CA readers are aware that Ross and I twice submitted a comment on Santer et al 2008 to International Journal of Climatology (both available on arxiv.org), showing that key Santer results (which were based on data only up to 1999) were overturned with the use of up-to-date data. These were both rejected (but have been posted up on arxiv.org). Ross has now led a re-framed submission, applying an econometric methodology for the analysis. This is available, together with SI and data/code archive here.

Although key Santer et al 2008 results are invalid with up-to-date data, they have been widely cited as showing that there is no inconsistency between models and observations in the tropical troposphere (e.g. CCSP, EPA), as had been previously believed/argued by some.

IJC reviewers and editor Glenn McGregor took the position that the invalidity of key Santer results was not of interest to the climate science community. They proposed all sorts of other investigations as a precondition for publication – many of them interesting enterprises and suggestions, but all very time consuming and not relevant to the simple issue of whether key Santer results were overturned with up-to-data.

The reviewers of our first submission refused to permit the editor to provide us with their actual reviews, requiring the editor to paraphrase their reviews.

In our second try, one of our reviewers objected to us using Santer et al 2008 methods in a comment on Santer et al 2008. He argued that the S08 methods were incorrect (blaming Douglass et al for leading them down a “cul-de-sac”) and condemned our demonstration that their results fell apart with up-to-date data as a “descent away to meaningless arguments”. He argued that our comment on S08 should instead use “diagnostic” of Santer et al 2005.

The authors should read Santer et al. 2005 and utilise this diagnostic. It is a pity that Douglass et al took us down this interesting cul-de-sac and that Santer et al 2008 did not address it but rather chose to perpetuate it. The authors could reverse this descent away to meaningless arguments very simply by noting that the constrained aspect within all of the models is the ratio of changes and that therefore it is this aspect of real-world behaviour that we should be investigating…

Again, potentially an interesting enterprise, but hardly relevant to the simple demonstration of our short comment. Particularly when Santer et al 2005 does not, in fact, have a “diagnostic” reduced to a statistical test.

The history of our comment was somewhat played out in the Climategate letters. In one Climategate email, Peter Thorne of the UK Met Office, a Santer coauthor, who appears to have been one of the reviewers who rejected our submission, wrote to Phil Jones notifying him of the rejection of our submission, using the defamatory term “Fraudit”.

Our first comment was submitted in January 2009 and the second comment in August 2009. I had previously reported some of the findings at Climate Audit. Despite numerous Climate Audit posts on our findings and two efforts to publish our results, Santer accused me of asking for data purely as a “fishing expedition” – see NASA blogger Gavin Schmidt’s realclimate here.

Mr. McIntyre’s FOIA requests serve the purpose of initiating fishing expeditions, and are not being used for true scientific discovery.

Santer’s campaign for support for his obstruction of my data requests accounts for many Climategate letters. As members of the editorial board of Climatic Change, Santer had previously co-operated with Phil Jones in 2004 in ensuring that Climatic Change did not require Mann et al to comply with reviewer requests for supporting data and code.

Santer did ultimately place some of the requested material online. Despite Santer’s whining and delaying, this archive was very useful as it enabled co-author Chad Herman of the excellent treesfortheforest blog to benchmark his own emulation of Santer’s calculations and to create a fresh archive of PCMDI runs. Chad’s archive is FAR more usable for statistical analysis than endlessly re-processing PCMDI and may well have use for interested parties over and above the analysis in this article. (Remind me to discuss this at greater length).

After a certain point, Ross gave up on us being able to publish the simplest of comments at IJC and re-framed the analysis with “new” econometric methodology and submitted to Atmospheric Science Letters. There was a Team reviewer, but the editor permitted Ross to respond and used his own judgment on the response – this is what is referred to in Climategate letters as a “leak” in the journal network.

Here is Ross’ letter to colleagues:

You might be interested in a new paper I have coauthored with Steve McIntyre and Chad Herman, in press at Atmospheric Science Letters, which presents two methods developed in econometrics for testing trend equivalence between data sets and then applies them to a comparison of model projections and observations over the 1979-2009 interval in the tropical troposphere. One method is a panel regression with a heavily parameterized error covariance matrix, and the other uses a non-parametric covariance matrix from multivariate trend regressions. The former has the convenience that it is coded in standard software packages but is restrictive in handling higher-order autocorrelations, whereas the latter is robust to any form of autocorrelation but requires some special coding. I think both methods could find wide application in climatology questions. The tropical troposphere issue is important because that is where climate models project a large, rapid response to greenhouse gas emissions. The 2006 CCSP report pointed to the lack of observed warming there as a “potentially serious inconsistency” between models and observations. The Douglass et al. and Santer et al. papers came to opposite conclusions about whether the discrepancy was statistically significant or not. We discuss methodological weaknesses in both papers. We also updated the data to 2009, whereas the earlier papers focused on data ending around 2000. We find that the model trends are 2x larger than observations in the lower troposphere and 4x larger than in the mid-troposphere, and the trend differences at both layers are statistically significant (p<1%), suggestive of an inconsistency between models and observations. We also find the observed LT trend significant but not the MT trend. If interested, you can access the pre-print, SI and data/code archive at my new weebly page http://rossmckitrick.weebly.com/



