Climatism is a Logic Fail

Two fallacies ensure meaningless public discussion about climate “crisis” or “emergency.” H/T to Terry Oldberg for comments and writings prompting me to post on this topic.

One corruption is the numerous times climate claims include fallacies of Equivocation. For instance, “climate change” can mean all observed events in nature, but as defined by IPCC all are 100% caused by human activities.  Similarly, forecasts from climate models are proclaimed to be “predictions” of future disasters, but renamed “projections” in disclaimers against legal liability.  And so on.

A second error in the argument is the Fallacy of Misplaced Concreteness, AKA Reification. This involves mistaking an abstraction for something tangible and real in time and space. We often see this in both spoken and written communications. It can take several forms:

♦ Confusing a word with the thing to which it refers

♦ Confusing an image with the reality it represents

♦ Confusing an idea with something observed to be happening

Examples of Equivocation and Reification from the World of Climate Alarm

“Seeing the wildfires, floods and storms, Mother Nature is not happy with us failing to recognize the challenges facing us.” – Nancy Pelosi

Mother Nature’ is a philosophical construct and has no feelings about people.

“This was the moment when the rise of the oceans began to slow and our planet began to heal …”
– Barack Obama

The ocean and the planet do not respond to someone winning a political party nomination. Nor does a planet experience human sickness and healing.

“If something has never happened before, we are generally safe in assuming it is not going to happen in the future, but the exceptions can kill you, and climate change is one of those exceptions.” – Al Gore

The future is not knowable, and can only be a matter of speculation and opinion.

“The planet is warming because of the growing level of greenhouse gas emissions from human activity. If this trend continues, truly catastrophic consequences are likely to ensue. “– Malcolm Turnbull

Temperature is an intrinsic property of an object, so temperature of “the planet” cannot be measured. The likelihood of catastrophic consequences is unknowable. Humans are blamed as guilty by association.

“Anybody who doesn’t see the impact of climate change is really, and I would say, myopic. They don’t see the reality. It’s so evident that we are destroying Mother Earth. “– Juan Manuel Santos

“Climate change” is an abstraction anyone can fill with subjective content. Efforts to safeguard the environment are real, successful and ignored in the rush to alarm.

“Climate change, if unchecked, is an urgent threat to health, food supplies, biodiversity, and livelihoods across the globe.” – John F. Kerry

To the abstraction “Climate Change” is added abstract “threats” and abstract means of “checking Climate Change.”

Climate change is the most severe problem that we are facing today, more serious even than the threat of terrorism.” -David King

Instances of people killed and injured by terrorists are reported daily and are a matter of record, while problems from Climate Change are hypothetical


Corollary: Reality is also that which doesn’t happen, no matter how much we expect it to.

Climate Models Are Built on Fallacies


A previous post Chameleon Climate Models described the general issue of whether a model belongs on the bookshelf (theoretically useful) or whether it passes real world filters of relevance, thus qualifying as useful for policy considerations.

Following an interesting discussion on her blog, Dr. Judith Curry has written an important essay on the usefulness and limitations of climate models.

The paper was developed to respond to a request from a group of lawyers wondering how to regard claims based upon climate model outputs. The document is entitled Climate Models and is a great informative read for anyone. Some excerpts that struck me in italics with my bolds and added images.

Climate model development has followed a pathway mostly driven by scientific curiosity and computational limitations. GCMs were originally designed as a tool to help understand how the climate system works. GCMs are used by researchers to represent aspects of climate that are extremely difficult to observe, experiment with theories in a new way by enabling hitherto infeasible calculations, understand a complex system of equations that would otherwise be impenetrable, and explore the climate system to identify unexpected outcomes. As such, GCMs are an important element of climate research.

Climate models are useful tools for conducting scientific research to understand the climate system. However, the above points support the conclusion that current GCM climate models are not fit for the purpose of attributing the causes of 20th century warming or for predicting global or regional climate change on timescales of decades to centuries, with any high level of confidence. By extension, GCMs are not fit for the purpose of justifying political policies to fundamentally alter world social, economic and energy systems.

It is this application of climate model results that fuels the vociferousness
of the debate surrounding climate models.

Evolution of state-of-the-art Climate Models from the mid 70s to the mid 00s. From IPCC (2007)

Evolution of state-of-the-art Climate Models from the mid 70s to the mid 00s. From IPCC (2007)

The actual equations used in the GCM computer codes are only approximations of
the physical processes that occur in the climate system.

While some of these approximations are highly accurate, others are unavoidably crude. This is because the real processes they represent are either poorly understood or too complex to include in the model given the constraints of the computer system. Of the processes that are most important for climate change, parameterizations related to clouds and precipitation remain the most challenging, and are the greatest source of disagreement among different GCMs.

There are literally thousands of different choices made in the construction of a climate model (e.g. resolution, complexity of the submodels, parameterizations). Each different set of choices produces a different model having different sensitivities. Further, different modeling groups have different focal interests, e.g. long paleoclimate simulations, details of ocean circulations, nuances of the interactions between aerosol particles and clouds, the carbon cycle. These different interests focus their limited computational resources on a particular aspect of simulating the climate system, at the expense of others.

Overview of the structure of a state-of-the-art climate model. See Climate Models Explained by R.G. Brown

Human-caused warming depends not only on how much CO2 is added to the atmosphere, but also on how ‘sensitive’ the climate is to the increased CO2. Climate sensitivity is defined as the global surface warming that occurs when the concentration of carbon dioxide in the atmosphere doubles. If climate sensitivity is high, then we can expect substantial warming in the coming century as emissions continue to increase. If climate sensitivity is low, then future warming will be substantially lower.

In GCMs, the equilibrium climate sensitivity is an ‘emergent property’
that is not directly calibrated or tuned.

While there has been some narrowing of the range of modeled climate sensitivities over time, models still can be made to yield a wide range of sensitivities by altering model parameterizations. Model versions can be rejected or not, subject to the modelers’ own preconceptions, expectations and biases of the outcome of equilibrium climate sensitivity calculation.

Further, the discrepancy between observational and climate model-based estimates of climate sensitivity is substantial and of significant importance to policymakers. Equilibrium climate sensitivity, and the level of uncertainty in its value, is a key input into the economic models that drive cost-benefit analyses and estimates of the social cost of carbon.

Variations in climate can be caused by external forcing, such as solar variations, volcanic eruptions or changes in atmospheric composition such as an increase in CO2. Climate can also change owing to internal processes within the climate system (internal variability). The best known example of internal climate variability is El Nino/La Nina. Modes of decadal to centennial to millennial internal variability arise from the slow circulations in the oceans. As such, the ocean serves as a ‘fly wheel’ on the climate system, storing and releasing heat on long timescales and acting to stabilize the climate. As a result of the time lags and storage of heat in the ocean, the climate system is never in equilibrium.

The combination of uncertainty in the transient climate response (sensitivity) and the uncertainties in the magnitude and phasing of the major modes in natural internal variability preclude an unambiguous separation of externally forced climate variations from natural internal climate variability. If the climate sensitivity is on the low end of the range of estimates, and natural internal variability is on the strong side of the distribution of climate models, different conclusions are drawn about the relative importance of human causes to the 20th century warming.

Figure 5.1. Comparative dynamics of the World Fuel Consumption (WFC) and Global Surface Air Temperature Anomaly (ΔT), 1861-2000. The thin dashed line represents annual ΔT, the bold line—its 13-year smoothing, and the line constructed from rectangles—WFC (in millions of tons of nominal fuel) (Klyashtorin and Lyubushin, 2003). Source: Frolov et al. 2009

Anthropogenic (human-caused) climate change is a theory in which the basic mechanism is well understood, but whose potential magnitude is highly uncertain.

What does the preceding analysis imply for IPCC’s ‘extremely likely’ attribution of anthropogenically caused warming since 1950? Climate models infer that all of the warming since 1950 can be attributed to humans. However, there have been large magnitude variations in global/hemispheric climate on timescales of 30 years, which are the same duration as the late 20th century warming. The IPCC does not have convincing explanations for previous 30 year periods in the 20th century, notably the warming 1910-1945 and the grand hiatus 1945-1975. Further, there is a secular warming trend at least since 1800 (and possibly as long as 400 years) that cannot be explained by CO2, and is only partly explained by volcanic eruptions.

CO2 relation to Temperature is Inconsistent.


There is growing evidence that climate models are running too hot and that climate sensitivity to CO2 is on 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 CO2 emissions.

The climate modeling 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 (natural factors) or their potential impacts on the evolution of the 21st century climate.


There are a series of posts here which apply reality filters to attest climate models.  The first was Temperatures According to Climate Models where both hindcasting and forecasting were seen to be flawed.

Others in the Series are:

Sea Level Rise: Just the Facts

Data vs. Models #1: Arctic Warming

Data vs. Models #2: Droughts and Floods

Data vs. Models #3: Disasters

Data vs. Models #4: Climates Changing

Climate Medicine

Climates Don’t Start Wars, People Do


Beware getting sucked into any model, climate or otherwise.



  1. terryoldberg · October 17

    The runs of a modern climate model convey nil information gain about the conditional outcomes of the events of the future for Earth’s climate system to an official of a regulatory agency. Thus, this official is incapable of regulating this system. However, an application of the reification fallacy by the argument made by this model creates the illusion that this official is capable of regulating this system. In the scientific work entitled “Detecting the Impossibility of Regulation,” I present a deductive proof of this allegation. This proof is available to anyone upon request to (signed) Terry Oldberg. Engineer/Scientist/Public Policy Researcher, Los Altos Hills, CA, USA


  2. HiFast · October 17

    Reblogged this on Climate Collections.


  3. Pingback: Weekly Climate and Energy News Roundup #524 – Watts Up With That?

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