Just after the release of the National Academy of Sciences report ‘Surface Temperature Reconstructions for the Last 2,000 Years‘ I compared the â€˜hockey stick graphâ€™ â€” a reconstruction of Millennial global temperatures based on tree-ring and other proxies by Mann and colleagues — to a broadway production in The Intelligent Design of MBH98.
Statistics packages like R are fun for ‘doing it yourself’ and getting involved in the debates.
However, for critical policy oriented work on climate
I strongly support the main findings of the recently released report
Ad Hoc Committee Report on the ‘Hockey Stick’ Global Climate Reconstruction“, aka the Wegman Report namely:
- Independent statistical expertise should be sought and used.
The report states on page 17 under the subsection discussing the background to principal components analysis (PCA) that:
In reality, temperature records and hence data derived from proxies are not modeled
accurately by a trend with superimposed noise that is either red or white. There are
complex feedback mechanisms and nonlinear effects that almost certainly cannot be
modeled in any detail by a simple trend plus noise. These underlying process structures
appear to have not been seriously investigated in the paleoclimate temperature
reconstruction literature. Cohn and Lin (2005) make the case that much of natural time
series, in their case hydrological time series, might be modeled more accurately by a long
memory process. Long memory processes are stationary processes, but the corresponding
time series often make extended sojourns away from the stationary mean value and,
hence, mimic trends such as the perceived hockey stick phenomena.
They then go on to argue for exactly the kind of models we have been describing in this blog.
One type of such long memory processes is a process driven by fractional Gaussian noise
(fractional Brownian motion). An object with self-similarity is exactly or approximately
similar to a part of itself. For example, many coastlines in the real world are self-similar
since parts of them show the same properties at many scales. Self-similarity is a common
property of many fractals, as is the case with fractional Brownian motion.
The paragraph concludes with a very stern criticism.
A serious effort
to model even the present instrumented temperature record with sophisticated process
models does not appear to have taken place.
Which constitutes another of the main conclusions:
- What is needed is deeper understanding of the physical mechanisms of climate change.