A repy to Dr. Jim Bouldin
Posted by Jeff Id on July 27, 2011
I’ve been gone for a while working on other things. MikeN called my attention to a criticism by Jim Bouldin, of my ‘probing’ of the hockey stick CPS methods. Since the Air Vent wouldn’t even be a climate blog, if it weren’t for Mann 08, it does seem important to address the criticisms by Jim. As it is my blog, the cool thing is that I can shove comments right in the middle of his criticisms to point out the issues of disagreement.
Oh boy. BIG problem with Jeff ID’s point that you quoted above.
To summarize: He is arguing that a hockey stick emerges as an artifact of the method used for screening proxies to include in a reconstruction (with specific reference of course, to *Mike Mann’s* reconstructions). The cause of this artifact production is supposed by him to be due to the fact that: “…The series are scaled and/or eliminated according to their best match to measured temperature which has an upslope. The result of this sorting is a preferential selection of noise in the calibration range that matches the upslope, whereas the pre-calibration time has both temperature and unsorted noise.”
This statement is entirely *false*, and it is so on several levels (including use of poor terminology such as “sorted” to mean screened). Not only is it false, it shows a phenomenal lack of attention to the most basic of facts, as presented by Mann et al in their 2008 paper in PNAS, both in the main paper and in the supplemental material. To wit:
There were 1209 proxies (from some larger candidate set) that met three initial screening criteria, (such as minimum length of record and stated minimum correlation among the individual members at a given site). From these 1209 records, a nominal screening cutoff of p < .10 with either of the two closest instrumental temperature grid points, was established. (After accounting for temporal autocorrelation, this p value rises slightly to p < .128). If one assumes a positive relationship between ring measure and temperature (i.e. one tailed test), the expected number of sites meeting this criterion is: 1209 * .128 = 155. (If one assumes that either a positive or negative relationship might occur, which they do not, the number is half that, about 78.)
The actual number of sites that passed this screening: 484, or over 3 times the number expected based on chance alone, (i.e. assuming no relationship between rings and temperature, and using a one tailed test).
See, Jim has several misunderstandings. The point he repeats from M08 is that Mannian correlation passed so many proxies, it couldn’t be by accident and they must be truly temperature!! This is the same point proven wrong here so often. Jim doesn’t read here for sure.
First we can remember Tiljander which was simply flipped to improve the high number of correlated series, from memory, this counts for 3? of 484 series but it is worse than that. Luterbacher, which included 71 series of ‘ACTUAL’ physical temperature data, also skewed the results – so subtract another 71 bs proxies from 484 as the portion of the proxy Mann checked for correlation to temperature – was actual temperature.
Don’t worry, I’m not done yet!
Furthermore, the mean correlation for sites with records that went back to 1000 AD was 0.33. The probability of getting an r value that high by chance, over a 150 year calibration period, for 59 sites, is very small indeed. Note that Mann et al pointed all but the last of these things out in either the paper, the supplement, or both.
In short, the probability of getting 484 sites that pass the p < .128 screening by chance, is very small, and his argument is utterly wrong. The only way it could be true is if somehow the temp-ring relationship magically arose in 1850 but didn’t exist beforehand, which of course is ludicrous.
It is about 120 series that would pass if you accept Mann’s incredibly generous autocorrelation assumptions. Far, far, higher if you do not. One of the most difficult scams of the paper is the determination of the correct autocorrelations to use for this particular correlation value. Jim apparently accepts it with a hand wave and zero consideration but climate science isn’t known for statistical prowess. It becomes even more fuzzy when you realize that the autocorrelations of individual series are so widely different that several won’t even converge with R’s arima fit function.
I imagine you had no intention that this post would devolve into another paleoclimate debate, which in the minds of some, is of course perfectly synonymous with the hockey stick “debate”.
I note also that Jeff ID states in the thread you mentioned: “Even though I am certain this is one hundred percent correct, this changes little about the climate story. What it does do is make one wonder how math skilled individuals still refuse to acknowledge it.”
Well Jeff, maybe because it’s perhaps, patently wrong?
Lessee, 484 sites, 71 Luterbacher are actual temperature, so these clearly do not help support the NULL proxy by accident theory and can be subtracted from the 484 and 1209 total series. We can’t forget the ‘high end’ climate scientists who decided the IPCC should ‘hide the decline’ of the latewood density data (MXD) and simply chop the data off. Yup, chop the offending bit of flacidity off and give it an Enzyte style prosthesis courtesy of RegEM — The Mann show. Scientifically speaking, we have now subtracted another 95 series of horsecrap data from the remaining 413 leaving only 318 series (at a maximum) that passed validation presumably using actual data taken from actual proxies. NOPE, not so fast, this is climate science so we’re not done yet!!
Of all 1208 series, there were only a small fraction which were not artificially infilled prior to screening. Yup, only a few percent gave the dog its wag.
Of the 484 series with enough Mannliness to pass correlation screening, 391 were infilled with fake data as plotted below.
With average data looking like that, even Bond would be proud. Individual series often looked like this realistic piece of RegEM’d jewelry. Imagine the pride you would feel presenting this piece of augmented data to your professor in college.
So with all but a few data series not artificially augmented, Jim Bouldin (PhD) has determined that little Jeff Id BS, has no clue what he is talking about — thus the BS I suppose.
Well Jeff, maybe because it’s perhaps, patently wrong?
Methinks the good doctor needs to stop worrying which team he is on and look at the paper. Even more importantly than the infilling, proper characterization of autocorrelation powerfully affects the ‘screening’ of Enzyte accredited series, as this post demonstrates.
Perhaps the good Doc thinks I need to take his matlab class
All kidding aside, I can and have physically demonstrated that the number of M08 proxies passing correlation cannot be stated to be biased toward having an upslope signal, let alone a temperature signal. It is a misnomer, promoted by duped reviewers and a scientific community sporting a lack of diligence and Jim has jumped two feet into the hole. It may not be his fault as the paper is obtusely written with more puzzles than the New York Times, but skepticism should be the core of a good scientist.
Not a good start for our relationship.
More to come when time allows.