I recently wrote about the wretched reporting on the claim that 2016 was the “hottest year on record,” using as my main example a New York Times article by Justin Gillis that gave his readers none of the relevant numbers they could use to evaluate that claim. None of them. If you search for the actual numbers, you will eventually find that the effect they are claiming, the actual amount by which this year was hotter than previous years, is smaller than the margin of error in the data.
Shortly afterward, I got a revealing response from Gillis. I’ll fill in all the details for you, because the whole thing is an important case study in why you can’t trust mainstream reporting on global warming. But let’s just cut to the chase. When I asked him why he didn’t include the basic numbers we need to understand his story, he gave me this reply:
So if I understand this correctly, a reporter from the New York Times is telling me that his readers are too dumb to understand numbers.
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Pushed a little on this, Gillis conceded that “there is no one number” for last year’s average global temperature, because it “depends on which of the five datasets you care to inspect,” and he went on to point to other complications.
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This is, pretty obviously, a dodge. His original article did not tell us that the numbers are complicated and that they vary depending on who is collecting the measurements. His original article simply hyperventilated about how amazingly hot it is. All the complications are just his fallback position when challenged.
