One point that many people do not understand is that merely labelling something a "proxy" and putting it in a multiproxy dataset does not mean that it has any correlation to temperature.
I’ve plotted up the 22 proxy series in the 15th century MBH98 dataset so that others could see a little more clearly what this means – the proxies are in black. This type of detailed plotting is really needed in presentations of multiproxy studies and is not really suited to academic journals (one of the many gaps that would be filled by the equivalent of engineering-calibre analysis of these studies before policy usage.)
The blue in Figure 2 is the Wahl-Amman version of the AD1400 MBH98 reconstruction based on the 22 “proxies” plotted individually; the red in Figure 1 is the last portion of the MBH98 stepwise reconstruction using 112 “proxies”. The level change in the MBH98 proxy index about 1930 is quite distinct.
Figure 1. The first 11 proxy series in the AD1400 network
Notice that most of the proxies look like white noise, but the Gaspé series has a distinct trend. I’m sure you can pick out Gaspé without it being identified. Of course the updated Gaspé series (which Jacoby has withheld) does not have this trend and they have "lost" the location. The series at bottom left (Svalbard ice melt) is obviously very non-normal, but no consideration is given to this in MBH98.
Figure 2. The other 11 proxy series in the AD1400 network, this time with the Wahl-Amman AD1400 version of MBH98 in blue.
Again most of the proxies look like white noise, but the bristlecones (the MBH98 NOAMER PC1) has a distinct trend. I’m sure you can pick out the MBH98 NOAMER PC1 without it being identified. I understand that Hughes has new data for Sheep Mountain, but this has not been reported.
You can readily see how the Gaspé and bristlecones stamp the reconstruction. In effect, if you take the weighted average of these two series, you replicate most of the variance in the MBH98 AD1400 reconstruction – the other proxies are there for padding.
Many people think that MBH98 is in some way an average of the proxies. It isn’t. For the portion of the algorithm that does most of the lifting, they regress the proxies against the first temperature principal component, which has an upward trend. The index itself is essentially a weighted average of the proxies weighted by this correlation. So their regression module has a mining element – over and above the mining element in their tree ring principal components calculation.For example, the upward trend in the top right Figure 2 series has been mined from 70 series and doesn’t represent an average or even a properly calculated principal component.
One reader commented that use of all these series shows that they weren’t data mining: that’s not the case. What happens is that their regression module, which is quite a weird algorithm itself, strongly picks up the trends. I’ve mentioned before some simulations where I’ve applied his method to one hockeystick shaped PC1 and 21 white noise series and the MBH98 method is imprinted by the hockeystick shaped PC1. So most of the other series are simply an illusion in terms of contributing – their weights may be as little as .1% of the Gaspé series.