Yamal- The Dirty Dozen
Posted by Jeff Id on October 5, 2009
We’ve all been looking at the Yamal (Steve Mosher named)treemometer ring width data. Yamal is a tree ring series with a huge hockey stick blade used in and likely to be highly influential in a lot of serious studies which demonstrate the unprecedentedness of recent temperatures. When Steve McIntyre replaced 12 of the hockey stick creating proxies (the dirty dozen) with equally valid schweingruber proxies the blade of the hockey stick disappears along with the unprecedentedness. Of course the boys at “Real” Climate made a big stink about it but notably missed any specific criticism of the methods or data chosen. However, in this post I looked at the methods of RCS standardization and the effects it has on the series.
RCS is a method for correcting the ring widths of trees based on the age. For instance, we would expect that a young tree would have thicker rings at its core. As it grew thinner rings would form with diameter and eventually the diameter would become basically a non-factor. So dendro guys figure that they should fit an exponential decay function to tree rings and that will give a basic correction factor for total width.
The function is of the form
correction = A + B * e ^ -(C * age)
Don’t worry too much if that’s not a familiar equation to you, you’ll figure it out either way. I’m sure it is to many of my readers though. This equation is fit to 100% of the data simultaneously in Yamal. The assumption is:
1 – All the trees in the same conditions grow at the same rates.
2 – Fitting the equation to all trees together will average out over all the variable climates and despite different conditions, we can achieve a similar result to #1.
There is a problem with these assumptions which occurs at the endpoints of dendroclimatology reconstructions in that the most recent trees are still alive and therefore on average going to have a skewed age – either younger because they are equal and haven’t died or older (as is the case here) because trees that are long lived are easier to find than partially fossilized mud bound trees.
What it means is that the assumption fails for trees existing in vastly different conditions.
Now what I wanted to see was first, what is the correction factor per year used and second how different is the correction factor when fit to the dirty dozen. After all, tree age, location, group and other conditions affect trees dramatically. So my question was – If we had only the 12 Yamal trees, how would the correction factor look.
The dozen trees fit to the same function have a very different result when run alone – these trees are different! Now climatology in general may be tempted to call this plot bunk because these trees are chosen in a timeframe where we should see hockey stick temperatures and we have too few samples. However, I would remind climatology that these were the same 12 trees used to create the MASSIVE blade on a 200 plus core study.
Well the next question I had was what would these 12 series look like wih RCS if the dirty dozen were used for the exponential fit alone.
The blade is dramatically reduced!! Just to show you how different Yamal is without the RCS correction factor calculated from the entire dataset, check out Figure 3. The black line is the same 12 trees with the original correction factor, the red is the new also valid corrections.
Note the substantial drop in the peak tempeatures and the fact that pre-1900 is actually higher in temperature than 2000. Below is the zoomed in version.
Now don’t forget that despite the low count of trees for my RCS standardization, the “blade” years of the Yamal hockey stick only consist of those trees. These TWELVE trees were considered good enough to represent a huge portion of the planet in reconstructions. In the recent Arctic temperature reconstruction, Yamal was individually responsible for the temperature being unprecedented in the last 2000 years. Yamal represented 1/23 of the Arctic in that reconstruction yet it’s huge blade had an enormous influence on the outcome.
Now let’s talk about the green line. This line is RCS with NO Yad061 – well Yad is the leader of the dirty dozen. Meaner and taller than the rest. The green line in the above two plots represents what happens when Yad is removed – Ocean’s eleven?? A single tree with a huge influence on the hockey stick. Now again the green line is normalized to the original 12 series.
Honestly, the RCS methodology makes some sense, however the blanket application of the same correction factor across different species and locations of trees is hard to swallow. I mean, the assumptions simply don’t allow for different species of trees to grow at different rates in different soil and weather conditions. That’s not a particularly comforting assumption and engineering wise, it requires validation.
If you take anything away from this think about this question — What do these plots mean?
Actually, it’s quite simple and is shown in Figure 1.
They change in growth rate of the dozen trees comprising the blade of the influential Yamal hockey stick are NOT the same as the mean of the trees in the rest of the series.
We don’t know if the difference is due to species, location or some other factor, however these trees have vastly different ratio”s in growth rate from young to old. Briffa attributed it to temperature and it was eagerly accepted by climatology, however the lack of tree count in the important portion is a huge embarassment.
As in the Antarctic reconstruciton, I like to refer to the simple methods as a sanity check. We know that the assumption that trees have wider rings and faster growth in higher temperatures is for the most part reasonable. The same is true for sunlight, moisture, nutrients and CO2. However, exraordinary differences in growth rate such as the Briffa Yamal series claim, require extraordinary evidence.
We would expect in a large sampling of data that the older and younger rings would balance out. The following figure is a mean of tree ring widths for the series. It should be relatively difficult for climatology to explain away the average of the Yamal series.
The mean just doesn’t have the same impact does it?
It is my contention that the Mean is equally as valid (and perhaps more so) a scribble as Briffa’s Yamal. All tree ring widths are accounted for equally, tree counts per year are taken into account and the result doesn’t match the RCS version – at all.
Trees make lousy thermometers.