Breaking news: a new analysis blows more holes in the “hockey stick” temperature reconstruction

Summary:  Breaking news about the third outside analysis of the statistics in the “hockey stick” temperature reconstruction of Michael Mann et al.  Published in a prestigious peer-reviewed journal, the results are not pretty — and confirm the two earlier reviews.   It’s worth reading if you’re interested in this vital issue.

A Statistical Analysis of Multiple Temperature Proxies: Are Reconstructions of Surface Temperatures Over the Last 1000 Years Reliable?, Blakeley B. McShane (PhD statistics, Asst Prof at Northwestern U’s Kellogg School of Management; bio) and Abraham J. Wyner (Asst Prof Statistics, Wharton), Annals of Applied Statistics, in press.  H/T to Anthony Watts.  The Institute of Mathematical Statistics (Wikipedia) publishes the AAS.  Abstract:

Predicting historic temperatures based on tree rings, ice cores, and other natural proxies is a difficult endeavor. The relationship between proxies and temperature is weak and the number of proxies is far larger than the number of target data points. Furthermore, the data contain complex spatial and temporal dependence structures which are not easily captured with simple models.

In this paper we assess the reliability of such reconstructions and their statistical significance against various null models. We find that the proxies do not predict temperature significantly better than random series generated independently of temperature. Furthermore, various model specifications that perform similarly at predicting temperature produce extremely different historical backcasts. Finally, the proxies seem unable to forecast the high levels of and sharp run-up in temperature in the 1990s either in-sample or from contiguous holdout blocks, thus casting doubt on their ability to predict such phenomena if in fact they occurred several hundred years ago.

We propose our own reconstruction of Northern Hemisphere average annual land temperature over the last millenium, assess its reliability, and compare it to those from the climate science literature. Our model provides a similar reconstruction but has much wider standard errors, reflecting the weak signal and large uncertainty encountered in this setting.

The article is clearly written, much of it understandable by laymen (easily understood by those who have followed this key debate).  Especially note the conclusions.


Conclusion #2 of the Report of the International Panel set up by the University of East Anglia to examine the research of the Climatic Research Unit (Chairman Lord Oxburgh), April 2010:

We cannot help remarking that it is very surprising that research in an area that depends so heavily on statistical methods has not been carried out in close collaboration with professional statisticians. Indeed there would be mutual benefit if there were closer collaboration and interaction between CRU and a much wider scientific group outside the relatively small international circle of temperature specialists.

Abaraham Wyner, comment at Climate Audit:

The paper has been accepted, but publication is still a bit into the future as it is likely to be accompanied by invited discussants and comment.

McShane, at his website:

The paper has been accepted at the Annals of Applied Statistics and a draft version is posted on the journal’s website in the forthcoming section. The posted draft was submitted for referee and editor comments and is not yet in “final” form. Likewise, some have obtained the code and data which was intended for the referees and editors as part of the review process. This code and data is not yet in final form nor is the documentation complete. The final draft of the paper and the code and data bank will be posted at the journal’s website come publication.  (

Some other reviews of Mann’s temperature reconstructions

Other articles about the statistics of climate change

For a longer list of articles about climate change see the FM reference page Science & climate – studies & reports.

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