Another large batch of tree ring chronologies was archived on June 21, 2006, this time with records up to 2003. Are the results for the 1990s and 2000s off the chart?
On June 21, Connie Woodhouse, Stephen Gray and David Meko archived 44 measurement data sets and site chronologies from Colorado, discussed in Woodhouse et al 2006, at WDCP. The data was published in Woodhouse et al 2006; it is gratifying to see such a thorough and prompt archiving. Woodhouse is a NOAA employee. (On a previous occasion, I’d expressed frustration about non-archiving in connection with communications her, but that pertained to an article in which she was a co-author with a Hockey Team author, who had control over non-archiving. Here she seems to have had jurisdiction, rather than a Hockey Team author, and commendably archived promptly.)
The chronologies covered a range from 1126 to 2003 (not all chronologies covering the full range.) The detrending method was described as follows:
Detrend method: Negative exponential or linear regression of any slope, or 2/3-length spline. Detrending was done interactively, and if a negative exponential or linear regression fit poorly, a 2/3-length spline was used.
If you are familiar with non-linear methods, you might feel that this is hardly an adequate description of methodology, but this is an expansive methodological description by dendro standards.
A simple average of the 44 chronologies is shown below. Personally I don’t see a loud signal in the 1990s for this data set.
Unweighted average of co589.crn to co632.crn
At Jean S’s request, I did a Mannian PCA on the data. Now you don’t always get a HS from Mannian PCA (as we’ve mentioned before) . For example, if you take out the bristlecones from Mann’s network, you don’t get a HS even using the strongly data mining mannomatic – we menitoned this in one or more of our articles. In Mannian PCA, mining for a HS competes with an inherent signal. Thus, if there actually is a signal in the data, either Mannian PC or regular PC will both get similar results. In the von Storch and Zorita case, there is a very strong signal (in paleoclimate terms) and either method looks about the same (as does the mean). Also for data mining, the larger the network, the more series to mine for (so the instability increases with the number of series, rather than being reduced.) Anyway the PC1 doesn’t have an HS, the PC4 shown below has an HS. If this went into the regression stage (mannomatic part 2), the PC4 of this network would probably be enough to impart a HS to the reconstruction. With all the attention on the PCs, the other part of the mannomatic – spurious regression – sometimes gets lost.
PC4 from co589.crn to co632.crn