New Nic Lewis Paper

Nic Lewis’s paper on climate sensitivity is available. See his BH post here. Also see discussion at Judy Curry and WUWT.

10 Comments

  1. David L. Hagen
    Posted Apr 16, 2013 at 6:23 PM | Permalink

    Links: Climate Etc. The Forest-2006 Climate Sensitivity Study and Misprocessing of Data: An update
    WUWT An objective Bayesian estimate of climate sensitivity

  2. Craig Loehle
    Posted Apr 17, 2013 at 9:20 AM | Permalink

    Nic demonstrates once again why archiving all code and data is important.
    It is interesting that the empirical studies are converging on a lower (like 1.6 deg C) sensitivity, of which we have already seen .6 to .8. This makes the likely rate of warming very close to the value we estimated in the following by subtracting out the natural cycles
    Loehle, C. and N. Scafetta. 2011. Climate Change Attribution Using Empirical Decomposition of Historical Time Series. Open Atmospheric Science Journal 5:74-86

    • Steven Mosher
      Posted Apr 17, 2013 at 9:48 AM | Permalink

      “Nic demonstrates once again why archiving all code and data is important.”

      Sadly, as you know, I’ve been unable and Steve Mc has been unable to convince Scaffeta to do as you suggest. Your 2011 paper with him is interesting. Kindly point to the code and data.

      • Craig Loehle
        Posted Apr 17, 2013 at 10:39 AM | Permalink

        I have no control over Scaffeta. I also wish he would document his code for the solar indices as well.

  3. Kenneth Fritsch
    Posted Apr 17, 2013 at 9:50 AM | Permalink

    The excerpt below from the Nic Lewis article at WUWT I think summarizes what he did and Forest did not do. Sounds to this novice as some pretty basic differences.

    I like Nic’s writing style.

    “As noted above, Forest 06 used uniform priors in the parameters. However, the relationship between the parameters and the observations is highly nonlinear and the use of a uniform parameter prior therefore strongly influences the final PDF. Therefore in my paper Bayes’ theorem is applied to the data rather than the parameters: a joint posterior PDF for the observations is obtained from a joint uniform prior in the observations and the likelihood functions. Because the observations have first been ‘whitened’,2 this uniform prior is noninformative, meaning that the joint posterior PDF is objective and free of bias. Then, using a standard statistical formula, this posterior PDF in the whitened observations can be converted to an objective joint PDF for the climate parameters.”

  4. Steven Mosher
    Posted Apr 17, 2013 at 2:49 PM | Permalink

    http://www.businessinsider.com/thomas-herndon-michael-ash-and-robert-pollin-on-reinhart-and-rogoff-2013-4

    Guys who wouldnt released data get PUNKED

    http://www.businessinsider.com/reinhart-and-rogoff-admit-excel-blunder-2013-4

    • Posted Apr 17, 2013 at 4:28 PM | Permalink

      Reinhart and Rogoff’s response is forthright and convincing, as is their discussion of the evolution of the dataset over time (one that they have been painstakingly building for a long time). Note how they display none of the “attitude” we have come to expect from the climate establishment about admitting error. They also show exactly how the error changes their results, and they use the clearest possible language to explain their methods and why those (apart from the spreadsheet error) were the most sensible ones. If the Climate Lords followed these guidelines we’d all be better off.

  5. NicL
    Posted Apr 17, 2013 at 3:34 PM | Permalink

    Kenneth F

    “I like Nic’s writing style.”

    Thanks! I always fear that my writing style is too dense, as I tend to emphasize accuracy over ease of reading. But in this case I had some very helpful editing input from Andrew Montford of Bishop Hill, who is an excellent writer.

    • John R T
      Posted Apr 17, 2013 at 6:02 PM | Permalink

      Thanks, then, to the two of you.

    • JasonScando
      Posted Apr 17, 2013 at 11:16 PM | Permalink

      Just wanted to second this, Nic, it was very clear and interesting to read.

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