Steve: the MBH PC1 has EXACTLY the same scale as the synthetic PC1s. This is necessarily so because of how singular value decomposition works. The scale of both gets converted to degrees in the regression phase. There has been considerable disinformation about this from critics of ours, but you’ll notice that neither Mann himself nor wahl and Ammann raised this particular criticism.

I’ve read Ross’s description so I understand how the freak trees were amplified.
Is it fair to say the only reason The Mann Hockey Stick was not produced from noise is because no noise sequence had randomly produced a freak late 20th century growth spurt in any series that was fast enough to be exaggerated to that scale?
If you put a single freak Sheep Mountain tree into the rest of the hundreds of noise samples you used, do you get the no-trend PC suddenly convert into the MBH98 icon?

Steve: Mannian PCs are a very biased methodology. If you put a couple of HS-shaped series into a series with a different signal, you will get a HS. See our Reply to VZ.

Surely the physical reasons (eg the Divergence Problem) are a much greater reason to reject the MBH hockey stick than the statistical reasons (eg- the slight effect of non-standard centering and non-standard PC thresholding) ?

Sorry if this is old ground, but I’ve been a climate skeptic for many years and am only now hearing that some of the things I’ve been told over the years may not be the whole story. If this has been answered already in the intervening 7 years, just show me the thread.

Steve: if you read our articles rather than secondary sources, you’ll see that the red noise argument, though it attracted a lot of attention, is only one of several important criticisms. In retrospect, I would have placed additional weight on questions and issues arising on application of principal components (of any type, not just Mannian incorrect principal components) to tree ring networks. I look attentively at criticisms of our position and none to date have undermined our points. There’s a great deal of disinformation. I would have expected specialists in the field to be understand the criticisms better than they have and have become a bit bored with what seems to be wilful obtuseness.

He says:

The bottom line is, unless you look at the singular values, you can’t say *anything* about your data. You can’t simply look at the principal components (aka singular vectors) without considering the associated singular value magnitudes and draw any reasonable conclusions about whether your data vectors contain a “common signal” or are just random noise. Without the information provided by the singular values, you simply can’t tell (no matter what your principal-components look like).

But that’s exactly what skeptics did when they attacked Mann by claiming that his procedure generates hockey sticks from random noise. They never bothered to compare their “noise hockey stick” singular values with Mann’s “tree-ring” singular values.

Could McIntyre respond, perhaps by saying whether this is a red herring argument about the validity of the temperature hockey stick, or whether caerbannog actually has a valid point.

Steve: In our 2005 GRL article, we comment on “eigenvalues” from simulations as compared to Mann’s. “eigenvalues” are the same thing as “singular values”. Not that the issue turns entirely on eigenvalue significance. The bristlecones in the AD1000 network are “significant” even without Mann’s erroneous PC method – a point made in our 2005 EE article. That doesn’t mean that they are magic thermometers. Other important issues in these articles are the failure of verification statistics said to have been used in MBH (verification r2) and the unreliability of RE as an arbiter of reconstruction validity in the face of spurious correlation.

RomanM: You have now posted under the names:

I have not deleted the comments (although I am hoping Steve will decide to do so), but the next time you post without properly identifying yourself, all of your comments are unrecorded history.

You may have read the same paper about the suns activity as I read. That one has been challenged by later papers working on the same data. The corrections used for the 8Ky paper introduced a bias (reminds me of the hokey graph).

You do not explain what your standards for “good” or not “good” evidence are (or even what your point is about cosmic rays). I hope you did more of your homework on cosmic rays than you did for your other topics.

“no evidence for Co2″ comment. I have heard this one before a million times. Try refuting evidence rather than denying its existence. Everyone I have ever heard make this argument uses arbitrary and counter intuitive standards for what is and isn’t evidence. Either that or they are just ignorant.