Guest Post by Willis Eschenbach
Over at Bishop Hill, the Bish has an interesting thread about a new proxy reconstruction by Rob Wilson et al. entitled “Last millennium northern hemisphere summer temperatures from tree rings: Part I: The long term context” , hereinafter Wilson 2016. The paper and the associated data are available here. They describe the genesis of the work as follows:
This work is the first product of a consortium called N-TREND (Northern Hemisphere Tree-Ring Network Development) which brings together dendroclimatologists to identify a collective strategy for improving large-scale summer temperature reconstructions.
At first I was stoked that they had included an Excel spreadsheet with the proxy data. Like they say in the 12-step programs, Hi, my name’s Willis, and I’m a data addict … anyhow, here’s a graph of all of the data, along with the annual average in red.
Figure 1. Plot of the proxy data from the Wilson 2016 Excel worksheet. All proxies cover the period 1710 – 1988, as indicated by the vertical dotted lines. Note what happens to the average at the recent end.
But as always, the devil is in the details. I ran across a couple of surprises as I looked at the data.
First, I realized after looking at the data for a bit that all of the proxies had been “normalized”, that is to say, set to a mean of zero and a standard deviation of one. This is curious, because one of the selling points of their study is the following (emphasis mine):
For N-TREND, rather than statistically screening all extant TR chronologies for a significant local temperature signal, we utilise mostly published TR temperature reconstructions (or chronologies used in published reconstructions) that start prior to 1750. This strategy explicitly incorporates the expert judgement the original authors used to derive the most robust [temperature] reconstruction possible from the available data at that particular location.
So to summarize the whole process: for most of the data used, it started out as various kinds of proxies (ring width, wood density, “Blue Intensity”).
Then it was transformed using the “expert judgement of the original authors” into temperature estimates in degrees celsius.
Then it has been transformed again, this time using the expert judgement of the current authors, into standard deviations based on the mean and standard deviation of the period 1750-1950. Why this exact period? Presumably, expert judgement.
Finally, it will be re-transformed one last time, again using the expert judgement of the current authors, back into temperatures in degrees celsius
This strikes me as … well … a strangely circuitous route. I mean, if you start with proxy temperatures in degrees C and you are looking to calculate an average temperature in degrees C, why change it to something else in between?
It got odder when I analyzed the authorship of the temperature records reconstructed from the 53 proxies. In 48 of the proxy, the original lead author is also an author on this paper. It is true that they said this study is the result of a consortium of dendroclimatologists. However, I had expected them to look at more tree ring temperature reconstructions from other authors. So when they say they depend on the expert judgement of the authors of the proxies, in more than 90% of the proxies studied, they are merely saying they trust their own judgment.
And indeed, they think quite highly of their own judgement. rating it “expert”.
But since that is the case, since they are depending on their own prior transformation of a record of, e.g., tree ring width in mm into an estimated temperature in degrees C, then why on earth would they convert it out of degrees C again, and then at the end of the day convert it back into degrees C? What is the gain in that?
My second surprise came after I’d messed with the actual data for a few hours, when I got around to looking at their reconstruction. They describe their method for creating their reconstruction as follows:
3. Reconstruction methodology
A similar iterative nesting method (Meko, 1997; Cook et al., 2002), as utilised in D’Arrigo et al. (2006) and Wilson et al. (2007), was used to develop the N-TREND2015 NH temperature reconstruction. This approach involves first normalising the TR data over a common period (1750 – 1950), averaging the series to derive a mean series and iteratively removing the shorter series to allow the extension of the reconstruction back (as well as forward) in time. Each nest is then scaled to have the same mean and variance as the most replicated nest (hereafter referred to as NEST 1) and the relevant time-series sections of each nest spliced together to derive the full-length reconstruction. For each nest, separate average time series were first generated for 4 longitude quadrats (Fig. 1). These continental scale time series were then averaged (after again normalising to 1750 – 1950) to produce the final large-scale hemispheric mean to ensure it is not biased to data rich regions in any one continent. 37 backward nests and 17 forward nests were calculated to produce the full reconstruction length from 750 to 2011.
Like the song says, “Well, it was clear as mud but it covered the ground” … I was reminded of a valuable insight by Steve McIntyre, which was that at the end of the day all these different systems for combining proxies are simply setting weights for a weighted average. No matter how complex or simple they are, whether it’s principal components or 37 backwards nests and 17 forwards nests, all they can do is weight different points by different amounts. This is another such system.
In any case, that explained why they put the normalized data in their spreadsheet. This normalized data was what they used in creating their reconstruction.
I got my second surprise when I plotted up their reconstruction from the data given in their Excel worksheet. I looked at it and said “Dang, that looks like the red line in Figure 1”. So I plotted up the annual average of the 53 normalized proxies in black, and I overlaid it with a regression of their reconstruction in red. Figure 2 shows that result:
Figure 2. Annual average of 53 proxies (black), and linear regression of Wilson 2016 iterative nested reconstruction. Regression is of the form Proxy_Average = m * Reconstruction + b, with m = 1.25 and b = 0.54.
All I can say is, I hope they didn’t pay full retail price for their Nested Reconstruction Integratomasticator. Other than the final data point, their nested reconstructed integrated results are nearly identical to a simple average of the data.
Finally, as you can see, in recent times (post 1988) the fewer the proxies, the higher the estimated temperature. This is abated but not solved by their method. We can see what this means by restricting our analysis to the time period when all of the proxies have data.
Figure 3. As in Figure 2, annual average of 53 proxies (black), and linear regression of Wilson 2016 iterative nested reconstruction (red). Blue lines show proxy data.You can see how the number of proxies drops off after 1988 by the change in the intensity of the blue color.
Again you can see that their reconstruction is scarcely different from the plain old average of the data. As you can see, according to the full set of proxies the temperature in 1988 was lower than the temperature in 1950, and there is no big hockey-stick in the recent data up to 1988. After that the number of proxies drops off a cliff. By 1990, we’ve already lost about 40% of the proxies, and from there the proxy count just continues to drop.
In closing let me add that this post is far from an exhaustive analysis of difficulties facing the Wilson 2016 study. It does not touch any of the individual proxies or the problems that they might have. I hope Steve McIntyre takes on that one, he’s the undisputed king of understanding and explaining proxy minutiae. It also doesn’t address the lack of bright-line ex-ante proxy selection criteria. Nor does it discuss “data snooping”, the practice of (often unconsciously or unwittingly) selecting the proxies that will support your thesis. I can only cover so much in one post.
My conclusions from all of this:
• Transforming a dataset from tree ring widths in mm to temperatures in degrees C, thence to standard deviations, and finally back to degrees C, seems like a doubtful procedure.
• Without seeing the underlying data, it is hard to judge the full effects of what they have done. While having the normalized datasets is valuable, it cannot replace the actual underlying data.
• Whatever their iterative nested method might be doing, it’s not doing a whole lot.
• I do not know of any justification for normalizing the proxies before averaging them. They are already in degrees C. In addition, normalization greatly distorts the trends a time series, in a manner that depends on the exact shape and variance of the time series.
Finally, to a good first approximation their reconstruction is the same as the annual average of the normalized data. That means their method uses the following process:
Transform the "expert judgement" proxy temperature estimates from degrees C to units of standard deviations. Average them. Transform them back to degrees C using linear regression.
I’m sorry, but I simply don’t believe you can do that. Well, you can do it, but the result will have error bars from floor to ceiling and will have little to do with temperature.
El Niño rains here tonight. We’ve gotten four inches (10 cm) in the last four days, and it’s supposed to rain on and off for a week … great news here in drought city.
Best of life to all, sun when you need it, rain when it’s dry, silver from the five-day-old moon far-reaching on the sea …
w.
My Usual Request: If you disagree with me or anyone, please quote the exact words you disagree with. I can defend my own words. I cannot defend someone’s interpretation of my words.
My Other Request: If you think that e.g. I’m using the wrong method on the wrong dataset, please educate me and others by demonstrating the proper use of the right method on the right dataset. Simply claiming I’m wrong doesn’t advance the discussion.
An issue that has bothered me about using tree ring data (beyond the error problem so well covered by Willis) is that even if the growing season is well represented, this is not necessarily average temperature dependent. Cold winter can occur along with warm growing seasons, and cold nights along with warm days (due to clear sky radiation at night). In addition, trees cover only a limited portion of the Earth (not on oceans, or very high latitudes), so this is not a global average. The problem of precipitation level, CO2 effect and others have been mentioned, and probably dominate growth as much or more than daytime temperature. Tree rings are just not a good tool as used.
The human species has an innate tendency to be infatuated with its own intellectual infallibility. We believe we can know a lot more than is possible. This self deception has assisted scientists to be misguided for centuries.
I have nothing but admiration for most the individuals in climate science. However, as a class, they should all take a time out, take a deep breath and reflect on the limitations for understanding the truth. For several decades I have seen “fact-theories” be obliterated by subsequent generations of scientists, who in turn had their findings discredited by successors.
I’m struck by how many climate scientists who are skeptics have “emeritus” at the end of the title. There might be a reason for this.
One of the reasons might be that they have retired and don’t have to toe the company line any more.
“The human species has an innate tendency to be infatuated with its own intellectual infallibility. We believe we can know a lot more than is possible. This self deception has assisted scientists to be misguided for centuries.”
The internet makes smart people smarter and dumb people dumber.
I live in Manitoba, Canada. To say the least, our temperatures are extreme (-35C to +35C). In some years our trees leaf out normally in early May. We often get a “killing frost” following leaf formation. They all die, but the trees re-leaf with fewer and smaller leafs. The rest of the summer/fall doesn’t matter and trees struggle to maintain themselves until fall. How would this show up in the tree rings?
I’m pretty sure that’s a microaggression, although you’d have to find other trees with altered rings.
I think you are basically right.
One observation is that none of the authors is explicitly a statistician (although one can’t tell which departments some of the authors are in).
One can process data as much as one likes but lousy data will only reveal so much.
I thought that tree growth depended on how much local water, CO2 and nutrients were available as well as temperature. I have always been astonished by the claim that temperature several hundred years ago can be measured from tree rings.
Also I don’t like using part of the record being used as a baseline for normalisation. Shades of Mann – at least they didn’t use PCA
Indeed one of the CRU emails leaked was written to one of the team (Jones I believe, but I might be mistaken after 5 years) by an expert on tree growth to explain why tree rings are a poor proxy for temperature, and the entire root (pardon the pun) of the decline hidden by “Mike’s Nature trick” was the divergence between tree-ring proxy temperature trends and measured temperature trends.
Ed Cook, considered by many n the field to be the foremost expert on dendro, basically said we know nothing about climate variability greater than 100 years ago (his words in the CRU emails were “we know fu** all”) So I’d like to know where the magic knowledge suddenly came from, and if there is no new knowledge, where is Ed Cook’s refutation of this sort of thing?
We lost a large white oak in a wind storm a few years ago. Right after the tree was cut up ready for removal, I took my kids out to count the rings. 178 of them. It was also amazing how tightly packed the rings were right up until 1927. After that, they were much more widely spaced apart.
According to historical pictures of the area, the tree was one of many in a densely packed forest until the lot was cleared to build the original house on the lot.. in 1927.
before looking at the data, the question to be asked is “how were the proxies chosen”. were they a random sample, or was some criteria used to filter the samples?
because if the samples were not chosen at random, then what is the justification for using statistical methods on the data?
the second question is, what evidence is there that the samples are actually reliable proxies for temperature?
So to summarize the contention of those who we are told are not in d-nial – we should place total faith in this pile of inferred and speculative sludge whilst regarding the modern satellite data set with great skepticism and suspicion.
And, furthermore – we should not query that the field of dendrochronology appears to have vanquished its own concerns with the observation that their methodology, when consistently applied, fails to replicate late 20th century warming.
We should disregard that they themselves accept that the same methodology that irons out known climate trends during the last 1000 years also tells us that the climate cooled during the late 20th century.
That is – if we take the results as valid, or useful, or in any way indicative of something that reflects reality.
Reality – remember that place?
The place where we all actually live.
Then again, who needs reality? It is an annoying place and should ideally be eliminated promptly.
And as we are now informed, by satellite expert Michael Mann, satellites can not be trusted.
We should place our faith in the mystical interpretation of tree-rings and premium cocoa beans, as hand selected, then carefully blended by the high church of self-proclaimed expert master chocolatiers.
Following the lead of Mann and Trenberth, I have now completely lost my faith in satellite technology and now I am unable to trust even the information provided by the GPS in my car.
So, it tells me that I at a junction.
And I may indeed appear to be at that very junction, but how can I know that my satellite based GPS is not lying to me?
How long must we wait before Michael Mann and his church of tea leaf interpreters will construct an alternative Global Positioning System that is based upon a network of location sensitive trees?
I, for one, will be the first to adopt such an alternative.
Nothing can be more irritating than to start out on a journey from the first millennium and then discover that only a few hundred years down the road you are caught up in a medieval warming and then a nasty little ice age.
Especially when you later discover that you could have taken a direct route all the way to the 19th century without the unnecessary diversions.
I have also lost my trust in the mars rover.
I suspect that it is not really on mars at all.
It looks to me like it may have landed in Arizona. (erm…may contain sarc).
My dad uses location sensitive trees to navigate his land in Northern Minnesota. He simply uses a ferrite rod to integrate Poynting vectors into the trees. The vectors are spacially integrated into the trees based on the digital location of the sun relative to sunrise or sunset. He never gets lost now.
Yes, I’m working on this tree.p.s. idea.
So far, I’ve managed to engrave the words “you are here” onto a piece of spruce.
It’s a start… 🙂
Willis has uncovered a number of issues of concern with the N-Trends reconstruction and as a number of commenters have pointed out tree ring data is not in any way suitable for estimating temperatures to any great accuracy – though I do think it can be an indicator of “favourable” and/or “non-favourable” climatic conditions.
That said, it occurs to me that the reconstruction is not exactly devastating to the sceptics argument. First, There are 2 good reasons why we can ignore the post-2000 spike.
1. The number of proxies available is considerably smaller after 2000.
2. There is no comparable spike in the measured observations over this period (not even in GISS).
Having had a quick look at the paper, it seems the study finds a clear MWP, a LIA of around 500 years during which temperatures were about 1 degree cooler than the MWP and a modern warm period in which temperatures have returned to MWP levels
The warmest non-overlapping decades cited in the paper with anomalies (relative to 1961-1990) were as follows:
1994-2003 0.34 +/- 0.25
1946-1955 0.30 +/- 0.19
1161-1170 0.27 +/- 0.23
I wouldn’t be in too much of a hurry to debunk this paper.
“as a number of commenters have pointed out tree ring data is not in any way suitable for estimating temperatures to any great accuracy ”
You just debunked the paper John. This nonsense should never have been published.
I think you’re wrong – because we are not using the reconstruction to estimate temperatures. Providing it’s limitations are made clear, the study COULD be useful in providing a general broad brush reconstruction of NH climate change over the past 1000 years or so.
I don’t believe for one minute that you can legitimately compare an annual proxy temperature anomaly with an annual thermometer anomaly nor do I think that the proxies capture the true range of temperature variability, but it’s possible they capture the timing of climate shifts and the RELATIVE magnitude of those changes.
If you ignore the post-2000 spike, the reconstruction isn’t that much different to what a lot of researchers who are sceptical of CAGW believe.
John..
So you think the tree thermometers are good because the results confirm your beliefs? The 1994 to 2003 result surely is bogus because of the CO2 issue. To a lesser extent, 1946-1955. How about using a correction factor based upon CO2 levels and do your post again.
John, I’m afraid I find the entire idea of trying to use tree rings to measure temperature intellectually offensive. It bothers me quite a bit that people who advance nonsense like this are considered scientists.
No, I don’t think this method is useful as either a relative or absolute measure of temperature. It’s been pointed out over and over that tree growth is influenced by many factors that experience large variation on an annual basis. It might have been an interesting hypothesis at one point, now it’s simply annoying.
Did you not read what I wrote?
I clearly said that you cannot estimate temperature using tree rings to any real accuracy nor can you use it compare temperature with thermometer measurements, but it is (or might be) possible to make a relative comparison – providing a consistent method is used over the entire period.
I’ve no idea whether an anomaly of 0.34 deg for 1994-2003 above 1961-90 baseline is valid or not – BUT IT DOESN’T MATTER. What does matter is how the anomaly for that decade compares with the anomalies for other decades.
Let me give you a simple example to illustrate my point. Imagine we have a lake and we want to measure the water level to find out if it rising or falling or neither. Each year we take regular measurements and record them over several years. We might also calculate the depth of water in the lake which might be based an initial survey.
Now imagine someone comes along and discovers that the lake is actually much, much deeper than we thought and the depth of the lake is actually twice what we thought it was.
Our measurements of the lake depth are completely inaccurate – but that doesn’t invalidate the lake level measurements because they are based on relative values. We can still provide an estimate for the change in level. It doesn’t actually matter that we have no idea how deep the lake is – just as it doesn’t matter what the actual temperatures are when comparing “temperatures” in the reconstruction.
I believe I both read and understood what you wrote. I’d ask you the same question but I’m almost certain you both read and understood my reply. It was very concise and it’s been made by many others. In essence:
It’s been pointed out over and over that tree growth is influenced by many factors that experience large variation on an annual basis.
I believe I clearly agreed with that statement, if not I’ll do so here. I went further to say I (and you AFAIK) can’t estimate temperature from tree rings at all.
Neither to I. I’d again go further to say I have no confidence any proxy measure known to humans can even approach a precision of 1/100th of a degree. The entire idea is silly and has no scientific basis.
So, your example demonstrates that using a measure of surface height is useless as a measure of depth? My point was that tree ring width is useless as a measure of temperature. There was never any reason at all to take a surface level measurement as a depth measurement. It’s a very clear representation of pure stupidity. I fail to see how this analogy of yours advances the argument that tree rings are, in any way at all, a useful measure of atmospheric temperature, frankly I believe you’ve just illustrated my point rather well.
Quite – but one of those factors is temperature. So – while you cannot infer temperature FROM tree ring growth it might be possible (with sufficient observations) to deduce the contribution of temperature TO tree ring growth.
Your points about the precision of the anomaly are irrelevant. The anomaly might be 1.34 degrees – in which case the anomaly for 1946-55 would be 1.30 degrees and for 1161-70 would be 1.27 degrees. It doesn’t matter. Just as it doesn’t matter if the depth of the lake is 10m in Year 1 and 10.01m in Year 2 or 20m in year 1 and 20.01m in Year 2. The level of the lake is 1 cm higher in Year 2 than it was in Year 1.
The anomaly is effectively an index. It is a relative value. I don’t particularly care whether it’s realistic or not. I simply want to know if it provides a reasonable comparison with other decade long periods. e.g. Is it reasonable to conclude that NH temperatures in 1946-1955 were broadly similar to those in 1994-2003 – and in 1161-1170 for that matter.
The researchers have been totally fair and unbiased (apart from the inclusion of post 2000 data). Their method may be flawed but if it is then it’s equally flawed for the entire series.
There is a paper from (1976 I believe) that examines the isotopic uptake that does correlate with temperature rather than just the width of the trees, which is not scientific at all. The isotopic record is very accurate all the way back to 910 ce. The record does go further back further , however there is a break going back before 910 ce and some uncertainty. Various long lived trees worldwide are consistent with one another. This record clearly shows both cooling and warmer periods in contradicting AGW rather than local events as the IPCC maintains.
Width of tree rings related to temperatures can be imprecise. A wetter cooler summer can produce a greater width than a hot dry one. Altitude for same species trees, soil conditions ( which causes differential in coloring, growth) , other competing trees which can stunt either by shade or chemical release, side of the hill, extent of range… all effect the width.
This particular issue truly pushed me over into the camp of being a critic of AGW. The published results and the resulting peer review support along with academic approval meant that they didn’t have any idea about the subject or were lying (and knew they were lying) to promote a cause.
If they are going to promote a cause based made up reasons, I’ll take up a new field, like astrology, I’d probably be pretty good at it.
rishrac writes: “This particular issue truly pushed me over into the camp of being a critic of AGW.” (while discussing opinions on the tree ring metric).
It’s odd you’d say this, it was exactly this issue that caused me to dig into Mann’s ’98 paper. I found it completely absurd he would assert the precision he did, or that he’d use a metric so obviously confounded with multiple variables. It said, more strongly and convincingly than any other part of his work, that he was either stone cold stupid, or a bought and paid for shill serving a political agenda.
At the time it was shocking. That he would do something so obviously and completely wrong astounded me. That anyone would take his work as serious science was offensive. At that point, right then, I lost any and all confidence in the IPCC, Michael Mann, an the AGW hypothesis.
Bartleby,
Looks like you and rishrac are on the same page.
I agree that treemometers are nonsense. There are many variables that make a bigger difference, like CO2:
That was sorted by CO2. This one’s sorted by temperature:
Tree rings are the outliers when compared with much more reliable proxies:
Oops, I didn’t look too closely at that last chart. Disregard.
A recent poster recommended a book called Hubris. I’m about a third through and it’s a pretty good read.
Dissects the field of broader field of science and identifies roots of some of the problems including the leaps made by some scientists to parlay their narrow field of knowledge into rock star opinion on other issues. Also discusses the self fulfilling peer review process and how academia’s publish or perish demands have created a mosh pit of unverified/unreplicated findings that hold very little value. Lots more to the book that makes you go hmmm.
I haven’t gotten to the solution part but the book is steering towards an expansion of the trust but verify mindset (replicability) with a dash of smackdown concerning the appeal to “only experts in the field” can weigh in on the worthiness of a fact.
I never said that – though they do go some way to supporting those who believe there was a MWP and LIA.
Tree rings cannot measure temperature. I KNOW THIS. However temperature does contribute to tree growth (within a range of temperatures).
While we can’t deduce the temperature from tree ring growth, there’s reason to believe we can deduce the contribution temperature made to tree ring growth (again within a range) – which is not quite the same thing.
This study uses the one method for producing the reconstruction. It doesn’t use tree ring proxies for early periods and thermometer record for the later years. It is comparing like with like. The variability may be flat but it’s the same for all years. It’s a relative issue – not an absolute one.
The study essentially says nothing more than this: the MWP was about 1 degree warmer than the LIA and the modern warm period was about the same as the MWP.
John I think it’s safe to conclude that trees don’t grow under the cover of ice. We have a fair amount of evidence that would support a true theoretical relationship between the presence of ice and the growth of trees. Frozen trees don’t grow, I’m virtually certain that’s true. I’m also certain trees don’t grow in temperatures exceeding 260 degrees C (500 degrees F). I haven’t formalized this into a physical model, but I’m sure one could be developed and that it would prove predictive.
That’s a level of precision I can accept.
John Finn, you say that although we cannot measure absolute temperature with tree rings, we can measure relative temperature using tree rings. There are a couple of problems with your plan.
The first problem with this idea is that both high temperatures and low temperatures cause narrow tree rings. As a result, the central assumption of treemometry is simply not true. This assumption is the incorrect idea that there is a linear (or basically linear) relationship between tree ring width and temperature.
The second problem is that growth is not a function of temperature alone, but (to a first approximation) a function of temperature, moisture, wind, insolation, crowding, disease, and insect infestation. Disambiguating temperature from that whole mix is not an easy or simple task.
As a result, when you say:
… I’m afraid that statement is not supported by the data, even if the analysis were done properly.
Unfortunately, the what they they have done it is not only not proper, it is bizarre. They take a bunch of proxy-estimated temperatures, normalize them to the period 1750-1950, average them, and convert them back to temperatures using linear regression.
I know of absolutely no theoretical justification for such a procedure.
w.
Willis
Rather, “The second problem is that growth is not a function of temperature alone, but (to a first approximation) a function of temperature, moisture, wind, insolation, crowding, disease, insect infestation, AND CO2 levels at the time. Disambiguating temperature from that whole mix is not an easy or simple task.”
The very rapid “growth” seen in tree rings post 1950 is far easier to ascribe to the continuing, ever-increasing CO2 levels from some 280 (1850 guesstimate) to 350 to today’s 400 ppm) that definitely cause a 12% to 27% increase in ALL plant growth,; than to the staggered, intermittent jumps and drops in recorded temperatures of 1/4 of one degree that “might” be related partially to temperature changes.
Prior to 1850? You “might” be able to claim that CO2 was constant w/r growth rates.
After 1850? That claim cannot be made at all, but Mann does not want to allow for ANY possible benefit of increasing CO2 in the atmosphere – it would be bad for his business, his industry of getting funds and publicity and power.
RA Cooke,
I had not ever thought of this prior to reading through the comments on this thread, but as soon as one thinks about it, the obviousness of what you say is…um…very obvious.
We KNOW that CO2 concentration relates to growth of most plants and trees, and higher amounts allow faster growth, assuming CO2 is the least limiting factor. Which is often is. More than often…almost always.
Willis
Indeed. The tree ring growth response to temperature is reckoned to be an upside down U shape, i.e. there is an optimal temperature after which tree ring growth is stunted. Fine – I know all this. However I also know that the temperature range for most regions over the past several centuries is unlikely to be much outside +/- 1 degree. Now it’s possible that the upper range of temperatures has pushed tree growth over the hump in *some* regions but is that going to happen right across the NH at exactly the same period in time.
The evidence suggests not. In general, ring widths are wider in the MWP and the modern period than during the LIA years.
We also know that crop failure and famine were more common in the LIA years – i.e. the years identified by the Wilson study as being cooler than the MWP or recent years. Now that could be because of widespread heat and drought in the NH but I somehow doubt it.
Providing we understand the limitations of this study I don’t think it’s entirely useless.
I don’t think the findings that the mid-12th century was about a degree or so warmer than the early 19th century is totally unbelievable.
Many thanks, once again, for a great post, Willis.
Yesterday, the local weather forecast for my region (Liverpool, England) was: “sunny, clear skies (day and night), with a max temp of 4 deg C and humidity from 75-77%. Today, the “forecast” for the same period is: cloudy and raining throughout, with same max temp and humidity at 95%. Presently, outside my home, its snowing!
“This strikes me as … well … a strangely circuitous route.”
Willis, you’ve certainly proven yourself a master of understatement.
After quite a long time building and using metrics myself, I have to say the entire endeavor surrounding temperature proxies based on tree rings is laughable. Any attempt to improve them are doomed; the base data is confounded in so many ways (water, CO2, etc.) it will never resolve to a measure precise +/- 5C, and that level of precision would be truly astonishing.
I’m pretty sure this won’t stop the folks feeding at the government research trough from continuing to “attempt” it, but I am certain they’ll never succeed. The real problem is we have folks like the NSF who’re either too stupid or too corrupt to de-fund this nonsense. As long as this situation persists, there won’t be any hope coming and the general public will continue to be bilked by these charlatans. It’s an egregious corruption of science and we, as scientists, have very clearly abandoned our duty to self-regulate.
So, Bartleby, I will put you down as undecided on the reliability of temperature proxies from tree rings.
🙂 I don’t suppose you’d care to hear what I really think?
If they had a sound scientific background it should have been beaten into these “scientists” that every stage of data processing of any sort increases the size of error bars. If not they are not scientists, if so where are the error bars and what is the calculation of these increasing errors.
I am giving you, Mr Eschenbach, more credit than the paper’s authors in assuming you did not simply ignore some deep discussion thereof in the paper, knowing its relevance to this article. Given the normal reluctance of alarmists and enthusiasm of sceptics for considering errors and given the normal dishonesty of alarmists and honesty of Mr Watts’s invited contributors I believe this is justified by the time saved in wading through a paper I am ill-suited to analyse in depth, but anyone is free to correct me if I am wrong.
Live and learn. Evidently, the term “scientist” is not just the guy slaving away at mundane, replicable experiment and observation but instead has been expanded into broader vocations such as modelers and those that make a living from extrapolating those observations. The book I’m reading mentions that up to 27000 articles a week (Van Noorden 2011) are published in some peer review publication each week. Surely, most of that is not based on new conclusions that move the ball of knowledge up the hill.
Willis,
While I don’t know what qualifications an expert in dendroclimatology has, these are pre-screened datasets. If you had an actual average of the original data you would very likely have a flat line with no blade whatsoever. In addition, very few trees exhibit correlation with temperature in any way.
Mann’s large 2008 series data (1109 series) showed no statistically significant signal on unmanipulated raw data. The opposite of what the paper claimed. So he used someone elses spliced-with-temperature tree data Luterbacher, to infill the rest of his series using PCA processes. Some of those series, he famously truncated to remove the decline.
The more they try the clearer it becomes to this layman that the only sure way to get temperature from a tree ring is with a match.
As always, follow the money .
Thanks, Wilis. GIGO, no matter what the process is; trees are good CO2 sinks, bad thermometers.
Paraphrasing Simon and Garfunkel:
After changes upon changes we dendrocrinologists are more or less the same.
Willis, you said, “Without seeing the underlying data, it is hard to judge the full effects of what they have done.” Let me clear that up for you.
The author data-mined previous granted studies he had done, probably applied for another grant to study this same data he had previously received grants on, and squeezed it to see if he could get gravy (money) out of it. Sure enough, gravy came out. The gravy train just keeps on trucking. Clever researchers. They have figured out a way to game the system.
Original research is so passe’ under post-normal science. However, the taxpayer is left with mumbo jumbo jargon in grant applications without realizing they are not funding original research. It is now more lucrative, and expensive for taxpayers, to re-wash been-there-done-that data than to get grants for original research.
another outstanding comment pamela ,keep up the good work 🙂
Hi Pamela: Richard from Canada here. I couldn’t agree more. During my career I wouldn’t have thought about trying to publish an article that didn’t contain new and original data. The publish or perish axiom has indeed taken over, much to the detriment of science.
@willis
The converted degrees C represent a normalized value with zero mean and unit variance, so it’s really a measure of temperature anomaly, not absolute temperature.
?w=720
But I assume the original values were also estimated temperature anomalies, which per se are more “accurate” than absolute values, in the sense that they are immune to calibration shifts and biases (provided the underlying proxy model is roughly linear in the support region). So not clear what is the “gain” in doing that.
Perhaps there are random errors in the each of the proxy-generated temperature step sizes such that they are no longer the same “units”. So normalizing to z-scores might help, assuming the data are all identically distributed. But that assumption seems unlikely because of the different underlying proxy mechanisms.
A more likely reason for using standard deviations might be to create the illusion of extremely high statistical significance. Looking at your Figure 2 plot one can see that the “hockey-blade” corresponds to a normalized value of “3-sigma”, which automatically suggests a confidence interval of 99.7% in the usual statistical interpretation of a normal distribution.
But this is not data drawn from a single, simple normal distribution of values. In fact it is a series of distributions which are not stationary, the mean and variance are a function of time. Also the sample density decreases significantly for the blade region values. Sampling confidence usually does not increase with decreasing sample density.
So this unit conversion could be just eye candy to impress its targeted lay-audience. But let’s reserve judgment until after reading the full paper.
Here’s a sample display from the Mesa Verde National Park museum. This picture was taken last summer.
http://i66.tinypic.com/9t32w6.jpg
This sample placard harkens back to a time when tree rings were not used as univariate temperature gauges.
Note that the stenciling of this placard (Variability of Annual Ring), dates it to before personal computers and printers now are used by sample curators to produce these kinds of display placards. This placard is at least pre-1980, over 35 years ago, before the rise of a fraudulent use of tree rings as temperature gauges was driven by the rent-seeking that the Global Warming scam fueled.
I thought that using tree-ring data to estimate palaeo-temperature had been thoroughly debunked by now, but here we go again.
What I fail to grasp is how anyone can even THINK you could create temperature records from tree rings alone. I mean it’s obvious (and has been repeatedly brought up in this thread) that tree growth is the resultant of many environmental variables. So how can you isolate the one variable you want to study (i.e. temperature) when you don’t have independent evidence of what all the other variables were doing over the same time sequence, in the same general areas where your tree samples come from?
Until someone can explain this in words that make sense, it seems appropriate to totally ignore this tree-ring circus.
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Here’s what I would do if I had the inclination and the resources to do it (and grad students to do the legwork). Take a few well-studied forests over a well-documented time span (e.g. the 20th century). Then try to isolate a species whose growth responds more to temperature than rainfall, and another species that responds more to rainfall, and another species that responds more to sunlight/cloud cover, and another that responds more to length of growing season (which is only loosely linked to temperature). And so on and so on. Then you would have the tools to tease palaeo-temperatures out of multi-species tree ring sequences in similar forests in historic times. Because you would have multiple parameters to play with and you could use fancy polyvariate statistics to isolate the independent variable you want to look at.
Maybe it’s possible, maybe it’s not. Perhaps all the trees in a forest respond more or less similarly to environmental changes (that, to a casual observer, seems quite likely to be the case, in which case your study was a bit of a time-waster). But that’s the SORT of approach that a SCIENTIST (which I’m reasonably sure I am) would take. Of course, it would be hard work, much harder than bundling together a bunch of other people’s over-processed data and pretending you’ve done something useful.
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And while thinking about this, without having read Mann’s work, how can you possibly use principal component analysis when you’ve only got one parameter? I mean, everyone knows that PCA is a way of taking a data set with multiple variables, and reducing it to a manageable handful of variables (which, if you’re lucky, can be related to other, identifiable features). I can’t do it myself, but I’ve watched people do it with multi-element geochemical data,and it’s a pretty neat tool. But the thickness of a tree’s growth ring is only one variable. What am I missing?
Smart Rock
I had a look at Bradbury’s book from 1999 and commented over at Bishop Hill. There’s a chapter (10) about dendro reconstructions. They use this type of multi variate technique. In principle the technique is sound. In reality not so much if you want it to be useful
To get good relationships you need good metrology, which requires painstaking characterisation if you want low uncertainty. For example, trees don’t grow according to temperature anomalies and they may not grow linearly (something Craig Loehle did a paper on in the past).
Common sense would tell you that you need to put in great effort to squeeze out that accuracy if you want tree rings to be useful thermometers. It may just not be possible.
For a theoretical exercise I don’t see any problem with it. I worry however that this paper may end up in some climate report as “evidence”.
“Take a few well-studied forests over a well-documented time span (e.g. the 20th century). Then try to isolate a species whose growth responds more to temperature than rainfall, and another species that responds more to rainfall, and another species that responds more to sunlight/cloud cover, and another that responds more to length of growing season (which is only loosely linked to temperature). ”
Why should anyone suppose that species exist that respond to such well defined but separate growth factors in the required way? Let alone exist within a single long lived and well studied forest? And that all of these relationships remain unchanged over long spans of time?
Sounds like how to make something that does not work, into something that is much more complicated and questionable, that does not work.
Hey, you should maybe apply for a climate science grant! Sounds like you have a winner!
Genetic variability of the seeds disbursed by a tree ensure that if conditions change, there will be some individual seeds that are able to thrive under these altered conditions. The lifespan of temperate forest trees may ensure that over a period of many hundred years, there is a predomination of trees that grow best at the prevailing average temperature.
In other words, it may well be the case that trees adapt to changing conditions through natural selection. I see no reason to expect that in a given area, as we transitioned from the MWP to the LIA, and then to the MWP, trees are not able to subtly adapt to these changes, and are principally affected by deviations from the long range averages over short periods of time.
You aren’t missing anything. The fact that tree rings reflect a number of variables obviates the ascription of any one variable as causative. Down thread I asked why recorded history is never used as an analytical variable. I have always wanted to see someone take tree ring analysis and try to correlate it to recorded human literature. For example, TonyB and others (Steele and Ball?) have reported historical records of catching fish well north of their range, the farming in Greenland, the distributional changes in seals and polar bears, the discovery of the PDO by a salmon scientist and other natural responses to climate variability. Critters only respond to environmental changes if they have to, and it has to last long enough for a response to occur. Surely, some of these tree samples have been taken in Europe, Eastern Canada and other locations that had to be affected by temperature changes that would be reflected in tree rings (if temperature is the operative factor). If you are going to claim tree rings reflect climate change, then let’s be honest enough to test it against other natural changes.
I’ll wait for Steve McIntyre’s analysis.
Willis:
Thanks to you WUWT now needs a humor section.
Don’t get me wrong — I followed your critique and I love the post. It seems to me that you are right on!
Luckily I forgot to bring my coffee to my office or I would be sending you a bill for a new keyboard as I’m sure that my coffee would have been spewed all over.
When I read the BH post I looked up the paper — decided it did not pass the smell test and went on… Clearly I missed some merriment. Thank you for setting me straight.
Jimmy Durante move over — you have a new companion in the Wax museums of today!
I did a study of tree rings when I was 18 years old for an alpine ecology class in Switzerland. The tree I studied Picea Albies (Norway Spruce) grew fastest at an elevation of 1400 meters. It grew slower above that elevation due to a colder shorter growing season, but it also grew slower at the lower elevations, where it had progressively more severe completion from deciduous trees. At 400 meters the few straggling trees I could find had the same growth rate as the trees at 1800 meters, which was alpine tree line. I knew from one study they are a poor proxy for temperature.
Let us hope that you used proper spelling for your main subject.
The word is abies, not albies.
My home is largely paneled in old-growth coastal redwood (built in 1909). There are beautiful diagonal stripes in the quarter-sawn panels, which are taken from the lower trunk, caused from compression of the cellulose from the colossal weight of the tree, which often exceed 200′, and will commonly top 300′, tall. The tallest living specimen is about 380′. If one were to take core samples at different heights on the base of the trunk, one would see thin rings at different radii, corresponding to these diagonal stripes. This should be an issue with any large tree, even if it’s not large enough to cause a visible figure in the wood when quarter-sawn. This would be similar to glacial cores where a similar compression from snow to firn to ice occurs. I think that, in addition to all of the other issues with using dendochronology as a thermometer, this effect will give spurious results as one looks at different trees, of different sizes, at different heights, etc. I’ve never seen any treatment of this error source. Perhaps that is because by the time you look at all of the other error sources, you should just toss this method anyway…
The problem with tree rings…is even if they had a perfect correlation with temp and nothing else…you still could not use them and they still would not work
They can’t tell you how much hotter it got and for how long after they stopped growing…..or how much colder it got and for how long
Those temperatures outside of their growth range are just a WAG…made up…and can be made to say anything you want
Latitude, in a comment above it was revealed that these studies only purport to relate summer temps to growth rates. I wondered why anyone should think summer temps are a valid way to arrive at world average temperature.
Is this what you are referring to as well?
N-TREND shows a hockey stick. Temperature measurements do not show a hockey stick. Does this show that tree rings can not be used as a proxy for temperature, using expert judgements?
N-TREND shows a hockey stick
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the underlying data doesn’t
http://oi63.tinypic.com/2mpzadu.jpg
They didn’t need all those trees. Briffa showed that one is enough, if the right one is picked:
Johanus says above:
… this unit conversion could be just eye candy to impress its targeted lay-audience.
IMHO that is exactly what their intent is. Their graph says it all. Most people will never read the paper, or even a summary. The graph will be published throughout the media, people will see the hockey stick at the end and think, “The scientists must be right! Looks like global warming is accelerating fast.”
That’s exactly what it looks like. But in the real world that’s not happening.
As Willis shows, that graph was deliberately fabricated from very questionable proxies and data. The graph is the goal, more than the paper — which is just the science veneer to make it seem legitimate. If someone questions that graph, the alarmist crowd will parrot, “It’s peer reviewed!” That’s been the pattern, over and over again.
Over the past century global temperatures have risen by only ≈0.7ºC. That is a smaller change in global T than almost any century long time frame found in the geologic record. But they are trying to make it look like global T is now skyrocketing. They’re lying, no?
Johanus adds:
But let’s reserve judgment until after reading the full paper.
Let’s not, Johanus. At this point they would have to produce an extremely convincing paper, showing that other temperature databases like satellites and radiosondes are completely wrong before I’d accept their Mann-style hokey stick chart.
My judgement is already in: they’re lying by chart.
column V ins the spreadsheet;
Yamal YAM 67.32 69.54 750-2005 RW RCS Briffa et al. (2013)
I am still searching for a definition of the scientific method which includes any reference to the pal review process.
How did this become the gold standard for what is valid science, let alone what is objectively true?
Particularly since the process seems to be little more than a redundant spell check?
Particularly since one can shop around if one’s first several bunches of attempts to have a paper peer reviewed and published hit a stone wall (just ask John Cook)?
The supposed justification for normalizing such data (besides the proxies which are not even temperature…) is to avoid the problem that reconstructions from Iceland will be colder than those from Africa and perhaps more variable. However, the correct way to deal with this is to weight regional proxies by their geographic regional area, not normalize. This screws up everything in my opinion.
Yet no one bats an eyelid when GISS LOTI and HadCRUFT4 [sic] average land air and sea surface temperatures.
This skews the result because air temps change about twice as quick as SST and so have twice the effect on the result , even when area weighted.
Plus this nicely adds UHI effect into the SST which does not suffer from that problem.
The end aim of all these temperature reconstructions is to compare them to radiative “forcings” and estimate climate sensitivity. Yet if you “average” the temperature of media with vastly different specific heat capacities ( air , land, water ) or start rescaling and adding, any physical meaning disappears and the CS calculation becomes totally false.
HadCRUFT! Snorted wine out my nose! Painful!
The idea that the temp of water can be accurately substituted for air temp is rarely discussed, but I have a big problem with this. I am sure it is not valid.