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Letter

Proxy inconsistency and other problems in millennial paleoclimate reconstructions

Stephen McIntyre and Ross McKitrick
  1. aClimateAudit.org, 25 Playter Boulevard, Toronto, ON, Canada M4K 2W1; and
  2. bDepartment of Economics, University of Guelph, Guelph, ON, Canada N1G 2W1

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PNAS February 10, 2009 106 (6) E10; first published February 2, 2009; https://doi.org/10.1073/pnas.0812509106
Stephen McIntyre
aClimateAudit.org, 25 Playter Boulevard, Toronto, ON, Canada M4K 2W1; and
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  • For correspondence: stephen.mcintyre@utoronto.ca
Ross McKitrick
bDepartment of Economics, University of Guelph, Guelph, ON, Canada N1G 2W1
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Mann et al. (1) present two paleoclimate reconstruction methods [“error-in-variables” (EIV) and “composite plus scale” (CPS)], claiming statistically significant skill for both. Their figure 3 reveals that from approximately 750 to 1100, the CPS 95% confidence interval excludes the EIV 95% confidence interval and vice versa. This is evidence not of skill, but of inconsistency.

Contrary to assurances (1), archived Mann et al. source code did not show how they calculated their figure 3 confidence intervals, which are unjustifiably narrow. Paleoclimate reconstructions are an application of multivariate calibration, which provides a theoretical basis for confidence interval calculation (e.g., refs. 2 and 3). Inconsistency among proxies sharply inflates confidence intervals (3). Applying the inconsistency test of ref. 3 to Mann et al. A.D. 1000 proxy data shows that finite confidence intervals cannot be defined before ≈1800.

Numerous other problems undermine their conclusions. Their CPS reconstruction screens proxies by calibration-period correlation, a procedure known to generate “hockey sticks” from red noise (4). The proportion of proxies with “significant” correlation to gridcell temperature is overestimated by comparison to two (not one) gridcells, inclusion of “proxies” incorporating instrumental temperatures, and underadjustment for autocorrelation.

Their non-dendro network uses some data with the axes upside down, e.g., Korttajarvi sediments, which are also compromised by agricultural impact (M. Tiljander, personal communication), and uses data not qualified as temperature proxies (e.g., speleothem δ13C).

Although Mann et al. purport to “follow the suggestions” of ref. 5, they employed “strip-bark” dendrochronologies despite the recommendation of ref. 5 that these chronologies be “avoided” and fail to observe the caveats of ref. 5 that negative CE statistics indicate unreliable results.

Footnotes

  • ↵11To whom correspondence should be addressed. E-mail: stephen.mcintyre{at}utoronto.ca
  • Author contributions: S.M. and R.M. wrote the paper.

  • The authors declare no conflict of interest.

  • © 2009 by The National Academy of Sciences of the USA

References

  1. ↵
    1. Mann ME,
    2. et al.
    (2008) Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proc Natl Acad Sci USA 105:13252–13257.
    .
    OpenUrlAbstract/FREE Full Text
  2. ↵
    1. Osborne C
    (1991) Statistical calibration: A review. Int Stat Rev 59:309–336.
    .
    OpenUrlCrossRef
  3. ↵
    1. Brown PJ,
    2. Sundberg R
    (1987) Confidence and conflict in multivariate calibration. J R Stat Soc Ser B 49:46–57.
    .
    OpenUrl
  4. ↵
    1. Stockwell D
    (2006) Reconstruction of past climate using series with red noise. AIG News 8:314.
    .
    OpenUrl
  5. ↵
    1. National Research Council
    (2006) Surface Temperature Reconstructions for the Last 2,000 Years (Natl Acad Press, Washington, DC).
    .
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Proxy inconsistency and other problems in millennial paleoclimate reconstructions
Stephen McIntyre, Ross McKitrick
Proceedings of the National Academy of Sciences Feb 2009, 106 (6) E10; DOI: 10.1073/pnas.0812509106

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Proxy inconsistency and other problems in millennial paleoclimate reconstructions
Stephen McIntyre, Ross McKitrick
Proceedings of the National Academy of Sciences Feb 2009, 106 (6) E10; DOI: 10.1073/pnas.0812509106
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