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Megan McArdle

Megan McArdle - Megan McArdle is a senior editor for The Atlantic who writes about business and economics. She has worked at three start-ups, a consulting firm, an investment bank, a disaster recovery firm at Ground Zero, and The Economist. More

Megan was born and raised on the Upper West Side of Manhattan, and yes, she does enjoy her lattes, as well as the occasional extra-dry skim-milk cappuccino. Her checkered work history includes three start-ups, four years as a technology project manager for a boutique consulting firm, a summer as an associate at an investment bank, and a year spent as sort of an executive copy girl for one of the disaster-recovery firms at Ground Zero … all before the age of 30.

While working at Ground Zero, Megan started Live From the WTC, a blog focused on economics, business, and cooking. She may or may not have been the first major economics blogger, depending on whether we are allowed to throw outlying variables such as Brad Delong out of the set. From there it was but a few steps down the slippery slope to freelance journalism. She has worked in various capacities for The Economist, where she wrote about economics and oversaw the founding of Free Exchange, the magazine's economics blog. She has also maintained her own blog, Asymmetrical Information, which moved to The Atlantic, along with its owner, in August 2007.

Megan holds a bachelor's degree in English literature from the University of Pennsylvania and an M.B.A. from the University of Chicago. After a lifetime as a New Yorker, she now resides in northwest Washington, D.C., where she is still trying to figure out what one does with an apartment larger than 400 square feet.

ClimateGate: Was Data Faked?

By Megan McArdle
Dec 9 2009, 1:43 PM ET Comment

I am thoroughly unimpressed with the belief that global warming scientists have been engaging in some kind of massive conspiracy to conceal the truth.  First, because we seem to be able to observe things like polar ice sheets melting, which point to warming.  And second, because, well, why the hell would they?  I can imagine a sort of selection bias in the grant process.  I cannot imagine hundreds of scientists thinking, well, I put ten years into getting my PhD--time to spend the rest of my life faking data in order to get some grant money!  One, yes.  All of them, no.

To me, the worry is the subtler kind of bias that we indisputably know has led to scientific errors in the past.  Richard Feynman has the most elegant exposition I've ever read:

  We have learned a lot from experience about how to handle some of the ways we fool ourselves. One example: Millikan measured the charge on an electron by an experiment with falling oil drops, and got an answer which we now know not to be quite right. It's a little bit off, because he had the incorrect value for the viscosity of air. It's interesting to look at the history of measurements of the charge of the electron, after Millikan. If you plot them as a function of time, you find that one is a little bigger than Millikan's, and the next one's a little bit bigger than that, and the next one's a little bit bigger than that, until finally they settle down to a number which is higher.

Why didn't they discover that the new number was higher right away? It's a thing that scientists are ashamed of--this history--because it's apparent that people did things like this: When they got a number that was too high above Millikan's, they thought something must be wrong--and they would look for and find a reason why something might be wrong. When they got a number closer to Millikan's value they didn't look so hard. And so they eliminated the numbers that were too far off, and did other things like that.

We've learned those tricks nowadays, and now we don't have that kind of a disease. But this long history of learning how not to fool ourselves--of having utter scientific integrity--is, I'm sorry to say, something that we haven't specifically included in any particular course that I know of. We just hope you've caught on by osmosis.

The first principle is that you must not fool yourself--and you are the easiest person to fool. So you have to be very careful about that. After you've not fooled yourself, it's easy not to fool other scientists. You just have to be honest in a conventional way after that.

That is the actual worrying question about CRU, and GISS, and the other scientists working on paleoclimate reconstruction:  that they may all be calibrating their findings to each other.  That when you get a number that looks like CRU, you don't look so hard to figure out whether it's incorrect as you do when you get a number that doesn't look like CRU--and maybe you adjust the numbers you have to look more like the other "known" datasets.  There is always a way to find what you're expecting to find if you look hard enough.

There are other issues:  selection bias in the grant process, papers with large results being much more likely to be published than papers with equivocal results, professors preferring students who agree with them, and so forth.  I doubt that could amount to faking the entire thing.  But it could amplify the magnitude.

That's why this sort of thing is so worrying:

Then I went to look at what happens when the GHCN removes the "in-homogeneities" to "adjust" the data. Of the five raw datasets, the GHCN discards two, likely because they are short and duplicate existing longer records. The three remaining records are first "homogenized" and then averaged to give the "GHCN Adjusted" temperature record for Darwin.

To my great surprise, here's what I found. To explain the full effect, I am showing this with both datasets starting at the same point (rather than ending at the same point as they are often shown).

darwin_zero7
Figure 7. GHCN homogeneity adjustments to Darwin Airport combined record

YIKES! Before getting homogenized, temperatures in Darwin were falling at 0.7 Celcius per century ... but after the homogenization, they were warming at 1.2 Celcius per century. And the adjustment that they made was over two degrees per century ... when those guys "adjust", they don't mess around. And the adjustment is an odd shape, with the adjustment first going stepwise, then climbing roughly to stop at 2.4C.

More than one blog is saying this proves that some of the data was falsified.  I think that's too strong.  But it does look like maybe they got a little too aggressive massaging it.

Is this an anomaly?  I hope it is, and think it probably is.  But I worry that it isn't. And I'm eagerly awaiting someone at RealClimate or similar to explain why and how this kind of correction got applied.




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