William M. Briggs, numerologist to the stars, has posted the claim that we don’t know whether temperature was cooler in the 1940s than in the 2000s. Apparently he objects to this graph:
Briggs’ reasoning boils down to this:
All you have to remember is these dots are estimates, results from statistical models. The dots are not raw data. That means the dots are uncertain. At the least, Plait should have shown us some “error bars” around those dots; some kind of measure of uncertainty.
Apparently Briggs thinks that computing an average means using a “statistical model,” and that entitles him to smear the result by association with the evil of “models.” That’s stretching the definition of “model” to the breaking point, for no other reason than to exploit the denialist tactic of denigrating anything and everything associated with the word “model.” Even, apparently, computing an average.
By the way, the plotted data are from the Berkeley project, and they included error estimates in their computation. They look like this:
Briggs goes on to say:
Now—here’s the real tricky part—we do not want the error bars from the estimates, but from the predictions. Remember, the models that gave these dots tried to predict what the global temperature was. When we do see error bars, researchers often make the mistake of showing us the uncertainty of the model parameters, about which we do not care, we cannot see, and are not verifiable. Since the models were supposed to predict temperature, show us the error of the predictions.
Notice that in the first paragraph Briggs said explicitly that the dots are estimates. Now he calls them “predictions.” Predictions? How is computing an area-weighted average a “prediction” rather than an “estimate”?
Briggs is just playing word games in an infantile example of novice sophistry. He wants you to believe that since he has called them “predictions” and claimed the come from some evil “models” they can’t be trusted. It’s not the “tricky” part, it’s the “tricksy” part.
Even if you leave out all adjustments (including unimpeachable ones like correction for time-of-observation bias which will reduce the uncertainty) so that the average is nothing more complicated than an area-weighted average of raw data, you still get the same, unambiguous warming pattern. And that warming pattern is statistically significant. Overwhelmingly so. Despite Briggs’ further sophistry.
Yes, folks, that’s it. Create a bogey-man made of straw, call it “uncertainty,” apply no analysis and no data, all just by waving of hands. That’s all he’s got.
But it’s enough for the numerologist to the stars! He uses his fiction about “prediction uncertainty” to conclude:
I don’t know what the prediction uncertainty is for Plait’s picture. Neither does he. I’d be willing to bet it’s large enough so that we can’t tell with certainty greater than 90% whether temperatures in the 1940s were cooler than in the 2000s.
What’s almost as impressive as the stupidity of Briggs’ post, is its condescending tone. Perhaps he should be nominated for an award.
P.S. Greg Laden has posted about Briggs’ nonsense too.