question; do you know of any course that is comparable to Penn State's METRO-523?

    Thank you.

  11. @Dayton

    It's OK if your answer is "no".  That isn't a problem.  No worries.

  12. Looking at CMIP6, I see about 100 different climate models from 49 modelling groups worldwide. Most of climate science is not building AOGCMs. Vast resources are required just to observe climate. I dont do GCMs but the models I work with and maintain involve people learning on the job not products of university courses. I expect the university to provide us with graduates who have the necessary skill base (physics, coding, numerical analysis) to be able to contribute and learn by getting their hands dirty improving the code or adding new features Models are developed by slow evolution.

    On a side note, as far as I can see EPA doesnt do any climate modelling of the AOGCM. I may be mistaken, but it also doesnt strike me as something that would be part of their brief.

    Most people dont have access to the kind machinery required to run an AOGCM.  You would be better getting the code from an earlier generation of models and starting with running that. You might want to look at the isca framework or an old model E. Tom has also suggested the EDCGM which looks an excellent way to learn how these are put together and get a feel for code. Lots of university resources based on it and fits with your desire to understand the models.

    "But there are scientists who disagree with their conclusions" Want to tell more about these people?  I assume you have investigated whether they have the requisite background to make useful criticism and not just reflecting an ideological bias.

  13. You can find the list of participants in the CMIP6 project here (via the map). CMIP models are what inform IPCC reports.

  14. @scaddenp

    Thank you for your response.  I'll look at the CMIP6 and respond to you.  But for now I have a quick question; When you say "us", what organization are you associated with?

    Thank you.


  15. I have a challenge for those who claim that I am making evidenceless assertions. Give me just one example of such an assertion. If you can, please do so and I will and I will make appropriate corrections. Otherwise, please don’t make such claims against me.

    Also, please keep in mind the fact that there are a few items upon which we must be in agreement, or there is no point in attempting to communicate.

    (1) The earth and its atmosphere are not in thermal equilibrium. This is well evidenced by the fact that temperature varies widely over the surface. If the globe were in thermal equilibrium, the surface temperature would be uniform.

    (2) The Clausius-Clapeyron equation is derived for determining the vapor pressure of a substance that is isolated and in thermal equilibrium with its condensed phase. While this equation may be useful in predicting local precipitation over ranges in which there is little temperature change, it is not applicable to global models or effects over which temperatures can vary by 50-60 degrees C.

    (3) We only use mathematical theorems or formulas within the range of their validity. This means we don’t apply the Pythagorean theorem to obtain the longest side of a non-right triangle. Similarly, we don’t use classical equations of motion to predict the motion of a particle traveling at or near the speed of light. Finally, we do not apply the Clausius-Clapeyron equation to the earth and atmosphere system for predicting global effects.

  16. ClimateDemon @1190 ,

    You have made the mistake of promoting "binary" assertions ~ all-or-nothing, black-or-white.  Not "evidenceless"  assertions ~ but illogical assertions.  Illogical, because not sufficiently evidential  i.e. you have chosen to cherry-pick one small area which pleases you, and you have ignored the bigger context that displeases you (and which does not support your assertions).   You have therefore failed to think logically.

    (1)  The globe as a whole is in thermal equilibrium (or very close to it) over duration of time.  Obviously the globe is warming gradually, as evidenced by melting ice and rising sea level.  Surface temperature varies : and the seasonal and historical evidence is that this variation has tight bounds.

    (2)  The Clausius-Clapeyron equation describes physical activities ~ at any local terrestrial site, of varying temperature humidity and pressure.  Obviously these activities operate within bounds, and so can be said to be in a form of equilibrium dynamically within these limits and durations.

    (3)  Because of the above, the C-C equation does apply "to the earth and atmosphere system for predicting global effects"  ~ which have been observed and measured in recent decades.

    ( If my memory serves me, you have fruitlessly questioned these concepts, in other threads in past years. )

  17. Deplore_This:

    I am still unsure as to exactly what you expect to accomplish with respect to climate models. So far, it looks like you have a pre-conception that something must be wrong, and you are on a search for details to support that position. I think you may experience a bad case of confirmation bias, if your postings here are an indication.

    As has been pointed out, climate General Circulation Models (GCMs) are only a small part of climate science. I suggest that you read Spencer Weart's "The Discovery of Global Warming" to learn more about climate science in general.

    In addition, you seem to be under the impression that GCMs represent a "single" climate model. They do not. A GCM is a collection of many types of climate-related models that are knit together to provide a comprehensive view of climate - much as the science of climatology has many, many areas of specialization that need to be knit togther to form a  full picture. Areas that represent distinct sub-classes of "climate" models include (but are not limited to):

    • radiation transfer. Much detailed work was done in the 1960s, when the military wanted to make sure that their IR-seeking missiles would hit the intended targets. (HInt: their "target" was not "climate")
    • atmospheric dynamics (motions). Especially important for weather forecasting. The general field is "Geophysical Fluid Dynamics" (GFD) and atmospheric motion is only one area of application. The same science is used to model air flow on airplane wings, or fluids in pipes or in-ground oil reservoirs, etc. Each application has its own specific issues, so modelling approaches differ - but there is a lot in common.
    • ocean dynamics. Another application of GFD, Oceans have some different issues from atmospheric motions, though.
    • Surface energy balance issues. Receipt of radiation, partitioning into evapotranspiration, thermal fluxes (to atmosphere, to soil or water). Effects of surface type, vegetation, etc. Often referred to as "microclimate". (This was my area of specialization when I worked in the discipline.)
    • soil heat transfer.
    • cloud physics.
    • and so on.

    And once the climatologists develop their theories, there is the task of finding efficient algorithms to transform the science (usually in some mathematical form) into computer solutions. Generally covered as "Numerical Methods" in the computing science world. Systems of partial differential equations that cah be solved either through finite difference, finite element, or spectral methods. These methods are not unique to "climate science".

    No single university course is going to cover the full level of details of every aspect of climate models - or climatology in general. Different groups that develop GCMs make different decisions on which components of which "climate" sub-models will be incorporated, and how they want to code numerical solutions.

    These difference approaches lead to different results in detail, but the broad picture is the same: CO2 from fossl fuels plays an important role in current temperature trends.

  18. @scaddenp 1187

    Thank you for your response. To answer your question here this is an example of scientists who disagree with the IPCC’s conclusion on GCMs:

    “GCMs are important tools for understanding the climate system. However, there are broad concerns about their reliability:

    • GCM predictions of the impact of increasing carbon dioxide on climate cannot be rigorously evaluated on timescales of the order of a century.
    • There has been insufficient exploration of GCM uncertainties.
    • There are an extremely large number of unconstrained choices in terms of selecting model parameters and parameterisations.
    • There has been a lack of formal model verification and validation, which is the norm for engineering and regulatory science.
    • GCMs are evaluated against the same observations used for model tuning.
    • There are concerns about a fundamental lack of predictability in a complex nonlinear system.

    There is growing evidence that climate models are running too hot and that climate sensitivity to carbon dioxide is at the lower end of the range provided by the IPCC. Nevertheless, these lower values of climate sensitivity are not accounted for in IPCC climate model projections of temperature at the end of the 21st century or in estimates of the impact on temperatures of reducing carbon dioxide emissions. The IPCC climate model projections focus on the response of the climate to different scenarios
    of emissions. The 21st century climate model projections do not include:

    • a range of scenarios for volcanic eruptions (the models assume that the volcanic activity will be comparable to the 20th century, which had much lower volcanic activity than the 19th century
    • a possible scenario of solar cooling, analogous to the solar minimum being predicted by Russian scientists
    • the possibility that climate sensitivity is a factor of two lower than that simulated by most climate models
    • realistic simulations of the phasing and amplitude of decadal- to century-scale natural internal variability

    The climate modelling community has been focused on the response of the climate to increased human caused emissions, and the policy community accepts (either explicitly or implicitly) the results of the 21st century GCM simulations as actual predictions. Hence we don’t have a good understanding of the relative climate impacts of the above or their potential impacts on the evolution of the 21st century climate.”
    -— Judith Curry, the former Chair of the School of Earth and Atmospheric Sciences at my alma mater

  19. @scaddenp 1187

    Here is another example of scientists who disagree with the IPCC’s conclusion on GCMs where more than 500 scientists and professionals in climate and related fields sent a “European Climate Declaration” to the Secretary-General of the United Nations asking for a “long-overdue, high-level, open debate on climate change” and were denyed.

    “There is no climate emergency…Climate science should be less political, while climate policies should be more scientific. Scientists should openly address the uncertainties and exaggerations in their predictions of global warming, while politicians should dispassionately count the real benefits as well as the imagined costs of adaptation to global warming, and the real costs as well as the imagined benefits of mitigation.”

    “Natural as well as anthropogenic factors cause warming. The geological archive reveals that Earth’s climate has varied as long as the planet has existed, with natural cold and warm phases. The Little Ice Age ended as recently as 1850. Therefore, it is no surprise that we now are experiencing a period of warming.”

    “Warming is far slower than predicted. The world has warmed at less than half the originally-predicted rate, and at less than half the rate to be expected on the basis of net anthropogenic forcing and radiative imbalance. It tells us that we are far from understanding climate change.”

    “Climate policy relies on inadequate models. Climate models have many shortcomings and are not remotely plausible as policy tools. Moreover, they most likely exaggerate the effect of greenhouse gases such as CO2. In addition, they ignore the fact that enriching the atmosphere with CO2 is beneficial.”

    “There is no statistical evidence that global warming is intensifying hurricanes, floods, droughts and suchlike natural disasters, or making them more frequent.” “However, CO2-mitigation measures are as damaging as they are costly. For instance, wind turbines kill birds and bats, and palm-oil plantations destroy the biodiversity of the rainforests.”

    “We invite you to organize with us a constructive high-level meeting between world-class scientists on both sides of the climate debate early in 2020. The meeting will give effect to the sound and ancient principle no less of sound science than of natural justice that both sides should be fully and fairly heard. Audiatur et altera pars!”

  20. @scaddenp

    As I stated in my first post 1162 I am an anthropogenic climate change skeptic because I’ve read criticism of the validity of the climate temperature models referenced by the IPCC like those posted in 1193 and 1194. The corrupt media and the bureaucrats at the EPA say it’s settled science but I see no record of balanced climate research or any open debate. It appears that scientists who raise doubts of the validity are shunned and unfunded.

    So my dilemma is how do I know what and who to believe. It is my nature not to blindly believe anything, especially what the government tells me. I thought a solution would be to take a university course in climate modelling so that I could hands on use and understand the development of GCMs and form my own opinion. If this was the 16th century and I’d probably get a telescope to test Galileo’s claim of heliocentrism. I am surprised to find that there aren’t such courses which leads to an even more startling revelation that the majority of the “97% of climate experts agree humans are causing global warming” have never been taught or used a GCM themselves and base their opinion on the opinion of others. To me that looks more like group think than science. And they call us climate skeptics “flat earthers”.

    So my dilemma remains and I’m not sure what to do next. I may contact Penn State and see if course material is available from their last course on GCM. I’m not going down the paleological path because there are other issues there and because the IPCC’s opinion that is used for public policy is based on GCM predictions. I remain open to any suggestions. Thank you again for your help.

  21. @Bob Lowlaw 192

    Thank you for your response. As I stated in my first post 1162 and my post at 1195 I am an anthropogenic climate change skeptic because I’ve read criticism of the validity of the climate temperature models referenced by the IPCC like those posted in 1193 and 1194. I am aware that there are multiple climate models and classes of climate models. According to the syllabus the Penn State course I referenced included multiple climate system components including atmosphere, ocean, land, cryosphere, biosphere, role of parameterizations and model coupling.

    Without repeating my post at 1195 I’ll just state here that I remain open to any suggestions. Thank you again for your response.

  22. Deplore_This:

    Judith Curry is not, I repeat, not, a reliable source of information. She peddles "uncertainty", and much of what she says is simply wrong. Start here:

    and continue here:

    In addition, pretty much anything published by the GPWF is full of crap:

    Same for the Climate Intelligence Foundation:

    You need to find better sources of information. You're paying attention to people that are selling shite to you.

  23. @Bob Lowlaw 1197

    As I stated Judith Curry was the Chair of the School of Earth and Atmospheric Sciences at my alma mater. I don’t know her personally but I know people who do and they tell me she is credible. As a courtesy I reviewed your links and I don’t see anything that refutes that opinion. It appears to me that Judith Curry is a scientist who disputes some of the “group think” and is shunned and unfunded. If the climate science community can not engage in open debate then it is not practicing science. As a climate skeptic I am accused of not believing science but without open debate it is not science.

    Bob, I believe Judith Curry before I believe you. So my dilemma remains and I’m not sure what to do next. Thank you for your response.

  24. Deplore_This:

    Who tells you she is "credible"? On what basis are they credible?

    You have chosen who you are going to believe. That is not the sign of a skeptic. You have bought into the shite they are selling to you. There are lots of places on the internet that will point out the crap you have read that is confirming your bias.

    Go read the Spencer Weart link I posted earlier.

    Have you read the IPCC reports, or do you just read the comments about the IPCC that you get from your "credible" sources?

    I agree with Tom Dayton. You are not here to learn anything.

  25. @Bob Lowlaw 1199

    Quit with your sanctimonious crap. It certainly doesn’t reflect well on your scientific reputation. I came here stating that I’m a skeptic and wanted a recommendation for university course on GCM, not to believe one person over another.

    Judith Curry was the Chair of the School of Earth and Atmospheric Sciences at a well-respected technical university and was obviously imminently qualified to get the job. I’m not going to post people’s names on the Internet to satisfy your curiosity.

    I looked at the Spencer Weart link and I’m already beyond that level. I have read the IPCC reports.

    If you were going to scientifically challenge Judith Curry’s opinions that I referenced you would point to published scientific scrutiny and not just make juvenile comments. The more emotional you become the more you add to her credibility in my eyes.


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