Thursday, June 7, 2012


date: Fri, 20 Jun 2008 00:42:58 -0400 (EDT)
subject: JOC-08-0160 - Invitation to Review


Dear Prof. Jones

Manuscript # JOC-08-0160 entitled "Spurious correlations between recent warming and indices of local economic activity" has been submitted to the International Journal of Climatology. The abstract and author details are to be found at the foot of this email.

As you are an acknowledged expert in this area, I am writing to see if you could find time to review this manuscript. Ideally I would like the review back to me within 6 weeks if possible. Please let me know within 7 days if you will be able to review this paper. If you are unable to review would you take a moment to please recommend one or two other possible referees with expertise in this area.

You can respond to this invitation by either emailing me directly, or if you are willing to review the paper you may use the shortcut of clicking on the "Agree" link below. This will initiate another email that grants you access to the manuscript.

To respond automatically, click below:


You will then have access to the manuscript and reviewer instructions in your Referee Centre.

Thank you for taking the time to consider this request.


Prof. Glenn McGregor
International Journal of Climatology


Spurious correlations between recent warming and indices of local economic activity

Schmidt, Gavin

I analyse a series of climate model simulations of the 20th Century to investigate a number of published correlations between indices of local economic activity and recent global warming. These correlations have been used to support a hypothesis that the observed surface warming record has been contaminated in some way and thus overestimates true global warming. However, the basis of the results are correlations over a very restricted set of locations (predominantly western Europe, Japan and the US) which project strongly onto naturally occurring patterns of climate variability. Across model simulations the correlations vary widely due to the chaotic weather component in any short term record. I find that the reported correlations do not significantly fall outside the simulated distribution and that the correlations are probably spurious (i.e. are likely to have arisen from chance alone). Thus, though this study can not prove that the global temperature record is unbiased, I conclude there is no strong evidence from these correlations of any large scale contamination.

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