Hide the decline was not just removing later values of a proxy. Take a look at the hockey stick, how it goes up at the end. It didn't have to do with just Briffa's proxy, you can see it MBH98 as well. Mike's Nature Trick is to add the instrumental temperatures, and then smooth with those values instead of the proxy values. So it looks like the proxy is showing a high value at the end instead of a 'low' value.
Mann is certainly dangerous. Just ask Mark Steyn. And as to your claim you know nothing of Mann's political views is total rubbish. He has expressed them many times and has even overtly pressed for legislation. You have to be blind not to see it or have an I. Q. demonstrably lower than a monkey.
Hiding the decline really refers to corrupting number crunching. You may call it anything else but it boils down to fraud.
Update 2: The algorithms take what you them and just do what they do (not unlike most Deniers, equations do not understand or care about the concept of data).
Quote by Chris Folland of UK Meteorological Office: “The data don't matter. We're not basing our recommendations [for reductions in carbon dioxide emissions] upon the data. We're basing them upon the climate models.”
Who doesn't care about the concept of data? I think you owe all true scientists, the ones you so maliciously call 'deniers', an apology.
My partner and i highly recommend applying http://www.vpnmaster.org to unblock web sites. I am using their services for more than 4 years with no issues.
What you say is correct (allthough there is no need to be so arrogant and abusive) the problem with proxy's is it so easy to cherry pick by selecting which proxy's suit your study
My apologies. I will not do this after I address Hey Dook's and Mike's comments.
This answers Hey Dook - and if my response to Mike fits here, this will be the end of it.
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Principal Component Analysis (PCA) is a data-reduction technique that, for example, takes 100 individual proxy records and creates 9 groups (components; aka Principal Components [PC]) – so you end up 9 instead of 100 independent variables. The method also ranks the PCs in terms of significance from strongest (PC1) to weakest (PC9). The net result is that you can end up 2 or 3 or 4 or whatever “significant” independent variables.
Mann’s PC1 consisted most of high-elevation bristlecone pine (BCP)/ Maybe “dominated by” would have been better than “leveraged.”
>>, "proxy data unaffected by CO2" are subtracted "from from the PC containing<<
As you get closer to the present (in general) sample depth increases – so there are more PCs (containing more of the original proxy data) after 1902 and even more after 1902. Before 1400, PC1 is all that there is. Mann subtracted the later values of the other combined PCs from the PC1 and kept the differences between them (the “residuals”) which he then used in place of the original PC1 values The PC1 values were still greater than the combined values of the remaining PCs, but the difference between the two was reduced.
