Exactly who was emailing who in Climategate

This social graph of CRU emails shows how miniscule is this IPCC “power group” if you ponder how many active climatologists there must be globally. Sent in by The Iconoclast. The software counts the To and CC lines but does not count the emedded emails, many of which are duplicates. The 300kb graphic is over 3000 pixels wide, best downloaded – it prints OK in A4 but A3 would be better.

19 comments to Exactly who was emailing who in Climategate

  • Ben Santer’s name seems to be missing, yet he figured prominently in the emails.

  • Chris

    Ben Santer is right there in the centre towards the left.

  • kandler

    So, scientists working in a common field are have a need to communicate with each other? Who knew?

    These emails are the ‘selected highlights’ of twelve years of communication sourced from one research unit and focused on a few juicy events. Bear that in mind. Every chapter of AR4 would show similar clusters of communication between authors and lead authors. Or indeed any report.

    Good lord,what would the social graph of your blog roll tell us?

  • kandler – I don’t think you’ve read the emails – they show a clear intererence in the peer review process, and the politicisation of the IPCC:

    A campaign against the Geophysical Research Letters editor (Prof Saiers) who allowed publication of the critique of the infamous ‘Hockey Stick’ graph resulted in his removal. A leaked email states that “the leak has been plugged.” The same fate befell Hans Von Storch at the journal Climate Research. More recently, an email from Prof Phil Jones reveals his influence in choosing 2 referees to review a critical comment of Ben Santer’s 2008 paper:

    Phil Jones (29/1/2009) “With free wifi in my room, I’ve just seen that M+M have submitted a paper to IJC on your H2 statistic – using more years, up to 2007. They have also found your PCMDI data – laughing at the directory name – FOIA?….Anyway you’ll likely get this for review, or poor Francis will. Best if both Francis and Myles did this. If I get an email from Glenn I’ll suggest this.”

    Ben Santer replied: “It would be great if Francis and Myles got McIntyre’s paper for review.”

    Needless to say, the paper hasn’t been published, despite the fact that Santer would have had the right to reply.

    Email discussions between scientists involved in the IPCC reports of 2001 and 2007 are also very revealing:

    Keith Briffa (22/9/1999) “I know there is pressure to present a nice tidy story as regards ‘apparent unprecedented warming in a thousand years or more in the proxy data’ but in reality the situation is not quite so simple. We don’t have a lot of proxies that come right up to date and those that do (at least a significant number of tree proxies) some unexpected changes in response that do not match the recent warming. I do not think it wise that this issue be ignored in the chapter. For the record, I do believe that the proxy data do show unusually warm conditions in recent decades. I am not sure that this unusual warming is so clear in the summer responsive data. I believe that the recent warmth was probably matched about 1000 years ago. I do not believe that global mean annual temperatures have simply cooled progressively over thousands of years as Mike appears to and I contend that that there is strong evidence for major changes in climate over the Holocene (not Milankovich cycles) that require explanation and that could represent part of the current or future background variability of our climate.”

    Giorgio Filippo (University of Trieste) (11/9/2000) “Essentially, I feel that at this point there are very little rules and almost anything goes. I think this will set a dangerous precedent which might mine the IPCC credibility, and I am a bit uncomfortable that now nearly everybody seems to think that it is just ok to do this.”

    Phil Jones (8/7/2004): “The other paper by MM is just garbage – as you knew. De Freitas again. Pielke is also losing all credibility as well by replying to the mad Finn as well – frequently as I see it. I can’t see either of these papers being in the next IPCC report. Kevin and I will keep them out somehow – even if we have to redefine what the peer-review literature is!”

    Keith Briffa (29/4/2007): “I tried hard to balance the needs of the science and the IPCC, which were not always the same.”

  • […] Warwick Hughes Blog: ‘Exactly who was emailing who in Climategate’ […]

  • Richard S Courtney

    Friends:

    Willis Essenbach has uncovered and circulated an email I sent 6 years ago but I had forgotten. It is directly relevant to the actions of CRU staff being discussed here, so I copy it here. Please note its original circulation list and contents, especially its final sentence.

    Richard

    From: RichardSCourtney@aol.com
    To: t.osborn@uea.ac.uk, m.allen1@physics.ox.ac.uk, Russell.Vose@noaa.gov

    Subject: Re: Workshop: Reconciling Vertical Temperature Trends

    Date: Sun, 23 Nov 2003 18:42:59 EST

    Cc: trenbert@cgd.ucar.edu, timo.hameranta@pp.inet.fi, Thomas.R.Karl@noaa.gov, ceforest@mit.edu, sokolov@mit.edu, phstone@mit.edu, ekalnay@atmos.umd.edu, richard.w.reynolds@noaa.gov, christy@atmos.uah.edu, roy.spencer@msfc.nasa.gov, benjie.norris@nsstc.uah.edu, kostya@atmos.umd.edu, Norman.Grody@noaa.gov, Thomas.C.Peterson@noaa.gov, sfbtett@metoffice.com, penner@umich.edu, dian.seidel@noaa.gov, trenbert@ucar.edu, wigley@ucar.edu, pielke@atmos.colostate.edu, climatesceptics@yahoogroups.com, aarking1@jhu.edu, bjorn@ps.au.dk, cfk @lanl.gov, c.defreitas@auckland.ac.nz, cidso@co2science.org, dwojick@shentel.net, douglass@pas.rochester.edu, dkaroly@ou.edu, mercurio@jafar.hartnell.cc.ca.us, fredev@mobilixnet.dk, seitz@rockvax.rockefeller.edu, Heinz.Hug@t-online.de, hughel@comcast.net, jahlbeck@ab

    Dear All:

    The excuses seem to be becoming desperate. Unjustified assertion that I fail to understand “Myles’ comments and/or work on trying the detect/attribute climate change” does not stop the attribution study being an error. The problem is that I do understand what is being done, and I am willing to say why it is GIGO.

    Tim Allen said;
    In a message dated 19/11/03 08:47:16 GMT Standard Time, m.allen1@physics.ox.ac.uk writes:

    “I would just like to add that those of us working on climate change detection and attribution are careful to mask model simulations in the same way that the observations have been sampled, so these well-known dependencies of nominal trends on the trend-estimation technique have no bearing on formal detection and attribution results as quoted, for example, in the IPCC TAR.”

    I rejected this saying:
    At 09:31 21/11/2003, RichardSCourtney@aol.com wrote:

    “It cannot be known that the ‘masking’ does not generate additional spurious trends. Anyway, why assume the errors in the data sets are geographical and not?. The masking is a ‘fix’ applied to the model simulations to adjust them to fit the surface data known to contain spurious trends. This is simple GIGO.”

    Now, Tim Osborn says of my comment;
    In a message dated 21/11/03 10:04:56 GMT Standard Time, t.osborn@uea.ac.uk writes:

    “Richard’s statement makes it clear, to me at least, that he misunderstands Myles’ comments and/or work on trying the detect/attribute climate change.

    As far as I understand it, the masking is applied to the model to remove those locations/times when there are no observations. This is quite different to removing those locations which do not match, in some way, with the observations – that would clearly be the wrong thing to do. To mask those that have no observations, however, is clearly the right thing to do – what is the point of attempting to detect a simulated signal of climate change over some part of (e.g.) the Southern Ocean if there are no observations there in which to detect the expected signal? That would clearly be pointless.”

    Yes it would. And I fully understand Myles’ comments. Indeed, my comments clearly and unarguably relate to Myles comments. But, as my response states, Myles’ comments do not alter the fact that the masked data and the unmasked data contain demonstrated false trends. And the masking may introduce other spurious trends. So, the conducted attribution study is pointless because it is GIGO. Ad hominem insults don’t change that.

    And nor does the use of peer review to block my publication of the facts of these matters.

    Richard

  • Malcolm

    Sample email #1120593115 from Phil Jones to John Christy 5/7/05 excerpt:
    ” IPCC, mm (Michael Mann), me and whoever will get accused of being political, whatever we do. As you know, I’m not political. If anything, I would like to see the climate change happen, so the science could be proved right, regardless of the consequences. This isn’t being political, it is being selfish.”

    This was his mindset leading up to the UEA’s contribution to the IPCC report on which subsequent global government policy has been based. In this dossier there a many more emails from the main advocates of Global Warming that underline the community acceptance of this mindset, at the expense of true science.

    Michael Mann of U. Virginia was one of the earlier drivers of Global Warming with Phil Jones. The emails in the dossier are in order of date over a 10 year period and the mid 2005 sequence leading up to the IPCC report is particularly interesting.
    That contribution was whipped in by Jon Overpeck. In email #1120593115, Overpeck to Keith Briffa 14/7/05 excerpt:
    “4) With respect to text, try hard to get it down to size (see below),
    and to ensure that it is FOCUSED on only that science which is policy
    relevant. ALL TEXT should support an Exec Summary Bullet. If it
    doesn’t the text should be removed, or a bullet created for
    discussion with our team.”

    email#1120676865 dated July 6 2005 has the following, which directly implicates the US DoE in the matter:

    From: Phil Jones
    To: “Neville Nicholls”
    Subject: RE: Misc
    Date: Wed Jul 6 15:07:45 2005

    Neville,
    Mike’s response could do with a little work, but as you say he’s got the tone almost dead on. I hope I don’t get a call from congress ! I’m hoping that no-one there realizes I have a US DoE grant and have had this (with Tom W.) for the last 25 years.
    I’ll send on one other email received for interest.
    Cheers
    Phil

  • Malcolm

    Obama’s Science Policy advisor John Holdren, then Professor of Science Policy at Harvard was involved in the high-powered concerted support for the Mann hockey stick when House Committee Chairmen Joe Barton and Ed Whitfield questioned Mann in detail about his data and methods: canadafreepress.com/index.php/article/17183
    www.geo.umass.edu/climate/scientists-letter.pdf
    Mann’s response is contained in MannHouseReply.pdf in the Documents folder in the FOIA dossier.

    Makes one wonder whether Obama is receiving unbiased advice on this matter.

  • Rob Potter

    Thanks for putting this diagram together. Has anyone checked to see how it matches with the social contact analysis in the Wegman report? That report stated how central Mann was in the large majority of publications If we are seeing the same group here, then the main defense of UEA, the IPCC, etc. completely falls:

    There are no multiple lines of independent study which confirm CRU models – they are all contaminated by the same source.

    For this leak to do more than just demolish Phil Jones, this is the point that has to be hammered home.

  • Nick

    Taint.

    I’ve been thinking about who is tainted too, but from a different perspective. Which paper’s are tainted?

    For example. Lets say paper A has a dodgy temperature record. ie. One where they have manipulated the numbers. Paper A is tainted.

    If paper B cites paper A, then its tainted too. You can’t rely on paper B either because its based on false data.

    It’s recusive too. If paper C relies on B, it too is tainted.

    So are there any citation databases where something like this could be mashed up? A list of papers containing certain words, and a short list of known tainted papers. Then you get the set of total papers that are tainted.

    That makes it interesting to show how far this mess has spread. If another tainted paper comes out, it gets added and the network gets changed.

    So if you can reach a tainted paper via citations, even if it is indirectly, that paper is tainted.

    Nick

  • So if you can reach a tainted paper via citations, even if it is indirectly, that paper is tainted.

    Nick, that’s not quite true. Consider a paper that attempts to refute something in a tainted paper: it would necessarily reference the tainted paper as well.

    What you mean is something unfortunately more complicated to evaluate: papers which depend on the conclusions or published data of a tainted paper are themselves tainted.

    The degree to which this clique appears to have tainted the literature in this stronger sense is, in my mind, maybe the worst of their faults.

  • Richard S Courtney

    Charlie (Colorado):

    I agree with you when you say:

    “Nick, that’s not quite true. Consider a paper that attempts to refute something in a tainted paper: it would necessarily reference the tainted paper as well.”

    However, few such papers have managed to get past the activities of the CRU clique. I refer you to the email from me (which I had forgotten) that Willis Essenbach found in the CRUtape Letters and I posted at #6 above. Perhaps its context is not clear so I explain that now.

    Climate change ‘attribution studies’ by CRU and IPCC use computer models to assess possible causes of global climate change. Known effects that cause climate change are input to a computer model of the global climate system, and the resulting output of the model is compared to observations of the real world. Anthropogenic (i.e. man-made) global warming (AGW) is assumed to be indicated by any rise in average global temperature (mean global temperature, MGT) that occurred in reality but is not accounted by the known effects in the model.

    Clearly, any error in determinations of changes to MGT provides incorrect attribution of AGW.

    The various determinations of the changes to MGT differ and, therefore, there is no known accurate amount of MGT change. But the erroneous MGT change was being input to the models (garbage in, GI) so the amount of AGW attributed by the studies was wrong (garbage out, GO) because ‘garbage in’ gives ‘garbage out’ (GIGO). The attribution studies that provide indications of AGW are GIGO.

    I and others attempted to publish a discussion paper that attempted to explain the problems with analyses of MGT.

    However, the compilers of the MGT data sets frequently alter their published data of past MGT (sometimes they have altered the data in each of several successive months). Hence, the attached paper always contained incorrect MGT data because the MGT data kept changing. The MGT data always changed between submission of the paper and completion of the peer review process. Thus, the frequent changes to MGT data sets prevented publication of our paper.

    Whatever you call this method of preventing publication of a paper, you cannot call it science.

    But the blocking of publication happened.

    1. I can show the work was presented to journals for publication.
    2. I can show it was rejected by the journals.
    3. I can show some rejections were for silly reasons
    (e.g. Nature “we publish original data and do not publish comparisons of data sets”.
    4. I can show that strange coincidences prevented publication
    (e.g. each time the work was submitted for publication the MGT data sets changed so the paper
    (a) was rejected because it analysed incorrect data
    or
    (b) had to be withdrawn to correct the data it contained.)

    But I cannot say who or what was behind this.

    It should be noted that the AGW attribution studies are wrong in principle for two reasons.

    Firstly, they are ‘argument from ignorance’.

    Such an argument is not new. For example, in the Middle Ages experts said, “We don’t know what causes crops to fail: it must be witches: we must eliminate them.” Now, experts say, “We don’t know what causes global climate change: it must be emissions from human activity: we must eliminate them.” Of course, they phrase it differently saying they can’t match historical climate change with known climate mechanisms unless an anthropogenic effect is included. But evidence for this “anthropogenic effect” is no more than the evidence for witches.

    Secondly, they use an attribution study to ‘prove’ what can only be disproved by attribution.

    In an attribution study the system is assumed to be behaving in response to suggested mechanism(s) that is modelled, and the behaviour of the model is compared to the empirical data. If the model cannot emulate the empirical data then there is reason to suppose that the suggested mechanism is not the cause (or at least not the sole cause) of the changes recorded in the empirical data.

    It is important to note that attribution studies can only be used to reject hypothesis that a mechanism is a cause for an observed effect. Ability to attribute a suggested cause to an effect is not evidence that the suggested cause is the real cause in part or in whole. (To understand this, consider the game of Cludo. At the start of the game it is possible to attribute the ‘murder’ to all the suspects. As each piece of evidence is obtained then one of the suspects can be rejected because he/she can no longer be attributed with the murder).

    But the CRU/IPCC attribution studies claim that the ability to attribute AGW as a cause of climate change is evidence that AGW caused the change (because they only consider one suspect for the cause although there could be many suspects both known and unknown).

    Then, in addition to those two pieces of pure pseudo-science – as the paper I attempted to publish demonstrates – the attribution studies use estimates of climate changes that are known to be wrong! And – as I explain above – it proved impossible to publish the paper.

    So, I think there are likely to be very few published papers that attempt to refute the tainted papers.

    All the best

    Richard

  • Will

    THIS IS A CALL TO ACTION
    We have been given a powerful tool in the form of GlimateGate.
    It now has a name and has the potential to get a life of its own.
    So if the mains stream media is not going to report on this then let us use the social Facebook and emails to spread the news.
    Send the following two YouTube videos to two people that you know and ask them to send it onto at least 2 others.
    www.youtube.com/watch?v=Cu_ok37HDuE
    And
    www.youtube.com/watch?v=nEiLgbBGKVk

    If you have a Facebook page post the two links.

    Will

  • Nick

    It’s a valid critique.

    The question is then, how does one remove this from the analysis?

    Does it matter?

    So we can take the approach of Richard. Pick a random sample of papers that are tainted, and look at them. If they are an attempt to refute or not we have an estimate of false positives. If the percentage is small it doesn’t really matter. We have the estimate of tainted papers as a percentage of the total.

    I suspect that the taint factor for climate change is very high.

  • Richard S Courtney

    Nick:

    Yes, I agree completely with all you say at #14.

    So, we need an authority on citation reviewing who has not published on climate and who is willing to conduct the initial study. Any suggestions?

    Pleas note that anybody (such as myself) who has had climate papers rejected should be rejected for conduct of the study because he/she could be said to be a biased.

    Regards

    Richard

  • Nick

    So, as I see it this would be a process.

    1. Search for papers containing certain phrases such as “climate change” and “global warming” to form the set of papers. Or pick certain journals relating to climate change. These form the initial set.

    2. Compute the papers that reference the initial set, recursively.

    That should give a good universe to start with.

    3. Pick papers by those involved in CRUdgate.

    4. Now compute the tainted set.

    5. Sample the tainted set to see if any in the sample are published as refutations of the original bad set. Since you only have to look at papers that directly site the suspect papers, it is likely to be a small set.

    6. Now estimate the percentage of tainted versus none tainted papers.

    Nick

  • Bob K.

    Michael Mann in 1067596623.txt writes:

    “Lets let our supporters in higher places use our scientific response to push the broader case against MM.”

    I was wondering – has anybody found out who were the “our supporters in higher places”?
    The email is dated 31 Oct 2003.

  • Well the WWF seems to be inextricable interlaced with all those in power on the climate. Hardly what you would expect from an “independent” organisation that seeks tax free status!

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