Climate myths are contradictory or contain reasoning errors. A guide to countering industry lies


Researchers propose deploying strategy in classrooms and on social media to teach people how to “neutralize” misinformation.  By Jessica Corbett, staff writer, Common Dreams, 6 Feb 2018

Also in The Guardian

Climate myths are often contradictory – it’s not warming, though it’s warming because of the sun, and really it’s all just an ocean cycle – but they all seem to share one thing in common: logical fallacies and reasoning errors.

John Cook, Peter Ellerton, and David Kinkead have just published a paper in Environmental Research Letters in which they examined 42 common climate myths and found that every single one demonstrates fallacious reasoning. For example, the authors made a video breaking down the logical flaws in the myth ‘climate changed naturally in the past so current climate change is natural.’

Peter Ellerton, one of the researchers, explains the six-step strategy in a video released Tuesday. (Photo:UQx Denial101x Making Sense of Climate Science Denial/Screenshot)

After examining more than 40 common climate change myths pushed by those who are hell-bent on discrediting scientific conclusions about the global crisis, three researchers teamed up to create a six-step critical thinking tool that helps people combat misinformation by “neutralizing” the lies.

John Cook, Peter Ellerton, and David Kinkead detailed their strategy in “Deconstructing climate misinformation to identify reasoning errors,” published Tuesday by Environmental Research Letters. The researchers also released a video that demonstrates what battling climate crisis lies can look like in everyday life.

“We offer a strategy based on critical thinking methods to analyze and detect poor reasoning within denialist claims,” the paper explains. “This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language.”

While the researchers mapped out the steps in a flow chart, Dana Nuccitelli at the Guardian included examples in his outline of the six-step process:

Step 1: Identify the claim being made. For example, the most popular contrarian argument: “Earth’s climate has changed naturally in the past, so current climate change is natural.”

Step 2: Construct the argument by identifying the premises leading to that conclusion. In this case, the first premise is that Earth’s climate has changed in the past through natural processes, and the second premise is that the climate is currently changing. So far, so good.

Step 3: Determine whether the argument is deductive, meaning that it starts out with a general statement and reaches a definitive conclusion. In our case, ‘current climate change is natural’ qualifies as a definitive conclusion.

Step 4: Check the argument for validity; does the conclusion follow from the premises? In our example, it doesn’t follow that current climate change must be natural because climate changed naturally in the past. However, we can fix that by weakening the conclusion to “the current climate change may not be the result of human activity.” But in its weakened state, the conclusion no longer refutes human-caused global warming.

Step 4a: Identify hidden premises. By adding an extra premise to make an invalid argument valid, we can gain a deeper understanding of why the argument is flawed. In this example, the hidden assumption is “if nature caused climate change in the past, it must always be the cause of climate change.” Adding this premise makes the argument logically valid, but makes it clear why the argument is false—it commits single cause fallacy, assuming that only one thing can cause climate change.

Step 5: Check to see if the argument relies on ambiguity. For example, the argument that human activity is not necessary to explain current climate change because natural and human factors can both cause climate change is ambiguous about the ‘climate change’ in question. Not all climate change is equal, and the rate of current change is more than 20 times faster than natural climate changes. Therefore, human activity is necessary to explain current climate change.

Step 6: If the argument hasn’t yet been ruled out, determine the truth of its premises. For example, the argument that “if something was the cause in the past, it will be the cause in the future” is invalid if the effect has multiple plausible causes or mechanisms (as with climate change). In our example, this is where the myth most obviously falls apart (although it had already failed in Step 4).

The paper notes that “social media presents one potent option” for deploying their strategy, as does the classroom. Acknowledging “there is in general a dearth of misconception-based learning resources for educators”—particularly when it comes to climate education—the paper emphasizes “this research is designed to act as a building block for developing educational material that teaches critical thinking through the examination of misinformation and evaluation of arguments.”

“This approach is practical, achievable, and potentially impactful in both the short-term (e.g., in social media applications) and long-term (incorporating this kind of content into curriculum),” Cook, the lead author, told the Guardian. “Misinformation needs short, sharp, immediate inoculation. Our paper provides a blueprint into how to write these inoculations.”

The basic facts about the global increase of CO2 in our atmosphere are clear and established beyond reasonable doubt. Nevertheless, I’ve recently seen some of the old myths peddled by “climate skeptics” pop up again. Are the forests responsible for the CO2 increase? Or volcanoes? Or perhaps the oceans?

Let’s start with a brief overview of the most important data and facts about the increase in the carbon dioxide concentration in the atmosphere:

  1. Since the beginning of industrialization, the CO2 concentration has risen from 280 ppm (the value of the previous millennia of the Holocene) to now 405 ppm.
  2. This increase by 45 percent (or 125 ppm) is completely caused by humans.
  3. The CO2 concentration is thus now already higher than it has been for several million years.
  4. The additional 125 ppm CO2 have a heating effect of 2 watts per square meter of earth surface, due to the well-known greenhouse effect – enough to raise the global temperature by around 1°C until the present.

Fig. 1 Perhaps the most important scientific measurement series of the 20th century: the CO2concentration of the atmosphere, measured on Mauna Loa in Hawaii. Other stations of the global CO2 measurement network show almost exactly the same; the most important regional variation is the greatly subdued seasonal cycle at stations in the southern hemisphere. This seasonal variation is mainly due to the “inhaling and exhaling” of the forests over the year on the land masses of the northern hemisphere. Source (updated daily): Scripps Institution of Oceanography.

Fig. 2 The CO2 concentration of the atmosphere during the Holocene, measured in the ice cores from Antarctica until 1958, afterwards Mauna Loa. Source: Scripps Institution of Oceanography.

These facts are well known and easy to understand. Nevertheless, I am frequently confronted with attempts to play down the dangerous CO2-increase, e.g. recently in the right-leaning German newspaper Die Welt.

Are the forests to blame?

Die Welt presented a common number-trick by climate deniers (readers can probably point to some english-language examples):

In fact, carbon dioxide, which is blamed for climate warming, has only a volume share of 0.04 percent in the atmosphere. And of these 0.04 percent CO2, 95 percent come from natural sources, such as volcanoes or decomposition processes in nature. The human CO2 content in the air is thus only 0.0016 percent.

The claim “95 percent from natural sources” and the “0.0016 percent” are simply wrong (neither does the arithmetic add up – how would 5% of 0.04 be 0.0016?). These (and similar – sometimes you read 97% from natural sources) numbers have been making the rounds in climate denier circles for many years (and have repeatedly been rebutted by scientists). They present a simple mix-up of turnover and profit, in economic terms. The land ecosystems have, of course, a high turnover of carbon, but (unlike humans) do not add any net CO2 to the atmosphere. Any biomass which decomposes must first have grown – the CO2 released during rotting was first taken from the atmosphere by photosynthesis. This is a cycle. Hey, perhaps that’s why it’s called the carbon cycle!

That is why one way to reduce emissions is the use of bioenergy, such as heating with wood (at least when it’s done in a sustainable manner – many mistakes can be made with bioenergy). Forests only increase the amount of CO2 in the air when they are felled, burnt or die. This is immediately understood by looking at a schematic of the carbon cycle, Fig. 3.

Fig. 3 Scheme of the global carbon cycle. Values ​​for the carbon stocks are given in Gt C (ie, billions of tonnes of carbon) (bold numbers). Values ​​for average carbon fluxes are given in Gt C per year (normal numbers). Source: WBGU 2006 . (A similar graph can also be found at Wikipedia.) Since this graph was prepared, anthropogenic emissions and the atmospheric CO2 content have increased further, see Figs 4 and 5, but I like the simplicity of this graph.

If one takes as the total emissions a “natural” part (60 GtC from soils + 60 GtC from land plants) and the 7 GtC fossil emissions as anthropogenic part, the anthropogenic portion is about 5% (7 of 127 billion tons of carbon) as cited in the Welt article. This percentage is highly misleading, however, since it ignores that the land biosphere does not only release 120 GtC but also absorbs 122 GtC by photosynthesis, which means that net 2 GtC is removed from the atmosphere. Likewise, the ocean removes around 2 GtC. To make any sense, the net emissions by humans have to be compared with the net uptake by oceans and forests and atmosphere, not with the turnover rate of a cycle, which is an irrelevant comparison. And not just irrelevant – it becomes plain wrong when that 5% number is then misunderstood as the human contribution to the atmospheric CO2 concentration.

The natural earth system thus is by no means a source of CO2 for the atmosphere, but it is a sink! Of the 7 GtC, which we blow into the atmosphere every year, only 3 remain there. 2 are absorbed by the ocean and 2 by the forests. This means that in the atmosphere and in the land biosphere and in the ocean the amount of stored carbon is increasing. And the source of all this additional carbon is the fact that we extract loads of fossil carbon from the earth’s crust and add it to the system. That’s already clear from the fact that we add twice as much to the atmosphere as is needed to explain the full increase there – that makes it obvious that the natural Earth system cannot possibly be adding more CO2 but rather is continually removing about half of our CO2 emissions from the atmosphere.

The system was almost exactly in equilibrium before humans intervened. That is why the CO2concentration in the air was almost constant for several thousand years (Figure 2). This means that the land ecosystems took up 120 GtC and returned 120 GtC (the exact numbers don’t matter here, what matters is that they are the same). The increased uptake of CO2 by forests and oceans of about 2 GtC per year each is already a result of the human emissions, which has added enormous amounts of CO2 to the system. The ocean has started to take up net CO2 from the atmosphere through gas exchange at the sea surface: because the CO2 concentration in the atmosphere is now higher than in the surface ocean, there is net flux of CO2 into the sea. And because trees take up CO2 by photosynthesis and can do this more easily if you offer them more CO2 in the air, they have started to photosynthesize more and thus take up a bit more CO2 than is released by decomposing old biomass. (To what extent and for how long the land biosphere will remain a carbon sink is open to debate, however: this will depend on the extent to which the global ecosystems come under stress by global warming, e.g. by increasing drought and wildfires.)

The next diagram shows (with more up-to-date and accurate numbers) the net fluxes of CO2 (this time in CO2 units, not carbon units!).

Fig. 4 CO2 budget for 2007-2016, showing the various net sources and sinks. The figures here are expressed in gigatons of CO2 and not in gigatons of carbon as in Fig. 3. The conversion factor is 44/12 (molecular weight of CO2 divided by atomic weight of carbon). Source: Global Carbon Project.

Fig. 5 shows where the CO2 comes from (in the upper half you see the sources – fossil carbon and deforestation) and where it ends up (in the lower half you sees the sinks), in the course of time. It ends up in comparably large parts in air, oceans and forests. The share absorbed by the land ecosystems varies greatly from year to year, depending on whether there were widespread droughts, for example, or whether it was a good growth year for the forests. That is why the annual CO2 increase in the atmosphere also varies greatly each year, and this short-term variation is not mainly caused by variations in our emissions (so a record CO2 increase in the atmosphere in an El Niño year does not mean that human emissions have surged in that year).

Fig. 5 Annual emissions of carbon from fossil sources and deforestation, and annual emissions from the biosphere, atmosphere and ocean (the latter are negative, meaning net uptake). This is again in carbon (not CO2) units; the 12 gigatons of carbon emitted in 2016 are a lot more than the 7 gigatons in the older Fig. 3. Source: Global Carbon Project.

The “climate skeptics” blaming the forests for most of the increase in atmospheric CO2, because of decaying foliage and deadwood, is not merely wrong, it is pretty bonkers. Have leaves started to decompose only since industrialization? Media with a minimum aspiration to credibility should clearly reject such nonsense, instead of spreading it further. In case of Die Welt, one of my PIK colleagues had explicitly pointed out to the author, in response to a query by him, that the 5% human share of CO2 is misleading and that humans have caused a 45% increase. That the complete CO2 increase is anthropogenic has been known for decades. The first IPCC report, published in 1990, put it thus:

Since the industrial revolution the combustion of fossil fuels and deforestation have led to an increase of 26% in carbon dioxide concentration in the atmosphere.

In the 27 years since then, the CO2 increase caused by our emissions has gone up from 26% to 45%.

How Exxon misled the public against better knowledge

One fascinating question is where this false idea of humans just contributing a tiny bit to the relentless rise in atmospheric CO2 has come from? Have a look at this advertorial (a paid-for editorial) by ExxonMobil in the New York Times from 1997:

Fig. 6 Excerpt from the New York Times of 6 November 1997

The text to go with it read:

While most of the CO2 emitted by far is the result of natural phenomena – namely respiration and decomposition, most attention has centered on the three to four percent related to human activities – burning of fossil fuels, deforestation.

That is pretty clever and could hardly be an accident. The impression is given that human emissions are not a big deal and only responsible for a small percentage of the CO2 increase in the atmosphere – but without explicitly saying that. In my view the authors of this piece knew that this idea is plain wrong, so they did not say it but preferred to insinuate it. A recent publication by Geoffrey Supran and Naomi Oreskes in Environmental Research Letters has systematically assessed ExxonMobil’s climate change communications during 1977–2014 and found:

We conclude that ExxonMobil contributed to advancing climate science—by way of its scientists’ academic publications—but promoted doubt about it in advertorials. Given this discrepancy, we conclude that ExxonMobil misled the public.

They explain their main findings in this short video clip.

Does the CO2 come from volcanoes?

Another age-old climatic skeptic myth, is that the CO2 is coming from volcanoes – first time I had to rebut this was as a young postdoc in the 1990s. The total volcanic emissions are between 0.04 and 0.07 gigatonnes of CO2 per year, compared to the anthropogenic emissions of 12 gigatons in 2016. Anthropogenic emissions are now well over a hundred times greater than volcanic ones. The volcanic emissions are important for the long-term CO2 changes over millions of years, but not over a few centuries.

Does the CO2 come from the ocean?

As already mentioned and shown in Figs. 4 and 5, the oceans absorb net CO2 and do not release any. The resulting increase in CO2 in the upper ocean is documented and mapped in detail by countless ship surveys and known up to a residual uncertainty of + – 20% . This is, in itself, a very serious problem because it leads to the acidification of the oceans, since CO2 forms carbonic acid in water. The observed CO2 increase in the world ocean disproves another popular #fakenews piece of the “climate skeptics”: namely that the CO2 increase in the atmosphere might have been caused by the outgassing of CO2 from the ocean as a result of the warming. No serious scientist believes this.

Remember also from Figs. 4 and 5 that we emit about twice as much CO2 as is needed to explain the complete rise in the atmosphere. In case you have not connected the dots: the denier myth of the oceans as cause of the atmospheric CO2 rise most often comes in the form of “the CO2 rise lagged behind temperature rise in glacial cycles”. It is true that during ice ages the oceans took up more CO2 and that is why there was less in the atmosphere, and during the warming at the end of glacial cycles that CO2 came back out of the ocean, and this was an important amplifying feedback. But it is a fallacy to conclude that the same natural phenomenon is happening again now. As I explained above: measurements clearly prove that the modern CO2rise has a different cause, namely our fossil fuel use. What is the same now and over past glacial cycles is not the CO2 source, but the greenhouse effect of the atmospheric CO2 changes:  without that we could not understand (or correctly simulate in our climate models) the full extent of glacial cycles.

The cyanide cocktail

A man offers you a cocktail with a little bit of cyanide at a party. You reject that indignantly, but the man assures you it is completely safe: after all, the amount of cyanide in your body  after this drink would be only 0.001 percent! This could hardly be harmful! Those scientists who claim that 3 mg cyanide per kg of body weight (ie 0.0003 percent) are fatal are obviously not to be trusted. Are you falling for that argument?

We hope not, and we hope you will neither fall for the claim that 0.0125 percent of CO2 (that’s the 125 ppm increase caused by humans) can’t be bad because that number is small. Of course, the amount of CO2 in the air could also be expressed in kilograms: it is 3200 billion tons or 3,200,000,000,000,000 kilograms. Of this humans are responsible for almost 1000 billion tons. (Does that sound more harmful than 0.0125 percent?) Since the year 1870, we have even emitted a total of about 2,000 billion tons. As already explained, forests and oceans have removed about half of that from the atmosphere.

Scientists specify the concentration of individual gases in the atmosphere as volume fractions (rather than, e.g., grams per cubic meter of air) because then the numbers do not depend on temperature and pressure, which vary greatly in the atmosphere. As far as climatic impact is concerned, however, the fraction of the total mass of the atmosphere is irrelevant since the atmosphere consists of 99.9% nitrogen, oxygen and argon, i.e. gases which cannot absorb infrared radiation. Only molecules made of at least three atoms absorb heat radiation and thus only such trace gases makes the greenhouse effect, and among these CO2 is the second most important after water vapor. All this has been known since John Tyndall’s measurements of the greenhouse effect of various gases in 1859. Tyndall back then wrote:

[T]he atmosphere admits of the entrance of the solar heat, but checks its exit; and the result is a tendency to accumulate heat at the surface of the planet.

That is still a great concise description of the greenhouse effect! Without CO2 in the air our planet would be completely frozen, no life would be possible. With CO2, we are turning one of the major control knobs of global climate.

The climate effect

So let’s finally come to the climatic effect of the CO2 increase. As for cyanide, the effect is what counts, and not whether compared to some large mass the fraction is 10 percent or 0.01 percent. The dose effect of toxins on humans can be determined from experience with victims. The climatic impact of greenhouse gases can either be calculated on the basis of an understanding of the physical processes, or it can be determined from the experience of climate history (see my previous post). Both come to the same conclusion. The climate sensitivity (global warming in equilibrium after CO2 doubling) is around 3°C, and the expected warming to date, due to the current CO2 increase, is around 1°C. This corresponds quite exactly to the observed global warming (Fig. 7). For which, by the way, there is no natural explanation, and the best estimate for the anthropogenic share of global warming since 1950 is 110 percent – more on this in my previous post.

Fig. 7 Time evolution of global temperature, CO2 concentration and solar activity. Temperature and CO2 are scaled relative to each other as the physically expected CO2 effect on the climate predicts (i.e. best estimate of the climate sensitivity). The amplitude of the solar curve is scaled as derived from the observed correlation of solar and temperature data. (Details are explained here ). This graph can be created here and you can copy a code that can be used as a widget inany website (as in my home page), where it is automatically updated every year with the latest data. Thanks to Bernd Herd who programmed this.

Finally, here is a slick new video clip illustrating the history of CO2 emissions on the map:


Physics Today: The carbon cycle in a changing climate

Deconstructing climate misinformation to identify reasoning errors

John Cook1,3Peter Ellerton2 and David Kinkead2

Published 6 February 2018 • © 2018 The Author(s). Published by IOP Publishing Ltd 
Environmental Research LettersVolume 13Number 2


Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking.

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Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

1. Introduction

Misinformation, defined as information initially presented as true that is later found to be false (Lewandowsky et al 2012), is a societal issue of growing concern. The World Economic Forum listed online misinformation as one of the top ten global trends threatening the world (WEF 2014). Oxford Dictionary named ‘post-truth’ the 2016 word of the year (Flood 2016) while Collins Dictionary named ‘fake news’ the 2017 word of the year (Flood 2017) in recognition of the prevalence and impact of misinformation.

The issue of climate change has been particularly impacted by misinformation. There is an overwhelming scientific consensus that humans are causing global warming (Cook et al 2016), with a number of studies converging on 97% agreement among publishing climate scientists or relevant climate papers (Doran and Zimmerman 2009, Anderegg et al 2010, Cook et al 2013, Carlton et al2015). However, there is little awareness of the scientific consensus among the general public with only 12% of Americans aware that the consensus is above 90% (Leiserowitz et al 2017).

A major contributor to public misperceptions about climate change is a persistent, decades-long misinformation campaign (McCright and Dunlap 2010). Content analysis of conservative think-tank articles found that arguments casting doubt on climate science are increasing relative to policy arguments (Boussalis and Coan 2016). Climate misinformation impacts public perceptions about climate change in various ways. It decreases acceptance of climate change and lowers confidence about people’s understanding (Ranney and Clark 2016). Climate misinformation also disproportionately influences conservatives (Cook et al 2017, van der Linden et al 2017), contributing to growing polarization over recent decades (McCright and Dunlap 2011). Misinformation cancels out the positive effect of accurate information (McCright et al 2016, van der Linden et al 2017), implying that accurate science communication is a necessary but insufficient condition to increasing science literacy levels.

Interventions are therefore required to help the public develop resistance to persuasion from misinforming sources. Inoculation theory provides a framework for helping people develop immunity to persuasive misinformation (McGuire and Papageorgis 1961). This approach applies the concept of vaccination to knowledge—it is possible to build resistance to misinformation by exposing people to a weak form of the misinformation. An inoculating text consists of a forewarning of an upcoming persuasion attempt as well as counter-arguments that refute the information.

Inoculation theory however, requires intervention prior to misinformation being received (Bolsen and Druckman 2015). In addition, inoculation theory usually involves the presentation of competing factual claims which if presented after misinformation has solidified subject belief, can result in the backfire effect (Nyhan and Reifler 2010).

We examine a different approach to pre-emptively refuting climate denial misinformation using critical thinking techniques—one that focuses on understanding the logical structure of denialist arguments rather than the truth claims they consist of. Reason-based inoculation is consistent with Compton (2005), who argued that Aristotelian rationality offers a useful framework for inoculating refutations. This approach has been tested experimentally, with an inoculation explaining a misleading technique without including competing factual information demonstrating success in neutralizing the influence of the misinformation (Cook et al 2017). This paper introduces key critical thinking concepts and outlines a straightforward process for identifying reasoning errors that allows for people who lack expertise in climate science to confidently reject certain denialist arguments.

2. Understanding arguments

It is important to distinguish between the colloquial use of the term argument to indicate disagreement, often heated, and its formal use here. By argument, we mean a connected series of statements used to establish a definite proposition (Chapman and Python 1989). It is a logical structure that uses the truth of one or more claims (called premises) to establish the truth of some other claim (called the conclusion). In short, arguments give us reasons to believe a claim is true, in a way not linked to the identity, social position, tenor, or rhetorical ability of the person making the claim.

Arguments consist of truth-bearing statements or claims called propositions. A proposition is any meaningful utterance that can be true or false, like ‘over 90% of climate scientists believe in anthropogenic climate change’ (true), ‘New York City is the capital of New York state’ (false), or ‘it will rain tomorrow’ (unknowable today). We can contrast propositional statements with non-propositional ones that can not be true or false like ‘What is the time?’ (interrogative), ‘Look out!’ (imperative), ‘Donuts—yum!’ (exclamative). Premises and conclusions must be able to be expressed as propositions. Arguments can answer questions but they can not be constructed with them.

Propositions can be combined in ways such that their truth content gives us information about the truth content of other propositions. If some set of propositions being true (the premises) makes some other proposition (the conclusion) more likely to be true, then we can say that the truth of the premises supports the truth of the conclusion. The degree of this support provides us with an important criterion for the judging the quality of an argument.

Figure 1.

Figure 1. Flowchart for evaluating contrarian claims. Circles indicate possible fallacies to be detected at each stage. See supplementary table S1 for definition of each fallacy.

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If the truth of an argument’s premises have no bearing on the truth of its conclusion, we say that the argument is a non sequitur4. For example:

P: I once saw a white swan.

C: My pet is a bird.

If the premises give the conclusion only limited support—if the premises being true makes our belief about the truth of the conclusion only somewhat more likely—we describe the argument as inductively weak.

P: I once saw a white swan.

C: All swans are white.

If the premises being true makes our belief about the conclusion’s truth much more likely, we describe the argument as inductively strong.

P1: I have seen a very large number of swans and they have all been white.

P2: The swans I have seen varied in age, sex, and location.

C: All swans are white.

Sometimes however, the premises of an argument together logically entail the truth of the conclusion. This notion of entailment means that it is impossible for the conclusion to be false whilst all the premises are true. When the truth of the premises guarantees or entails the truth of the conclusion, we describe the argument as deductively valid.

P1: All swans are white.

P2: My pet is not white.

C: My pet is not a swan.

As anyone who has travelled to Australia may have seen however, not all swans are white. A good argument relies on more than just logical structure—its premises must also be true. These examples highlight two important measures for evaluating the quality of an argument—how strongly the premises support the conclusion (the logical structure) and whether or not the premises are in fact true.

3. Definitive and provisional claims

Whether an argument is deductive or inductive depends on what type of concluding proposition the argument is supposed to establish. Propositions can be made true in different ways. Some are necessarily true: ‘All bachelors are unmarried men’ or ‘Deciduous trees shed their leaves’. Necessarily true propositions are made true by virtue of their meaning.

Contingently true propositions by contrast are true but need not have been—’Berlin is the capital of Germany’ or ‘The Sydney Swans won the 2012 AFL grand final’. Given the meaning of the terms, it could never have been the case that necessarily true statements were false but contingently true propositions could have been.

Of these contingently true propositions, we might further distinguish between those that are demonstrably true and those that are provisionally true. ‘Donald Trump is the 45th President of the United States’ is demonstrably true because we have observable and verifiable evidence for it. ‘Liberal democracies do not go to war with one another’ by contrast is provisionally true since there have been no counter-examples to it thus far.

Conclusions with definitive claims require deductive inferences to support them. When the conclusion of our argument is intended to be definitive, that it is in fact the case, then no new claim should be able to undermine this. The argument must be indefeasible and the conclusion becomes necessarily true if the premises are all true.

Provisionally true claims do not require such support. Because they are always open to refutation, the arguments that support them need only be defeasible. Inductive inference is therefore indicative of provisionally true claims.

4. Evaluating denialist claims as arguments

Much of the effort to date in refuting denialist arguments has focused on the truth content of particular claims—showing for example that global temperatures are rising (Lewandowsky et al 2016) or that there is overwhelming expert consensus that human activity is responsible for much of this change (Cook et al 2013). Whilst identifying factual errors is important, research into the ability of misinformation to neutralize factual information indicates that there are limitations to this approach (McCright et al 2016). A more comprehensive approach should include identification of flaws in misinforming arguments and explain how the reasons offered do not adequately support their conclusions (Cook et al 2017, van der Linden et al 2017).

Our contention is that a basic understanding of argumentation is sufficient to refute a large number of climate denialist claims. Applying the introduction to argument structure from section 2, we now outline a process for evaluating climate denialist arguments and apply it to common denialist claims.

Figure 1 outlines a flowchart for evaluating an argument’s cogency. The following sections detail each step in the analysis process. Within the chart, we have also identified locations where certain fallacies of reasoning are typically made. This is to progress work already done on fallacies found in the denial of climate science (Cook et al 2015). Supplementary table S1 available at includes definitions of the fallacies found in the most common contrarian claims about climate change.

4.1. Identification of claim

We begin by identifying a denialist claim for evaluation (Step 1). For example, a common contrarian claim is ‘Earth’s climate has changed naturally before, so current climate change is natural.’ In constructing and evaluating an argument, it is critical to have clarity about the claim being made. It is also important that the claim is not misrepresented or changed to alter its meaning. As such, we recommend seeking claims made by contrarians and dealing with these as presented.

4.2. Construction of argument

We construct the argument supporting a claim by identifying the set of propositions constituting the premises and conclusion (Step 2). In the case of the claim above the structure would be:

P1: The climate has changed in the past through natural processes

P2: The climate is currently changing

C: The climate is currently changing through natural processes

Having established the argument structure, we next determine the inferential intent of the argument as either deductive or inductive (Step 3).

4.3. Determine inferential intent

How strongly the conclusion of an argument is formulated determines the type of inferential support required from the premises. Definitive conclusions require the support of deductively valid arguments whilst provisional conclusions require only inductive support. Within science, we find both deductive and inductive arguments. Deductive inferences are common and form the basis of the hypothetico-deductive method:

P1: If my theory is correct, then I will observe this phenomenon.

P2: I did not observe this phenomenon.

C: My theory is not correct.

Yet it is inductive reasoning that underpins the bulk of our empirically derived knowledge:

P1: There is a strong correlation between smoking and cancer in many studies that controlled for numerous possible confounders.

P2: There is a plausible explanatory framework for why smoking would cause cancer.

C: Smoking very likely causes cancer.

Whilst the conclusions of inductive inferences are often stated definitively in everyday language e.g. ‘smoking causes cancer’, they are not intended to be definitive. The majority of scientific claims are open to adjustment, correction and even refutation. The ability to state the conditions under which a theory can be falsified, and hence refuted, is an important determiner for discriminating science from pseudo-science (Popper 1957).

Climate denialist claims however, are typically definitive, taking a form such as ‘human activity is notthe cause of current climate change’ rather than ‘human activity might not be the primary cause of current climate change’. Similar definitive denialist claims are common (Elsasser and Dunlap 2013)

  • ‘Climate change is not happening.’
  • ‘There is no empirical evidence that humans are causing global warming.’
  • ‘There is no scientific consensus that human-caused climate change is occurring.’

If we are to accept these denialist claims, then like any definitive conclusion, they must be supported by a deductively valid argument.

Of course, not all denialist claims are stated definitively, such as arguments that exaggerate the role of scientific uncertainty (Freudenburg and Muselli 2013, McCright and Dunlap 2000). As such they only require inductive support. In cases where non-definitive denialist claims conflict with non-definitive claims of climate science, then we need some other method to reconcile competing inductive arguments. How we should reconcile competing inductive inferences is outside the scope of this paper.

If the denialist intent is to support a definitive claim through a deductive argument, then the next step in the process is to check for validity. If the intent is to produce a claim which is not definitive because it relies on an inductive argument, then the attempted refutation of anthropogenic global warming (AGW) has already failed.

4.4. Check for validity

If the argument in question is deductive in intent, it is then checked for validity (Step 4). An argument in support of definitive claims must be deductively valid, for without this degree of logical entailment the truth of the premises gives us insufficient reason to accept the truth of the conclusion.

The claim that ‘Human activity is not causing climate change’ is often supported with the idealised argument below.

P1: A previous change in climate was not the result of human activity.

P2: The climate is currently changing.

C: The current change in climate is not the result of human activity.

There is a variety of formal methods available to prove that an argument is valid, such as truth tables, trees, or tableau. Unfortunately, formal methods require a degree of training in formal logic to use and therefore it is usually much simpler to demonstrate an argument is invalid by use of a parallel argument.

Parallel arguments use the same logical structure as the target argument but instantiate it in such a way that the conclusion is obviously false. In a valid argument it is impossible for the conclusion to be false whilst all the premises are true. Parallel arguments identify a clear counter example and show that an argument is not valid. Parallel arguments have strong pedagogical value because they use concrete examples, which are closer to our own experience than abstract reasoning (Juthe 2009). For example:

P1: A previous swan death was not the result of human activity.

P2: This swan is dying.

C: This swan dying is not the result of human activity.

It is clear that the conclusions do not necessarily follow from the premises and the arguments are therefore invalid. Just because something can be a cause, does not make it a cause in any particular instance. The conclusion is not justified by the reasons given, so we must either reject the conclusion or revise it so the argument is valid as follows:

P1: A previous change in climate was not the result of human activity.

P2: The climate is currently changing.

C: The current change in climate may not be the result of human activity.

(Note that now the conclusion has been changed to make the argument valid, it is no longer definitive and the attempt at refuting AGW fails. This will be explained further in section 4.5).

4.4.1. Identify hidden premises

If the argument is determined to be invalid, we next attempt to identify any hidden premises that might be added to the argument to make it logically valid (Step 4a). Arguments often rely on unstated assumptions and implied conclusions to be valid. These hidden premises must be made explicit for the argument to become valid. Another common denialist argument against human-caused global warming can be articulated as follows:

P1: There is no empirical evidence that humans are causing global warming.

[P2 (Hidden): If there is no empiric evidence for something, then it is not happening.]

C: Humans are not causing global warming.

By making clear the hidden premise, we can made this argument valid. We can do the same with the first argument from section 4.4. Rather than reject the conclusion because it was not adequately supported by the premise or change the conclusion’s modality from necessarily not the cause to possibly not the cause, we can keep the stronger conclusion and add a new premise to make the argument valid.

P1: A previous change in climate was not the result of human activity.

P2: The climate is currently changing.

P3: (Hidden) If something was not the cause in the past, it will not be the cause in the future.

C: The current change in climate is not the result of human activity.

Now both arguments are valid and the conclusions would be true, if all of the premises were in fact true. Whether the an argument should convince us is dependent on both the strength of the logical structure and the premises actually being true.

4.5. Check for ambiguity

If an argument is logically valid (or we added hidden premises to create validity), we next check for ambiguity. A common form of ambiguity is equivocation—when the same word or phrase is used with two different meanings (Step 5). Consider now the following trope:

P1: Nothing is better than eternal happiness (true).

P2: A ham sandwich is better than nothing (true).

C: A ham sandwich is better than eternal happiness (entailed from 1 and 2).

Obviously, the conclusion is false even though the argument is valid and the premises (when stated in isolation) are (arguably) true. The argument however, relies on ambiguous language, or equivocation, regarding the term ‘nothing’. In premise 1, we mean no thing is better than eternal happiness; in premise 2 we mean having a ham sandwich is better than not having one. Once we remove the equivocation, the argument becomes invalid (indeed a non sequitur) and we can reject the conclusion.

Some climate denialist arguments rely on similar equivocation. Consider the following variation of the ‘past climate change’ contrarian claim:

P1: Natural process and human activity can both cause climate change.

P2: Climate change is currently occurring.

C: Human activity is not necessary to explain current climate change.

The syntax conveys the impression that the argument is valid, but it is not. The term ‘climate change’ referred to in Premise 1 and Premise 3 do not have the same meaning, since the rate of change is different in each. If equivocation exists, we resolve it by either clarifying the argument’s language or adding premises to resolve any ambiguity (Step 5a). In this example, Premise 3 is amended to clarify the rate of current climate change. Once Premise 3 is amended, the argument becomes invalid:

P1: Natural processes have caused climate change in the past.

P2: Human activity can cause climate change.

P3: The climate is currently changing at a much more rapid rate than can be explained by natural processes.

C: Human activity is not necessary to explain current climate change.

We can attempt to restore validity by accepting the premises and seeing what conclusion must follow from them (Step 5b):

P1: Natural processes have caused climate change in the past.

P2: Human activity can cause climate change.

P3: The climate is currently changing at a much more rapid rate than can be explained by natural processes.

C: Human activity is necessary to explain current climate change.

If the resolution resulting from the amendment of any premises renders the argument invalid, then the contrarian claim is considered to have failed in refuting AGW. If the argument remains valid after resolution, then we see whether the conclusion has changed as part of that validation process. If the conclusion is off-point relative to the original conclusion, then the contrarian claim has failed. In this example, the conclusion has changed such that natural causation of climate change has been ruled out, coming to the opposite conclusion to the original version of the argument. Importantly, in rewriting the premises to avoid equivocation, the conclusion has necessarily changed—it is not something that was arrived at arbitrarily.

4.6. Check premises for truth or plausibility

If the conclusion stays on-point or the argument has not been ruled out in earlier steps (i.e. it is deductive, valid, and with no equivocation), then the final step is to determine the truth of the premises (Step 6). A major advantage of the approach we are proposing in this paper is that evaluating climate denialist claims as arguments allows a general reader to judge the veracity of many claims about science without the need for expertise in climate science (and allow non-expert recipients of a refutation to comprehend why a claim is false). Yet as we have just outlined, good arguments require more than the conclusion being true if the premises were all true, they also require the premises to be true. So then how do we evaluate the truth of the premises without expertise in climate science?

The simple answer is that we often do not need to. Denialist arguments, once made valid by articulating any required suppressed premises, will tend to rely on demonstrably false or implausible general claims. Take for example, the assumed premise in the last argument ‘If something was the cause in the past, it will be the cause in the future’. This claim is highly implausible for any effect that has multiple possible causal mechanisms. So too, the claim ‘If there is no empiric evidence for something, then it is not happening’ which mistakes an absence of evidence for evidence of absence.

5. Discussion

Psychological research indicates that explaining the techniques employed to distort scientific information is an important component of neutralising misinformation. This paper lays out a template for systematic deconstruction and assessment of denialist claims, in order to identify false premises and fallacious reasoning. We explicitly restrict ourselves to deductive claims that purport to refute mainstream climate science. However, inductive arguments have also employed in order to cast doubt on the reality of climate change, usually by misrepresenting or exaggerating the nature of scientific uncertainty (Freudenburg and Muselli 2013, McCright and Dunlap 2000). Assessment of inductive denialist claims from a critical thinking perspective is an area of future research.

Our reason-based approach to refuting climate science misinformation could be used as a specific application of current inoculation theory. Typically, inoculation interventions are information-based, containing facts that counter the misleading information. For example, van der Linden et al (2017) countered the Global Warming Petition Project by communicating the 97% scientific consensus on human-caused global warming, as well as explaining specific misleading elements of the Petition Project. In contrast, Cook et al (2017) used a reason-based inoculation against the Global Warming Petition Project that refrained from mentioning the 97% consensus or the Petition Project. Instead, the explanation of the general technique of fake experts was successful in inoculating participants against the negative influence of the Petition Project. Further research into this approach is recommended, directly comparing its efficacy to information-based inoculations, measuring how susceptible reason-based interventions are subject to decay effects, and exploring whether reason-based inoculations can convey resistance against multiple arguments.

Supplementary table S2 includes analysis of 42 common climate myths that feature deductive arguments, taken from the Massive Open Online Course (MOOC), Denial101x: Making Sense of Climate Science Denial (Cook et al 2015) and employing the critical thinking approach explained in the MOOC Meta101x: Philosophy and Critical Thinking (Brown and Ellerton 2015). Our analysis found that all of the 42 denialist claims failed to falsify anthropogenic global warming. However, these claims are effective in misinforming the public and decreasing climate literacy. Consequently, refuting and neutralizing the influence of this misinformation is necessary.

Social media presents one potent option for practically deploying resources of this type to neutralize misinformation, using an approach described as ‘technocognition’: an approach that incorporates principles from behavioural economics, cognitive psychology, and philosophy in the design of information architectures (Lewandowsky et al 2017). Misconception-based learning, applied in the classroom, is another powerful and practical model for deploying inoculation content (McCuin et al2014). While there have been efforts to apply this approach to climate education (Bedford 2010, Cook et al 2014), and development of resources (Bedford and Cook 2016), there is in general a dearth of misconception-based learning resources for educators (Tippett 2010). Consequently, this research is designed to act as a building block for developing educational material that teaches critical thinking through the examination of misinformation and evaluation of arguments.

This work may also serve as a template for analysis of misinformation on other topics besides climate change. Misinformation about vaccination, evolution, and other scientific topics have negative impacts on science literacy and can lead to severe societal consequences. Consequently, application of our process for evaluating misleading claims may be useful in developing resources for scientists, communicators, and educators seeking to reduce the influence of misinformation across a variety of issues.


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    Whilst the term non sequitur is sometimes used as a synonym for any invalid inference, here we use it in its more common sense as a failure of relevance.


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