I’m finding some benefit to having spent some time on station histories prior to my present re-visit to Mannian proxies. Digging into the handling of station histories gives some interesting perspectives on network handling that are worth considering for tree ring networks.
For example, assume for a moment that North American tree ring chronologies used in MBH98 actually were little thermometers. Yeah, yeah, I know all the problems with them. But let’s suppose that they actually were little thermometers, noisy little station histories going back hundreds of years. What would Phil Jones or Hansen or USHCN would do if they had dozens of North American station histories going back 600 years?
You know right away what they’d do: they’d lay out a grid over North America; they’d allocate each station to its respective gridcell; they’d form anomaly series by subtracting the mean over a common interval, take an average over each gridcell of available records and then take an average over all the gridcells.
Would they do principal components on the raw geographically inhomogeneous station data? Of course not. What meaning could one possibly attach to geographically inhomogeneous station data? Would they do stepwise principal components when there was missing data? The mind boggles at CRU doing something like that.
As an exercise, I thought that it would be interesting to do a CRU-type “gridcell history” for Mann’s NOAMER network.
An interesting issue arose in starting this – one that we reflected on a bit in MM2003, but haven’t discussed much. The MBH “NOAMER” network is actually a subset of about 75% of the North American tree sites used in MBH98. The first figure shows a location map of all the tree ring sites mentioned in the original MBH SI, color coded to illustrate the following.
The pink dots show the Graybill bristlecone sites in the AD1400 network – the sites that so much controversy attaches to. Geographically they obviously in a restricted range in the US southwest; the blue dots show the rest of the 70 sites in the AD1400 NOAMER network; the green dots show the other 141 sites used in later steps of the NOAMER network; the cyan dots show the Jacoby network (each site being used individually in MBH), with the Gaspe site used in the AD1400 regressions shown a little larger. The brown dots show the Stahle SWM and Stahle OK networks, many sites being between “NOAMER” sites and a couple of sites in the Four Corners area being used in both networks. The red dots show the sites listed in the original SI but not used in the NOAMER network – for reasons that have been never been properly explained. Their non-use was admitted in the MBH Corrigendum , which provided a false excuse for their non-use:
These series, all of which come from the International Tree Ring Data Bank (ITRDB), met all the tests used for screening of the ITRDB data used in ref. 1 (see ref. 5), except one—namely, that in 1997, either it could not be ascertained by the authors how these series had been standardized by the original contributors, or it was known that the series had been aggressively standardized, removing multidecadal to century-scale fluctuations.
This is untrue. Some of the excluded series (red) were Schweingruber series; all sorts of Schweingruber series were used in MBH98 and the excluded series came from identical publications as included series. This was pointed out to Nature, but they didn’t care. When I plotted this up, I noticed two red dots in Alberta – these are both locations where Rob Wilson has worked; one of the series was used in Esper et al 2002.
Anyway, continuing with my development of a “station history” type procedure. As a test, I did one on the MBH NOAMER network without worrying about exclusions and Stahle and that sort of stuff. I standardized the series on 1613-1900 as a long period over which the MBH NOAMER network has values to the beginning. My guess is that standardization with 1613-1970 values wouldn’t make much difference and I’ll probably do this calculation as well if I pursue this any more.
I allocated all the series to 5×5 Jones-style gridcells and averaged all available standardized chronologies within each gridcell, thereby forming a gridded network of 31 gridcells. I then calculated an annual average over all available values using a truncated mean (not using the two extreme values on either end). This yielded the following North American Tree Ring Index, shown to 1980 the final year of MBH tree ring calculations.
I’ve marked a few years with extreme values. 1934, known to be an exceptionally hot year in the U.S., had the lowest “Tree Ring Index” in the period 1880-1980. 1946 had the highest. The decade in the 1840s had exceptionally low growth – something that we also noticed in our Almagre samples. There’s certainly no hockey-stick in this Tree Ring Index.
Intrigued by this result, I download a CRU gridded temperature history (using HadCRU2 for this since it’s a little more contemporary to MBH98) and calculated the correlation of the gridded growth index to CRU temperature history for each gridcell. I then made a contour map using the akima package that I had previously used for station history plots. For this calculation, I re-did the grids using all the available stations – Stahle, Jacoby, excluded sites.
Obviously one feature that sticks out like a sore thumb: the gridded growth histories in the U.S. Great Plains are negatively correlated to temperature. It looks to me like the core of this negative correlation is pretty near Crawford, Texas.
There’s a strip along western Canada that shows positive correlation. If you look back at the location map, you’ll see that this has mostly been filled in by interpolation as there are no MBH network stations. Also something curious – this positive correlation area is bounded at either end by stations that Mann deleted from his network, stations that weren’t used.
So we can see one reason why a station history approach doesn’t work very well – we don’t know whether our little thermometers are reading up or down. For example, suppose that a new treasure trove of instrumental measurement data decoded from Aztec or Maya glyphs were delivered to Phil Jones – the only problem was that you didn’t know whether the numbers ran up or down. Even CRU wouldn’t just dump all this data into their data base and hope that some algorithm could sort it out. Before the Aztex instrumental data was incorporated into station history data bases, one would hope that some sort of technical study would be done showing how to convert the Aztec instrumental data into modern terminology, demonstrating which direction was up in their nomenclature and what their scale was? Tree rings should be no different.
And what if Phil Jones found that some of the Aztec data was actually instrumental precipitation measurements. Would he just dump that into his data base and hope that it improved things? That maybe there was a teleconnection between Aztec instrumental precipitation and temperatures in some other part of the world. As soon as you even write this down, you realize that someone would first have to demonstrate that there was a solid relationship between modern measured precipitation in the Yucatan and modern instrumental temperatures in (say) Timbuktu or wherever, and demonstrate that this information actually aided in the estimate in a way that rose above data mining before assuming that Aztec instrumental precipitation measurements contained useful information for temperature reconstructions.
Comparison to the MBH PC1
The above graphic showing the relationship of gridded tree ring growth and gridcell temperature may provide a helpful perspective on bristlecones and the Mannian PC1 (or the PC4 or whatever).
In the graphs below, I show the geographical properties of the MBH weighting so that readers can appreciate how the locations of the famous MBH PC1 fit in the above map. On the left I’ve done a contour map in which each value of the MBH98 PC1 eigenvector is located spatially at its site. I’m experimenting a little with this still. On the right is a plot in which the weight of each site is shown by the area of the dot. Graybill bristlecone/foxtail chronologies are shown in red; all others are shown in green. The key Sheep Mt site is near the CA-NV border in California.
The Graybill bristlecone chronologies (especially the key Sheep Mountain chronology) are, on this coarse scale, in areas where there is neither a strong positive nor strong negative correlation of growth to temperature – in a shoulder zone. This agrees with site specific analyses, which show little positive correlation of bristlecone growth to temperature (nor negative correlation.)
For someone that’s looked at a lot of geophysical maps in my life, the supposed occurrence of bristlecone chronologies measuring world climate in such a shoulder zone raises red flags. Why should a site chronology in a U.S. shoulder zone have a loud response to world climate, when the chronology (and the gridded “station history”) have negligible correlation. One would surely investigate the possibility of some artifact in the Graybill chronology. Given Linah Ababneh’s failure to replicate the Graybill chronology, the alarm bells should be ringing even in Mann-world.
UPDATE: Woodhouse and Overpeck (BAMS 1998) show the following comparison between a tree ring reconstruction of drought and observed Palmer PDSI in 1934 – a year of low overall growth. It’s not that relevant specialists are unaware of the connection between U.S. tree rings and drought. Exactly why none of them ever commented on these issues in connection with MBH is something you’d have to ask them.
Here’s the MBH98 PC1 (bristlecones) again marking 1934. Given that bristlecone ring width are allegedly responding positively to temperature, it is notable that the notoriously hot 1934 is a downspike.