Posted on 10/15/2004 2:39:25 AM PDT by Goat Locker Freeper
Progress in science is sometimes made by great discoveries. But science also advances when we learn that something we believed to be true isnt. <>
In the scientific and political debate over global warming, the latest wrong piece may be the hockey stick, .... This plot purports to show that we are now experiencing the warmest climate in a millennium, and that the earth, after remaining cool for centuries during the medieval era, suddenly began to heat up about 100 years ago....
-SNIP-
But now a shock: independent Canadian scientists... have uncovered a fundamental mathematical flaw in the computer program that was used to produce the hockey stick. In his original publications of the stick, Mann purported to use a standard method known as principal component analysis, or PCA, to find the dominant features in a set of more than 70 different climate records.
But it wasnt so. McIntyre and McKitrick obtained part of the program that Mann used, and they found serious problems. Not only does the program not do conventional PCA, but it handles data normalization in a way that can only be described as mistaken.
Now comes the real shocker. This improper normalization procedure tends to emphasize any data that do have the hockey stick shape, and to suppress all data that do not. To demonstrate this effect, McIntyre and McKitrick created some meaningless test data that had, on average, no trends. This method of generating random data is called Monte Carlo analysis, after the famous casino, and it is widely used in statistical analysis to test procedures. When McIntyre and McKitrick fed these random data into the Mann procedure, out popped a hockey stick shape!
-SNIP-
Suddenly the hockey stick, the poster-child of the global warming community, turns out to be an artifact of poor mathematics.
(Excerpt) Read more at technologyreview.com ...
Perhaps we all should contact our local newspaper and ask them to describe PCA, and then use this as an example?
No, I don't think that they understand the math.
Yes, but given the usage of them by the "global warmers", they appear to THINK that they are singular. I can't think of any other way they can come up with some of the extrapolations that they do.
"(Born and raised a Marylander, North Dakotan by choice.)"
Masochist??? (North Dakota winters :^) ) My blood is WAY too thin to handle that kind of cold weather!
Cold? What cold? We'd never get the tourists out of here if we didn't tell those stories...
BUMP!
Canadians know about hockey sticks.
Hey, little things like "experimental data" mean nothing to the eco-"computer modellers". Far be it from them to let "historical fact" stand in the way of a good theory/model.
Ah, I see---it's like the "it rains a lot in Seattle" verbiage.
Yes, but the rest of us are supposed to catch them at it. Me, I just assumed they had done the basic analysis correctly. Bad assumption, it turns out.
(Thank heavens this isn't actually my field. I'd be mortified.)
That's EXACTLY what I was thinking. Of course I'm paranoid and cynical.
I don't know, I have never been to Seattle. If so, I'd better take my water wings if I ever go :)
I don't follow you here. The little ice age is taken to be between about 1300 and 1800 (depending on when you count it). In the "corrected" plot they are showing temperatures higher then now during the little ice age!!!
The little ice age really started to take hold in Shakespeare's day (late 16th century) and was at its most severe around 1700.
Well, the latest date I could find for the start of the little ice age was about 1500. Most seem to be about 1450 e.g.
http://www.grisda.org/origins/10051.htm
The ones that are later have a previous period called the Medieval glaciation which indicates it was still cold.
Looking at the graph we see a large warm spike that was much warmer than current temperatures at 1500.
regards,
Yelling
Yep.
That's right, but these guys don't care about that. It's their agenda they care about, not the physics of the situation. That's why their simulations include lots of bogus methods and data accompanied by as much handwaving. Like Bellisiles account of American history, or any leftist construction, reality doesn't matter. It's the desired outcome that does.
I totally agree with your assertions about patterns in random data (they can be expected). Where I disagree is that PhD professional statisticians can by chance make an error that supports their case without intent. If you and I know about this potential, bet your but they do. There is one area where lesser PhD level statisticians make genuine mistakes, IMO. It is not in data normalization, but in the application of a priori rules to a posteriori questions. So, my starting point is malice on their part, because their mistakes systematically supported their political agenda. Regards,
(a) applying, as this graph does, as close to Mann et al's _unreplicable_ method as possible to the datasets actually disclosed (including updates, excluding undisclosed truncations, etc) in the Mann et al paper will
(b)actually reflect hemispheric climate history.
It is the rolling, 20-year mean; a lot easier to see the fraud than the yearly one. I am sure you are correct. I will post the yearly one shortly.
You know yer stuff!
The previous graph that I posted showed a rolling, 20-year mean, with the charts overlaid. This is the yearly ones; not as easy to see, but trend is the same.
Top one is the bogus one, bottom is the corrected one.
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