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  1. Well done Tim, Tom and Keith and thank you for your courage and determination. The story of the attacks you have been forced to endure and your response to them is an important one to tell and needs to be known widely by scientists, politicians, and the public.

    Comment by Chris McGrath — 3 Jun 2013 @ 3:21 AM

  2. Fig 1 of the article does not appear, and the reference to the original article is wrong (should be http://dx.doi.org/10.1016/j.quascirev.2013.04.008).

    [Response: Fixed the figure, but
    I don't see the problem with the doi. The in-text link points to the references which have the right doi - and indeed it has to be right since the ref is automatically generated from the doi. Let me know if I missed something. - gavin]

    Comment by toxymoron — 3 Jun 2013 @ 3:45 AM

  3. Aren’t the conclusions of 1 and 2 post hoc explanations for exclusion of data? Was the excluded data and reasons for exclusion stated in the original papers? Post hoc data exclusion of data was a big problem in medical research and was in part one of the reasons for the development of the CONSORT statement.

    [Response: The original data selection was discussed earlier http://www.cru.uea.ac.uk/cru/people/briffa/yamal2009/ - gavin]

    Comment by fred smith — 3 Jun 2013 @ 5:35 AM

  4. fred smith: “Aren’t the conclusions of 1 and 2 post hoc explanations for exclusion of data?”

    No.

    The fact that some Polar Urals cores were taken from root collars was noted at the time the samples were taken — please see figures PU05 and PU06 of SM3 at our supplementary materials webpage:
    http://www.cru.uea.ac.uk/cru/papers/briffa2013qsr/
    Once aware of this information, the decision to exclude the root collar samples was taken on the the basis of the likely incompatibility of the ring widths from root versus trunk samples. We did attempt an adjustment to compensate for different mean ring widths between root versus trunk samples, so that the root data could be retained and used, but without success due to the added complication of difference growth trends as well as mean growth rates. These attempts are documented in SM4. For tree density (MXD), such an approach did work and we could therefore use the MXD data even from the root samples.

    For the second case, the potential problems with the Khadyta River site were also noted at the time the samples were taken — please see SM2 (pages 1, and 5 to 8). Also note that we have previously demonstrated that inclusion of these data would have a relatively small impact anyway, something that we updated in Figure 10 of our new paper. Panels (b) and (e) include Khadyta River data, while the other panels do not (note that there are data and method differences between the panels too, which make larger differences to the final chronology).

    Comment by Tim Osborn — 3 Jun 2013 @ 6:35 AM

  5. I am SO glad to see a post such as this– Thanks.

    A few questions:

    1. Is this “root collar” problem in any way similar to the “strip-bark” problem (other than the idea that “strip bark” may be declared a non-issue on the basis that it agrees with what we think the other trees are basically saying (from Salzer et al)? Meaning, if the “root collar” issue occurred in samples that were registering similar results after analysis they would be still declared acceptable for dendroclimatological use?

    2. I always get it in bits and pieces from the various places that discuss climate, but to date I haven’t found a self-contained explanation as to why studies in Dendroclimatology are not on the same plane as medcal/phar research, and in effect “unique” in that they can pick and choose samples (to paraphrase Esper). For as common a signal as the trees are representing, there still are surprisingly few trees in the mix compared to the number of trees in the world (and at these prior-chosen sites).

    3. From what I’m reading here, the indicated research/enlightenment into discounting the Khyadta came after the determination of what its data showed, not before. Is this true?

    Comment by Salamano — 3 Jun 2013 @ 8:51 AM

  6. Much of the criticism could have been neatly sidestepped by transparently releasing the tree-ring chronology when first requested, instead of sitting on it for two years while (admirably) continuing its development, but “in the dark” so to speak.

    There is much to be said, in a positive way, for total transparency and admitting the light and expertise of other researchers. It is unfortunate that UEA chose not to.

    [Response: Sorry but that's rather naïve. Releasing our incomplete and unpublished work, specifically a chronology that we consider to be biased, before we had time to complete our evaluation and provide the written explanation about why it was biased, would not have avoided any of the manufactured controversy. Recall also that the existence of this work-in-progress chronology was only "public" because of its mention in some of our hacked emails. Taking your suggestion to its logical conclusion would mean that everything we do should be public while we work on it. The UK EIR/FOI exempts incomplete information for a good reason, and UEA applied this exemption in good faith.- Tim Osborn]

    Comment by tomwys — 3 Jun 2013 @ 9:11 AM

  7. Answer to Salamano’s Q1…

    First, note that root collar samples are acceptable to use in some circumstances. Take a look at Figure 5a of our main paper: at timescales below 100 years, there’s agreement between the updated Polar Urals (with many root samples) and the original sub-fossil Polar Urals data (with few root samples). It is on longer timescales that the different growth behaviours are apparent (Figure 5b, 5d).

    Ideally dendroclimatologists would like to avoid using such samples (if their interest is in the longer timescales). But if the sample count is low, then comparison with other trees may be a reasonable approach to deciding whether non-ideal samples could be used to increase the replication. We cover this quite a bit in our paper — looking for common behaviour between independent sets of data as one measure of confidence (Figure 5f shows the high standard deviation 900-1100 and 1400-1600 when roots are included, and thus lower confidence in the chronology mean value).

    Fritz Schweingruber was aware that the replication of the original Polar Urals chronology was quite low during medieval times and asked for further samples (see page 4 of our SM4 document), which turned out to be non-ideal, as we’ve demonstrated by comparison with other trees but which might have been expected because they are from the root collar. Note that Fritz was particularly interested in the MXD values, which are much less affected. Our approach was to go with the better replicated Yamal TRW chronology instead.

    Comment by Tim Osborn — 3 Jun 2013 @ 10:01 AM

  8. Does anybody still read McIntyre? I thought his complete lack of reasonableness had put him into the cyber dustbin. I used to come here and look there but I haven’t looked at his blog in several years. I actually thought he had packed it in.

    Comment by Golden — 3 Jun 2013 @ 10:01 AM

  9. 1) Thanks for the good science. Some of these examples show thoughtful analysis of data rather than blind statistics that just includes outliers. In many fields, some outliers may be real and need to be included, but all too often, something is truly wrong with part of the data and it needs to be discarded. Of course, some people then claim it was post hoc discarding data you didn’t like, but I’d say your choices are well reasoned. The most famous recent analogy could be the “faster-than-light neutrinos” caused by a loose cable.

    2) Thanks for publicly documenting McIntyre’s extra-science methods.
    Hopefully more will do so.

    Comment by John Mashey — 3 Jun 2013 @ 10:08 AM

  10. I see that #3 and part of #1 of my questions are answered in post 4. Thank you :)

    Comment by Salamano — 3 Jun 2013 @ 10:17 AM

  11. Answer to Salamano’s Q2…

    We don’t generally pick and choose samples. I’m not sure of the background behind Jan Esper’s comment, but did he mean that you can sample from moisture-stressed sites if you want to try reconstructing precipitation/drought and you can alternatively sample from temperature-limited sites if you want temperature?

    Our approach was to begin with all samples unless there was a reason not to (e.g. root collar samples), but then to consider common signal between independent subsets to identify any issues. None of our selection was based on correlation or non-correlation with temperature observations. The comparison with temperature came only after we had finalised the chronology.

    So it is an unfair characterization to say that we just pick and choose samples.

    Comment by Tim Osborn — 3 Jun 2013 @ 10:27 AM

  12. Answer to Salamano’s Q3..

    Not true. Our initial plan was to include the Khadyta River data in the main chronology for our new paper — even after we had inspected them and seen that they behaved differently to data from other sites in the region. Subsequently our Russian colleagues pointed out that there were issues with this particular site, that the trees were not considered ideal for dendroclimatic analysis and were not healthy. That was the basis of their exclusion from the final presented chronology (though they are in some panels of Figure 10 for comparison; see my earlier comment).

    Comment by Tim Osborn — 3 Jun 2013 @ 10:36 AM

  13. Thanks Gavin#3, Tim#4,

    The two links provided still appear to be post-hoc explanations as fred#3 suggests. I think the criticisms were related to Briffa 2000, and Briffa et al 2008?

    These links are for post-hoc disclosure in 2009 and 2013? Is there any earlier disclosure so far not referenced?

    [Response: The Polar Urals update (dominated by root collar samples in the medieval period) and Khadyta River data were not considered in Briffa (2000). Therefore there was no decision to include or exclude them, and thus neither an a priori nor a post hoc justification is relevant. They weren't considered in Briffa et al. (2008) either, though we had begun some preliminary comparisons of different sites within the Yamal region and identified some potential problems in combining data from multiple sites. Given these problems in using multiple sites, Briffa et al. (2008) instead chose the single site with the best replication -- Yamal. -Tim Osborn]

    Comment by GSW — 3 Jun 2013 @ 10:39 AM

  14. [Minor edit: final sentence, "while cloaked them" should be "while cloaking them".]

    Comment by Sphaerica (Bob) — 3 Jun 2013 @ 11:04 AM

  15. Thanks a lot for this very informative post, for the great science in your new paper and for not letting ‘them’ get to you.
    And thanks for your long term contribution to expand the human knowledge.
    With best regards, Jos

    Comment by Jos Hagelaars — 3 Jun 2013 @ 6:00 PM

  16. Doctors Osborn, Melvin and Briffa – Thank you for the extended information on your paper.

    Also, my compliments to Briffa, Melvin, Osborn, Hantemirov, Kirdyanov, Mazepa, Shiyatov, and Esper for the very interesting paper – clearly the result of long hours of dedicated effort.

    And my sincere sympathies to all of you for having to put up with the nonsense that made this post necessary.

    Comment by KR — 3 Jun 2013 @ 9:42 PM

  17. Ah! Mr. McIntyre will be so happy that the 2006 chronology is all out in the open now.

    Won’t he? ;-)

    Comment by Kevin McKinney — 3 Jun 2013 @ 11:03 PM

  18. Golden says:
    3 Jun 2013 at 10:01 AM
    Does anybody still read McIntyre?

    Actually yes. I note his blog has had 10,149,478 hits since Sep 2010. Not exactly invisible

    Comment by Peter Wilson — 3 Jun 2013 @ 11:54 PM

  19. On his blog, Dr Bouldin has made a series of convincing posts on severe analytical problems in dendroclimatology. From the account of the paper given above, it would seem that it falls into many, if not all, of the traps diagnosed by Dr Bouldin. Would anyone be prepared to comment on that?

    http://ecologicallyoriented.wordpress.com/2013/03/21/severe-analytical-problems-in-dendroclimatology-part-twelve/

    [Response: I think he's commenting over there... - gavin]

    Comment by Graeme — 4 Jun 2013 @ 9:50 AM

  20. Thank you for this post, it clears up a number of questions. Forgive my ignorance, perhaps you can shed some additional light one item. The discussion of root collar vs tree bole samples includes the statement “it is because more samples were from the root collar with their inherently wider rings”. I would have thought the comparison across sites and even different sample locations within the same tree would be relative ring width rather than absolute ring width. Trees in more favorable micro-environments, or species that tend to achieve higher diameters on the same site, would have wider rings. Leaning or wind exposed trees develop difffernt wood on compression and tension sides of the bole. I would have thought a standard process in dendroclimatology would be to normalize based on relative difference within the same sample so absolute width would not be an issue. It seems odd that the wider tree collar widths were not accounted for initially. Am I misinterpreting the root collar discussion? Thanks for any assistance you can provide.

    Comment by MJB — 4 Jun 2013 @ 9:53 AM

  21. I have no direct experience with this work, but I am familiar with issues of data stewardship and custodianship, primarily in a business context, but also elsewhere. Releasing data which has not been well-vetted can be a source of harm, since many people will use such data without question, and are wildly uncritical, leading them to incorrect conclusions. Sometimes, as in Internet measurements research, these results, in turn, make it into the conference literature, which leads still others to believe the work is well-founded. The “random networks” subfield of Internet modeling was one such example.

    The U.S. Geological Survey qualifies map data according to the level at which it has been checked and corroborated, such as their Digital Elevation Maps. They use a Likert scale of 1-4 to indicate this. While such an approach may be okay for a standard product like a digital map, it’s more difficult for complicated data sets in general scientific work.

    Thus, I applaud efforts at being careful regarding release of data, and of complete scientific datasets, especially in an environment where transparency is being enforced by policy.

    It’s an interesting statistical question whether or not there might be a scoring procedure devised which assessed consistency of a given datum with its neighbors. Such a score might be in the form of a Likelihood value, namely, L(data|model), but that begs the question of what to use for “model”. I have not examined whether Owen’s work on empirical likelihood may apply here, but that’s where I would go with the question if I were to pursue it (\cite{A.B.Owen, EMPIRICAL LIKELIHOOD, Chapman & Hall, 2001}).

    Comment by Jan Galkowski — 4 Jun 2013 @ 1:57 PM

  22. Response to MJB:

    Thanks for the interesting comments.

    The issue of root collar samples having wider rings can’t be dealt with by using relative ring-widths because that would remove all long timescale variability.

    Using “relative ring widths” would mean dividing the measured ring widths by the mean ring width (or mean growth rate) for that tree core. The mean of the relative ring widths for that tree core would then be equal to one. Cores from a tree growing, say, during 1000-1300 and from one growing during 1700-2000 would have the same mean relative ring-width regardless of whether the climate was more or less favourable to tree growth in each period.

    This is the problem with what are often called “curve-fitting” standardisation methods — they remove differences in mean growth rate between tree cores even if the difference arises from climate changes that we are trying to reconstruct. (In fact they also remove the trend over the course of the tree’s life as well.) Thus tree-ring chronologies developed using curve-fitting standardisation will have little variability on timescales longer than the typical length of a tree-core sample — the “segment-length curse” described by Cook, Briffa, etc.

    The RCS standardisation approach retains differences in the absolute growth rates of different tree cores. Thus it can retain evidence for long timescale variability. But it is also more sensitive to issues such as those you raise. Some of these other influences on ring growth may be random and therefore can cancel out with a larger sample — one of the reasons why a larger sample is needed for RCS. Some may be more systematic and various approaches can be used to address this. In our paper we grouped tree cores into faster and slower growing trees (which might reflect some of the micro-environmental factors you mention) and processed them separately. See Figure 3b and 3c of our paper — the red and blue curves contain independent data, yet note the agreement between them.

    You also mention different growth rates between species — here we have used only Larch (Larix sibirica) to avoid that issue.

    Comment by Tim Osborn — 4 Jun 2013 @ 7:17 PM

  23. Otoh, maybe you guys owe Stevie McInt a beer. If he hadn’t spent his time inventing alternate climate recon-fictions, and badgering for a right to stand over your shoulder critiquing your WIP … you wouldn’t have produced this obvious quality piece of research. And he might have made someone else’s life miserable.
    Guelph’s legacy was a home for retired Mafia members, HQ for a popular local brewery that sold out, site of a university furnace that’s been used for burning pot & hash seizures … and now Steve McIntyre. Go ahead, claim it’s just co-incidence.

    Comment by owl905 — 5 Jun 2013 @ 1:04 AM

  24. I am enjoying this dialogue, as dendroclimatology has somewhat of a unique position within science and statistics that permits a deeper exploration of both fields with each publication.

    To conitnue… when you said:

    “Our initial plan was to include the Khadyta River data in the main chronology for our new paper — even after we had inspected them and seen that they behaved differently to data from other sites in the region. Subsequently our Russian colleagues pointed out that there were issues with this particular site, that the trees were not considered ideal for dendroclimatic analysis and were not healthy.”

    I was immediately wondering (a) who would core unhealthy trees if this is a disqualifying factor at the outset? (b) couldn’t presently unhealthy trees still be informative in a healthier state long ago? ( c) who’s to say that presently valued cores are from still healthy trees? It’s amazing that these trees are geotagged with such specificity that anyone can go back and pay a visit to the exact specimen later and re-core it if necessary.

    I’m still a little hung-up on the phrases ‘non-ideal’ and ‘replication’ … Some samples can be acceptable and others rejectable if they are ‘non-ideal’, but it appears the basis is on the degree of ‘replication’… Is that correct? The idea “better replicated” data is ‘went with’ more often, and the less replicating data being more mined for exclusionable grounds. However, I do understand that if the original purveyor of the data declares a set as useful and another as not, you would presumably have to go with their diagnosis lest there arise a contradiction/conflict.

    Oh, and by the way, the quote attributed to Esper is from Esper et al (2003) where it is said,

    [one could conceivably improve a chronology by reducing the number of series used]“…if the purpose of removing samples is to enhance a desired signal. The ability to pick and choose which samples to use is an advantage unique to to dendroclimatology” – hence my med/phar comparison question. I sure would bet that those researchers would love to be able to similarly declare such a uniqueness for their products.

    [Response: We can't speak for Fritz Schweingruber (who cored the Khadyta River trees) or Jan Esper (re. the quote from Esper et al., 2003), though we offer the following:
    _
    (a) if trees are patently 'unhealthy', wouldn't generally sample them, unless one is interested in identifying the timing (and possibly cause) of the condition.
    _
    (b) yes, presumably so – but in interpreting the 'signal' represented by their changing ring widths, one would have to explicitly recognise and ideally take account of the anomalous signal they would present when "unwell".
    _
    re. geotagging: many trees are not precisely locatable, but returning to a proximal region should be sufficient to identify a coherent regional growth signal.
    _
    re. replication: note that Tim used this in his earlier comment to indicate simply the sample size available in any one year. "Better replicated" meant based on more samples, rather than implying anything about the strength of the agreement between samples. "Better sampled" or "more highly replicated" might have caused less confusion.
    _
    There are several concepts entwined in your comment, relevant to the underlying rationale of chronology construction and working approaches. We say "approaches" because the particular techniques in chronology building and assessment of chronology confidence will depend on the specific questions being asked. If the aim is to reconstruct the short-timescale (say interannual to decadal) variability of tree-growth it makes sense to remove the unwanted variability at source – say by high-pass filtering the measurements before averaging the series to produce a chronology. The averaging then efficiently cancels "noise" (i.e. variance which is not commonly represented in the high-pass filtered series) and the statistical confidence of the chronology can be accurately assessed by comparing the magnitude of signal (common variance) to residual noise. However, if we are interested specifically in the long-term common growth variability of a group of trees, this is harder to isolate and quantify in terms of chronology confidence.
    _
    Tree-ring measurement series contain long-timescale variability that is not forced by climate but by systematic thinning of radial growth rings in older and larger trees. This thinning process must be modelled and the effect removed. Slight errors in this process and the generally weaker representation of common long-timescale variability expressed in groups of trees mean that low-frequency chronology variability is not as strongly expressed as the high-frequency given the same number of tree core samples. This problem is reduced if a very large number of samples are available, but when this is not the case, rather than rely on the averaging process to cancel non-common growth signals it could be argued that it is more efficient to remove clearly "anomalous" data from the sample. Provided "clearly anomalous" is defined with regard to the underlying pattern of common growth variability and not with regard to some "desired" target, such as the observed temperature trend.
    _
    In the case of the Khadyta River data, one might argue that it is better practise to leave the data in and depend on the averaging process to produce the "best estimate" of the underlying regional tree-growth signal. Without explicit knowledge that the apparent health of these trees was sub-optimal, we would probably agree with this logic. However, given the additional knowledge that the trees are unhealthy and the site not considered ideal for dendroclimatic analysis, it is reasonable in this case to exclude these data from the regional chronology. As it happens, the chronology including these data is not significantly different from our final chronology.
    -Keith Briffa, Tim Osborn, Tom Melvin]

    Comment by Salamano — 5 Jun 2013 @ 7:01 AM

  25. Thanks for this informative update. In your 3rd to last paragraph, should the sentence read: “It is worth noting that [neither] this rejection, nor any acknowledgement of his erroneous conclusions….”?

    Comment by Bruce Currie — 5 Jun 2013 @ 3:28 PM

  26. Could you translate the summer temperatures to yearly temperatures?

    Comment by Armando — 6 Jun 2013 @ 4:16 AM

  27. I was recently pointed to this topic by a skeptic who suggested I Google “most influential tree in the world”. Your post and others are good responses to McIntyre but I’ve never seen a response to that particular point anywhere. I do not believe that 80% of the postulated warming is due to one tree, an 8-sigma outlier called YAD06, for the simple reason that you and your reviewers are not total idiots, but it would be nice to have something to point to to show that McIntyre is a total idiot on this point.

    Comment by Philip Cohen — 6 Jun 2013 @ 9:34 AM

  28. I appreciate the huge effort you have clearly put into this “definitive” work and admire the fact that you have also made the data available. It is obvious though that the spotight will now fall on whether or not the data show an anthropogenic signal during the 20th century. I have downloaded your combined “Yamalia” data and would agree that they show a 20th century warming signal of about 1C, noting however that a similar magnitude excursion occurred ~ 300 AD. However, my main question concerns the 15 year and which 100 year “smoothing” algorithms you used since I am unable to reproduce them. I suspect this 100y smoothed graph will be the one most likely picked up by the media. You yourselves state under Fig 13: “Note that the smoothed values at the ends of the series are much more uncertain due to the presence of end effects on the spline filters, especially for (e–f).” so this could back-fire.

    Comment by Clive Best — 7 Jun 2013 @ 4:25 PM

  29. Graeme,

    I’m commenting on the paper relative to those more fundamental issues, as time permits. The Yamal data is definitely better than most data sets, at least relative to RCS detrending concerns (as is that of Esper et al., 2012), and also better than the Polar Urals, but other critical concerns remain (as they do for virtually all tree ring studies attempting to estimate relative climatic state variables over centuries). See:
    http://ecologicallyoriented.wordpress.com/2013/06/08/briffa-et-al-2013-part-two/

    Comment by Jim — 8 Jun 2013 @ 12:58 PM

  30. One more aggravating comment on the left-out Khadytla sample, purely from methodological curiosity. It is clearly okay to discard an anomalous outlier when studying 20th century climate. But once you compare the 20th century to the middle ages, I think one would need to leave in the outliers. There might well be trees in your medieval sample that represent a local, anomalous, non-climate signal, too. (You can’t really know, can you? If you are able to spot and discard medieval problem trees, forget my comment) When you discard 20th-century non-climate signals, then compare with a medieval sample where non-climate-variation isn’t excluded, you will probably get an enhanced climate signal in the 20th century. Won’t you?

    Comment by ruth — 9 Jun 2013 @ 1:29 PM

  31. Ruth,

    Your point is a good one on a couple of levels. We can quantitatively know the relationship between environmental driver and ring response only during the calibration period, when we have both types of data. In the pre-calibration period, the response to the environment has to be inferred from correlations between the growth responses of different trees, relative to expectation under a null model of randomness. It would be an interesting study, IMO, to examine the intra-site coherence in ring response (across some set of sites), to see how that coherence changes between the pre-calibration and calibration periods.

    Your point also relates to calibration itself. If we calibrate a driver/response relationship based on a criterion of some minimal correlation (or probability) from a linear model, but the calibration period from which that derives only actually samples some part of a more complex, non-linear response surface/curve, then the estimates of the parameter of interest in times past could be seriously wrong and/or the certainty in the parameter over-estimated. And that’s a major consideration and potential problem.

    Comment by Jim — 9 Jun 2013 @ 4:25 PM

  32. Thanks for the comments over the weekend… we’ll answer/respond as time allows. Here’s the first.

    Response to Clive Best:

    Thanks for your comments.

    Yes, we highlighted the high-growth (and inferred warm summers) anomaly around 250 AD in our abstract and elsewhere in the paper. There are many interesting features to study, in addition to the modern warming.

    The smoothing was done using a spline approach. The algorithm/code for that was published in Melvin et al. (2007, Dendrochronologia, doi: 10.1016/j.dendro.2007.01.004) – see Appendix A for the computer code.

    We drew attention to the issue of end effects of the spline. Comparing the relative levels of different periods should only be done using means of the unfiltered data to avoid end-effects from influencing the outcome. Our comparisons of recent values versus earlier reconstructed values (as reported in, e.g. our abstract, Table 1, and Sections 9, 11, and 12) all used the means of the unfiltered data for this reason.

    Tim Osborn, Tom Melvin

    Comment by Tim Osborn — 10 Jun 2013 @ 9:19 AM

  33. Response to Ruth and to Jim’s follow-up to Ruth:

    The decision to exclude the Khadyta River Larch (or “khadytla”) sample was not based on comparison with instrumental data and hence not on the basis that it had a non-climate signal. Instead, the decision was based on the TRW data themselves:

    (1) evidence that the behaviour of this sample/site was different to the behaviour of the other samples/sites considered (see Fig. YT07 and YT06 in our Supplementary Material SM2.pdf); and

    (2) evaluation of site and recommendation from the scientists who have visited this site.

    It is the two things together that were important for our decision. Neither of these require instrumental data. But can these two conditions also be evaluated for the pre-20th century data?

    The first can be done fairly easily – as Jim suggests, we can look at coherence between tree-ring data over time. We have done this extensively in our paper and in the supplementary information (indeed our chronology confidence ranges are based on the spread from individual values in each year, and become broader when tree indices are in less agreement). Take a look at Fig. 5(f) in our main paper, which shows the changes over time in the standard deviation of the Polar Urals tree-ring widths – the periods with the root-collar samples stand out clearly as having much greater spread between the tree indices. This is the type of analysis that can test whether condition (1) is met in the earlier data, and in the Polar Urals case this was supporting evidence for the removal of the root-collar samples from the tree-ring chronology.

    The second is more difficult. For the Polar Urals case, we have the remnant wood. Therefore we do know that some samples were taken from the root collar, with its inherently wider rings, and thus support for our decision to exclude those samples that is separate and independent of the lack of coherence with the other data. But for Khadyta River, the evidence for the living trees being unhealthy and possibly dying came from a site visit and clearly we cannot visit the site 1000 years ago. We do, however, have information about the time-span of the subfossil samples – and if we align these by the year of the last-ring in each sample it can highlight periods of enhanced mortality. See for example Fig. 3(b) of Gunnarson and Linderholm (2002; Holocene, 12, 667-671) for a Swedish chronology. We didn’t include such a plot in our paper, but we have inspected the data in this way and there is no obvious period of enhanced mortality within a group of trees that corresponds with (but partly suppresses) a period of enhanced mean chronology values. That is, there is no obvious pre-20th century equivalent to the modern period Khadyta River case.

    Nevertheless, it is worth noting that we did include the Khadyta River data in the chronologies shown in panels (b) and (e) of Fig. 10 in our main paper, which gives an indication of the development of this chronology over time in response to inclusion of extra data and changing methods of processing the data.

    Tim Osborn, Tom Melvin

    Comment by Tim Osborn — 10 Jun 2013 @ 10:03 AM

  34. Yamal shows an accelerating rise and a gross 3C rise. Yamalia shows a variable but steady rise from the 1800s, with a gross 1.8C rise. Big difference when the difference between AGW and “normal” is slight, and the difference between AGW and CAGW is points of a degree.

    Polar Urals and Yamal-Khad are of the same style, quite different from Yamalia. The numbers may be questionable, but the style may still be okay. Yamalia has the same style as Yamal, which is why you are saying the first work was good despite the numerical change. If the Polar Urals and Yamal-Khad style is similarly good to the original Yamal, you are facing a regional style with the Yamal data, not a global or global-representative style.

    And the difference from the MWP isn’t that great from today to justify the use of “unprecedented” for today.

    Looks to me as if your new work supports a general recovery from the LIA, a continuation of such a recovery with a power equal to, if not the same as, the “natural” processes we all agree brought us out of the LIA. Your new work supports the contention that warming is not accelerating except within the rising portion of any cycle, and that the overall rate of temperature growth is in the low, Scenario B- of the IPCC reports. Which is not supportive of CO2 as demon, leading to catastrophe.

    If it weren’t for the political, social and financial costs and implication of your work, you would be feted by all. It is too bad that the energy and struggle you do is used in such a way (with your social group’s enthusiasm)that many wish to toss your baby out with the dirty bathwater.

    Comment by Doug Proctor — 11 Jun 2013 @ 12:07 PM

  35. Doug Proctor,

    Do you really want to bet the future of human civilization on a single study of a single proxy–especially when there is a whole helluva lot of science out there that suggests the situation is a whole lot more grave even than that portrayed in the IPCC summaries?

    Comment by Ray Ladbury — 11 Jun 2013 @ 3:58 PM

  36. Doug Proctor @34 — The temperature increase following LIA is almost entirely of anthropogenic origin. Orbital forcing indicates that temperatures should have continued to decrease in the absence of human activities.

    Comment by David B. Benson — 11 Jun 2013 @ 6:00 PM

  37. I’m not sure why the contrarians make such a big fuss over past global warmings. These only serve to support the current warming of today — the fact that there can be global warmings. So even if the MWP were as warm as today, that would only strengthen and support the fact that we are in the midst of global warming; and throw in the warmings of 55 & 251 mya, and we can see that it can get much higher than even today. And who knows how much higher it can get than back then, since the sun is now hotter, and we are causing GW a lot faster.

    Now whether past warmings were initiated and/or caused by factors other than GHGs (with GHGs perhaps playing a positive feedback role in great warmings not initiated by excessive GHGs in the atmosphere), in no way negates the fact that GHGs can cause or contribute to global warming (just as many factors can contribute to cancer). Also to my meager knowledge the atmosphere and the warming properties of GHGs do not distinguish between “natural” and industrial-emitted GHGs, responding only to the former with warming, but not to the latter.

    The problems with the denialist arguments is that they have more to do with logical fallacies than data (proxy or instrumental). Denialists need to be studying rhetoric and logical fallacies, not clamoring for unpublished data. They need to take their biased microscopes off of the tree-rings (as if they can find some proof in them to disprove the warming of today), and look at the larger picture.

    Comment by Lynn Vincentnathan — 12 Jun 2013 @ 2:10 AM

  38. I have question relating to the divergence of tree ring proxy data with instrumental data in the 20th c. (the tree data showing cooler climates). It seems that one aspect of the enhanced greenhouse effect is that the minimum diurnal (night) temps are increasing faster than the maximal diurnal (day) temps (I suppose unlike warmer periods not caused by an enhanced GH effect).

    While higher day temps may help plants, it seems these higher night temps have a negative impact on at least some plants, and perhaps other creatures, like humans. I remember the high death toll in the European heatwave of 2003 was more attributed to the high night temps that did not give people a chance to recuperate from the higher day temps.

    Anyway, this is was found to have a similar impact on rice paddy in South and SE Asia, and I was wondering if this might also be affecting trees and tree rings.

    See: Welch, J., J. R. Vincent, M. Auffhammer, P. F. Moya, A. Dobermann, and D. Dawe. 2010. “Rice Yields in Tropical/Subtropical Asia Exhibit Large but Opposing Sensitivities to Minimum and Maximum Temperatures.” Proceedings of the National Academy of Sciences 107(33): 14562-14567. http://www.pnas.org/content/107/33/14562.full

    Comment by Lynn Vincentnathan — 12 Jun 2013 @ 2:16 AM

  39. Doug Proctor @34

    The differences between Yamal and Yamalia (= Yamal + Polar Urals) aren’t so big — Fig. 1(e),(f) of our main post (which is Fig. 13 of our paper) shows them in red and blue, respectively. Of course this is expected because Yamal TRW is in both! You can see Yamal TRW vs. Polar Urals TRW in Fig. 8 of our main paper (no filtering) and in Fig. PY17 (with filtering) of our Supplementary Material section 5 (i.e. SM5). It isn’t clear to me that they are of different “styles”.

    Invoking “recovery from the LIA” is rather woolly. I recall reading work by Akasofu a few years back which postulated a linear 0.5 degC/century “recovery from the LIA” that would last for centuries. What?! Why would that happen, what controls how long the “recovery” takes? Things don’t just “recover”, they respond to forcing factors. And the recovery timescale is linked to the heat capacity of the system, and we can’t pick a long timescale for response to natural forcings (e.g. “recovery from LIA”) but then pick a short timescale when considering the response to more recent anthropogenic forcings. [Doug, I'm not saying that you are suggesting all these things, these are just examples of the woolly thinking that often accompany the suggestion that much of the observed warming can be explained away as "recovery from the LIA".]

    We need to have a more precisely defined framework than that to understand what is going on. What forcings caused the LIA and how did those forcings change since the LIA? How long would the system take to respond to those changes? What part of the observed/reconstructed changes can these natural factors explain? Various studies have used more precisely defined frameworks along these lines (see Fig. 6.14 of IPCC AR4 for example) and (subject to assumptions and uncertainties as always) found that “recovery from the LIA” would have made only a small contribution to the observed warming.

    Comment by Tim Osborn — 12 Jun 2013 @ 7:08 AM

  40. #34, #39–Yep.

    Akasofu’s “recovery from the LIA” might just as well have been “pixie dust.” It sounds much more plausible and ‘scientific’ (and does have a tangential relation to reality, in that there really was an LIA and we really have ‘recovered’ from it)–but without a physical mechanism, it has no more explanatory value than would “pixie dust,” or for that matter, any other label one might choose to apply.

    To put it differently, for “recovery from the LIA” to be meaningful, we’d need to have some idea what was causing that recovery–how that recovery ‘works.’ (Then, and only then, we’d be able to generate testable hypotheses about it–like, “Is it done yet?” Or, more immediately testable perhaps, “Is its observed temporal and spatial structure physically consistent with other knowledge?”)

    To my knowledge, Akasofu and acolytes haven’t even attempted that test, let alone passed it.

    Comment by Kevin McKinney — 12 Jun 2013 @ 1:39 PM

  41. Lynn @ 37

    No-one is denying anything. CO2 is a GHG and any increase will (given sufficient time) “force” the climate to reach a new equilibrium. First order physics (assuming a fixed lapse rate) can be shown to result in a net rise in global temperatures of ~1.1C – after a doubling of CO2. The debate is really just about second order effects. In other words how does the rest of the climate system react? Will more evaporation enhance the CO2 greenhouse effect or can more humidity also reduce the lapse rate acting to dampen the GHE ? Does more evaporation lead to more clouds and if so is the net effect of more clouds to increase albedo or to further increase GHE ? I don’t believe any model or any climate scientist really knows the answer. That is why experimental results like this are so important.

    Recent results (like this one and Otto et al.) hinting at lower climate sensitivity and reduced feedbacks should be seen as positive developments. Human ingenuity can only work outside the straight-jacket of national or international governments – just look at the Internet! It is a big mistake to legislate now pre-determined technical solutions for restricting CO2 emissions no matter how well-meaning or enlightened the protagonists. There is a problem. It can be solved. We have at least 50 years to solve it. One should never pre-select technological solutions on the basis of transient current political fashion. Solutions will be found and the world will not end.

    Comment by Clive Best — 12 Jun 2013 @ 4:21 PM

  42. #41–”We have at least 50 years to solve it.”

    Totally unsupported assertion–and one that flies in the face of physical changes observable today in the real world.

    Comment by Kevin McKinney — 12 Jun 2013 @ 11:10 PM

  43. Clive Best @37: “Human ingenuity can only work outside the straight-jacket of national or international governments – just look at the Internet” You’re joking, right? Or are you truly unaware of the role of DARPA in the creation of the Internet?

    Comment by Steven Sullivan — 12 Jun 2013 @ 11:12 PM

  44. Clive Best, how exactly does this particular work hint at a lower climate sensitivity?

    Comment by Marco — 12 Jun 2013 @ 11:25 PM

  45. Clive Best #41, water vapour is first-order physics too. Go read some textbooks before wasting our time with nonsense

    Comment by Martin Vermeer — 13 Jun 2013 @ 3:53 AM

  46. #41–”No-one is denying anything.”

    HA! If only it were so. Even you, Clive, are denying that there is an immediate, urgent problem in the same comment in which you deny denialism itself.

    Were there any point in linking to trash, I could provide immediate, comprehensive examples right now of denialism at every stage: from denial that there’s been warming since 1980(!)–WUWT, yesterday–to denial of human causation, to denial of the potential seriousness of the issue. And there is direct evidence (and volumes of it, at that) that this denialism is supported and nurtured by a deliberate, sustained PR campaign funded by economic and ideological interest groups.

    For just one book on this topic:

    http://doc-snow.hubpages.com/hub/Climate-Cover-Up-A-Review

    OK, scratch “just one”–I shouldn’t fail to mention Dr. Mann’s memoir:

    http://doc-snow.hubpages.com/hub/Michael-Manns-The-Hockey-Stick-And-The-Climate-Wars-A-Summary-Review

    Comment by Kevin McKinney — 13 Jun 2013 @ 7:51 AM

  47. Ya know, Clive Best, when you rebunk stuff, it maybe fools new readers who don’t recognize old assertions repeatedly debunked in the past.

    True, the more successful the site is, the more new readers come along. So you can always hope nobody points this out.

    If there were only a way to flag any actually interesting new claims, versus the old ones (sigh). We need better software.

    Comment by Hank Roberts — 13 Jun 2013 @ 10:17 AM

  48. Do you have any results concerning the impact of volcanos?

    Comment by T Marvell — 13 Jun 2013 @ 11:04 AM

  49. CB @41: “The debate is really just about second order effects.”

    With respect to Mr. Best’s post, which I may be unfairly implying is a good example, one of the fallacious but clever debate manipulations utilized by CC deniers and (way too many) lukewarmers is to focus relentlessly (often inaccurately) on climatological research frontiers such as climate sensitivity, or relations between evaporation, cloudiness, and global albedo.

    But that’s just one set of ‘second-order’ effects to be concerned about: from a purely anthropogenic perspective, one should arguably be a lot more concerned about the ‘second-order’ impacts upon estuarine, coastal marine, and freshwater ecologies that are without question unfolding now pretty much everywhere. These cascading transformations throughout the planet’s ecosystems rarely seem to be of much rhetorical concern for the naysayers and ideologues, as evidenced in all those carefully engineered and web distributed denialist PR campaigns and blog comments, and not even here much at RC; although of course the field of dendrology includes the study of how trees are responding to a warming climate.

    Why the lack of greater awareness to the intensifying biological and ecological responses to CC beyond scientists and environmentalists? Lots of reasons; but from the perspective of denialism, likely one reason is that the surprising and troubling ecological impacts of AGW and CC that the world’s farmers, fishermen, naturalists, birdwatchers, eco-tourists, and alpinists are observing and experiencing in horror will continue to push denialism into the dustbin of history, only to be held up for cynical ridicule by future generations as they sit and wonder, ‘what the heck were our ancestors thinking?’

    Comment by Sloop — 13 Jun 2013 @ 11:15 AM

  50. Response to Philip Cohen @27… (sorry for the long wait)

    YAD061 is not the “most influential tree in the world”. It is a tree with high growth rate and some wide rings, and these contribute to the high values in the original Yamal chronology. But these occur in a period with elevated growth for many of the trees, not just that one tree. So its influence on the Yamal chronology – and on the conclusions drawn from the Yamal chronology – is rather limited. In the Briffa (2000) and Briffa et al. (2008) Yamal chronologies it has only a small influence. In our new chronology, its influence is imperceptible. For multi-proxy reconstructions that use the Yamal chronology along with other proxies, its influence is of course diluted further. And its influence on the climate change issue as a whole is negligible.

    Let’s take a closer look at YAD061. In a few years since 1950, this tree had a very high index value of 7 or 8 (meaning these rings are 7 or 8 times wider than would be expected for rings of that age growing in average climate conditions). But this is nowhere near as rare as an 8-sigma value from a Normal distribution, because the TRW index values have strong positive skew (see Fig. PY03 in our SM5) favouring more frequent very high values. It is not the tree with the largest tree index value in the original Briffa (2000) and Briffa et al. (2008) datasets – tree L04551 has larger index values in the 1720s.

    There is no clear justification for excluding YAD061, without also excluding other trees with high index values or indeed with low index values – and note the earlier discussion and concerns about post hoc data removal.

    However, if you do remove core YAD061 and recreate the old Yamal chronology, the difference is quite limited: see this image. Of course the recent values are lower because you have deliberately searched for and removed the tree with the highest recent index values! But the difference is not enough to affect the main conclusions drawn from that work – clearly not the most influential tree in the world then.

    For our new Yamal chronology the inclusion or exclusion of YAD061 makes no perceptible difference to the chronology (see this image; the red line is there, but virtually hidden under the black line). Our conclusions are compatible with those obtained with the old Yamal chronology. So how can YAD06 be the “most influential tree in the world”?!

    There are two reasons why YAD061 has no effect on the new chronology and is not an outlier. (1) We have additional data. (2) We have improved tree-ring standardisation processes.

    In our new chronology, 17 other trees have peak tree index values that exceed the peak value of YAD061, so it no longer even peaks at the 2nd highest, it peaks at the 18th highest. Of these 18 trees with the highest peak index values, 8 peak values occur in the 20th century and no more than 2 occur in any of the preceding 20 centuries. Clearly the 20th century is a period with enhanced tree-growth, so it is perhaps not surprising to find a tree like YAD061 during this period.

    The improved standardisation includes a number of innovations. The key one here is that we now transform the tree index values to follow a normal distribution, which reduces the extremely high index values – e.g. YAD061 peaks around +3.5 standard deviations after this step, compared with the +8 index value before. Together with the expanded dataset, these are the reasons for the lack of sensitivity to inclusion/exclusion of core YAD061. See Fig. 2(a) of this blog to compare “old” and “new” chronologies.

    McIntyre overstates the role of this single tree. His post title “YAD06 – the Most Influential Tree in the World” is hyperbole. Maybe he just wants to appear provocative and/or interesting. It has its downsides.

    Not least causing others to also overstate things: Booker’s Telegraph piece: “On this astonishing tale, it is no exaggeration to say, could hang in considerable part the future shape of our civilisation.” Really? No exaggeration?

    But it can also cause confusion. On 1 March 2010, Lord Nigel Lawson gave evidence to the UK House of Commons Science and Technology Committee that “for a long period before 1421 they relied on one single pine tree” (volume II, evidence EV4, page 9). We don’t know what he meant by this, nor what his source was, and maybe he didn’t really know either – but could he have read a blog post or an article talking about “the most influential tree in the world” and conflated that vague knowledge with questions about tree-ring divergence? It’s possible.

    Tim Osborn, Tom Melvin

    Comment by Tim Osborn — 13 Jun 2013 @ 12:10 PM

  51. Hey Kevin, thanks for those review links. I’ve read both those books, but really enjoyed watching the Hoggan interview, and they did a great job summarising Mann’s book.

    Comment by Steve Metzler — 13 Jun 2013 @ 3:14 PM

  52. #41: in addition to the rebuttals above, a few questions:
    Who in the Free Market is going to do the research from which the solutions will emerge? The biggest investment so far seems to be in denialism.

    When solutions do emerge, who’s going to pay for them? Insurance companies? The Laissez Fairy?
    And, as has been pointed out over and over, even if we survive for fifty years without terrible upheavals, how are we going to afford those global-scale multi-gigabuck solutions when more and more and more of our limited resources are going to disaster relief and remediation?

    Comment by Philip Cohen — 13 Jun 2013 @ 4:40 PM

  53. Yamal to the Rescue!

    It’s a race against time, because temperatures are anomalously high and the ice continues to melt.

    Comment by Pete Dunkelberg — 13 Jun 2013 @ 10:23 PM

  54. #50 Tim Osborn, Tom Melvin

    Thank you for this additional information.

    Is there any other tree you could remove from the chronology which would make more than a 1C difference to the result as the removal of YAD061 does according to your linked plot?

    You state: “Of these 18 trees with the highest peak index values, 8 peak values occur in the 20th century and no more than 2 occur in any of the preceding 20 centuries.”

    Please could you provide a table or plot showing the positions and durations of the samples from those 18 trees in the chronology.

    Regarding the prevalence of peak values in the C20th, to what extent may they be due to increased CO2 fertilisation rather than increased temperature?

    Comment by Roger Tattersall — 14 Jun 2013 @ 3:23 AM

  55. Thanks, Steve M! Glad to provide something worthwhile.

    Comment by Kevin McKinney — 14 Jun 2013 @ 8:43 AM

  56. Sloop #49

    > which I may be unfairly implying is a good example

    I don’t think so. Denial of the first-order significance of water vapour feedback is a classical denialist talking point, at least among those denialists who have bothered to acquire a sciency-sounding vocabulary. And our friend CB clearly also belongs to the Church of the Free Market, where dogma has it that the Internet was a free-market product.

    But, am I correct in seeing in your comment an illustration of the principle that we all have the greatest concerns about the fields of study we are most familiar with?

    Comment by Martin Vermeer — 14 Jun 2013 @ 11:31 AM

  57. re: 50
    Great description, thanks, I wondered what that was ever about, but the Lawson quote may be useful to Bob Ward, as per Lord Lawson’s climate-change think tank risks being dismantled after complaint it persistently misled public.

    Back to science, or rather presentation thereof. Those images clearly convey the fact that there is little difference, but I found myself also wishing for the *addition* of a similar-scaled chart showing the actual differences, i.e., one line instead of two.

    I generally find spaghetti charts challenging, especially in steep-sloped areas. I liked Nick Stokes’ display, where mouseover of a label highlighted its corresponding line , but that only works interactively, a bit like a “blink” At least with only 2 lines, one could show a single difference line.

    Comment by John Mashey — 14 Jun 2013 @ 6:34 PM

  58. Osborn&Melvin @50: Thank you! I’ll send this to my friend. Even if it doesn’t affect his opinions, it should prove useful in future.

    Comment by Philip Cohen — 15 Jun 2013 @ 3:46 PM

  59. I’ve wondered how are you taking into account the fertilizing effect of CO2?

    In field trials in Finland, where trees were grown in increased CO2 atmospheres, scientists have noted that tree ring widths are really good indicator of CO2, but not so much temperature while tree growth is a good indicator of temperature, less of CO2.

    As both temperature and CO2 have increased you can’t differentiate the effect of CO2 and temperature from each other from pure tree ring data. So how much of the tree ring width increase comes from CO2 and how much from temperature, in your study?

    If the coefficient is too low, or not taken into account any pre industrial temperature swings are underestimated as the CO2 fertilizing effect increases modern temperature proxies and by calibrating to increased proxies, past temperature swings are dampened when read from past tree ring data.

    Comment by Curious — 15 Jun 2013 @ 7:57 PM

  60. > 28, 50
    > Response to Philip Cohen @27… (sorry for the long wait)
    > YAD061 is not the “most influential tree in the world”.

    Thanks much for that clear response.
    I hope it starts showing up in ‘oogle searches — right now searching that quoted phrase returns nothing but the deniers’ assertions. Time will tell.

    Comment by Hank Roberts — 16 Jun 2013 @ 6:43 AM

  61. M Vermeer @ 55:

    How we function cognitively and socially apparently results inevitably in functional, operative distinctions between the sciences of ecology and climatology. It is how, given the evolved nature of our brains, we must go about describing and understanding different facets of the same massive phenomenon. Of course though one of the great insights of the earth sciences is how the planet’s chemical, physical, and biological spheres alter and in turn are altered by each other.

    Governance seeks to maintain pace with real and imminent planetary changes that affect the well-being of citizens. Humanity’s collective well-being stems from the tightly inter-related dynamics of biology and economy. To move people to action and sacrifice, Government tries continually to reveal and manage connections between human self interest and utility-maximization and healthy, high-quality, and resilient natural environments at multiple geographies. We have to begin where people perceive most tangibly the risks to their well-being and their children.

    Simple principle. Devilishly difficult to apply well. Take lobster: commercial lobstering may disappear from southern New England waters in a matter of decades because of warming coastal ocean temperatures (and yes other factors including the historical harvests and multiple ecological impacts that ensue from warming water and altered current regimes). Convincing folks of the truth of this risk is difficult enough because livelihoods are threatened. It’s all the more difficult because the US is cutting funds for lobster monitoring and devoting paltry sums to the study of how lobsters respond as organisms and as populations to changing oceanographic conditions. Even long-term databases on coastal ocean temperature trends are surprisingly rare.

    But commercial lobstermen don’t need multi-decadal temperature records and more science on lobster shell disease to conclude strange things are happening in the ocean waters they spend their lives on. They see the changes intimately and they want help to survive economically. They want the rest of us to both compensate them for losses they didn’t cause and to address proactively the causes of looming lobster recruitment failure. It’s a matter of understanding and connecting with them and building political support from there.

    An incomplete, lunch hour response. Sure I have a predilection for science I’m more familiar with; but given the realities of policy and economy, which science to be particularly concerned with seems reasonably self evident.

    Comment by Sloop — 17 Jun 2013 @ 1:36 PM

  62. First I would like to thank Tim Osborne (#32) for pointing me to the spline smooting algorithm used in the paper. I implemented it and compared the results to a 30 year FFT filter see http://clivebest.com/blog/?p=5040 . The results are surprisingly similar except for end effects.

    To respond to some of the other remarks if I may:

    One of the problems of climate science is that it has all become rather too devisive. You are either with us or you are against us. This then leaves little room for any middle ground, which is where I feel I stand. There is AGW but there is also still uncertainty about feedbacks. The models do not make firm predictions on future warming, and recent temperatures are significantly less than those predicted in AR4. It is indeed prudent to reduce CO2 emissions, but drastic action is both dangerous to society and even illogical (IMHO).

    One should never propose a policy without proposing a realistic solution. To cut carbon emissions by say 80% in 30 years is fundamentally impossible through renewable energy. If you take for example the UK, power consumption averages around 40GW rising to a peak demand of ~70GW. This means that nationally we must have an installed capacity of 70GW, – perhaps rising to 100GW if electric transport takes off. However we will always need a 100% reliable base-load of 30GW. Currently there are 3700 wind turbines installed in UK receiving an annual subsidy of ~ 1.2billion. As I write – the sum total power being generated by ALL these turbines combined is 0.3GW (<1% of demand) – see http://www.gridwatch.templar.co.uk/. The maximum power generated on the windiest day this year was 5GW – but only for 2 days. The sums just don't add up. Suppose we quadruple the number of turbines – ignoring the environmental impact on our small island. This massive effort would be to no avail because instead of 0.3GW we would instead be generating 1.2GW right now – which is still insignificant. Renewables really do cost the earth!

    Current energy policy is miss-conceived and physicists should stand up and say so. Myles Allen recently actually did stand up and say so! The only proven non-carbon energy source remains nuclear power. Nuclear Fusion could also work given the political will.

    Comment by Clive Best — 18 Jun 2013 @ 3:54 AM

  63. Curious (59):

    This was wrongly placed in the bore hole and I’ve retrieved it; it’s an entirely legitimate question.

    The CO2 fertilization effect remains a very serious difficulty in tree ring analysis generally. There needs to be some serious thought given as to how to deal with it, and a general analytical solution proposed, to the extent possible. Currently none exists, but it would have to take advantage somehow of the differences in the spatio-temporal pattern of climate (highly heterogeneous), versus CO2 (highly homogeneous).
    Jim

    Comment by Jim — 19 Jun 2013 @ 12:19 PM

  64. > CO2 fertilization effect remains a very serious difficulty
    For what geological eras or time spans, Jim?
    Where we have instrumental records for CO2 and temperature, is it understood?
    (pointer welcome to discussion elsewhere, don’t want to derail this if it’s a long conversation)

    [Response: It's definitely a long conversation, getting deep into plant physiology quickly, but I meant "serious" in the sense of "difficult to separate two potentially (but strongly) confounded effects (CO2 fert. and climate), given the observational data available". The data on CO2 effects, vs those used in dendroclimatology studies, are largely disparate and therefore difficult to connect. People are working on it, but it's a big bridge to cross effectively.--Jim]

    [Response: Here is an example of the type of study I referred to in my previous comment. I like it for its approach: the authors tried, given the limitations of the data, to separate out climatic from non-climatic effects in the ring response. They concluded that CO2 fert. (+/- a possible N effect) was likely a major contributor to increased ring width responses observed in two one species in the Alps (Pinus cembra), but that conclusion is less important, to me, than is their approach to the problem.--Jim]

    Comment by Hank Roberts — 19 Jun 2013 @ 3:09 PM

  65. wait: over yonder at his blog, Clive Best says:
    June 12, 2013 at 6:17 pm “… The new results already show about half the 20th century warming compared to their original 2000 paper – so the “consensus” is shifting.
    There is some (moderate) AGW but in no way is it catastrophic !”

    I saw the goalposts go by, they were going, uh, thataway ….

    The catastrophe’s only begun to be detectable now against the background noise in the physics measurements, but it’s been clear in our more sensitive detectors — ecologies — for quite a while. Look up phenology.

    Comment by Hank Roberts — 19 Jun 2013 @ 3:43 PM

  66. The *actual* topic of this post was interesting, maybe it could be discussed, especially when some authors have taken the time to watch and answer questions.

    Nuclear power and especially fusion power do not seem very relevant to this topic.

    Comment by John Mashey — 19 Jun 2013 @ 6:45 PM

  67. “The new results already show about half the 20th century warming compared to their original 2000 paper – so the “consensus” is shifting.”

    Has Clive Best forgotten that real thermometers exist, and that the instrumental record, not regional proxy reconstructions, is what’s focused on when 20th century warming is discussed?

    Comment by dhogaza — 19 Jun 2013 @ 6:47 PM

  68. Isn’t it funny that everyone always thinks they are “the middle way”? Ain’t nothin’ in the middle of the road but yellow stripes and flat armadillos.

    Comment by Ray Ladbury — 19 Jun 2013 @ 8:34 PM

  69. @(66) John Mashey.

    I agree with you – my apologies for over-reacting !

    Comment by Clive Best — 20 Jun 2013 @ 3:43 PM

  70. “This then leaves little room for any middle ground, which is where I feel I stand.”

    There is no scientific reason for choosing the middle ground, just because it is the middle. Clive Best should know this. But of course his “middle ground” is 1C warming per doubling of CO2, which is hardly a middle ground within science.

    In geology, his “middle ground” would be to declare that the earth is 2 billion years old, splitting the difference between cosmologists and young-earth creationists, because, you know, the middle ground is most likely to be accurate …

    Comment by dhogaza — 20 Jun 2013 @ 11:16 PM

  71. Middle ground

    Comment by Martin Vermeer — 21 Jun 2013 @ 1:17 AM

  72. Using tree rings to assert whether the trees had hot/dry/C02/infection/poisoning/..add more. Is a daft premise from the outset.
    You cannot separate the variables.
    Tree’s with high C02 grow faster. They can also withstand drought and freezing better due to the reduction of stoma that is required.
    Linearity is not what tree’s do. Even the outer rings compress as new growth takes over.

    [edit]

    [Response: It's definitely not simple or easy to separate out the various possible drivers of ring response in trees, but that doesn't make it a "daft premise from the outset". It does mean that some hard and creative thinking is required if the problem is to be solved correctly, and an ability and willingness to acknowledge when the limits of analysis have been reached. As is always true in all of science--Jim]

    Comment by Andyj — 21 Jun 2013 @ 3:23 AM

  73. Andyj:

    “Using tree rings to assert whether the trees had hot/dry/C02/infection/poisoning/..add more. Is a daft premise from the outset.”

    And another internet genius shoots down an entire field of research with a SINGLE sentence!

    Comment by dhogaza — 21 Jun 2013 @ 11:56 AM

  74. Andyj #72,

    don’t project your own ignorance on others. You (well, not you, but actual scientists) can separate out many of these factors. E.g., you use trees from locations where growth is temperature limited (i.e., at the tree line) to extract — you guessed it — temperatures. And so on.

    [Response: That concept is certainly highly important and useful, but not necessarily fully effective either. For example, there is solid evidence that most--perhaps even all?--plants with the C3 photosynthetic pathway (which all trees used in dendroclimatology have) are carbon limited to a greater or lesser degree. Additionally, there is reason to believe that that limitation should be greater at higher elevations, for reasons that have to do with the reduced CO2 partial pressures there and tradeoffs between the biophysics of the resistance to CO2 diffusion/fixation, and the reduced carbon loss via reduced photorespiration as atmospheric [CO2] increases. It’s complex (and highly interesting to some of us), and a mistake to think that just because there is a known limitation in one environmental driver, that it necessarily predominates over others. It may–and it may also not.–Jim]

    And do you think scientists are dumb? (No, don’t answer that.) Ever heard of multi-proxy reconstructions? It is routine to check that you get the same result (within uncertainties) taking tree-ring proxies along, and leaving them out. E.g., Mann et al. 2008 figures S5-S7.

    And denialist’s should learn to spell :-)

    Comment by Martin Vermeer — 21 Jun 2013 @ 1:56 PM

  75. A different question for the authors:
    I’m always fascinated by thing paleoclimate researchers do to extract signal from noisy data for which one cannot simply replicate experiments in the lab.

    So, for this region, what data do you wish you had, that could be plausibly gotten (i.e, not like 1000-year-old measured temperature records), that you don’t have? And why?

    [Response: Great question John, and I'll let them go first.--Jim]

    Comment by John Mashey — 21 Jun 2013 @ 2:45 PM

  76. Andyj’s post illustrates an important distinction. Laymen see complexity and despair. Scientists find a way to make sense of it. If it were easy, someone would have done it already.

    Comment by Ray Ladbury — 21 Jun 2013 @ 4:56 PM

  77. Perhaps this should go in unforced variations, but as it’s plant related, will post here. Along with kudzu and poison ivy, it appears CO2 is good for brambles in Africa:

    http://www.guardian.co.uk/environment/nature-up/2013/jun/21/blind-starving-cheetahs-climate-change

    Farmers and researchers recognised bush encroachment as a serious problem in many parts of southern Africa by the 1980s, and it has long been thought to be caused by poor land management, including overgrazing. But, as I recently reported in Yale e360, an emerging body of science indicates that rapidly increasing atmospheric carbon dioxide may be boosting the onrushing waves of woody vegetation.

    Savanna ecosystems, such as those that cover much of Africa, can be seen as battlegrounds between trees and grasses, each trying to take territory from the other. The outcomes of these battles are determined by many factors including periodic fire, an integral part of African savannas.

    In simple terms, fire kills small trees and therefore helps fire-resilient grasses occupy territory. Trees have to have a long-enough break from fire to grow to a sufficient size — about four metres high — to be fireproof and establish themselves in the landscape. The faster trees grow, the more likely they are to reach four metres before the next fire.

    Lab research shows that many savanna trees grow significantly faster as atmospheric CO2 rises, and a new analysis of satellite images indicates that so-called ‘CO2 fertilisation’ has caused a large increase in plant growth in warm, arid areas worldwide.

    Although poor land management is undoubtedly partly to blame for bush encroachment, increased atmospheric CO2 seems to be upsetting many savanna ecosystems’ vegetal balance of power in favour of trees and shrubs.

    [Response: By coincidence, I just posted about that very topic on my blog late yesterday. As I mentioned to Martin, pretty much all C3 plant species (which are the vast majority of all species) are carbon limited, both plants we like and plants we don't like. I like the science issues involved here, but I dislike the negatively-biased spin the author puts on it with several statements, especially regarding effects on cheetahs, which border on the ludicrous. Along those lines, it's not "so-called 'CO2 fertilisation'"-- it's real, actual CO2 fertilization, exactly in the sense of N or P fertilization, even if the biochemical mechanism is, of course, going to be different.--Jim]

    Comment by Susan Anderson — 21 Jun 2013 @ 8:37 PM

  78. Jim #74, now that I have your ear: is it true that RCS determination is still done by ‘stacking’ and averaging? Has anybody considered (this may teaching granny to suck eggs) using a simultaneous least-squares adjustment giving both the RCS and the adjusted chronology?

    This would have the merit of producing uncertainty measures automatically for all the adjusted unknowns. Also the condition number of the normal matrix would tell you immediately how well you have separated growth curve and local climate (and CO2, if you try that). I suspect such an adjustment is formally equivalent to Briffa’s “signal-free” RCS determination, which avoids climatic trends leaking into the RCS curve when stacking. Least-squares would do this implicitly.

    [Response: Martin, the RCS "stacking and averaging", by ring number (= "cambial age") is typically followed by fitting a smoothing spline to those averages (the underlying idea being that the age/size effect should be relatively smooth, which the un-smoothed averages alone will not always be), and in the literature both relatively stiff and flexible splines have been used to do so, which are mirrored in the two publically available softwares for performing RCS (ARSTAN and an R package called dplR). I'm not 100% sure what you mean by "simultaneous least-squares adjustment", so hard to respond exactly. If indeed that method were +/- equivalent to the so-called "signal-free" standardization, then it would not prevent "climatic trends leaking into the RCS curve when stacking", because that method does not guarantee any such result. The problem of an environmental trend being partially captured by the RCS curve is due to the inhomogeneity of the age/size structure of the sample combined with the existence of an environmental trend over time. This causes the entire RCS curve to be biased by a constantly increasing amount over time, not just at the series ends, and not with offsetting errors in the middle as claimed by Briffa and Melvin, but the entire curve, from one end to the other. This is the main point in my series on that whole topic at my blog, is easily demonstrable with a flexible growth model that can produce any type of age/size effect, and was the point of a PNAS paper I submitted last year (but which was rejected because the reviewers completely failed to understand this issue and the evidence I presented for it). So, even though I don't know exactly what you have in mind, I highly doubt that it can solve this problem.--Jim]

    Comment by Martin Vermeer — 22 Jun 2013 @ 2:46 AM

  79. Yep. I’ve been seeing poison oak show up at higher elevations in California the last few years, places it’s never appeared in the past. Likely birds have always pooped seeds, but the winters aren’t getting as cold.

    Ever been fighting a fire downwind of burning poison oak? It’s nasty.

    [Response: Gotta factor the fire regime changes into that calculus Hank. And never do the latter--highly dangerous if you breathe the active agent into your lungs. Firefighters have suffered serious injury that way.--Jim]

    Comment by Hank Roberts — 22 Jun 2013 @ 10:28 AM

  80. but,oops, offtopic. sorry

    Comment by Hank Roberts — 22 Jun 2013 @ 10:28 AM

  81. Jim #78, as standard least squares produces unbiased estimators for the RCS parameters (in fact for all unknowns — it’s a basic property), I don’t see how they could pick up biases from climatic trends.

    [Response: Martin, we're talking about two different types of bias here. You're talking about the bias that could arise from curve fitting algorithms. I'm talking about the bias that arises when different ages/sizes of the sampled trees sample different portions of the environmental space. For RCS to work right, they all have to sample the full domain of that space, but they cannot if the age structure doesn't allow it. Completely different things, and the latter is the much more potentially serious. The point is that no matter what curve fitting method you choose: least squares, robust regressions, whatever--they're not going to be able to to remove the bias due to this sampling issue --Jim]

    Comment by Martin Vermeer — 22 Jun 2013 @ 12:54 PM

  82. Jim, no, I’m not talking curve fitting. I must say that I sympathise with your PNAS reviewers… I don’t get what you mean either :-)

    [Response:Readers will notice that someone here at RealClimate has seen fit to delete my extended comment to Martin (without justification and without any notice), so hold on while I re-compose it.--Jim]

    [Response:Original comment: Then I'm not sure what application of least squares you are referring to. As for understanding the issue, the reviewers, who were (supposedly) tree ring experts, had available to them a huge amount of detailed information. I have discussed the issue in great detail beginning here and going to here. The problem is as follows. The RCS method is designed to estimate the age/size effect by taking an ~ mean ring response for each age/size in the data set. But this is only fully accurate if each sampled age/size fully samples the environmental space covered over the full time period. If instead you have, for example, a situation in which early rings preferentially sample one end of that continuum, while later rings tend to sample the opposite end, this will cause the entire RCS "regional curve" to be biased by a constantly increasing amount over time. Not just at the series ends, and not with offsetting errors in the middle as claimed by Briffa and Melvin, but the entire curve, from one end to the other. This is the main point in my series on that whole topic at my blog, is easily demonstrable with a flexible growth model that can produce any type of age/size effect, and was the point of a PNAS paper I submitted last year (but which was rejected because the reviewers completely failed to understand this issue and the evidence I presented for it). This problem is one reason–and only one–for why trying to estimate climate states over long periods, from tree ring widths, is completely unreliable. Completely.–Jim]

    [Response: It's probably worth adding that Jim's last conclusion is not universally shared (e.g. fig 3 from Esper et al, 2012 shows a very good correspondence between TRW and MXD chronologies). That isn't to say that there aren't issues... ;-) - gavin]

    Comment by Martin Vermeer — 22 Jun 2013 @ 1:48 PM

  83. In my comment at #21, I failed to say how much I am enjoying both the primary post and the discussion that follows. RC does it again, and congrats to Tim, Tom, and Keith for an awfully nice job. While primary, peer-reviewed papers cannot be done without, this kind of medium let’s us all “under the wrappings” to see some of the materials and concerns which are necessarily implicit in published works. It is very informative and a good deal of fun. Thank you!

    Now professionally, I’ve always found looking over the shoulders of people grappling with experimental problems in geophysics to be enlightening, principally because the character and distributions of your data are so different than most people are taught. I learnt about directional data that way and went on to appreciate things like Best Linear Unbiased Estimation in the spatial realm, a.k.a. “kriging”. So keep on!

    Comment by Jan Galkowski — 24 Jun 2013 @ 7:56 AM

  84. Jim, actually it was having read your blog posts on this that made me bring up the least-squares proposition as a way of addressing at least this bias problem. I’m not sure you appreciate what least squares with a properly formulated model can do — there is no shame in that, I know some clever folks who don’t either :-)

    [Response: Of course I can't appreciate it--because you haven't explained what you have in mind. If you'd like to do that, go ahead. Note also that my original, more extensive response to you was again deleted by someone here--Jim]

    Comment by Martin Vermeer — 24 Jun 2013 @ 1:40 PM

  85. Comment 3. fred smith: “Aren’t the conclusions of 1 and 2 post hoc explanations for exclusion of data?”

    Comment 4. Tim Osborne: No. The fact that some Polar Urals cores were taken from root collars was noted at the time the samples were taken … For the second case, the potential problems with the Khadyta River site were also noted at the time the samples were taken …

    When ClimateAudit publicized information about Yamal in 2009, CRU published two responses at their website discussing McIntyre’s recent posts on this subject. Neither CRU post mentions root collars or permafrost (the postulated problem at Khadyta River). Now in 2013 – more than a decade after the field work was done and published and years after your initial reply to McIntyre – information appears concerning root collars and permafrost. Why doesn’t this constitute a post hoc exclusion of data? If this doesn’t, what would?

    Those of us who have knowledge of fields where confirmation bias is a widely recognized problem find such situations problematic. In the ideal case, you design your experiment, you collect as much of the data as you intended as possible, you analyze it by a pre-planned method, and publish the result. This process may lead to the hypothesis that a better answer lies in a subset of the data you initially collected or an alternative statistical treatment; a post hoc analysis that always risks confirmation bias. In critical fields such as human clinical trials, post hoc analyses aren’t acceptable, because everyone knows that one can usually find some sub-population that behaves as originally anticipated and devise a post hoc explanation. In those cases, the FDA demands that drug companies collect a new, independent data set with the patients (or trees) that are now hypothesized to provide the “right” answer. Of course, this isn’t always practical in dendrochronology, climate science or drug development. In that case, you are stuck with two possible answers to the question you were investigating: one answer arising from analysis of all the data you collected and analyzed, and a second answer arising from a subset or re-analysis of that data.

    Are you reviewing all of your earlier work to see if root collars or permafrost might have biased those results?

    [Response: Comment restored from trash folder.--Jim]

    Comment by Frank — 24 Jun 2013 @ 5:42 PM

  86. Martin Vermeer wrote:

    “Jim, actually it was having read your blog posts on this that made me bring up the least-squares proposition…”

    Jim’s posts on this topic form a very powerful argument in my opinion. I share his bewilderment on how a least squares approach can resolve the issues he very carefully lays out. Can you show how the least squares adjustment would improve the results from Jim’s flexible age model approach with synthetic data?

    [Response: Comment restored from the trash folder.--Jim]

    Comment by Matt Skaggs — 24 Jun 2013 @ 5:43 PM

  87. Jim, sure, we can try… drop me an email.

    [Response: You're welcome to present it here Martin if you like--would be informative for everyone.]]

    Comment by Martin Vermeer — 25 Jun 2013 @ 4:39 PM

  88. A question for Tim Osborn or someone from CRU. Various papers by Shiyatov state that he crossdated 888 subfossil trees and more than 400 trees from two Polar Urals transects, with coordinates and altitudes carefully recorded.

    Why didn’t CRU use this dataset in Briffa et al 2013 instead of the inadequately replicated dataset that it reported on? Did CRU attempt to obtain access to this data and receive a rejection? And why didn’t CRU report the existence of Shiyatov’s crossdated dataset in its review of previous work at Polar Urals?

    [Response: We were aware that many additional wood samples were collected, measured and cross-dated in the Polar Urals by our co-authors, as part of their excellent ongoing ecological monitoring at the tree-line. In fact there are even more data, from more recently sampled material. As with the previous data, these are a complex mix of stem, root, prostrate forms, etc. and indeed many samples will not be suitable for dendroclimatological analysis using the basic RCS approach.

    A preliminary analysis of some of the "stem" samples produces a similar picture of tree-growth change when using RCS processing as that shown by the Polar Urals chronology in our paper. We made this preliminary check to satisfy ourselves that we could proceed with our publication with the knowledge that we were not publishing a chronology that was likely to be contradicted when the more recent samples are analysed and published.

    It was evident that much additional work will be necessary to examine and assess their suitability (and potential biases) when processing these data, and we had already demonstrated in our paper the difficulties in using the existing root-collar samples for example. I repeat that some, or many, of these will not be suitable for straightforward RCS processing because they are from prostrate or root-collar samples.

    The dendrochronological data from this recent sampling have not yet been published and it is the prerogative of the Ekaterinburg laboratory to publish the first dendroclimatological analysis of the data that they have spent many years and extensive effort in collecting and processing. We hope to continue our long-standing collaboration with our Russian colleagues in this work.

    Your question and other commentary at your blog may give readers the false impression that we have published using an inadequate dataset. This is ironic given your advocacy for publishing (a biased version of) this chronology when you believed that it would support an elevated Medieval Warm period, advocacy that extended to questioning our integrity for not doing so. It is unfortunate that you fail to acknowledge the careful analysis reported in Briffa et al. (2013) to demonstrate the biases that would arise from a naïve use of the Polar Urals update data. It is also unfortunate that you fail to acknowledge that Briffa et al. (2013) was based on a significantly increased set of tree-ring data for the adjacent Polar Urals and Yamal regions, with overall replication that is much improved over previous work. --Tim Osborn]

    Comment by Steve McIntyre — 26 Jun 2013 @ 2:44 PM

  89. Thanks for the interest in our work and the many interesting follow-up comments, and sorry we’ve not had time to respond to the many comments that came in since last week. We’ll read them all and respond where we can…

    Comment by Tim Osborn — 26 Jun 2013 @ 6:23 PM

  90. Armando @26

    Sorry, missed this one before: “Could you translate the summer temperatures to yearly temperatures?”

    Possibly. During the instrumental period, summer and annual-mean temperatures tend to be correlated, and that relationship could be used to make an estimate of annual temperatures. Probably it would be more uncertain because the summer-annual relationship is not perfect. I would also be concerned that seasonal insolation changes due to orbital forcing would change this relationship on the longer (millennial) timescales.

    Comment by Tim Osborn — 26 Jun 2013 @ 6:37 PM

  91. Lynn Vincentnathan @38

    re. max/min day/night temperatures and trees… differing sensitivity to day/night temperatures is possible. Rob Wilson, for example, has found some cases where tree-ring chronologies are more strongly correlated with day (maximum) temperatures. See:

    Luckman and Wilson (2005) Climate Dynamics

    Wilson and Luckman (2003) Holocene

    Comment by Tim Osborn — 26 Jun 2013 @ 6:51 PM

  92. John Mashey @57

    “I found myself also wishing for the *addition* of a similar-scaled chart showing the actual differences”

    Ok, I’ve added an extra panel to each of those to show the difference:

    Effect of YAD061 on original Yamal chronology

    Effect of YAD061 on new Yamal chronology

    Hope that’s useful.

    Comment by Tim Osborn — 26 Jun 2013 @ 7:22 PM

  93. Roger Tattersall @54

    (1) In the original chronology, removal of YAD061 makes a bigger difference than the removal of any other individual tree core (note these are chronology values, not calibrated reconstruction, so it isn’t 1degC). This is a combination of the high values in YAD061 occurring in the final few years when the sample size is small. In our new chronology, many cores make a bigger difference than YAD061 if removed.

    (2) Plot of trees with peak index values that exceed the peak YAD061 value is now here. Black lines show all tree index series, red lines show those that peak higher than YAD061 peak, purple line is the YAD061 index series.

    Hope you find that useful.

    Regarding CO2 fertilisation… I see further discussion of this in comments below, so I’ll read them before responding in one go.

    Comment by Tim Osborn — 26 Jun 2013 @ 7:41 PM

  94. Tim Osborne @89

    I am not sure but looking at thermometer data from the region , it looks like the annual temperature anomalies are relatively higher than the summer anomalies in the period from 1925 to 1955.

    Comment by Armando — 27 Jun 2013 @ 3:41 AM

  95. Here’s a webinar link to an interesting presentation by a UMinn forest ecologist Dr. Jane Foster on her recent work to “use tree-ring reconstructions of biomass growth to ask (a.) how tree, stand, and weather interact to predict forest biomass growth, and (b.) whether the variance in growth due to climatic variability is as important as other factors.”

    http://necsc.umass.edu/webinars/characterizing-sensitivity-tree-species-and-forest-types-past-weather-variability-using-tre

    This study’s objectives are: “establishing a [long-term] monitoring network in Superior National Forest, gauging vulnerability of forests to climate change, examining forest management and carbon storage, simulating future forest productivity.”

    This presentation was organized by the US Department of Interior’s relatively new Northeast Climate Science Center, whose on-line resources and webinars are well-worth checking out.

    [edit--just stick to the science]

    [Response: Those are closed forest stands in Minnesota, the trees in which have a very low response to climate because they're growing in a highly competitive environment. Not relevant.--Jim]

    Comment by Sloop — 27 Jun 2013 @ 10:09 AM

  96. Tim Osborn @ 91

    Thanks! that is indeed useful (although you must have meant YAD061, not YAD06). No surprise, but I think the visual appearances make the point strongly.

    Comment by John Mashey — 27 Jun 2013 @ 11:38 AM

  97. John Mashey @96:

    Re. YAD06 vs. YAD061. Depends whether you are talking about the tree or the tree core. In this case the tree has only one core so it’s the same thing.

    Comment by Tim Osborn — 28 Jun 2013 @ 9:55 AM

  98. Armando @94:

    Yes, that’s correct. Winter and autumn anomalies were positive in that period — graph here.

    Comment by Tim Osborn — 28 Jun 2013 @ 10:08 AM

  99. Tim Osborn @98

    Thank you for your time and answer.

    Seeing the significant difference between yearly and summer anomalies in the period from 1925 – 1955 what does that mean for the uncertainty in yearly anomalies derived from tree rings?

    Comment by Armando — 28 Jun 2013 @ 1:25 PM

  100. Are there any southern hemisphere tree ring datasets? Assuming uniform CO2 atmospheric mixing, it would be interesting to see trees that have a growing season inverse to the CO2 concentrations in those seasons (i.e. max annual CO2 at max solar exposure).

    [Response: Yes there are some. Remember though, we're only talking about a few ppm of CO2 intra-annual variation--not enough to make a difference.--Jim]

    Comment by Tim Beatty — 28 Jun 2013 @ 11:33 PM

  101. Interesting stuff. Thanks for posting.

    One thing I don’t understand is the 100-year smoothing graphs. I’m not really a math guy, but I would have thought that smoothing for 100 years would mean averaging every point with all years 50 ahead and 50 behind. That would mean (I think!) that the graphs should stop 50 years before the end of your study (i.e. 1963 at the latest). But the graphs go on to today.

    To a naive reader it seems like the only way to have the 100 year moving average for the year 2000 is to have the data for 2050 (which, obviously we don’t have). So I assume you do something different for all the years past 1963. In looking at the graphs, the uptick at the end doesn’t seem to fit very well with those that are fit at 15 years.

    Just curious how that works. Is there a CSV file with the unsmoothed data I could play way? Mostly I’m just curious.

    Thanks!
    tim

    [Response: The raw data are at the links given above, so smooth away as you like. The smooths above are described in the caption as being spline fits, and indeed, there are important 'end-point' effects that can arise (as noted). - gavin]

    Comment by TimG — 29 Jun 2013 @ 8:04 AM

  102. Thanks! Just for my own use, I plotted the data using (I guess) naive smoothing. I also added HadCRUT4 to the graph just for reference (I know that is global temp). If anyone else cares to see (or tinker with) it the same way, I published a Google Spreadsheet:

    https://docs.google.com/spreadsheet/ccc?key=0Ah7u41b9NIu0dEZOSU9ET1E4RjY2QlBkNjRONVFwY3c#gid=2

    You can comment on it or make your own copy.

    –t

    Comment by TimG — 29 Jun 2013 @ 9:48 AM

  103. > 84, 86, 87, Jim and Martin
    I hope y’all pick a forum/website/blog, where you can go on extensively, and do have what may become a fascinating hard argument to pound on this until you both feel you’ve understood each other’s issues. From the peanut gallery, this is –always– the most instructive thing to watch. I’d guess it’d develop and deserve a dedicated topic — somewhere Gavin and others participate.

    It’s as all have said a difficult and developing area of the science. A well moderated thread is always helpful.

    [Response: Keep in mind that I'm only describing the existing problem (because it's gone un-recognized). The realm of solutions to it is another matter, and one that requires serious testing under simulation. That's the problem with all existing methods--they haven't been fully tested that way.--Jim]

    Comment by Hank Roberts — 29 Jun 2013 @ 12:52 PM

  104. Here a write-up on the ideas that I tried to present here, for those interested. I’m sorry if it has a “spherical cow” quality to it ;-)

    Comment by Martin Vermeer — 29 Jun 2013 @ 1:18 PM

  105. In your recent inline comment and in your blog article, you made a number of false or inaccurate characterizations of my view on proxies and Polar Urals in particular.

    You stated that I had “heavily promoted” a Yamal chronology using only modern samples from Khadyta and had both “advocated” and “heavily promoted” a Polar Urals chronology incorporating the polurula measurements. However, you did not provide a quotation or link supporting these claims, which I believe to be untrue. Contrary to your statements, I have not “advocated” or “heavily promoted” the Polar Urals, Khadyta or any other proxies. A far more common complaint of my critics is that I’ve consistently refused to put forward my own alternative reconstruction. In addition, on numerous occasions, I’ve counselled readers to be equally critical of proxies that they “like”. I reject your assertion that I’ve advocated or promoted any tree ring chronology.

    [Response: In this new comment and over at CA you choose to misrepresent my statements. You advocated publishing an 'updated Polar Urals' chronology (that you believed it would support an elevated MWP). Now that we have published an updated chronology for the region, with careful consideration of the source data (and do not find evidence of an elevated MWP), you have changed your position and are now complaining that we are publishing with an inadequate dataset. As to your promotion of the biased versions of Polar Urals and Yamal, I will not search through the hundreds of comments you have made on the subject in multiple venues to find ones that might meet some agreed definition of "promotion". The point about promotion is this: have people reading CA gained the impression that these alternative chronologies were reasonable, perhaps more reasonable than ones that we had published or used because you claimed they were based on newer or less biased data? If so, then you've promoted them. (Because where else did any of this come from?). Given that your advocacy has extended to explicitly claiming that we refused to publish this work in order to hide
    academic fraud, I think that it is a fair comment to make. - Tim Osborn]

    On the other hand, I have frequently pointed out the inconsistency between seemingly like proxies (e.g. Polar Urals, Yamal, the Decline) and observed that reconciliation/explanation of such inconsistencies was, in my opinion, a prerequisite prior to the use of either. For example, in response to criticism from Tom Crowley at Andy Revkin’s here

    Crowley interprets the inconsistency as evidence of past “regional” climate, but offers no support for this interpretation other than the inconsistency itself –- which could equally be due to the “proxies” not being temperature proxies. There are fundamental inconsistencies at the regional level as well, including key locations of California (bristlecones) and Siberia (Yamal) …Without such detailed regional reconciliations, it cannot be concluded that inconsistency is evidence of “regional” climate as opposed to inherent defects in the “proxies” themselves.

    [Response: We have moved towards a regional reconciliation for Yamal/Polar Urals, as reported in our paper. - Tim Osborn]

    In my submission to Muir Russell, I similarly took issue with preferring one series over another without proper reconciliation of different proxies within a region:

    In the absence of any explanation of the substitution, there is reason to be concerned about the reasons for using one series rather than the other.

    [Response: Sure, that is a reasonable point to raise in a discussion of the science. In the context of an inquiry looking for evidence of manipulation or suppression of data, it comes across as an insinuation of misconduct. - Tim Osborn]

    In your inline comment, you complain that I did not sufficiently acknowledge that Briffa et al 2013 had identified an inhomogeneity arising from radial deformation associated with root collars. This is unfair. In the first blog article in my recent series, I explicitly credited your recognition of inhomogeneity arising from radial deformation – an issue that has actually been a longstanding concern at Climate Audit (e.g. here. I also observed that recognition of the importance of such inhomogeneity would logically require reconsideration of strip bark (bristlecone) chronologies, where the radial deformation is far more severe than that shown in the Polar Urals.

    [Response: Unfair? Hmmm... perhaps I missed your acknowledgement that we had demonstrated the flaws in the "Polar Urals update" that you had previously advocated? If so, please point me to it. The use of strip bark is an interesting problem and I'd like to do more work on those chronologies sometime. But for this thread it is a diversion from the significant progress we have made at Yamal/Polar Urals. - Tim Osborn]

    Comment by Steve McIntyre — 30 Jun 2013 @ 1:16 PM

  106. I’ve just had a look at McIntyre’s entry in Wikipedia and it is clearly biased in his favour
    For instance,a summary of the ‘Hockey stick controversy’ concludes with the definitive statement ‘A 2006 report to Congress by a team of statisticians led by Edward Wegman found the criticisms of the hockey stick graph by McIntyre and McKitrick to be “valid and compelling.”‘

    I have no idea how to edit an entry on Wikipedia, so I just thought I would put it out there in case anyone fancies having a go. Cheers.

    Comment by Jonbo — 30 Jun 2013 @ 2:01 PM

  107. Know what you mean, Jonbo. Deep Climate showed just how shoddy McIntyre’s effort (and Wegman’s parroting of same without checking the work) was here:

    Replication and due diligence, Wegman style

    ‘Valid and compelling’ are not the words that apply there, no.

    Comment by Steve Metzler — 30 Jun 2013 @ 3:43 PM

  108. ‘Valid and compelling’ are not the words that apply there, no.

    Ah! They are not the words you would have used. Maybe if you had a former grad student or a political hack to help you with the phrasing, though…

    Or should that be “‘help’ you with the phrasing?”

    Comment by Kevin McKinney — 1 Jul 2013 @ 1:07 PM

  109. I find it amusing that McIntyre feels (#105) that this post is ‘unfair’.

    “Unfair” might be misrepresenting my earlier post (criticizing McIntyre’s never-ending accusations of misconduct and his ultimately futile attempts to use FOIA/EIR to get hold of unpublished work) as a criticism of any specific analysis, despite the opening line being “Steve McIntyre is free to do any analysis he wants on any data he can find” and not mentioning his results at all.

    “Unfair” might be taking a statement I made in that post (on May 11 2012 – note the date), pointing out that Briffa et al’s results would be different from what McIntyre had put up (on May 6 2012) (as the figure below demonstrates), and then using a calculation made on May 15 2012 to claim I was wrong.

    Claiming that my comments were an intemperate response to his results posted 4 days later might, in some circles, also be considered “unfair”.

    But, as my father always told me, no-one ever said the world was fair… ;-)

    Comment by gavin — 2 Jul 2013 @ 6:42 AM

  110. Just now getting to respond to Gavin’s comment regarding the significance of Esper et al 2012 relative to RCS detrending concerns and the reliability of climate estimates from tree rings. Part (a) of Figure 3 is the relevant detail there, and the “very good correspondence” that it shows (r=0.58) between tree-ring widths (TRW, blue lines) and maximum latewood density (MXD, black) is driven primarily by the high-frequency variations, not by the long term trends, which the linear regressions to the two clearly show are different. This is one of the problems with using linear correlation to make assessments of similarity, and it is not at all uncommon to find very high correlations at short time scales, but much poorer ones at longer scales, including in sites showing the so-called “divergence problem”. Since the RCS method was used to detrend both series in their Fig 3a, there is no guarantee that the MXD long term trend is necessarily correct either. However, its estimated trend is supported much more strongly by the other types of truly independent long-term climate information supplied in their Figure S1, including glacial, treeline and data from two climate models (the gray/black lines in the figure are the tree-ring based estimates, green is treeline data, blue is glacial data and red and orange are climate model data; see the paper, linked to above, for the details on all figures). Therefore it is much more likely that the MXD is giving the better trend estimate. My guess for the likely reason for that is that the MXD data contain less of an age/size trend than the TRW data do, and there is therefore less confounding of size and climate, though I don’t know for sure. So, this lack of ability to capture long term trends, using RCS methods on ring widths, is exactly the concern that I have been trying to raise.

    Comment by Jim — 2 Jul 2013 @ 1:45 PM

  111. Gavin: ““Unfair” might be taking a statement I made in that post, pointing out that Briffa et al’s results would be different from what McIntyre had put up and then using a calculation made on May 15 2012 to claim I was wrong.”

    Congratulations for not reaching for the words ‘pea’ and ‘thimble’ ;-)

    Comment by Phil Clarke — 2 Jul 2013 @ 2:33 PM

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