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Tai Chi Temperature Reconstructions

Posted on 6 July 2010 by Peter Hogarth

Guest post by Peter Hogarth

This article was inspired by Rob Honeycutts investigation into temperature reconstructions in Kung Fu Climate and follows on from previous posts on temperature proxies here and here.  One gauntlet often thrown down at the feet of climate skeptics is “ok, if you are claiming the proxy reconstructions are fudged, fiddled, or wrong, then why not create your own?”

Well, the idea of collecting as many proxy temperature records as possible and then generating a global time series might seem daunting, but, as a novice in the gentle Martial Art of commenting on and hopefully explaining the science of climate change, I thought I’d follow this process of temperature reconstruction through a little way, break it down, and see what trouble it gets me into.  I fear that both more specialised scientists and hardened skeptics will find much to criticize in the following simplistic approach, but from the comments on Kung fu Climate, I hope some readers who fit into neither category will find it illustrative and interesting.

There are all sorts of other common questions (some addressed briefly in the links above), for example about tree ring data, and about the Medieval Warm Period or “why can’t the proxy records be updated so as to compare with instrumental records?”  Can we touch on these issues? Maybe a little…

First, which proxy data to use?  I guess I need a few records, from as global a geographic area as possible, not so few as to be accused of cherry picking, and not so many that I have to work too hard…  Also I didn’t want to pick a set of records where the final output reconstruction was already generated, as I could be accused of working towards a pre-determined outcome…In addition, I wanted as many records as possible which included very recent data, so that some comparison to the instrumental record could be made.  What to do?

Fortunately, there is a recent peer reviewed paper that lists a manageable number of proxy records, and doesn’t try to generate a composite global record from them, Ljungqvist 2009 “Temperature proxy records covering the last two millennia: a tabular and visual overview”. This describes 71 independent proxy records from both Northern and Southern hemispheres, covering the past two thousand years, a fair proportion of which run up to year 2000, all of which have appeared in peer reviewed papers, and 68 of which are publicly accessible.

First we have to download the data.  This is available here from the excellent folks at the NOAA paleo division.  This can be loaded as a standard spreadsheet, but remember to remove any “missing data” (represented by 99.999) afterwards.   Note that 50 of the records are proxy “temperatures” in degrees Celcius, and 18 records are Z-scores or sigma values (number of standard deviations from mean). The records are from a wide range of different sources, including ice cores, tree rings, fossil pollen, seafloor sediments and many others.

Next, we should have a quick look at the data. Ljungqvist charts each time series individually, and it can be seen that many of the charts provide ample fodder for those who wish to single out an individual proxy record which shows a declining or indifferent long term temperature trend.

A zoomed in small selection of individual proxy records showing the high variance in many individual time series (note the wide temperature scale).

The approach of taking one or a few individual time series in climate data (such as individual tide station records) is often used (innocently or otherwise) to question published “global” trends. A cursory glance at these charts has justified a few “skeptical” commentators citing this paper on more than one blog site. My initial thoughts on looking at these charts were simply that this would be, well,  interesting. 

We must also check the raw data, as at least one of the time series contains an obvious error which is not reflected in the charts (clue, record 32, around year 1320).  This will be corrected soon.  For now we can rectify this by simply removing the few years of erroneous data in this series.

Now, some of these records are absolute temperature and some are sigma values.  We will put aside the Z-score values for now and look at the 50 temperature proxy records. We have to get them all referenced to the same baseline before attempting to combine them.  To do this, we can simply subtract the mean of a proxy temperature time series from each value in this series to end up with an “anomaly”, showing variations from the mean.  The problem here is that some records are longer than others, so one approach to avoid potential steps in the combined data is to use the same range of dates, using a wide range which most records have in common, to generate our mean values for each time series.  This also works for anomaly data sets in order to normalize them to our selected date range.  Here the range between year 100 and 1950 was selected, rather arbitrarily, as representing the bulk of the data.

Now we have a set of temperature anomaly data with a common baseline temperature.  How do we combine them?  At this stage we should look at missing data, interpolation within series, latitudinal zoning effects, relative land/ocean area in each hemisphere and geographical coverage, we should then grid the data so that higher concentrations of data points (for example from Northern Europe) do not unduly affect the global average, and bias our result towards one region or hemisphere, and also try to estimate the relative quality of each data set. This is problematic but is necessary for a good formal analysis.  The intention here is not to provide a comprehensive statistical treatment or publish a paper, but to present an accessible approach in order to gain insight into what the data might tell us in general terms.

Therefore I will stop short and suggest a quick and dirty “first look” by simply globally averaging the 50 temperature results.  I must emphasise that this does not result in a true gridded picture.  However averaging is a well known technique which can be used to extract correlated weak signals from uncorrelated “noise”.  This simple process will extract any underlying climate trend from the individual time series where natural short term and regional variations or measurement errors can cause high amplitude short term variations, and should reveal something like a general temperature record. Due to the relatively large number of individual records used here, we might expect that this should be similar to results obtained from a more comprehensive and detailed analysis. However we must accept that biases caused by the limited geographic sampling, unequal spatial distribution, or over-representation of Northern Hemisphere data sets will be present in this approach.

Given the caveats, is a result of any merit? as a way of gaining insight, yes.  If we accept that any average is only a useful “indicator” of global thermal energy, we can cautiously proceed, and as we add the individual records to our average, one after the other, we see evidence that some data series are not as high “quality” as others, but we add them anyway, good, bad, or ugly.  Nevertheless, the noise and spikiness gradually reduces and a picture starts to emerge.

Average of 50 temperature proxy records, with one standard deviation range shown

Now, the fact that this resembles all of the other recent published reconstructions may (or may not) be surprising, given the unpromising starting point and the significant limitations of this approach. The Medieval Warm Period, Little Ice Age, and rapid 20th century warming are all evident. Remember for a second that these are proxy records which are showing accelerated recent warming. We have not hidden any declines or spliced in any instrumental data.  We can remove data sets at will, and see what changes.  If the number of removed series is small, and are not “cherry picked” we can see that the effect on the final result is small and that many of the features are robust.  We can also look at correlating the dips with known historical events such as severe volcanic eruptions or droughts.  This is beyond the scope of this article, but this topic is covered elsewhere.

There are many more proxy records in the public domain, which offer much better coverage allowing the data to be correctly gridded to reasonable resolution without too much interpolation.  Adding more records to our crude average doesn’t change things dramatically for the Northern Hemisphere, but would allow higher confidence in the result.

Average of 50 temperature proxies, annual values and ten year average with error bars omitted for clarity.

Now, to complete this illustration let us zoom in and look at the instrumental period. Not all of the proxy time series extend to 2000, although 35 extend to 1980.  We would expect from our previous discussion that the variance would increase if less samples are available as we get closer to the year 2000, and this is the case.  26 of our proxy records cover the period up to 1995, 10 of which are sigma values.  Only 9 records have values for year 2000, and 4 of these are sigma values.  Can we make use of these sigma values to improve things?  We could easily convert all of our records into sigma values and then compare them, but many readers will be more comfortable with temperature values.  We  could perhaps track down the original data, but in the spirit of our quick and dirty approach we could cheat a little and re-scale the sigma values given knowledge (or an estimate) of the mean and standard deviation…this isn’t clever (I do appreciate the scaling issues) but for now will give an indication of whether adding these extra samples is likely to change the shape of the curve.  The original temperature derived curve from 50 proxies and the new curve derived from information in all 68 series are both shown below.  There are some differences as we might expect, but the general shapes are consistent.

The versions of the zoomed proxy record again look vaguely familiar, they show a general accelerating temperature rise over 150 years, with a mid 20th century multi-decadal “lump” followed by a brief decline, then a rapid rise in the late 20th Century.

Proxy record 1850 to 2000. As not all records extend to 2000, the “noise” increases towards this date. If we use all of the available information we can improve matters, but the general shape and trends remain similar

We can compare this reconstruction with global temperature anomalies based on the instrumental records, for example HadCRUT3.  In the instrumental record we have full information up to 2010, so our ten year average can include year 2000 showing the continuing measured rise.   Given the standard deviation and tapering number of samples in our very preliminary reconstruction it appears to be reasonably representative and is surprisingly robust in terms of lack of dependence on any individual proxy series.

Global Instrumental temperature record, HadCRUT3, 1850 to 2000, annual average values and longer term average shown.

So, was the medieval warm period warm? Yes, the name is a clue.  Was it warmer than the present?  Probably not, especially given the last decade (after 2000) was globally the warmest in the instrumental period, but it was close in the higher latitude Northern Hemisphere.

Does the proxy record show natural variation? Yes.  There is much debate as to why the Medieval Warm Period was warm, and over what geographical extent, but there is evidence (for example in all of the high resolution Greenland Ice core data) of a longer term general slow long term declining trend in Greenland, Arctic (Kaufman 2009), and probably Northern Hemisphere temperature believed to be due to orbital/insolation changes over the past few thousand years.  This trend has abruptly reversed in the 20th century, and this is consistent with evidence of warming trends from global proxies such as increasing sea level rise and increasing global loss of ice mass.

Does the proxy record in any way validate the instrumental record, given some skepticism about corrections to historical data?  To some degree, but I would argue that it is more the other way around, and it is the instrumental record which should be taken as the baseline, corrections and all.  The proxy records are simply our best evidence based tool to extend our knowledge back in time beyond the reach of even our oldest instrumental records such as in Bohm 2010. Taken as a whole the picture that the instrumental records and proxy records present is consistent (yes, even including recent work on tree rings, Buntgen 2008)

For more comprehensive analyses, I will hand over to the experts, and point to the vast amounts of other data and published work available, some of which Rob cited.  The more adventurous may want to examine the 92 proxies and other proxy studies that NOAA have available here, or look at the enormous amounts of proxy data (more than 1000 proxy sets), the processing methods and source code of Mann 2009, or see Frank 2010, which is also based on a huge ensemble of proxy sources. The weight of evidence contained in these collected papers is considerable and the knowledge base expands year on year.  Simply put, they represent the best and most detailed scientific information that we currently have about variations in temperature, before we started actually measuring it.

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Comments 51 to 73 out of 73:

  1. scaddenp at 07:08 AM, only a quick response re "to pick trees where circumstances dictate that the growth rings will determined by primarily by temperature." If that is done, and all growth factors accounted for, then there shouldn't be such a thing as a "divergence problem" should there?
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  2. Johnd. I agree. I'm all for understanding the divergence problem and what it might tell us about better selection for temperature proxies. However, whatever the answer is, the agreement of existing ring proxies with other proxies suggests that it is not going have effect on our understanding of past temperatures. Perhaps we will better proxies in the future and be able to refine existing proxies as a result of this understanding but I doubt very much if you will get a different paleoclimate. Every proxy has limitations and problems, but the concordance of them is a cause for believing that the paleoclimate record is reasonably well defined. Also, in the sense that the point of paleoclimate record is to validate climate models, having a record that has more certainties than our proxies for forcings is of limited value. The important result from paleoclimate work is that it does not invalid our current understanding of how climate works.
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  3. johnd at 04:41 AM on 9 July, 2010 Your implication that I am unfamiliar with basics of plant biology, or that the researchers I cited do not understand plant growth, or even that I might not read my own references is presumptuous. Science please. I read the section of the book you cited and there is nothing new here, but then it is 24 years old. You are correct to say SO2 is an important factor. Many will remember much concern about SO2 when “acid rain” and tree die-back in Europe was becoming a major climate concern in the late 1970s and 1980s. EU emission controls have now dramatically reduced atmospheric Sulphur levels (legislatively driven change is possible). However I disagree with your logic and dismissive conclusions. You claim to have read Buntgen 2008, but you can not have read very carefully. You state "all it basically confirms is that there is a divergence problem by examining data" In fact what it says is "Indication for an unusual late 20th century DP (Divergence Problem) is thus not found" and it repeats this conclusion several times, it is the main point of the paper, and you missed it? You claim Buntgen does not account for SO2. You must have missed his reference to “effects of airborne pollution” as one of the possible causes of DP and the references he cites which specifically look at SO2. I have read these also. You also seem to claim that SO2 is not factored into tree ring studies. I (or anyone) can easily falsify this. The negative effects of SO2 are well known and well documented and have been studied for more than two decades. In some heavily polluted regions the effects of SO2 on trees were severe, and caused reduced growth and tree ring width for around a decade after the 1970s, or were even a factor in mortality. Tree ring researchers are of course very aware of this. For example see Elling 2008 which shows highly significant effects of SO2 on tree growth in Southern Germany, Rinne 2010 refers to the effect of SO2 on growth, and describes the reduced growth episode in late 20th Century corresponding to pollution. Also Zhu 2009 which looks at the strong correlation of temperature and tree ring width (in North East China), but mentions that “a study based on tree-ring width in central Japan (Yonenobu and Eckstein, 2006) did not track such a warming trend, probably due to the consequence of anthropogenic SO2 emissions”. Also Rybnicek 2009 which states “The regional standard tree-ring chronology shows a decrease in the radial increments starting at the beginning of the 1970s and ending at the end of the 1980s”. “The main cause of this significant decrease is most probably the heavy air pollution load, mainly SO2 pollutants in the 1970s” “with the current air pollution load the climatic conditions are the factor determining the resulting effect of the synergic influence of the stressors on the stands” (ie recent changes are now down to temperature and precipitation). We should remember that anthropogenic SO2 pollution is wind transported, regional, and relatively short lived. We should also remember that high levels of SO2 decrease tree ring growth. This is why many studies suspect SO2 of being a possible cause of the Divergence Problem. In less polluted areas where Sulphur content is low Ulrich 2009, the dominant factors in tree ring growth are temperature and precipitation, whether in Europe Koprowski 2009 or elsewhere. For many species we see high correlation between increasing temperature and wider tree ring width (see the references). This is why tree rings are such a good proxy and this is why the DP mattered, and why recent work (Buntgen etc) is important. To round this off, are there are any general correlations between long term trends of global SO2 emission levels Smith 2010 and the growth trends in the tree ring studies? No, we see almost the opposite. I am therefore worried that you are so dismissive of this work on tree rings, and draw conclusions (based on limited reading) which appears pre-judged. I suggest you start with an introduction and please read the references supplied.
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  4. Peter Hogarth at 22:01 PM on 9 July, 2010, I think you missed the overall findings of Buntgen 2008 by focusing on certain aspects only. First the study acknowledges that the DP exists right at the beginning:- "Abstract Evidence for reduced sensitivity of tree growth to temperature has been reported from multiple forests along the high northern latitudes. This alleged circumpolar phenomenon described the apparent inability of temperature-sensitive tree-ring width and density chronologies to parallel increasing instrumental temperature measurements since the mid-20th century." Secondly they acknowledged the concerns such evidence brings:- "If DP is widespread and the result of climatic forcing, the overall reliability of tree-ring-based temperature reconstructions should be questioned." It appears to me that what the study set out to achieve was to determine whether the DP is climate related or not. My understanding of the results is that from the data they analysed, they found that there was no DP evident in the trees they studied. Thus my interpretation of their conclusions is not that the DP is non-existent, but that it most likely is not climate related. Whether or not it is widespread cannot be determined simply by what has been the case at one study site, but it certainly has been found at a number of sites as mentioned in the abstract, thus I believe it is real. However, it appears that the Buntgen 2008 study didn't consider one possibility, that being that the consistent growth they found may be the nett result of two opposing factors, namely CO2 and SO2. It didn't even mention what the growth response to rising CO2 levels was to be expected from the trees under study. These are matters that I believe have to be accounted for before any such study can be seen as complete. Thus I don't believe that Buntgen 2008 has really advanced the understanding of the DP at all, hence my comment of it being of limited use. Therefore what causes the DP? Something obviously does, and apparently that something still hasn't been identified. I suggested SO2. You appear to both acknowledge the effects of SO2 and dismiss it because it is short lived. What you are missing is that once the SO2 has been absorbed by the vegetation, the sulphur so released is deposited to the soil below where it remains. Where "acid rain" occurred in farming areas, the sulphur was stripped from the soil along with the other nutrients that were taken up by the plants and animals that were being farmed and initially the extra sulphur was actually beneficial. When SO2 emissions were reduced, farmers were forced to add additional sulphur to their land in order to maintain production. Such stripping of sulphur from the forests does not occur unless logging takes place, and thus if the sulphur has built up to the extent it has effected tree growth, it will remain there for an extended time. I think any study that tries to tie tree growth to any climatic indicator must firstly reference any research that examines how the trees under study respond to changing CO2 levels, especially to levels less than the current ambient where historical growth patterns are being analysed, and secondly other relevant "pollutants" both from anthropogenic and natural sources especially where there may be an accumulation over time.
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  5. johnd at 03:43 AM on 10 July, 2010 John, I think we are at cross purposes on Divergance Problem. I have not missed the purpose of this paper or the others, I'm fairly familiar with them. I have not denied the DP exists, just tried to point out that it is an an effect most likely unrelated to temperature, ie the validity of tree rings as temperature proxies, away from significant SO2 influence and where other factors such as moisture are accounted for, is solid, as in your comment 51, as in Buntgen. Are we agreeing on this? The correlation of growth with instrumental temperature records for the Buntgen and other studies I referenced in my first comment is compelling and credible (or I think so). The correlation with CO2 less so, though again this is a recognised factor, and I have papers on this also. Have a look at the ones supplied so far, they contain a lot of pertinent information. Your suggestion of competing SO2 and CO2 is opinion. I don't dismiss it, but without evidence, I take it as such. The seasonal and year to year growth patterns and seasonal temperature are relevant evidence here, as correlation is seen at this level. In terms of Sulphur absorption you should read the references I supplied. The tree ring growth, measured SO2 atmospheric levels, and sulphur levels in the woody growth itself are direct evidence concerning your "extended residence time" suggestion. SO2 is one potential explanation for DP, based on the data available, the references I cited cover this, and Buntgen does (briefly). One other specific factor mentioned is decreasing moisture (climatic). It may well be combinations of several factors which are challenging to disentangle, but the experts would not "dismiss" any of them, and I don't either.
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  6. Peter Hogarth at 05:45 AM, tree growth, indeed any plant growth, is subject to a number of different conditions all being in place, the final result depending on how well balanced the combination is at any given period of time. Temperature is but one of those conditions. I think that once all the other factors have been adequately accounted for, then what is left over could reasonably be attributed to temperature. However the understanding of all the other factors is far from complete, the science is not settled, the understanding for some of the factors it is almost certainly less than adequate. It is difficult enough in controlled circumstances such as occurs in agriculture or in plantation forestry where soil and tissue testing and ongoing monitoring of local conditions is possible, let alone in some remote natural environment, even in real time. Trying then to establish how that combination of factors all came together at some distant point in time requires a lot more information then merely the width of the growth rings, information, some of which I am not convinced is even available. The fertilisation effects of CO2 have been known for over a century, trials in more recent times show that the effect is not uniform across all species, and is subject to other local contributing factors. Thus this contributing, and perhaps significant factor can only be adequately allowed for once it has been studied on the trees that are being used to correlate growth with temperature. This is vitally important because both CO2 and temperature are claimed to be directly related and thus it is necessary to separate and allocate each of the inputs. Much the same applies to all other inputs be they positive or negative factors. One additional factor that I have become aware during my reading on the subject of tree ring growth temperature relationship, is that the selection of trees to measure is far from random. It relies not only the selection of species, but the selection of individual trees whose growth is considered to faithfully represent a robust relationship between growth and temperature. This is referred to in Buntgen 2008. "Tree-ring width chronologies from 40 larch and 24 spruce sites were selected based on their correlation with early (1864–1933) instrumental temperatures to assess their ability of tracking recent (1934–2003) temperature variations." That may inspire confidence in some, but does the opposite for me. To sum up, I have always understood that temperature is an influence on all forms of plant, and animal, growth. However I have also been equally aware of all the other essential factors, thus once temperature reconstructions using tree growth rings started to be given prominence, I began having reservations as there didn't appear to be adequate understanding of the all the other factors. The emergence of the divergence problem was, and still is justification for such reservations. If it cannot be accounted for during recent times with all the access to high quality data and the ability to study the contributing factors in real time, what faith can one have that the same factors have been allowed for in the historical reconstructions. It is our individual acceptance of that which I think puts us at cross purposes, if we are that is, on the matter of the divergence problem.
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  7. johnd at 10:01 AM on 10 July, 2010 John, you may be confusing selection of sites with selection of individual trees when you state: “It relies not only the selection of species, but the selection of individual trees whose growth is considered to faithfully represent a robust relationship between growth and temperature” and you then quote a section from the abstract which refers to selecting numbers of sites? Reading past the abstract, “A dataset of 3069 larch and 1600 spruce TRW series from 124 sites (62 per species) distributed across the European Alps was compiled” We then see that 64 sites are selected from the network of 124 sites, but this is spread over a wide geographical area and each site may contain hundreds of individual trees. The methodology for site selection is discussed. I would hope this increases your confidence? I suggest you will find the later references from Esper and Buntgen very interesting, it is not that the DP has been disproven or dismissed, just found to be more prevalent at sites of high latitude or elevation (for example), and not as widespread as previously assumed. From Buntgen 2009 “Therefore, the DP should not be thought of as an endemic large-scale phenomenon with one overriding cause, but rather a local- to regional-scale phenomenon of tree-growth responses to changing environmental factors including multiple sources and species-specific modification”
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  8. Peter Hogarth at 08:21 AM, I think it is very clear that the term "site" can only refer to a collection of individual trees, trees which in this case had been predetermined as being able to reflect temperature changes. As for the number of trees per site, the average number of larch trees in a site appears to be 50, and the average number of spruce trees appears to be 26. That is not many trees nor likely a very big area. In fact my back yard would have more fully grown trees than the average spruce site and possibly the average larch site as well. However given that only about half the available sites were selected seems to indicate that there was only an 50/50 chance that the trees would adequately reflect the correlation required, so that opens up the possibility that something other than the trees has a deciding influence, perhaps something related to the site conditions rather than the tree species itself, perhaps even the divergence problem was evident at those sites not selected. Can Buntgen legitimately claim a greater than 50% confidence, a toss of a coin, in their findings based on their selection process? They should at least explain why the high rejection rate. Another factor that reduces the number of effective trees under study is their age. Using larch as an example, the trees ranged in age from 65 to 447 years, the average 210 years. Given the total period of the study was 1864-2003, 139 years, a certain proportion could only be tracked for a reduced portion of the study period. However that is diverging away from why my confidence was perhaps not as inspired as yours. It seems to me that given one set of data covered the period 1864–1933 and the other 1934–2003, it should be that the latest set of data should be what is used to validate the earlier set, not the other way around as was done in the Buntgen 2008 study.
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  9. johnd at 09:39 AM on 11 July, 2010 That’s some back yard John! How many trees over what sort of area would you find to be a convincing sample? I think these researchers have used sufficient numbers. Their methodology is fully explained and makes sense. Why would they use later data to validate anything when they are specifically looking for DP or late 20th century effects in the later set? surely they would use earlier (presumably less affected) data as reference?
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  10. Peter Hogarth at 10:06 AM, it's not actual numbers that is important within itself, but whether or not those numbers are representative of the whole environment under study. Hovering around 50% selection as a start is hardly representative, especially when further attrition can be found as the processing continues. As the quality and quantity of data collection advances, any modelling for reconstructions of earlier periods must be validated against the most recent data. Having done that, the earlier reconstruction data cannot then be used as validation of the later data. It's the cat chasing it's own tail.
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  11. johnd at 10:22 AM on 11 July, 2010 No, I think you have misunderstood the methodology. We do not have controlled experimental conditions. The site selection process involves looking at older tree ring data to see if the "site" is likely to give results which are affected by temperature, rather than other factors (such as drought), by comparing pre 1934 tree rings data with pre 1934 historical climate data. If it is a "good" site, on this basis, then the later tree ring data is examined to assess more recent effects of temperature (other factors notwithstanding). No assumptions are made to pre-select on the basis of correlations in later data. This is important. The authors admit that this cannot account for changes in other factors in the meanwhile, but if the correlation with instrumental temperature continues in later data, then confidence increases. I think you see the logic of this?
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  12. Peter Hogarth at 02:38 AM, whilst temperature is one of the many factors that influences plant growth, and not the dominant one, it's increasingly seems to me that the selection of sites, or groups of trees, is done by finding trees that by COINCIDENCE rather than by science, seemingly track temperature sufficiently well enough for them to be considered useful indicators. I say by coincidence, because if all the other factors that are perhaps even more important in influencing tree growth were sufficiently well understood to be quantified, then all trees should be able to be used as proxy indicators. But more than that, if those factors were able to be quantified, the divergence problem would not be, well, a problem. The problem is not that the growth of trees that had been previously selected as temperature indicators began to diverge, the problem is that the reasons are not understood, and this is happening at a time when the resources and knowledge is available that should be able to identify such reasons. If those reasons are not understood well enough to be able to account for present day situations, then how can anyone be confident enough to claim that those same, still unknown factors, have not been present and an influence, either positive or negative, at other previous times. I would hope that the selection of "good" sites involved more than someone with a wooden ruler in one hand and a temperature chart in the other, but that is what it seems to come down to. The one thing that is always in the back of my mind whenever tree growth ring data is used is that what has been done to ensure that the tree growth is not tracking CO2 levels rather than temperature. With the Buntgen 2008 study, about half of the available sites were selected because of their supposed historic correlation. But those sites used in other studies where the divergence problem is now evident also were supposed to have a historic correlation, so obviously some things change over time. But that doesn't mean that they are only changing now, and haven't done so in the past. So what is there to say that perhaps the basic assumptions used to model tree growth against temperature are wrong, and that instead, the other half of the trees that were rejected are better indicators once everything has been allowed for. If we were to work backwards and select trees that today show good growth correlation with temperature, then those trees that are now showing divergence would be rejected, or else any modelling done that correlated their present day growth with temperatures would when applied to historic growth rings, present a different result. The other thought that is also always in the back of my mind is how well are the actual site conditions documented over time. Temperatures can vary widely even between close localities, so correlation should be to and with site temperatures, not regional or global. Precipitation patterns can vary widely over just a few kilometres. Given that some of the locations where the samples have been taken seem to be remote, perhaps even these most basic of all factors have not been accurately accounted for.
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  13. johnd at 04:43 AM on 12 July, 2010 John, I agree it is a complex subject. However much of what you say appears to be conjecture and not directly referenced to the research I have seen. I suggest that if you look at the recent references supplied, particularly the ones from the last two years, there is much to learn. There has been a lot of focus on DP and some of the correlation work with temperature is highly convincing (I previously mentioned the seasonal growth and year on year growth correlating with local temperature variations) and Buntgen 2008 for example shows temperature monitoring sites on tha map above. I suspect this would be inconsistent with CO2 as main factor.
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  14. Peter Hogarth at 07:20 AM, Peter, concentrating for a moment on the location of the instrumentation sites in relation to the tree locations. The instrumentation sites seem well dispersed, however quite some distance from most tree locations especially those at the higher elevations where differences could be significant. I want to mention an example of a study that was related to me by a friend who actually peer reviewed some research that has some relevance I feel, at least philosophically. The research was undertaken in my region but this example could be relevant wherever the natural environment is being measured. The study was comparing the productivity of a pasture based enterprise in relation to climate factors, in particular precipitation. The study was duly completed and sent with it's very positive results for peer review. Fortunately one of the peer reviewers was considered one of the most knowledgeable scientists in that particular field of research, certainly he knew far more than the research scientist who conducted the study. However, more importantly, he also had close personal knowledge of the location of the research site and the first thing he picked up on was the location of the site in relation to the official weather station that provided the required data. The weather station was reasonably close, about 15 km, however the reviewer happened to know that that particular weather station was located in a rain shadow, and any precipitation data collected from there was not representative of the wider area, especially the location of the research site. Thus the conclusions reached by the researcher were completely wrong. I doubt than anyone called upon to peer review the paper who did not have the same personal knowledge as my friend would have understood the significance of those 15 km, certainly the researcher himself who conducted the study didn't. I keep this example in mind whenever I am trying to understand what a peer reviewed study has found. I try and see firstly if any climate data used is from the actual location of the study, and thus can be accepted as relevant, or is it from some distant point, or some general data that has been assumed to be relevant. The second point is whether it is likely or not that those unknown persons called upon to conduct a peer review would have an equal or better understanding of the subject, and the location than those conducting the research. This of course remains an unknown, but in some fields one can accept that there would be better qualified persons who are perhaps more knowledgeable than the researchers, however, when new concepts are being presented, I am often left wondering just how many peer reviewers would be capable of grasping the essence of such new concepts, especially if it goes against the established understanding. We can only but wonder, but ultimately time may answer one way or another as it has done so for those renowned scholars in the past who had trouble getting others to see what appeared so clear to them.
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  15. Peter Hogarth at 07:20 AM, following up on your dismissal of CO2 being a factor in increased growth, these two studies are interesting and relevant. Larch Budmoth Outbreaks in the European Alps shows how rising CO2 may be related to increased growth due to the lack of periodic growth depressions that characterise larch growth. Changes in needle quality and larch bud moth performance in response to CO2 enrichment and defoliation of treeline larches studies the effects in CO2 enrichment trials.
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  16. johnd at 06:09 AM on 13 July, 2010 John, thanks, but you misquote me. I did not dismiss CO2, nor would I. I was referring to the high correlation with temperature and lower correlation with CO2 found by many workers, and I justified this. The author of your first reference (I read this last year) should know as this is Buntgen !!!! Esper is also a co-author! The second reference doesn't link, but don't think I've read this one. I'll see what I can dig up on CO2 and growth.
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  17. Peter Hogarth, I have a question for your original post. The approach you describe for averaging the proxies seems in my view to be very close to the Composite-Plus-Scale (CPS) method. Especially as it is applied in Ljungqvist, 2010. What are your thoughts on this?
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  18. To elaborate on myself in #67: Peter Hogarth's approach is mostly similar to Ljungqvist 2010 except that Ljungqvist matches the variance of his composite series to the variance of the instrumental record. But there is no gridding or area weighting, all proxies contribute with equal weight. I have implented Ljungqvist approach and made a reconstruction using all proxies from Ljungqvist 2009 - note since the original post was written a few more have been added, the total number is now 71. The resulting graph is below, plotted together with Ljungqvist 2010. This graph allows one to compare the Tai Chi approach of the original post with the result of Ljungqvist, 2010. Disclaimer: I have also used my implementation of Ljungqvist 2010 approach on the original data from that article (data kindly provided by the author). I don't get a perfect match so there must be some small differences in the methods of me and Ljungqvist.
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  19. SRJ at 22:24 PM on 14 October, 2010 Thanks for this work. On first read through the Ljungqvist 2010 paper I would have to agree with you, but I would have to spend some time checking. The 2010 work is decidedly Northern Hemisphere above 30N whereas the Ljungqvist 2009 data has a fair proportion of tropical and Southern Hemisphere data also. I suspect that gridding will make some difference, but my original post wasn't meant to be a reconstruction that would withstand too much scrutiny! Your chart above is very interesting, and in my view further supports the idea of enhanced variability of the higher latitude Northern Hemisphere temperature anomalies, compared with the global average. There is some evidence of this high relative variability in paleo data going back through the ice ages.
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  20. #69 Peter Hogarth at 08:01 AM on 19 October, 2010 Thanks for the comments- I am fully aware that your originial post isn't supposed to withstand much scrutiny. Neither are my reconstruction here. As a side note, I was able to replicate your plots to a satisfying eyeball degree. I wanted to highlight that Ljungqvist 2010 is using a much more simple approach than e.g. Mann 2009. I would like to try and redo my global reconstruction using some kind of gridding or area weighting, but to do that I need some tips on how-to-do. Even better some Matlab code. By the way, how did you use those proxies given as z-scores? I just run them through the same averaging process as the temp proxies. For baseline I use the years, 1000-1900, as Ljungqvist 2010.
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  21. Overall: a tentative 1-degree shift over a 150-year period is hardly what any educated person might call "conclusive." Likewise, simply averaging various claimed indicators is no "magic carpet" to the truth, without weighting each according to its respective accuracy. Finally, various data must be discounted due to spoliation-- particularly ice-core samples, which are completely worthless due to polar-ice temperatures ALWAYS rising above the -70C maximum required for validity. Overall, this article simply assumes far too much-- and discounts far too *little*-- to be considered reliable in even its conservative conclusion.
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    Moderator Response: You have posted the same claim about ice cores in at least five different threads on this site. Please do not spread discussions of a single, narrow topic across many different threads. Another commenter (KR) has already responded to your claims in the thread where you first posted this material ((What does past climate change tell us about global warming?), so it would be a good idea to respond there. Thank you.
  22. "any educated person " - how about cutting the rhetoric and getting educated? Start with IPCC WG1, then come back here. "Finally, various data must be discounted due to spoliation-- particularly ice-core samples, which are completely worthless due to polar-ice temperatures ALWAYS rising above the -70C maximum required for validity." Care to give us a cite for this amazing opinion?
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  23. I derived this myself from the ljungqvist2009 data file. I used columns 64 to 71, 8 series. Unfortunately the southern hemisphere isn't represented as well as the north, but can't be ignored it is half of the globe. For each the sigma is calculated and the average of all is taken. Columns names are: 64. Lake Pallcacocha, Ecuador 65. W. Argentina 66. Subtropical Atlantic off W. Africa 67. Makapansgat Valley, S. Africa 68. SE. South Atlantic 69. Mt. Read, W. Tasmania 70. Law Dome, E. Antarctica 71. Dome C, E. Antarctica
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