Esper's April Fool's Joke

Esper the non-Archiver is Trouet’s supervisor (see url.), so I’ve taken the liberty here of ascribing this clever April Fool’s prank to Esper, though undoubtedly Trouet deserves some credit for her role in pulling off the prank.

In a recent post, I alluded to the point that the England precipitation index shown in the Trouet Esper graphic below is derived from Figure 4 of Lamb 1965.

The idea that Lamb’s reconstruction should be held out as a key element in their disproof of the Medieval Warm Period is such a pretty prank that it really deserves to be savored a little more than we’ve done so far. It’s almost as good as prank as Mann using Sherwood Idso’s strip bark results to disprove that MWP. Maybe it’s a better prank since it uses a variation of the IPCC 1990 graphic itself: the link between the IPCC graphic and the Lamb-Esper precipitation series being readily seen in the following excerpt from a Lamb graphic – the rounded version is carried forward into the well-known IPCC 1990 graphic while the more angular version is carried forward into the Esper-Trouet Figure (compare to the cyan line in Trouet-Esper graphic):

Anyway, today I thought it would be interesting to report on exactly how Lamb derived his estimate of winter precipitation, as readers should take care to be aware of exactly what’s in Lamb’s winter precipitation estimate so that they can better protect themselves against pranksters like Esper.

Lamb’s original Table II excerpt for rainfall is shown below – the first column is annual, 2nd is high summer (July-August) and the 3rd is the rest of the year (Sept-June), all expressed as percentages of 1916-1950 values.

The high summer rainfall is calculated through a regression relationship with the “Summer Wetness Index” of Lamb and Johnson, 1961 (I don’t know how this Summer Wetness Index was calculated and have no plans at present to investigage this rabbit hole further).

The regression equation for decade values of July and August rainfall (as % of the 1916-1950 average) over England and Wales (R_JA) on the summer wetness index value (W) is: R_JA = 6.52W + 29.1. The standard error of the resulting percentage figure appears to be ± 4.01. (p. 26)

Next the annual rainfall was calculated through a 2nd regression relationship – this time with the famous Lamb temperature reconstruction (which is why the shape ends up being so familiar).

The estimates of average yearly rainfall in Table II and Fig.4 are derived from the yearly mean temperatures given, and from the winter temperatures adjusted to be at their mildest in the medieval warm epoch the equal of the present century, using the appropriate regression equations[2] …

Footnote 2: The regression equation for decade values of average yearly rainfall in England and Wales (Ry) as % of the 1916-1950 average rain on average yearly temperature Ty is: Ry = 9.80Ty + 6.2. The standard error of the percentage estimates so derived appears to be 4.65.

Thus, Lamb’s estimate of annual rainfall is a linear re-scaling of the famous temperature series. (BTW the IPCC 1990 is a little different than the Lamb 1965 version and appears to be taken from a slightly different version in Lamb 1967, as discussed in a post on an earlier occasion.)

Next the Sept-June rainfall is estimated as the difference between the two values:

Finally, the rainfall averages in Table II for the 10-month period that excludes the high summer, were given by the differences between the amounts of rain implied by the other two columns.(page 33)

The reason why the Lamb-(Esper) winter precipitation estimate has the same shape as the famous annual temperature series is that the summer wetness index does not have a lot of “low frequency” variability relative to the annual temperature series, and thus the famous shape carries through to the winter index.

Somewhat inconsistently, footnote 2 on page 33 reports a third regression equation relating Sept-June rainfall to temperature as below (the running text appears to indicate that it was calculated by difference; I haven’t tried to verify which is the case as it doesn’t matter for present purposes):

The corresponding regression equation for values of rainfall over the 10 months September- June (R10) on winter temperature is: R10 = 7.81 T_DJF + 66.6. The standard error of these estimates appears to be 4.29.

As you can see from Table II, there aren’t a lot of degrees of freedom in any of these regression equations.

Here again, Esper has again pulled a very clever prank as he’s smoothed all his data into 50-year bins as well, so that no one can complain about about overly coarse data in Lamb 1965. Esper has done an additional tease by saying that they used 25 year bins even though the merry prankster used 50 year bins as shown in my earlier post.

All in all, even CA readers must grudgingly respect both Esper and Science for pulling off such an inventive and witty April Fool’s prank.

14 Comments

  1. bender
    Posted Apr 5, 2009 at 5:35 PM | Permalink | Reply

    Haha. Does the joking never end?

    • Steve McIntyre
      Posted Apr 5, 2009 at 10:14 PM | Permalink | Reply

      Re: bender (#1), who knew that Esper had such a dry sense of humor?

  2. Raven
    Posted Apr 6, 2009 at 12:53 AM | Permalink | Reply

    Steve,

    I don’t suppose you could let the statistically deprived in on the joke.

    The most I can see is the rainfall series used by Esper to draw conclusions is derivied from the Lamb temperature series which:

    1) raises questions on why one series is ‘robust’ enough for use by the team but the other is not.
    2) the error bars on the rainfall series are so large that any conclusion is dubious at best.

    Is this even close to your point?

  3. michel
    Posted Apr 6, 2009 at 2:26 AM | Permalink | Reply

    His point seems to be partly as said – that the two series are equally indicative of temperature. But the joke is (if this is it) that both are precipitation based.

    So we are going around and around in circles. Lamb takes precipitation and turns it into a temperature record, which is then disputed by the HS, but despite being disputed and eliminated from history, it is then re-accepted as valid, so as to be used to validate a further precipitation series.

    The two precipitation series correlate, as they should since they are measuring the same thing. What this cannot however do is show that the second precipitation series is calibrated to temperature.

    This is what M seems to find to be proof of a delicious sense of irony. You use a reconstruction which is not of temperature but of precipitation to validate your precipitation series as a temperature proxy. However, you pick not just any reconstruction for this, but one which appears to show the existence of a temperature bump, the MWP, that skeptics will have trouble denying since their arguments majored on that, and yours generally were skeptical about it.

    This new series now appears to show what Lamb found about temperature in the first place, though what that can really be, considering that it is actually all about rainfall is a real question, but Lamb’s temperature reconstruction, once so heavily fought over, is not now disputed any more, because it can allegedly somehow be used to show the MWP was regional.

    So we are simply recovering the previously rejected Lamb in a very complicated roundabout way, without admitting it, and without answering the basic underlying question about the reconstruction, which is how temperature relates to precipitation.

    Not sure if this is right, someone correct me if not, the twists and turns of logic make ones head spin. And give one a powerful desire to see these guys build bridges and then drive over them!

  4. Steve McIntyre
    Posted Apr 6, 2009 at 7:42 AM | Permalink | Reply

    My point was a little simpler.

    The classic series showing the MWP was Lamb’s temperature recon used in IPCC 1990 and hated by the Team. The Team argues that the Lamb recon was regional and regional in a more restricted way than modern warming. (I don’t think that they’ve proved their point, but their failing to prove the point doesn’t imply that the opposite has been proved either.) Even if it is only regional evidence, an MWP in northern Europe is not evidence against a global MWP though, if it is only regional, it doesn’t prove the point either.

    Whatever the merits of the arguments on the above issue, the Lamb series on its face is not evidence against a global MWP and surely there is irony in it being so used.

  5. Craig Loehle
    Posted Apr 6, 2009 at 4:04 PM | Permalink | Reply

    Not to put too fine a point on it but to prove the MWP was absent from the rest of the world, don’t you need data from the rest of the world?

    • Mark T
      Posted Apr 6, 2009 at 8:14 PM | Permalink | Reply

      Re: Craig Loehle (#6),

      Not to put too fine a point on it but to prove the MWP was absent from the rest of the world, don’t you need data from the rest of the world?

      Not when you have The Mannomatic: it slices, it dices, put anything in and it will become… whatever you want.

      Mark

      • bender
        Posted Apr 6, 2009 at 8:40 PM | Permalink | Reply

        Re: Mark T (#7),

        I think there’s a more productive line of enquiry that could follow from Dr Loehle’s question, which was:

        Not to put too fine a point on it but to prove the MWP was absent from the rest of the world, don’t you need data from the rest of the world?

        which is “what was the empirical basis for the Trouet assertion that the MWP is linked to a NAO-style anomaly, and not some other pattern?”. i.e. What is the quantitative degree of similiarity between the present-day NAO and the MWP-era “MCA”? The Team has made this type of assertion on other occassions – that this pattern here “resembles” that one there – for example in the Steig et al. paper. What’s the difference between that kind of statement and some clown saying this apple here looks quite a bit like that orange over there? What is the IPCC-approved metric of pattern “resemblance”? Is hand-waving ok? Is that all that Nature and Science reviewers ask?

        • Steve McIntyre
          Posted Apr 6, 2009 at 9:23 PM | Permalink

          Re: bender (#9),

          They do have a graphic showing smoothed versions of ROW proxies, including some ones that I haven’t seen before and not available digitally. I’ll discuss them at some point.

          But the argument doesn’t rise above handwaving.

          When we visited the Spirit Cave in Thailand, the guide (a hill person who didn’t speak English or Thai) pointed to a stumpy rock and said “Buddha”. Was the resemblance more or less “remarkable” than the resemblance between squiggles that we are regularly invited to consider by climate scientists? I didn’t think so.

        • bender
          Posted Apr 6, 2009 at 9:45 PM | Permalink

          Re: Steve McIntyre (#10),
          I saw the image of christ in my toast this morning. The resemblance was remarkable. [Ok, maybe it was "hello kitty". Still.]

  6. bender
    Posted Apr 6, 2009 at 8:21 PM | Permalink | Reply

    Raven, it’s the irony of using Lamb’s own data in an attempt to prove the MWP was caused by a regional anomaly. And the irony of the double standard regarding uncertainty. Lamb’s data are too imprecise to allow one to conclude anything about GMT in MWP vs CWP, but it is precise enough to be used in a paleo-calibration. Isn’t that convenient? But excuse me: where does the uncertainty on Lamb’s input data get factored into the reconstruction?
    .
    You see: uncertainty is an instrument to be played one way, but not any other. That’s the power you have when you control the agenda. That’s why it is critical to keep Wegman out of the debate.

  7. James Erlandson
    Posted Apr 7, 2009 at 4:33 AM | Permalink | Reply

    Pattern Matching

    Linus Van Pelt: That cloud up there looks a little like the profile of Thomas Eakins, the famous painter and sculptor. And that group of clouds over there [points] gives me the impression of the Stoning of Stephen. I can see the Apostle Paul standing there to one side.

    Lucy Van Pelt: Uh huh. That’s very good. What do you see in the clouds, Charlie Brown?

    Charlie Brown: Well… I was going to say I saw a duckie and a horsie but I changed my mind.

  8. Posted Apr 7, 2009 at 8:56 AM | Permalink | Reply

    There is such a thing as unhealthy skepticism. As I keep telling Andrew, “natural variability” is not an alternative theory for GW. It’s just a simple fact that must be contended with, can not be ignored, but is often ignored (or over-simplified) when it comes to statistical attribution exercises.

    No alternate theory is required if the new theory (AGW) doesn’t adequately explain what it purports to theorize. IOW, there’s nothing to see here.

    • bender
      Posted Apr 7, 2009 at 10:03 AM | Permalink | Reply

      Re: Jeff Alberts (#13),
      This is a standard device used by deniers masquerading as skeptics. Disprove the theory as a whole and you can happily dismiss all of its parts. That’s effectively throwing the baby out with the bathwater.
      .
      That current observations depart significantly from IPCC’s projections (thank, you, lucia) suggests to me that their projections were not as precise as they made them out to be. That is VERY different from concluding that GHG physics is flawed and the GHG effect is negligible etc. etc. They ignored the natural variability and the uncertainty on their forcings and now they must sleep in the bed of fiction that they chose to promote. They should have listened to me six years ago. I told them this would happen. Oh the irony.

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