Of Coin Flips and 'Climate Change'

Heads I win, tails you lose. That might as well be the motto of the left these days, and not least of its Green flank.

For instance, it has become a commonplace that whenever anyone anywhere jokes during winter that global warming sounds nice right about now, for leftist condemnation to come in hot and heavy. As Eric Felton reminds us, when Donald Trump tossed off a one-liner to that effect during a speech on a frigid day in 2019, he was bitterly mocked by environmentalists. Anthony Leiserowitz of Yale's project on climate change communication (yes, such a thing does exist) said that the then-president's comment was "scientifically ridiculous and demonstrably false," adding,

There is a fundamental difference in scale between what weather is and what climate is. What's going on in one small corner of the world at a given moment does not reflect what's going on with the planet.

Good to know. But its hard not to notice that whenever it suits their purposes Greens will unreflectively sling bowls of hot, steamy, anecdata with the best of them. Have you noticed that you hear more about hurricanes during hurricane season these days? Climate change! Still wearing shortsleeves on Halloween? Climate change! Catch the news about that big tornado down south? Climate change!

As noted college drop-out and rich guy Derek Jeter said at Davos a few years ago, "[W]e’re seeing more and more natural disasters each year... Something has to be causing it.” Something other than the 24 hour news cycle and the rise of social media, I think he means.

Felton has a helpful evaluation of this summer's hottest example of this observation bias, the heat wave that hit the Pacific Northwest which saw temperatures consistently exceeding 100ºF. In a piece for RealClear Investigations, he discusses an organization called World Weather Attribution, "a group organized not just to attribute extreme weather events to climate change, but to do so quickly." While the heatwave was still ongoing, WWA put out a statement claiming that they'd analyzed the data and that the extreme weather would have been “virtually impossible without human-caused climate change.”

Considering their mission statement, it's hard to label this conclusion a shocker. But their claim of scientific objectivity gave cover to virtually every mainstream media outlet to confidently report that the heat was attributable to climate change. So saith the science!

Science!

Or saidth -- until a climatologist named Cliff Mass took the time to actually look through the data himself and came to an entirely different conclusion. Mass happens to be an expert in the weather of the Pacific Northwest -- he has actually written a book entitled 'The Weather of the Pacific Northwest' -- and his own weather models accurately predicted the heatwave.

According to Felton, Mass's modeling suggested that "global warming might have been responsible for two degrees of the near 40-degree anomaly. With or without climate change, Mass wrote, the region 'still would have experienced the most severe heat wave of the past century'." In short, the true culprit was the environmentalist movement's least favorite -- “natural variability.”

Mass made it a point to call out the shoddiness of World Weather Attribution's analysis, and they responded to his critique, saying that his report was "misleading and incorrect." But Felton notes that, after the release of Mass's study, WWA's statements on the topic were much more cautious and equivocating.

Let us all be inspired by their belated humility. Caution is king, at least where climate science is concerned. Better to be cautious than embarrassed when someone comes along and checks your work.

Damned Lies and Statistics: 'Climate Change'

“There are three kinds of lies: lies, damned lies and statistics,” a quote which Mark Twain in his Autobiography attributed to Benjamin Disraeli—though it more likely derives from the obiter dicta of the First Earl of Balfour. We all know—or should know—that statistics can be deceptive. Like language itself, they serve a dual function: to tell the truth and to lie—except that, unlike ordinary language, statistical contrivances appear to share the property of pure mathematics, that is, they seem objective, factual, impartial, and irrefutable. People are easily convinced, writes Darrell Huff in How to Lie with Statistics, by a “spurious air of scientific precision.”

The only way to disarm plausible but specious statistical accounts is to dig down into the source data or, when feasible, simply to use one’s common sense. Of course, statistics can be woven out of whole cloth, total fabrications which are easily rumbled with a modicum of attention, but it is their subtlety, their playing with half-truths, that can be most persuasive and damaging. Telling half the truth can be more insidious than a manifest falsehood.

Stars and shadows ain't good to see by.

Global Warming statistics are among the most readily manipulable, delivering factoids that are true and yet false—in other words, in other words. The tactic is to present a lesser truth that disguises a greater one. For brevity’s sake, let’s take just a few examples of how “climate change” statistics can rank among the most effective means of producing assent to outright mendacities, coating whoppers with honey.

Consider the twaddle that came out of the University of Illinois’ 2009 survey that 97.4 percent of scientists agree that mankind is responsible for global warming, a finding which is easily debunked when one accounts for the selection methodology.

As Lawrence Solomon explains in a crushing putdown, the Illinois researchers decided that of the 10,257 respondents, the 10,180 who demurred from the so-called consensus “weren’t qualified to comment on the issue because they were merely solar scientists, space scientists, cosmologists, physicists, meteorologists, astronomers and the like.” Of the remaining 77 scientists whose votes were counted, 75 agreed with the proposition that mankind was causing catastrophic changes in the climate. And, since 75 is 97.4 percent of 77, overwhelming consensus was demonstrated.

The real percentage, however, of concurring scientists in the original survey is a paltry .73 percent. That the chosen 75 were, as Solomon writes, “scientists of unknown qualifications” adds yet another layer to the boondoggle. This sort of thing is not a little white lie or an inadvertent statistical error. Once it reaches the point where a deliberate misconstrual must be maintained by the omission of details, the distortion of data and the suspicious liability to intentional error, we are in the presence of the great statistical charade as it is practiced by our accredited “experts.”

Not to be outdone, the Climate Research Unit (CRU) at the University of East Anglia developed a graph showing the trend to global warming, but neglected to note that it is calibrated in tenths of degrees rather than whole degrees, giving the misleading impression that the world is heating up when there is, in effect, little to no global warming to speak of. Similarly, the British climate journal The Register points out that NASA data have been “consistently adjusted towards a bias of greater warming. The years prior to the 1970s have again been adjusted to lower temperatures, and recent years have been adjusted towards higher temperatures.” Moreover, NASA data sets, as is so often the case, were predicated on omission, so-called “lost continents” where temperature readings were colder than the desired result.

Eureka! It's alive! 

As The Register writes, “The vast majority of the earth had normal temperatures or below. Given that NASA has lost track of a number of large cold regions, it is understandable that their averages are on the high side.” Additionally, NASA reports their global temperature measurements “within one one-hundredth of a degree. This is a classic mathematics error, since they have no data from 20 percent of the earth's land area. The reported precision is much greater than the error bar.”

The problem, warns Joel Best in Damned Lies and Statistics, is that “bad statistics live on; they take on a life of their own.” Their longevity supports their putative truthfulness. And the public is gullible, prey to the baked-in lies that Best calls “mutant statistics,” no matter how implausible.

Similarly, Tim Harford in The Data Detective, a celebration of good and useful statistical models, refers to the tendency toward motivated reasoning, i.e., “thinking through a topic with the aim, conscious or otherwise, of reaching a particular kind of conclusion.” Obviously, such thinking can work both ways, disparaging reliable statistics as well as valorizing dubious ones. The whole point, of course, is obfuscation, to keep people in the dark. Our soi-disant climatologists could just as well have written that climate is defined by a statistical curve in relation to a congruence subgroup of a modular elliptic, and the effect would have been the same. Whatever it means, it sounds official and incontrovertible.

In his essay, “March of the Zealots,” John Brignell comments on such acts of dissimulation. “If the general public ever got to know of the scandals surrounding the collection and processing of data [about global warming]… the whole movement would be dead in the water… It is a tenuous hypothesis supported by ill-founded computer models and data from botched measurement, dubiously processed.”

Examples of data manipulation abound. For more thorough analyses, see Michael Shellenberger’s Apocalypse Never, Steven Koonon’s Unsettled, Tim Balls’ The Deliberate Corruption of Climate Science, and Rupert Darwall’s Green Tyranny, all of which are eye-openers. As Stanford professor Dr. John Ioannidis writes in a much-circulated paper provocatively titled Why Most Published Research Findings Are False, “There is increasing concern that in modern research, false findings may be the majority or even the vast majority of published research claims. However, this should not be surprising.”

Flawed statistical analyses have become the established currency of the climate economy.