Vincent J. Curtis
4 Apr 2026
Ross McKittrick is a professor of Economics at the University of Guelph, and he has become famous for his interventions in climate science. This is possible because the mathematical methods often used in climate science, regression analysis, are the bread-and-butter of economic analysis; and someone well-versed in statistical analysis is well-positioned to spot errors in the application of economic analytical methods to climate data analysis. McKittrick is an expert in a field of poorly trained amateurs applying mathematical methods they clearly don’t understand.
Dr. McKittrick presented a paper at the October, 2021 ICCC conference that had been published in the August edition of Climate Dynamics, in which he, and his co-author Richard Tol, proved invalid a method of analysis used in climate science since 1999, and begun in a paper referred to as ‘AT99.’
The science of attribution begins with the propositions that; (a) we can observe patterns and changes in climate data; (b) it can be hard to tell if there’s been a statistically significant change in the climate; and (c) it’s hard to prove that those changes were caused by GHG emissions. The attribution methodology works by comparing observed patterns to patterns from climate models. This requires that we assume that climate models provide a true and complete representation of the climate, and that involves a statistical methodology known as regression analysis.
The beginnings of a logical fallacy are already evident. A model is a representation of reality, and if the model fails to accurately forecast the behavior of reality, it is assumed here that there’s something wrong with reality. This is a form of begging the question. A second problem arises from the data used to construct the model: is it truly representative, or is there a sampling problem unrecognized by the modellers? Sampling could be a problem if not a long enough period of time was sampled for data; in addition, there’s an implicit assumption of stasis in the climate and model. ‘Alteration/ is not a change deemed within the principle of the climate. Attribution tries to get around these logic problems by adjusting the parameters of the model to fit observed reality, and if more GHG is required by the model to fit the new data, that is grounds for attributing GHG as the cause of the deviation of reality from the expectations of the model. There is a fallacy in this also, but it goes unobserved by the Attributors.
Attribution was begun in 1999 with a paper entitled, “Checking for model consistency in in optimal fingerprinting” by Myles Allen and Simon Tett, published in the journal Climate Dynamics (AT99). The authors claimed to have provided an unbiased and ‘optimal’ (precise) measurement of the size of effects of GHGs on climate patterns (the ‘Fingerprint’), which allowed researchers to check that the statistical models are properly specified (the RC or residual consistency test). Theirs was a regression method. The IPCC grew to love the method, and claims it gives results that show unequivocally that “human activities” or “anthropogenic emissions” were responsible for the “observed warming over the last fifty years.”
Another logical error lies hidden in these words. By “human activities” and “anthropogenic emissions” they mean carbon dioxide, and hence “warming”, “climate change”, and alleged increases in incidents of bad weather were caused by carbon dioxide. There is no effort to correlate in detail rising concentration with rising temperature, extreme weather events, or other effects, as one would expect in a linear regression analysis; blaming carbon dioxide is the broad assumption.
McKittrick and Tol examined the certainty in the IPCC-approved fingerprinting method. AT99 specifically invoked the Gauss-Markov theorem to prove that their method of regression estimation was unbiased and efficient, or as precise as possible. (BLUE: best linear unbiased estimator)
McKittrick observed that AT99 made a number of errors with respect to the Gauss-Markov theorem: the authors didn’t state it correctly, and failed to noticer that it did not apply to their estimator! Hence, there is no basis for confidence in the estimator that others thought there was. AT99 results are biased, completely misleading, and largely meaningless. McKittrick found that it was unclear what the RC test actually tested, the test wasn’t derived in the usual way, no mathematical derivation of the test was presented, the RC test doesn’t relate to the Gauss-Markov theorem, and it doesn’t actually test what the authors said it tested. The RC test is a completely meaningless statistic, said McKittrick.
The errors in the use of the Gauss-Markov theorem jump off the page to those experienced in using it and statistical analysis in general; and so the question arises, why didn’t anyone in the field notice this before McKittrick? He speculates that people with a lot of experience in statistical analysis haven’t been looking at this literature, and hence the theoretical inaccuracies have gone hitherto undetected.
McKittrick sums up the situation with a pair of quotes from his co-author, Richard Tol, who tweeted on Aug 21, 2021, “Allen & Tett introduced an FGLS estimator that is completely wrong and a test to show that they’re right, when they’re not.” And another on Aug 20, 2021, “Another literature that is entirely wrong…” There is, in short, no reason to believe that AT99 fingerprinting method produces valid results; and a lot of the literature attributing changes in atmospheric moisture, snow cover, forest fires, etc. are based on a method that gives wrong and meaningless results.
Thus, the basis for claims of certainty of around climate attribution is mathematically flawed and invalid.
Those of a philosophical bend will find interesting a back-door introduction of Thomism into the “science of attribution”. To say that one’s model is a true and accurate representation of a climate is to say that the model is a true understanding the form, or essence, of the climate. Following upon that are efficient and final causality, or end-directedness, of the climate; the form directing the climate towards a normative range of ends, which may be weather events. If ends other than these normative weather events occur, these anomalies or perturbations may be caused by “human activities” and “anthropogenic emissions”, which are nothing but efficient causes of change to the end-directedness, to the essence, of the climate being perturbed. The climate is expected to behave in accordance with the essence or form understood in the model. “Alteration” is not a change deemed within the principle of the climate, and hence, when reality doesn’t follow the model, the cause of that anomalous behavior, or alteration, is deemed due to external forcing, possibly by man’s emissions of carbon dioxide into the air, being the efficient causes of that alteration. The element of morality follows upon putting the efficient causality of ‘climate change’ on the activities of man, even as the proximate agent of change is carbon dioxide. Following upon that, the attributors attribute efficient causality to carbon dioxide - for bad weather events!
Since Newton, physical sciences have attempted to eliminate efficient and final causality, forms and essences, from the picture, and places all the causal eggs in the matter and in mechanisms. The science of attribution offers no mechanisms by which small increments in carbon dioxide cause changes in large atmospheric processes, or “weather events” (a possible violation of the principle of proportionate causality). Climate science, in attribution, adopts a Thomist view of the physical world, including that of immorality in its efficient causes.
From its early days, the climate “crisis”
has been a means of casting moral opprobrium upon the United States and Europe
for their cultural and economic successes, and was used as a means of
undermining a foundation of those economic successes, namely cheap and abundant
energy. Newtonian science, with its materialism and mechanisms, does not
readily lend itself to casting moral aspersions; but a Thomist view of the
world, with its recognition of formal, efficient, and final causes, as well as
material causes, enables the casting of moral blame upon its efficient causes,
namely “anthropogenic emissions” and “human activities”, or, in short, America
and Europe. Hence, the peculiar adoption of a Thomist analysis in what should
be a Newtonian science
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