There is a new paper that has been submitted for publication which is open for discussion. [I will be glad to post guest posts on my weblog regarding the analysis in this paper].
The paper is
McKitrick, R. and Timothy J. Vogelsang, 2011: Multivariate trend comparisons between autocorrelated climate series with general trend
Ross sent out the announcement of the paper with the following summary e-mail
Following on from my paper with Steve McIntyre and Chad Herman last year, I have looked at the 1958-2010 balloon record. Since there is a step-change at 1977 due to the Pacific Climate Shift I had to figure out how to deal with it while also dealing with the autocorrelation. I put the problem to Tim Vogelsang, a theoretical econometrician at Michigan State. He ended up deriving a new estimator for the purpose and coauthored a paper with me with a specific application to the tropical troposphere. We’ve written it up for a climate journal and we’ll submit it shortly. Meanwhile, for your interest, it is posted as a discussion paper online http://rossmckitrick.weebly.com/uploads/4/8/0/8/4808045/2011-09.pdf
The bottom line in the application is that we find the 1958-2010 balloon trend to be insignificant in the tropics (LT and MT) and the model-observational discrepancy highly significant.
Ross wrote this on his weblog
TROPOSPHERIC TRENDS: MODELS vs OBSERVATIONS ROUND II: In fall 2010 I published a paper with Steve McIntyre and Chad Herman comparing climate model-generated predictions to observations from satellites and weather balloons in the lower- and mid-troposphere over the tropics, a key region for assessing climate model validity. That paper applied two methods, the panel model, which is a fairly well-known econometric method, as well as the Vogelsang-Franses multivariate trend estimation method, a less-well known but superior alternative which adapts the general HAC method to the estimation of robust confidence intervals for linear trends. The data set used in MMH spanned 1979 to 2009. I extended the data set to include weather balloon data back to 1958 for the purpose of comparing observed lower- and mid-troposphere trends in the tropics to climate model predictions. A challenge in this case is that the 1977-78 Pacific Climate Shift introduces a step-like change in the mean of the data which causes a spurious increase in the estimated trend. But controlling for the step-change affects the VF critical values. Tim Vogelsang has extended the theory behind the VF method to yield robust trend variances in the presence of autocorrelation of unknown form when a step-change occurs at a known point in the sample. In our new paper, just released as a Discussion Paper and en route to a journal, Tim and I present a detailed explanation of the HAC approach to trend comparisons, including the relevant asymptotics and a bootstrap method for generating empirical critical values, then we apply the method to the Hadley and RICH balloon data for the tropical troposphere. Controlling for the 1977 Pacific Climate Shift we find the trends are insignificant from 1958-2010 and the discrepancy with climate models is highly significant.
There paper includes the text in the conclusion
The empirical focus of the paper is a comparison of trends in climate model-generated
temperature data and corresponding observed temperature data in the tropical troposphere. Our
empirical innovation is to model a level shift in the observed data corresponding to the Pacific
Climate Shift that occurred in 1977-78. With respect to the Vogelsang Franses (2005) approach,
this amounts to adding a mean shift dummy to the model which requires a new set of critical
values which we provide.
As our empirical findings show, the detection of a trend in the tropical lower- and midtroposphere
data over the 1958-2010 interval is contingent on the decision of whether or not to
include a mean-shift term at January 1978. If the term is included, a time trend regression with
error terms robust to autocorrelation of unknown form indicates that the trend observed over the
1958-2010 interval is not statistically significant in either the LT or MT layers. Most climate
models predict a larger trend over this interval than is observed in the data. We find a statistically
significant mismatch between climate model trends and observational trends whether the meanshift
term is included or not. However, with the shift term included the null hypothesis of equal
trend is rejected at much smaller significance levels (much more significant).