Climate alarmists all over are having fun pushing the picture of historically unprecedented global warming in a recent cartoon timeline. It’s fun stuff, and granted the scientific and statistical illiteracy of most Americans (and others), it seems compelling.
But then a real statistician who’s also a climate scientist steps in and spoils all the fun. In “Global Warming Alarmists Promote SKCD Time Series Cartoon, Ignore Its Mistakes,” Matt Briggs explains, in as clear terms as seem possible, why the whole timeline lacks credibility, particularly as it projects temperature into the future, because in fact it depicts not temperature but models—models (as the Indian guru explained to the child who brazenly asked what was under the elephant that holds up the world) “all the way down,” only models, and models that we know are wrong.
Briggs explains that the Achilles’ heel in the cartoon timeline and all other attempts to graph long-term global temperature series is the failure to take seriously the degree of uncertainty not just in the measures of proxies for temperature (like coral and tree growth rates) but also in the measures of temperature itself (once we reach the age of thermometers):
The combined effect of forgetting about the measurement error is to produce uncertainty bounds that are again too narrow (because of the first measurement error type), and they produce graphs which are way, way too smooth (because of the second).
Have you ever noticed how smooth and cocksure plots of historical temperature are, like xkcd’s? These errors are why. What we should actually see, instead of xkcd’s smooth, pretty line, is a vast wide blur, which is blurrier the farther back in time we go, and more focused the nearer to our time.
And he concludes:
Because we can measure temperature in known years now (and not then), and we need not rely on proxies, the recent line looks sharper and thus tends to appear to bounce around more. It still requires fuzz, some idea of uncertainty, which isn’t present, but this fuzz is much less than for times historical.
The effect is like looking at foot tracks on a beach. Close by, the steps appear to be wandering vividly this way or that, but if you peer at them into the distance they appear to straighten into a line. Yet if you were to go to the distant spot, you’d notice the path was just as jagged. Call our misperceptions of time series on which xkcd relies for his joke statistical foreshortening. This is an enormous and almost always unrecognized problem in judging uncertainty.
There is one error left. From Anno Domini 2016 to 2100 xkcd shows dashed lines which are claimed to be temperatures. They aren’t, of course; at least not directly. They are guesses from climate models. These too should have uncertainty attached, but don’t.
The type of uncertainty xkcd should have put is again not “parametric” but predictive. We could rely on what the models themselves are telling us to get the parametric, or we could rely on the actual performance of models to get the predictive. Only the actual performance counts.
I’ll repeat that, too. Only actual model performance counts. That’s how science is supposed to work. We trust only those models that work.
Can we say anything about actual performance? Yes, we can. We can say with certainty that the models stink. We can say that models have over a period of many years predicted temperatures greater than we have actually seen. We can say that the discrepancy between the models’ predictions and reality is growing wider. This implies the uncertainty bounds on xkcd’s dashed lines should be healthy and wide. This is why xkcd’s, and the climatologists’, “current path” is not too concerning. There is no reason to place much warrant in the models’ predictions.
As we at the Cornwall Alliance have often put it (e.g., https://cornwallalliance.org/en… (1) On average, the models predict/simulate two to three times the warming actually observed over the relevant period. (2) 95% of the models predict more rather than less warming than observed; if their errors were random, they’d as frequently predict less as more; therefore they’re not random but driven by some kind of bias, honest mistake or dishonest deception, written right into the models themselves. (3) None of the models predicted the complete absence of statistically significant warming from early 1997 through late 2015 (roughly 18 years 9 months)–a zero trend interrupted by an unusually strong El Nino that, if nature takes its usual cyclical course, will be replaced by a La Nina, bringing global temperature back to what it was before the El Nino, resuming the zero trend to beyond the 18 years 9 months.
The consequence of (1), (2), and (3) is that the models provide no rational basis for any prediction about future global temperature and therefore no rational basis for any policy related to it.
And the consequence of that is that the IPCC and the various national climate policy-making bodies should close up shop and stop wasting billions of dollars, and all policies already adopted as means to control future temperature should be scrapped to prevent our wasting trillions more dollars.
