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Hockeystick curve supported by statistics

15.12.2010, Age: 3966 days

In a paper in the next issue of the Annals of Applied Statistics Blakeley B. McShane and Abraham J. Wyner assess the reliability of climate reconstructions based on proxies such as tree rings, ice cores, etc. Their models generally confirm Michael Mann's hockeystick albeit with a larger uncertainty.

The interesting aspect of this issue of Annals of Applied Statistics is the discussion, which Editor Michael Stein allowed. Michael Mann and his colleagues join with a critical comment and so did the authors of 12 more discussion articles.

From a blog at RealClimate by Gavin Schmidt and Michael Mann:

"Inevitably, focus in the discussions is on problems with MW [McShane and Wyner], but it is worth stating upfront here (as is also stated in a number of the papers) that MW made positive contributions to the discussion as well - they introduced a number of new methods (and provided code that allows everyone to try them out), and their use of the Monte Carlo/Markov Chain (MCMC) Bayesian approach to assess uncertainties in the reconstructions is certainly interesting. This does not excuse their rather poor framing of the issues, and the multiple errors they made in describing previous work, but it does make the discussions somewhat more interesting than a simple error correcting exercise might have been. MW are also to be commended on actually following through on publishing a reconstruction and its uncertainties, rather than simply pointing to potential issues and never working through the implications."

Abstract of McShane and Wyner's paper

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.

Blakeley B. McShane and Abraham J. Wyner. A Statistical Analysis of Multiple Temperature Proxies: Are Reconstructions of Surface Temperatures Over the Last 1000 Years Reliable?
Submitted to the Annals of Applied Statistics

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