### Abstract

- Top of page
- Abstract
- 1. Introduction
- 2. Monte Carlo Simulations of Hockey Sticks on Trendless Persistent Series
- 3. The PC1 in the North American Network
- 4. Benchmarking the Reduction of Error Statistic for the Algorithm
- 5. Discussion and Conclusions
- Acknowledgments
- References
- Supporting Information

[1] The “hockey stick” shaped temperature reconstruction of Mann et al. (1998, 1999) has been widely applied. However it has not been previously noted in print that, prior to their principal components (PCs) analysis on tree ring networks, they carried out an unusual data transformation which strongly affects the resulting PCs. Their method, when tested on persistent red noise, nearly always produces a hockey stick shaped first principal component (PC1) and overstates the first eigenvalue. In the controversial 15th century period, the MBH98 method effectively selects only one species (bristlecone pine) into the critical North American PC1, making it implausible to describe it as the “dominant pattern of variance”. Through Monte Carlo analysis, we show that MBH98 benchmarks for significance of the Reduction of Error (RE) statistic are substantially under-stated and, using a range of cross-validation statistics, we show that the MBH98 15th century reconstruction lacks statistical significance.