Perhaps the DC bias prior to 1400, such as during the MWP, which coincidentally shows up in most of the proxies (as I recall), would cause problems for the “warmest in a milluuuuun years” claim?

Or lack of long-term cooling trend might be the reason, who knows

The premise of a physical system …… of linear ordinary or of linear partial differential equations

Tree ring response to temperature can hardly be described as “linear”. I would think “parabolic” is more apt…. The pretext for using Preisendorfer seems to collapse from the outset.

With 20-20 hindsight, it would have been possible for Mann to have used a PC method which was less bad – in which case the issue would be squarely on the validity of applying conventional principal components to the North American tree ring data set as a means of obtaining a temperature proxy – which has never been established – and of the validity of bristlecones.

Think of a murder victim with multiple stab wounds. The police arrest the husband and can prove that he stabbed his wife repeatedly and charge him with murdering his wife by stabbing her to death. Let’s now suppose that his defence is that he had already smothered his wife to death and the stabbing took place into her dead body so the claim that he murdered her by stabbing her to death was wrong. As I understand it, the count could be amended and the accused would not go free on such a technicality.

Mann applied PC methodology applied to a tree ring network with multiple bristlecones. Trying to find the “real” problem in such a mess is like a complicate episode in CSI. The bristlecones are one problem; applying ordinary PCA to tree ring networks is another problem; Mannian PCA is another problem. Removing bristlecones from this nbetwork doesn’t necessarily improve things at all. I’m not saying that there’s a “right” way to get an answer out of this mess.

There is much talk of the bristlecones being overweighted, that I understand & hence the reason the hockey stick appears – what I don’t quite get is how the weightings get to be where they are. Is it a deliberate choice by Mann et al, or is it some artifact of PCA analysis which up-weights certain datasets “automagically”?

(Apologies if this is a dumb question, or is answered elsewhere)

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In # 36 above I mentioned that temperature of trees and wind direction confounded. The tree is a living system with cycles of growth and rest that are impacted by temperature. There are times when a short blast of hot or cold out of season can limit or help growth for a year or more.

Analogy: People need to drink water to avoid getting ill/dying. Over a month, one might drink a similar volume each day; or to argue by extreme, could drink at twice this rate in the first fortnight and drink nothing in last fortnight. Monthly average remains the same, conseqence is reduced growth, maybe permanently.

Same with trees. Growth is affected not just by the average value of monthly temperature, but also by the distribution pattern of temperatures within each month. If the calibration period cannot infill the fine structure, the stats will not be capable of reconstructing the past.

Having taken very rare trees from China to Australia, I know a little about coping wih seasonal changes (NH to SH in a day), so my comment contains practical as well as theory. Is that so novel?

The reasoning is simple. You have no gridded surface data for temperature or rainfall or any weather phenomena, you have scattered stations around the globe and nearly nothing on the ocean. With satellite data you at least have a grid, but the physicist in me says good luck finding an equation that can represent the physical reality you’re collecting data from. In too-simple terms, no boundary conditions = no understanding of what’s going on.

My read of what Steve and Ross (and others here) have done is point out that PC1 or the HS factor is a characteristic of group of respondents (the BCPs) and not the underlying temperature signal.
Is this a correct interpretation?

If you amend that to may not be the underlying temperature signal then yes, your interpretation is correct. This is confounded by the fact that the HS signal is predominantly present in BCPs, which end up getting weighted heavier than other proxies. Whether or not it is truly temperature is hard to say without removing other factors that may be contributing to their shape, too. PCA does not assign a “flag” to the results indicating which is which, and when multiple inputs to the system (e.g. solar, precipitation, CO2 fertilization) are correlated, disaggregation is even more difficult (if not outright impossible).

The short answer is that the “signal” that shows up is assumed to be temperature simply because the surface temperature readings are increasing at the same time, and the BCPs are assumed to be responding to temperature, not other factors. That BCPs will necessarily respond to local temperatures, not global temperatures, is lost on the proponents of the proxy reconstruction theory (via PCA), btw.

Mark