Guest Post by Willis Eschenbach
The discussion of the 1998 Mann “Hockeystick” seems like it will never die. (The “Hockeystick” was Dr. Michael Mann’s famous graph showing flatline historical temperatures followed by a huge modern rise.) Claims of the Hockeystick’s veracity continue apace, with people doggedly wanting to believe that the results are “robust”. I thought I’d revisit something I first posted and then expanded on at ClimateAudit a few years ago, which are the proxies in Michael Mann et al.’s 2008 paper, “Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia” (M2008). This was another salvo in Mann’s unending attempt to revive his fatally flawed 1998 “Hockeystick” paper. I used what is called “Cluster Analysis” to look at the proxies. Cluster analysis creates a tree-shaped structure called a “dendrogram” that shows the similarity between the individual datasets involved. Figure 1 shows the dendrogram of the 95 full-length proxies used in the M2008 study:
Figure 1. Cluster Dendrogram of the 95 proxies in the Mann 2008 dataset which extend from the year 1001 to 1980. The closer together two proxies are in the dendrogram, the more similar they are. Absolute similarity is indicated by the left-right position of the fork connecting two datasets. The names give the dataset abbreviation as used by Mann2008, the type (e.g. tree ring, ice core) the location as lat/long, the name of the princiipal investigator, and if tree rings the species abbreviation (e.g. PIBA, PILO).
What can we learn from this dendrogram showing the results of the cluster analysis of the Mann 2008 proxies?
First let me start by describing how the dendrogram is made. The program compares all possible pairs of proxies, and measures their similarity. It selects the most similar pair, and draws a “fork” that connects the two.
Take a look at the “forks” in the dendrogram. The further to the left the fork occurs, the more similar are the pairs. The two most similar proxy datasets in the whole bunch are ones that are furthest to the left. They turn out to be the Tiljander “lightsum” and “thicknessmm” datasets.
Once these two are identified, they are then averaged. The individual proxy datasets are replaced by the average of the two. Then the procedure is repeated. This time it compares all possible remaining pairs, including the average of the first two as a single dataset. Again the most similar pair is selected, marked with a “fork” (slightly to the right of the first fork), and averaged. In the dataset above, the most similar pair is again among the Tiljander proxies. In this case, the pair consists of the “darksum” proxy on the one hand, and the average of the two Tiljander proxies from the first step on the other hand. These two are then removed and replaced with their average.
This procedure is repeated over and over again, until all of the available proxies have been averaged together and added to the dendrogram and it is complete.
In this case, the clustering is clearly not random. In general a cluster is composed of measurements of similar things in a single geographical area (e.g. Argentinian Cypress tree rings). In addition, the proxies tend to cluster by proxy type (e.g. speleothems and sediments vs. tree rings).
Next, the dendrogram can be read from the bottom up to show which groups of proxies are most dissimilar to the others. The more outlying and more unusual group a group is, the nearer it is to the top of the dendrogram.
Next, note that many of the groups of proxies are much more similar to each other than they are to any of the other proxies. In particular the bristlecone “stripbark pines” end up right at the top of the dendrogram, because they are the most atypical group of the lot. Only when there is absolutely no other choice are the bristlecones at the top of the dendrogram added to the dendrogram.
So how does this type of analysis clarify whether the “Hockeystick” is real? The question at issue all along has been, is the “hockeystick” shape something that can be seen in a majority of the proxies, or is it limited to a few proxies? This is usually phrased as whether the results are “robust” to the removal of subsets of the proxies. And as usual in climate science, there are several backstories to this question of “robustness”.
The first backstory on this question is that well prior to this study, the National Research Council (2006) “Surface Temperature Reconstructions for the Last 2,000 Years” recommended that the bristlecone and related “stripbark” pines not be used in paleotemperature reconstructions. This recommendation had also been made previously by other experts in the field. The problem for Mann, of course, is that the hockeystick signal doesn’t show up much when one leaves out the bristlecones. So like a junkie unable to resist going back for one last fix, Dr. Mann and his adherents have found it almost impossible to give up the bristlecones.
The next backstory is that a number of the bristlecone proxy records collected by Graybill have failed replication, as shown by the Ababneh Thesis. Not only that, but one of the authors of M2008 (Malcolm Hughes) had to have known that, because he was on her PhD committee … so the M2008 study used proxies that were not only not recommended for use, but proxies not recommended for use that they knew had failed replication. Bad scientists, no cookies.
The final backstory is that the Tiljander proxies a) were said by the original authors to be hopelessly compromised in recent times and who advised against their use as temperature proxies, and b) were used upside-down by Mann (what he called warming the proxies actually showed as cooling).
With all of that as prologue, Figure 2 shows the average signals of the clusters of normalized proxies (averaged after each proxy is normalized to an average of zero and a standard deviation of one). See if you can tell where the Hockeystick shaped signal is located …
Figure 2. Left column shows average signals of the clusters of proxies shown in Figure 1, from the year 1001 to 1980. Averages are of the cluster to which each is connected by a short black line.
You can see the problems with the various Tiljander series, which are obviously contaminated … they go off the charts in the latter part of the record. In addition, if the Tiljander data were real it would be saying record cold, not record hot, but the computational method of Mann et al. flipped it over.
The reason for the unending addiction of Mann and his adherents to certain groups of proxies becomes obvious in this analysis. The hockeystick shape is entirely contained in a few clusters—the Greybill bristlecones and related stripbark species, the upside-down Tiljander proxies, and a few Asian tree ring records. The speleothems and lake sediments tell a very different story, one of falling temperatures … and in most of the clusters, there’s not much of a common signal at all. Which is why the attempts to rescue the original 1998 “hockeystick” have re-used and refuse to stop re-using those few proxies, proxies which are known to be unsuitable for use in paleotemperature reconstructions. They refuse to stop recycling them for a simple reason … you can’t make hockeysticks without those few proxies.
To sum up. Is the mining of “hockeystick” shaped climate reconstructions from this dataset a “robust” finding?
Not for me, not one bit. While you can get a hockeystick if you waterboard this data long enough, the result is a chimera, a false result of improper analysis. The hockeystick shaped signal is far too localized, and occurs in far too few of the clusters, to call it “robust” in any sense of the word.
w.
PS – The entire saga of the Ababneh Thesis, along with lots and lots of other interesting information, is available over at ClimateAudit. People who want to improve their knowledge about things like the proxy records and the Climategate FOI requests and the whole climate saga should certainly do their homework at ClimateAudit first … because in the marvelous world of Climate Science, things are rarely what they seem.
[UPDATE] Some commenters asked for the data, my apologies for not providing it. It is located at the NOAA Paleoclimate repository here.
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Mike N “Willis, you are in error when you say the computational method of Mann et al flipped over Tiljander. The software does not do any flipping of Tiljander proxies.”
Mike, I made the same mistake. Let’s first go back to what Mann said about the upside down data.
Mann: “The claim that ‘‘upside down’ data were used is bizarre. Multivariate regression methods are insensitive to the sign of predictors. Screening, when used, employed one-sided tests only when a definite sign could be a priori reasoned on physical grounds. Potential nonclimatic influences on the Tiljander and other proxies were discussed in the SI, which showed that none of our central conclusions relied on their use.”
And now let’s look at what Steve M said about Mann’s statement.
Steve M. “These comments are either unresponsive to the observation that the Tiljander sediments were used upside down or untrue. Multivariate methods are indeed insensitive to the sign of the predictors. However, if there is a spurious correlation between temperature and sediment from bridge building and cultivation, then Mannomatic methods will seize on this spurious relationship and interpret the Tiljander sediments upside down, as we observed.”
It was from this that I concluded that Mann’s algorithm was at fault. Can you give us more details about how you think that Mann got the sign backwards. Did he just start with an inverted physical interpretation. And what do you make of his incoherent argument about gettting it right?
One more thing, what is Mann talking about when he says, “a priori reasoned on physical grounds”. A priori knowledge is knowledge which can be know to be true or known to be false without experiential reference to the physical world. So the phrase basically makes no sense. I think Mann loves to throw out obtuse explanations, and then claim that he has addressed an issue when it comes up by reference to those explanations, regardless of how illogical the explanations are.
Wow! .. Beautiful work Willis! .. thank you!
I’m on board with Squidly. Willis is the master of clear, objective thinking.
And thanks to Tilo Reber. That needed to be said. The day that Michael Mann is in an adversarial setting is the day that Mann will be destroyed, because he will no longer be able to obfuscate. Mann is nothing more than a climate charlatan.
PaulD says:
June 1, 2011 at 7:16 am
Mikael Pihlström says
“And that is my main point: with the increasing basic evidence available the sceptic tenet that allHS-resembling datasets are corrupt/misinterpreted/falsified is faring badly.”
As someone who is actually interested in understanding this issue and getting to the bottom of it, I would appreciate a link or a citation that would support this point.
Willis Eschenbach says:
June 1, 2011 at 10:41 am
What “HS-resembling datasets” are you claiming are NOT corrupt under the
rubric of “increasing basic evidence”? Names, Mikael, locations, specifics, that’s
what is necessary. Not your unsubstantiated vague fantasies about some unspecified new “basic evidence”.
————————————–
1.
Twentieth century warming in deep waters of the Gulf of St. Lawrence: A unique feature of the last millennium.
http://www.agu.org/pubs/crossref/2010/2010GL044771.shtml
2.
Ammonium concentration in ice cores: A new proxy for regional temperature reconstruction?
http://www.agu.org/pubs/crossref/2010/2009JD012603.shtml
“For the time period from about 1050 to 1300 AD, our reconstruction shows relatively warm conditions that are followed by cooler conditions from the 15th
to the 18th century, when temperatures dropped by up to 0.6°C below the 1961–1990 average. The last decades of the past millennium are characterized
again by warm temperatures that seem to be unprecedented in the context of
the last ∼1600 years.” [in Bolivia]
3.
Recent Warming Reverses Long-Term Arctic Cooling
http://www.washingtonpost.com/wp-dyn/content/article/2009/09/03/AR2009090302199.html?hpid=artslot
The temperature history of the first millennium C.E. is sparsely documented, especially in the Arctic. We
present a synthesis of decadally resolved proxy temperature records from ‘
poleward of 60°N coveringthe past 2000 years, which indicates that a pervasive cooling in progress 2000 years ago continued through the Middle Ages and into
the Little Ice Age. A 2000-year transient climate simulation with the
Community Climate System Model shows the same temperature sensitivity to changes in insolation as does
our proxy reconstruction, supporting the inference that this long-term trend
was caused by the steady orbitally driven reduction in summer insolation.
The cooling trend was reversed during the 20th century, withfour of the five
warmest decades of our 2000-year-long reconstruction occurring between
1950 and 2000.
4.
A multi-proxy paleolimnological reconstruction of Holocene climate conditions
in the Great Basin, United States osu.academia.edu/ScottReinemann/Papers
“Subfossil chironomid analysis indicates that Stella Lake was characterized by a warm, middle Holocene, followed by a cool “Neoglacial” period, with the last two millennia characterized by a return to warmer conditions.” [The recent warming clearly exceeds the MWP, but there is also a peak 1300 y ago]
5.
Summer Temperature Variations in the European Alps, a.d. 755–2004
Ulf Büntgen, David C. Frank, Daniel Nievergelt, and Jan Esper, Swiss Federal Research Institute WSL, Birmensdorf, Switzerland.
http://journals.ametsoc.org/doi/full/10.1175/JCLI3917.1
Annually resolved summer temperatures for the European Alps are described.
The reconstruction covers the a.d. 755–2004 period and is based on 180 recent
and historic larch [Larix decidua Mill.] density series. The reconstruction indicates positive temperatures in the tenth and thirteenth century that resemble twentieth-century conditions, and are separated by a prolonged cooling from 1350 to 1700.
Six of the 10 warmest decades over the 755–2004 period are recorded in the twentieth century.. The record captures the full range of past European
temperature variability, that is, the extreme years 1816 and 2003, warmth
during medieval and recent times, and cold in between.
6.
Recent unprecedented tree-ring growth in bristlecone pine at the highest
elevations and possible causes.
Salzer MW (Salzer, Matthew W.)1, Hughes MK (Hughes, Malcolm K.)1, Bunn AG (Bunn, Andrew G.)2, Kipfmueller KF (Kipfmueller, Kurt F.)3
http://www.pnas.org/content/early/2009/11/13/0903029106
Great Basin bristlecone pine (Pinus longaeva) at 3 sites in western North America near the upper elevation limit of tree growth showed ring growth in the second
half of the 20th century that was greater than during any other 50-year period
in the last 3,700 years. The high growth is not overestimated because of standardization techniques, and it is unlikely that it is a result of a change in tree growth form or that it is predominantly caused by CO2 fertilization. Increasing temperature at high elevations is likely a prominent factor in the modern unprecedented level of growth for Pinus longaeva at these sites.
My conclusions:
We don’t have to rely on tree rings; other proxies are increasingly available.
There are new tree ring sets, admittingly there is large variation in signals
E-g. the bristelcone is not generally disqualified because the sceptics say so
Mikael Pihlstrom: ” ”
So I looked as some of your papers.
“2. Ammonium concentration in ice cores: A new proxy for regional temperature reconstruction?”
Here is the actual paper for that:
http://www.leif.org/EOS/2009JD012603.pdf
And it says:
“Relatively warm temperatures during the first centuries of the past millennium and subsequent cold conditions from the 15th to the 18th century suggest that the MWP and the LIA are not confined to high northern latitudes and also have a tropical signature.”
So, for years the warmers have been claiming that the LIA and MWP were regional phenomena. Hopefully we can put that lie to rest. Now, it you look at the temperature chart that they gave you will see that A. It doesn’t look like a hockey stick. B. There is nothing alarming about it. C. When they use the term “unprecedented” to mean “just a little bit more” they are going off the reservation.
“3. Recent Warming Reverses Long-Term Arctic Cooling”
When I check your link I get a picture from a newspaper of some greenpeace guys standing on an iceberg. You are going to have to do better than that.
Your number four has no source, no link, no anything. You are really going to have to do better than that.
“5. Summer Temperature Variations in the European Alps,”
So here is the link for the crucial chart from that paper. Again, no hockey stick; nothing to be alarmed about; and the twentieth century does not look warmer than the MWP.
http://journals.ametsoc.org/na101/home/literatum/publisher/ams/journals/content/clim/2006/15200442-19.21/jcli3917.1/production/images/large/i1520-0442-19-21-5606-f02.jpeg
And they also provide a solar activity chart that you can compare to three global reconstructions at the bottom. Very interesting, don’t you think. Also, if you look at those global reconstructions you will see one where the MWP was slightly warmer, one where it was slightly cooler, and one where it was about the same. So again, the term “unprecedented” is simply political hyperbole.
http://journals.ametsoc.org/na101/home/literatum/publisher/ams/journals/content/clim/2006/15200442-19.21/jcli3917.1/production/images/large/i1520-0442-19-21-5606-f07.jpeg
“6. Recent unprecedented tree-ring growth in bristlecone pine at the highest elevations and possible causes.”
http://www.pnas.org/content/early/2009/11/13/0903029106
They say:
“The high growth is not overestimated because of standardization techniques, and it is unlikely that it is a result of a change in tree growth form or that it is predominantly caused by CO2 fertilization.”
How do they know that CO2 fertilization is not a factor?
And they also say:
” The growth surge has occurred only in a limited elevational band within ≈150 m of upper treeline”
So they found that this occured only in a band of trees that were 150 meters from the treeline. ROFL. Talk about cherry picked data. If you look at their chart of ring width versus instrument temperature from 1900 the correlation looks good for about 7 years from 93 to 2000. And it looks very bad for the 33 years from 1960 to 1993. Before 1960 it is only so, so.
Here is their 4000 year chart:
http://www.pnas.org/content/106/48/20348/F2.expansion.html
First of all, the last 2000 years don’t look like any other reconstructions. And they have a growth period about 3700 years ago that closely matches that of today – except today we have CO2 fertilization.
This looks to me to be an amplified proxy. The growing period of that last 150 meters is so small that a tiny change in temperature will greatly increase it’s length as a percentage of the whole. Also, looking at the time period for that final spike at the end ( 7 years ), this may well be nothing more than a regional tick with little value for global proxy analysis.
I think that you have proven with your own samples that in the arena of proxy reconstructions, nothing unusual is happening today, and that there is no hockey stick shape to be found except when it is Mann made.
Thanks for your help.
Mikael Pihlström says:
June 2, 2011 at 5:22 am
My friend, you are totally funny, although you likely don’t appreciate that. The authors of the paper you recommend (above) had to issue a correction to Science magazine, generally regarded as an admission of serious failure. And why did they have to do that?
Well, because they had used the Tiljander proxies upside down. Again. Note that this made the third time, as Mann had previously used them upside down twice. And they also used three other proxies upside down.
Ooops … the paper you recommend as so much improved makes the same stupid mistake FOR THE THIRD TIME!
Of course the authors claim that it makes no difference to their reconstruction … now hang on. There’s 22 proxies in their network. They had used four of them upside down. When they turned them over it made no difference.
What kind of funky analysis is it where turning over almost 20% of their proxies makes no difference?
In addition, the reconstruction contains three very shonky tree ring collections of Keith Briffa, one of the un-indicted co-conspirators in Climategate and a co-author of the study. These three proxies (Taimyr, Fennoscandia, and Yamal) have been shown to have huge problems, including the fact that Briffa hasn’t fully archived them … bad Briffa, no cookies … but the team just keeps recycling them.
So no, that study is no evidence for your side at all. It’s actually evidence for my side, evidence that the Mann/Briffa/Amman/Bradley/Hughes axis re-uses known bad proxies because that’s how they can get hockeysticks.
Finally, the study has a common problem with many of these types of studies in that there are no ex ante criteria for proxy selection. As I’ve shown above, if you pick the right proxies you can get a hockeystick by simple averaging. So ex ante selection criteria are critical for this kind of analysis. But the study you recommend has no such criteria.
w.
Here is some more detail on the sediment records from the bottom of Lake Korttajarvi, Finland, that Mia Tiljander and her colleagues analyzed. These make up the Tiljander data set — I no longer think they should be called “proxies”. (I’m writing this from memory, so caveat lector: minor errors could have slipped in. See my blog for details, starting with this post.)
In their publications (listed here), Tiljander et al describe recovering cores from the lake bed. Their key feature is that each year forms a distinct layer (varve), because of seasonal variations in the material that settles out of the lake water. So, starting from the present, one can count year-by-year back to 1000 B.C. or so.
Tiljander et al measured the following properties of each varve (annual deposit):
* its thickness (millimeters)
* the effective thickness of the inorganic (mineral) component (millimeters)
* its transparency to X-Rays (arbitrary units)
Tiljander et al then deduced the contribution from organic matter to each varve by this formula:
(Organic effective thickness in mm) = (Thickness in mm) – (Inorganic effective thickness in mm)
These four data series were deposited in data archives. As used in Mann08, the three “thickness” series were transformed by taking their natural log — a common procedure in the field, I believe.
Mann08 employed these series as temperature proxies. (See Figure 1, the cluster dendrogram in the body of the main post, Figure 1. Similarly, see Figure S8 of Mann08’s Supporting Information.):
* xraydenseave — X-Ray Density (arbitrary units)
* lightsum — Inorganic matter (ln of derived thickness in mm)
* thicknessmm — Varve thickness (ln of measured thickness in mm)
* darksum — Organic matter (ln of calculated thickness in mm)
IIRC, xraydenseave did not pass Mann08’s Screening Procedure, and was not used in the paper’s paleotemperature reconstructions. The other three series did, and were.
In their 2003 paper, Tiljander et al proposed interpretations for XRD, lightsum, and darksum — but not for total varve thickness. In all cases, they cautioned that the varves were progressively contaminated from about 1720 through the end of the 20th century by local activities such as farming, lake eutrophication, and road construction.
Tiljander et al (2003) interpretation
* xraydenseave — Pre-1720 only: higher density means colder
* lightsum — Pre-1720 only: thicker means colder, wetter winters
* thicknessmm — [No interpretation offered]
* darksum — Pre-1720 only: thicker means warmer summers
Mann et al (2008) usage
* xraydenseave — Entire series: higher density means warmer
* lightsum — Entire series: thicker means warmer
* thicknessmm — Entire series: thicker means warmer
* darksum — Entire series: thicker means warmer
Thus:
* xraydenseave — Pre-1720, Mann disagrees with Tiljander. Post-1720, disagree
* lightsum — Pre-1720, Mann disagrees with Tiljander. Post-1720, disagree
* thicknessmm — Pre-1720, neither agree nor disagree. Post-1720, disagree
* darksum — Pre-1720, Mann agrees with Tiljander. Post-1720, disagree
I’ll point out that Mann08 uses lightsum, thicknessmm, and darksum as if they are three independent data series. They are not, because darksum is simply thicknessmm minus lightsum. (The use of natural-log transforms of these series unfortunately obscured this for some time.)
Finally, I will caution that Tiljander03’s interpretations of XRD, lightsum, and darksum are plausible, but they are not necessarily correct. My own view is that these series aren’t suited for use as temperature proxies, as discussed here. Search for “Regarding another question” and note that the Little Ice Age is clearly visible in the profile of Chironomid fossils from Lake Hamptrask. No clear-cut changes in any of the Tiljander data series from nearby Lake Korttajarvi are evident.
Thanks for an interesting analysis, AMac, that points out some of the problems that exist not just with the Tiljander proxies but with many other proxies.
The problem with the Mann method is that he seems to just wander around looking at proxies and picking ones that fit his theories. In truth, it’s hard to find anything that’s a good proxy for temperature. I mean, consider the difficulty that humans had in coming up with a proxy to measure temperature before finally settling on the expansion of mercury with temperature. And that’s before we get to questions of confounding variables.
Your contribution, as always, much appreciated.
w.
AMac, thanks for the cite, I’d forgotten about the whole episode at Collide-A-Scape where Gavin Schmidt came in all full of bravura and disappeared without comment midstream when you asked him the tough questions …
And I loved Mosh’s comment there, viz:
Yep. Sure enough. The team seems to feel that if they admitted one mistake the rot would set in … while never seeming to realize that the unwillingness to admit mistakes IS the rot …
w.
Mikael Pihlström says:
June 2, 2011 at 5:22 am
Mikael, as with the endangered species question, again you are being deceived by what the scientists say, as opposed to what they show.
But what they show in Figs S4A & B is very, very different. There’s a good discussion of the issues with Salzer here. Read it beginning to end, and then come back and tell us exactly where it is wrong, quoting what you think is objectionable or incorrect and then telling us exactly why it is incorrect. (Or, you could just quietly leave without either reading it or commenting on it. However, I must warn you that people will judge you on your actions.)
Back to Salzer, their upper figure (S4A) shows the raw tree ring widths for stripbark (solid lines) and regular (dotted lines) bristlecones, while the lower figure shows the results after standardization. They claim that the problem with the modern data is due to improper standardization (despite the fact that the original authors used the industry-accepted techniques).
But if you look at the data, they’re just blowing smoke. The difference between the two datasets, whole- and strip-bark, exists whether they are “standardized” or not. All the standardization does is shift the disagreement from early to late.
So while their statement is true on its face, that “when their raw ring widths are plotted in the same manner as our Fig. 3, there is little difference between their strip-bark and whole-bark groups in the modern period”, it is also very deceptive because when there is no difference in the modern period there is then a huge difference in the earlier period.
Mikael, I understand both your frustration and your desire to set things straight. But you have to get about 723 times more doubtful and about 635 times less trusting of climate science papers. The authors, as in this case, often have a huge axe to grind—to take just one example, Hughes is one of the co-authors of the Hockeystick paper. Do you really think that he will present an unbiased case? Because I can assure you that he won’t. Your job is not to read their claims and go “Yep, uh-huh, that sounds right”.
Your job is to go through line by line, ignore their claims and their interpretations, look at their actual results, and then judge for yourself whether their claims and interpretations of the actual results are correct.
And if you are not competent to do that … then why are you bothering us by simply parroting their claims without (apparently) the slightest attempt to see if they are worth more than a bucket of spit? It has been demonstrated over and over that there are many mainstream AGW scientists including some of the biggest names who are willing to lie, cheat, and steal to convince people that they are right.
And you simply believe them? At one time, that could have been reasonable ascribed to ignorance of their habits and their motives.
But to still blindly believe them in the year 2011, to swallow their claims without the simplest attempt to check their validity?
That’s serious selective blindness, Mikael, and it doesn’t redound to your credit.
Two problems there. The “new tree ring sets” get mixed with the old standard bogus hockeystick sets, so they can still get hockeysticks.
More to the point, the bristlecones are not “generally disqualified because the sceptics say so”. They are disqualified because, as the NAS and a number of other researchers in the field have repeatedly pointed out, they a) don’t agree with all the rest of the proxies, and b) have failed replication.
The reason for this is obvious to some of us. When part of a tree’s bark is gone, all of the growth occurs under the bark that remains, and inevitably the tree rings there will be wider than they were when the tree had its whole bark … duh, it’s not rocket science.
But then we’re not rocketing around trying to cooper up the holes in a failed theory. Mikael, you are putting your trust in people who will very happily deceive you, and by all appearances they have succeeded. Truly, you need to become as skeptical of your side of the debate as you are of the other side, because those “friends” on whose word you are depending are looking out for their own necks and not for the truth.
w.
“So overall I don’t think cluster analysis would be much help there. All you would end up saying is “well, the tides in the Solomons are most like the tides in X”, but that doesn’t help much.”
You think too much, for one thing, ha ha. Perhaps your method is not indeed the best display of what I noticed in individual tide gauges, but what I saw your method’s strength as was that it exposed how the majority of underlying data failed to show a hockey stick, so my suspicion is that the vast majority of tide gauges would not scatter all over the place into little islands of local effect, but in fact form a mega-cluster that lacked much trend change at all, thus exposing the potential fact that only a few do show much recent trend change. Of course I would want to simply ignore records that did not carry back a full century or so, long enough to contain within each of them the true historical trend prior to the modern one. I’m onto something here (after six hours of tide gauge browsing), and am fishing for the best expression of it that is also rigorous and immune to observer bias.