Vigilanis, on 14 April 2012 - 09:15 AM, said:
There are a plethora of people who claim to have irrefutable evidence that climate change exists, the climate does change and vary but not in the 'end of the world' manner that is peddled by scientists and pseudo scientists alike.
That climate varies naturally is no secret. What is meant by "global warming" is surface warming caused by human activities. There are several lists of global temperature anomalies, among them, Hansen's list which goes back to 1880 and shows a very definite warming trend since 1908, interupted briefly in the 50s and 60s. That's the one I use, but there are others, all of which show that same "Hockey Stick" shape. The antis offer no evidence to counter this. Do you have some?
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Regional Curve Standardization in Dendroclimatology is in itself subject to a few problems, where I agree that individual tree indices are represented in low and mid frequencies, one flaw of this method is RCS detrending and its failure to incorporate the average slope which it omits from the individual tree measurement, the average slope being the data which is obtained from all trees. This results in a 'trend-in-signal' bias, as you will know this occurs when the underlying growth forcing signal has variances on timescales that approach or exceed the length of chronology. This will bias and affect the start and end of your RCS.
I think you're trying to sucker me into something here. You have exactly reversed the problems/advantages of RCS. RCS, in its pure form, does not use detrending; thus, it doesn't have the "stair-step" problem that results when detrended series are averaged. For that reason, it can be used for time intervals beyond the span of the component series.
ALL of the samples in my datasets come from living trees. There are several series that date to 1700. A single series that covers the entire time span in question does not have the problem of interpolation between series.
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Then we move onto the problem of contemporaneously growing trees which might represent a modern sample as you mentioned. You get biasing of the RCS curve by the residual climate signal in age aligned samples and the undesirable subsequent removal of this signal variance when using an RCS application.
RCS does not use regression, except as a smoothing function for the finished chronology; the chronology does not have to be smoothed and smoothing can be accomplished using other methods. No regression, no residuals.
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Then there is the spurious trend over your modern chronology caused by differing contemporaneous growth rate.
I am unsure which trend you are talking about here. The chronology does have more series from young trees than from old ones. And with few exceptions, they are contemporaneous. I am actually using 10 of my own chronologies from the Ouachita Chronology plus the Shortleaf Canyon, McCurtain County Wilderness, Lake Winona and Hot Springs chronologies. That's 722 series from 14 chronologies, so differential growth rates caused by endogenous disturbances should be more than averaged out. Growth rate differences caused by suppression and release are handled in the cross-dating process.
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So you instantly lose some data,
The inflection point in the Hugershoff model for Ouachita Shortleaf pine, occurs in Year 4. Simply delete the oldest four years of the series and it can be fit with a negative logarythm. Of course, those are the very years you most want to know about, but you can't have everything.
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therefore creating a flaw in your findings
If the lack of the oldest four years from two-thirds of your series is a flaw, then it is a flaw, but it does not distort the rest of the data. And I still have over 200 pith-dated cores that can fill in those years.
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by having to use (respectively) signal free RCS in the first case
Again, making the dataset signal free is the whole idea behind RCS. "Signals" from regressions are artificially induced, so it is desireable to eliminate them if possible. RCS does this.
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then multiple sub RCS curves in the latter. This biasing therefore flaws your data.
Again, RCS does not use detrending; therefore, no multiple curves to combine; thus, no biasing.
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Hugershoff Curve Fit in itself has start and end fitting problems, oh dear another flaw.
In this case, the Hugershoff model is used only to smooth the RCS dataset. It could be smoothed as easily (in fact, more easily) with a running average. Fitting it with regression puts undue weight on the ends, but one can fit it with numerical methods, basically, trial-and-error (Number crunchers are good at that.). A partial solution to this problem is to cut off the chronology at some minimum number of series (I'm using eight, but might increase it.). That way, the end weighting problem gets cut at the same time.
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So before you come on here and start throwing around scientific terminology in an attempt to stun people with your brilliance, just remember...there is always someone out there a lot smarter than you,
You might take your own advice. You are good at using big words, but you fail to understand the concepts behind them.
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i'm confident enough with the REAL scientists out there who are proving that these environmental problems you waffle so well about are wrong
Name some. There are experts in other fields (like medicine) who don't seem to understand that a Ph.D. doesn't mean they know everything. What are CLIMATOLOGISTS saying? Name a few who disagree with global warming theory. What are ECOLOGISTS saying? Name a few who don't think that warming is the cause of a great many of those changes noted in ecological journals. And how about atmospheric chemists and physicists?
Yes. There are differences of opinion over minor issues. But the overall concepts are no longer being debated.
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And no I don't claim to be a scientist, I am just a humble medical professional, educated in my own field.
You did a good job with RCS, even though your conclusions are based on a complete misunderstanding of the process. But you're right: you should stick to medicine.
Doug
If I have seen farther than other men, it is because I stood on the shoulders of giants. --Albert Einstein
Do not meddle in the affairs of dragons for thou art crunchy and go good with ketchup.