Do We Really Know That Human Greenhouse Gas Emissions Cause Significant Climate Change?

From the MANHATTAN CONTRARIAN

Francis Menton

It’s by far the most important scientific question of our age: Do human emissions of CO2 and other such “greenhouse gases” cause significant global warming, aka “climate change”? Based on the belief that an affirmative answer to that question is a universally accepted truth, our government has embarked on a multi-trillion dollar campaign to transform our economy by, among other things, eliminating hydrocarbon fuels from electricity generation (without any demonstrated workable plan for the replacement), outlawing the kinds of vehicles we currently drive, suppressing fossil fuel extraction, banning pipeline construction, making all your appliances work less well, and much more. Express any doubt about the causal connection between human activities and climate change, and you could very well get labeled as a “climate denier,” fired from your academic job, demonetized by Google or Facebook, or even completely ostracized from polite society.

But is there actually any real proof of the proposition at issue? In fact, there is not.

I had two important posts on this subject back in 2021: one from January 2, titled “Causation Of Climate Change, And The Scientific Method,” and the other from October 28, titled “‘The Climate Is Changing And Human Activities Are The Cause’: How, Exactly, Do We Know That?” Those posts covered the basics of how causation is generally established under the scientific method. Those posts also reviewed certain articles published at the time that gave good reasons to doubt the truth of the proposition that human greenhouse gas emissions are a main driver of significant climate change. Go to those posts for discussions of and links to the 2020/21 articles that I reviewed at the time.

The reason for today’s post is that a couple of important new articles have come to my attention that further make clear that the proposition that human activities, particularly “greenhouse gas” emissions, are causing significant climate change has not been proved and, based on existing data, cannot be proved. I’ll provide links and summaries, and let you draw your own conclusions as to the significance of these new articles.

But before that, let’s review one more time the basics of how causation is extablished under the scientific method. This is from my January 2, 2021 post:

We start with the basic maxim that “correlation does not prove causation.” Instead, causation is established by disproof of all relevant alternative (“null”) hypotheses. Everybody knows how this works from drug testing. We can’t prove that drug A cures disease X by administering drug A a thousand times and observing that disease X almost always goes away. Disease X might have gone away for other reasons, or on its own. Even if we administer drug A a million times, and disease X almost always goes away, we have only proved correlation, not causation. To prove causation, we must disprove the null hypothesis by testing drug A against a placebo. The placebo represents the null hypothesis that something else (call it “natural factors”) is curing disease X. When drug A is significantly more effective at curing disease X than the placebo, then we have disproved the null hypothesis, and established, at least provisionally, the effectiveness of drug A.

And yet somehow these principles don’t apply in the field of climate science. Instead, all the inside clique of the climate science community have decided to agree that the new way to prove causation is to show really, really good correlation with the preferred hypothesis, in which case subjecting the proposition at issue to a test of invalidation against a null hypothesis can be dispensed with. The climate science community calls its system for establishing causation “detection and attribution” studies. The basic idea is to come up with a model (i.e., a hypothesis) that predicts global warming based on increased greenhouse gases, and then collect data that show a very close match between what the model predicted and the data. Correlation with the model predictions is the claimed proof of causation. There are hundreds of such studies in the climate literature. My January 2, 2021 post linked to a classic of the genre, a 2018 IPCC-sponsored article written by a collection of some 36 co-authors who constitute a virtual “who’s who” of the insiders of the climate science cult (e.g., Michael Mann, Phil Jones, Tom Wigley, Ben Santer, etc., etc., etc.). The title is “Detection of Climate Change and Attribution of Causes.” Key quote:

There is a wide range of evidence of qualitative consistencies between observed climate changes and model responses to anthropogenic forcing, including global warming, increasing land-ocean temperature contrast, diminishing Arctic sea-ice extent, glacial retreat and increases in precip- itation in Northern Hemisphere high latitudes.

Just get yourself enough “qualitative consistencies” with your hypothesis and proof of causation will be yours!

The authors of the two new papers beg to differ. First, we have a paper by John Dagsvik and Sigmund Moen of Statistics Norway, dated September 2023, titled “To what extent are temperature levels changing due to greenhouse gas emissions?” This paper is particularly significant because it has been issued by a governmental agency — the government statistical agencies being otherwise all in lockstep in support of the human-caused global warming narrative. Excerpt from the Dagsvik and Moen paper (page 5):

At present, there is apparently a high degree of consensus among many climate researchers that the temperature increase of the last decades is systematic (and partly man-made). This is certainly the impression conveyed by the mass media. For non-experts, it is very difficult to obtain a comprehensive picture of the research in this field, and it is almost impossible to obtain an overview and understanding of the scientific basis for such a consensus (Koonin, 2021, Curry, 2023). By looking at these issues in more detail, this article reviews past observed and reconstructed temperature data as well as properties and tests of the global climate models (GCMs). Moreover, we conduct statistical analyses of observed and reconstructed temperature series and test whether the recent fluctuation in temperatures differs systematically from previous temperature cycles, due possibly to emission of greenhouse gases.

And the conclusion of Dagsvik and Moen (from the abstract):

[W]e find, . . . that the effect of man-made CO2 emissions does not appear to be strong enough to cause systematic changes in the temperature fluctuations during the last 200 years.

A good deal of the discussion in Dagsvik and Moen covers various deficiencies and inadequacies of the existing temperature data series — inadequacies that make it impossible to draw conclusions from existing data about causation of temperature increases from human greenhouse gas emissions. Here is one comment on the data from page 10 that I find particularly significant:

For all three surface air temperature records, but especially NCDC and GISS, administrative changes to anomaly values are quite often introduced, even for observations several years back in time. Some changes may be due to the delayed reductions of stations or addition of new station data, while others probably have their origin in a change of technique to calculate average values. It is impossible to evaluate the validity of such administrative changes for an outside user of these records.

For more than you will ever want to know on that subject, see my thirty part series “The Greatest Scientific Fraud Of All Time.” Bureaucrats altering the data to support their preferred narrative have rendered the data completely useless for any legitimate public policy purpose.

A second important new paper is from Antonis Christofides and co-authors dated September 26, 2023. They introduce their paper with a long post of that date at Climate, Etc. titled “Causality and Climate.” The part of the full technical paper relating to the climate science application can be found at this link. If you go to that last link and try to read through it, you will find technical math that will quickly have your head swimming, even if you are a quasi math geek like myself. However, their fundamental point as to causality in climate science is not very complicated: if you plot recent temperature increases against increases in CO2 in the atmosphere, it’s the temperature increases that come first, and the CO2 increases follow. Thus, if there is causality, it must be that the temperature increase is causing the CO2 increase, rather than the other way around.

Here is the key chart from the post at Climate, Etc.. The authors present it as a quiz: look at the chart, and the explanations, and without any further mathematical analysis, draw a conclusion as to the direction of causation:

From the technical paper:

[T]he surprising finding [is] that, while in general the causal relationship of atmospheric T and CO2 concentration, as obtained by proxy data, appears to be of hen-or- egg type with principal direction 𝑇 → [CO2], in the recent decades the more accurate modern data support a conclusion that this principal direction has become exclusive. In other words, it is the increase of temperature that caused increased CO2 concentration. Though this conclusion may sound counterintuitive at first glance, because it contradicts common perception (and for this reason we have assessed the case with an alternative parametric methodology in the Supplementary Information, section SI2.4, with results confirming those presented here), in fact it is reasonable. The temperature increase began at the end of the Little Ice Period, in the early 19th century, when human CO2 emissions were negligible; hence other factors, such as the solar activity (measured by sunspot numbers), as well as internal long-range mechanisms of the complex climatic systems had to play their roles.

I would make this comment as to both the Sagsvik and Christofides work: They both are using the only available data, which is data emanating from government sources that have been tampered with and altered. However, the important point is that even that data would appear to refute, and certainly does not prove, the endlessly repeated claims of impending climate doom from human CO2 emissions.