51ce5b13_Quark_Soup_by_David_Appell__ode_Highlights_HIDE_HIGHLIGHTS
[Time] 24:08
Russ: Yeah. It's in economics, as I said, as well. I find it very frustrating. It's obviously the case that at any point in time there can be disagreement about, say, cholesterol, about the causes of ulcers. It takes a while. It's not like everybody immediately sees the data and it immediately changes there mind. But eventually controversial theories get either accepted or rejected. And new things come along to change that. In economics--and I'm afraid in climate change, what they have in common is that they are multi-causal, complex phenomena using time series data frequently. It's very hard to measure these things with precision. And the other thing that I think I want to emphasize here, and I want to turn to, is this question of where the data come from. Talk about the hockey stick, the reaction to the hockey stick and the reaction to the reaction and what its impact on you was. Guest: Yes. The hockey stick is a chart of temperatures over basically the last thousand years. Produced in the late 1990s and based on so-called proxies. Now that means--you obviously can't go back and measure the temperature in, you know, Arizona or in 1420 because no one was walking around with a thermometer there. But what you can do is look at the width of tree rings. And if you make the assumption that trees are growing faster in warmer temperatures, then you can say it was warmer then or it was colder then, and you can produce a chart. And if you combine lots of these proxies, you come up with a rough estimate of temperature over the last 1000 years. And what it appeared to show was a sort of gentle cooling for most of that time, followed by a very rapid warming in the last 50 or 100 years. Russ: Corresponding to the onset of modernity, modern economic growth and human activity. Guest: Exactly. Exactly. Now it turned out that there were two things badly wrong with it. One was that many of the data sets, the most dominant data set of all, was from bristlecone pine trees in the American West, which had been explicitly gathered by scientists who knew they were measuring a different phenomenon, namely the fact that overgrazing in that area had caused tree bark wounds, which resulted in rather rapid growth as the tree tried to cover up the wounds if you like--of course stripped bark. But any way, the point was nobody who was actually measuring the tree rings of bristlecone pine trees thought that bristlecone pine tree ring width reflected temperature. So that data shouldn't have been used. And I'm simplifying a bit here--there's a lot of other details and a lot of other data to discuss. But the second problem, if you like, was that the statistical filter through which the data was passed, called short-centering, resulted in any data series which showed a 20th century optic being vastly exaggerated. Being able to influence the final outcome more than a hundred times. In other words, the statistical method was--and this was beautifully demonstrated by Ross McKitrick and Steve Macintyre, Canadian economist and mathematician, basically, who were incredibly diligent in tracking this down. And they showed that actually this method was fishing out any data with a hockey stick shape and giving it undue emphasis. So, what happens if you leave the bristlecone pines out, and one other paper from the Gaspé Peninsula in Canada? And the answer is if you do that the hockey stick disappears altogether. Now, this was known to the scientists doing the work, because they'd actually done that; and they accidentally revealed this when they sent a data file called 'Censored' into the public domain, which showed that they had discovered that without those two data sets they couldn't get a hockey stick. Now, you don't have to get lost in the details of this or start accusing people of malfeasance, which I'm not doing here. I'm just saying that this one incredibly influential graph--and it was influential, not only on me but on the world: it was used 6 times in the Second Assessment Report of the IPCC; it was displayed at the Press Conference when the Report was announced. It was a fantastically important chart. This chart was based on data which--you only had to take one data set out and the chart changes completely. Now, for me, that's a real alarm bell. That tells you that--you are potentially contaminating your conclusions with very, very suspect data. There were further attempts to sort of rescue the hockey stick which involved large trees from Siberia. And again, when you drilled down, it turned out that there was one incredibly influential larch tree in the sample. One tree. Russ: A single tree. Well, it could be very informative. But of course it could be that distinctive things happened in that neighborhood that had nothing to do with the world as a whole. That's the problem. Guest: Exactly. If you've got a larch tree growing in the shade and all the other larch trees fall down because of a storm and it's left alone in the sun, it will suddenly grow faster. That might have been what happened in the 20th century to that particular larch tree.
Quark Soup by David Appell
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