Thanks to Peter Spero and Alex Chernavsky.
Thanks to Dennis Mangan.
Thanks to Anne Weiss.
One episode of A History of Ancient Britain, the recent BBC series, is about the Ice Age. If you know there was an Ice Age, you should grasp that the Earth varies in temperature a lot for reasons that have nothing to do with human activity. To measure the effect of recent human activity on global temperatures, you need to know what the Earth’s temperature would have been in the absence of human activity. Then you find the effect of humans by subtraction (actual temperature – predicted temperature assuming no human activity).
That’s hard to do. Because the non-human effects are so large, you need a really accurate model to “control” for them. No such model is available. No current climate model has been shown to accurately predict global temperatures — the IPCC chapter called “Climate Models and Their Evaluation” (informal title: “Why You Should Believe Them”) is the most humorous evidence of that. Lack of accurate predictions means there is no good reason to trust them. (That the models can fit past data means little because they have many adjustable parameters. “With four parameters I can fit an elephant,” said John von Neumann.) The case against the view that humans have dangerously warmed the climate (sometimes called AGW, anthropogenic global warming) is that simple.
Because it is so simple, “the other side” consists of saying why 2+2 really does equal 20 or whatever. Sure, many people say it, so what? When I was an undergrad, I gave a talk called “The Scientific ____ “. I said usage of the term scientific without explaining what it meant was a sign of incompetence and a reader could safely stop reading right there. That isn’t terribly helpful, because few people use scientific that way. My grown-up version of this test is that when someone claims AGW is true, I stop taking them seriously as a thinker. I don’t mean they can’t do good work — Bill McKibben is an excellent journalist, for example. Just not original thought.
Q: How many climate scientists does it take to change a light bulb?
A: None. No need to change it. Because it’s been changed in the past, they say, it will be changed in the future.
A tiny fraction of climate scientists publish papers showing how their model can fit past data — say, global temperatures from 1600 to now. The authors of these papers claim that this sort of thing shows their model can predict accurately. In fact, it means roughly nothing — perhaps the model was flexible enough to fit any plausible past data.
Outsiders take fitting past data seriously, but what do they know? However, when a graduate student in atmospheric science takes fitting past data seriously (“it is perfectly reasonable to treat reproductions of the past climate as [successful] predictions”), the whole field has a problem.
A few weeks ago I pointed out the lack of a good reason to believe the scary predictions of climate models. Al Gore, Bill McKibben, and a million other public figures say we should believe what the models predict about global temperature ten years from now. Yet, as far as I know, the models have never made accurate and surprising predictions of global temperature. They are claimed to do what they have never been shown to do. In contrast to the absence of accurate predictions of global temperature is the presence of wrong predictions.
The lack of persuasive predictions is clearest when experts who believe climate models fail to supply them. This is why I linked to a warmist web page with a wealth of “supporting” information. Surely its creator had studied the issue deeply. This is why I noted that the Science Editor of The Independent, a major English newspaper, failed to supply such evidence. Surely he had read a lot about the issue.
And this is why I note that a graduate student in atmospheric science has failed to supply such evidence. On my Psychology Today blog I reposted one of my earlier posts about this. The graduate student said I was “misinformed about the nature of climate models” and that he “could go on for pages” about why. But he too failed to supply an example of an accurate surprising global-temperature prediction. (For an inaccurate prediction of a 1986 model, see here.)
In a comment on a previous post about lack of convincing evidence for climate models — the ones that predict catastrophe — I wrote:
At any time — right now, 5 years ago, 10 years, 15 years ago –” the people who work with those models and claim we should pay attention to their predictions could make/have made a set of predictions: next year, the year after that, and so on. Then, as time passed, we would have found out if the models predict correctly. The modelers haven’t done that.
From this talk by Richard Muller, a Berkeley physicist, I learned of two instances where the modelers did what I said they haven’t done.
1. In 2009, James Hansen predicted, based on his model, that 2010 would be the hottest year on record. Since temperatures had been roughly constant — not rising — for the previous 12 years, this was an interesting prediction. When 2010 ended, Hansen’s own data (analyzed in an unusual way, according to Muller) found this to be true, but two other datasets found it to be false.
2. In 2001, several scientists, based on nine climate models, predicted that Antarctic ice would increase over the next ten years. In fact, it decreased (“exactly the opposite of the prediction”). In response, John Holdren, President Obama’s science advisor, said, according to Muller (at 26:22):
Well, those models were really wrong. But now we’ve changed those models. And now if we run them again they show that the ice will decrease. And therefore this is evidence in favor of global warming.
The audience tittered.
If you think Climategate was not important, and that the scientists whose email was revealed did nothing seriously wrong — as several official investigations, Bill McKibben (“if you managed to hack 3,000 emails from some scientist’s account, you might well find a few that showed them behaving badly”) and New Yorker staff writer Elizabeth Kolbert have concluded — you should see what Muller says about it (starting about 30:00).
I liked the talk. Muller makes several points with which I agree and presents helpful data. However, there were several things I didn’t like. There is one big gap. Muller thinks current climate models are probably right, but doesn’t explain why. I would have liked to know. And he says two things with which I deeply disagree. First, he says scientists shouldn’t say what the data will show — that is, make predictions. I believe that making and testing predictions is by far the best way to learn how much we know. Second, Muller says that buying a Prius does nothing. The improvement is too small, the cost of a Prius too great. People in China can’t afford a Prius, says Muller. This misses a really important point. When you buy a Prius you are supporting innovation. To solve the big problems that arise in any society, innovators need support. My theory of human evolution goes on and on about this. Long ago, connoisseurs supported innovation. Festivals such as Christmas supported innovation. Art lovers supported innovation. Fashion supported innovation. The great achievement of Tyler Cowen’s new book The Great Stagnation, which I will discuss tomorrow, is its focus on rate of innovation. What controls rate of innovation is a supremely important question usually ignored by economists — as Muller ignores it.
In any case, here are two actual predictions and how they fared.