The question in my mind now is…. what is treeline? This is not cynical.

Where I was, there was no specific treeline. The trees are not in the form of a closed forest but rather were in clumps of 2 – 20 trees with large spaces between them, on all but north facing slopes. Some slopes in the area are completely treeless and instead have brush. The true upper limit, above which there are truly no more trees (including no more krumholz) varies considerably. One peak it’s at 8000 feet, the next one 10000 feet. On some peaks, there are no krumholz, the trees just stop – below are normally sized trees, above, none.

Even slogging through deep snow, had I wanted to do some coring, I would have had no trouble with equipment transport – would have strapped it to my pack …. LOL!

http://www.geos.ed.ac.uk/homes/rwilson6/Publications/LuckmanandWilson2005.pdf

The composite MXD and RW chronologies, lagged at t and t+1, were regressed (using a stepwise process) against several combinations of mean, maximum and minimum temperature variables. Optimal results were found for May’€”August Tmax using MXD (t) and RW (t and t+1) as predictor variables. The calibration and verification results plus plots of actual and predicted values are presented in Fig. 3. There is, statistically, no difference between the calibration results using the RCS generated MXD data (hereinafter RCS2004; Fig. 3a) and a second reconstruction (hereinafter STD2004;
Fig. 3c), employing composite chronologies developed using only standard traditional’ detrending methods (negative exponential and linear fits to the data). Both models explain 53% of the temperature variance and pass all conventional verification tests. The calibration for both RCS2004 and STD2004 is stronger than that for L1997 which explained 39% of April’€”August Tmean and failed verification using the more stringent CE statistic.

These improved results are, in part, related to the fact that calibration was made against Tmax (see Wilson and Luckman 2003). Regression results of the RCSMXD and STD RW data against May’€”August Tmean are weaker (Fig. 3b).

I found this in WL05 and it gives me a better view of the sensitivity issue to which I was referring (They use a 20 year spline in presenting the information). To be of the most use for climatology, do not we need to find proxies that reconstruct mean temperatures for the entire year and do it such that we are not so concerned about proxy to proxy correlations but that proxies reproducibly give similar measures of climate changes?

In Figure 3 in WL05 it appears to me that STD and RCS predicted values do not follow the extreme values of the actual Tmax temperatures.

http://www.climateaudit.org/wp-images/tree/treethermometer.jpg

Rob, I am back from a couple of walks but we have not heard from you since you went for a beer. I was hoping that you could provide a few lines in a post giving more details on the graphs in post #45. I will eventually go back to the original papers, but in the meantime it would help to know the locations of the proxies listed and the corresponding instrumental temperature data. I continue to see trends over significant time periods going in different directions for the top two proxies and judge that a couple of graphs with different moving averages (comparing 2 proxies at a time to avoid the plate of spaghetti) might help us see what is really going on.

I have recently looked at Midwest historical crop yields (corn and soybeans) as it related to climate (primarily maximum monthly selected temperatures and precipitation). What I saw was a strong interaction between temperature and precipitation effect on yields when that product went below a given level (high temperature and low precipitation). Most of the time, the yields were on a plateau where yields were essentially independent of temperature and precipitation. There were reasonably high correlations of yields with temperature, but that came primarily from the droughty years. Outliers on the graph were always below the plateau line and appeared to be related to plant disease and insect damage. Would these observations have any relationships to the tree physiology affecting TR growth?

I would expect these crop yields to react similarly to similar changes in climate conditions much as you have shown with the 4 proxies of tree rings, but that does not answer the questions about the separate effects of temperature and how trees would react over longer periods of time.

Also, there is the question of changing localized non-climate factors such as fertilization that could exaggerate or diminish the effects of temperature. One would expect to see a good proxy to proxy correlation under these conditions, but with differing local responses/sensitivities to temperature.