Science Heresy  December 2010 Huybers and Curry (2006)
Reid (unpublished)
How Peer Review Fails by John Reid A detailed analysis of one reviewer's comments
My paper on Ice Ages was rejected by Journal of Climate. The original reviews can be downloaded here (A) and here (B). Below are my comments on Reviewer B’s review of my paper. My comments are in italics.
Review of "A reexamination of Ice Age Time Series" by J.S. Reid
My “strange” point of view is described in more detail
here
In contrast to the author's claim, it is simply not possible, in physics,
to define a sharp distinction between the two, in particular from data analysis.
See
Any physical realisation of a stochastic process is actually a deterministic chaotic process.
Is this an a priori philosophical statement, part of the Reviewer’s belief system or is it founded in observation? If the latter I would appreciate a reference.
"Stochastic processes" are a mathematical notion, not a physical one.
For instance, the random number generator of any computer is a deterministic
algorithm very sensitive to initial condition (this is called chaos).
What a strange interpretation of the term “stochastic” which actually means “governed by the laws of probability”. Are we to believe that the equations of statistical physics, e.g. the FokkerPlanck equation, are purely mathematical?
A contrario, it is very easy to design mathematical stochastic processes with very nice spectral peaks (for instance, AR(n) processes when n>1).
Agreed. It is impossible, experimentally, to detect the difference between a narrow band AR(2) process and a sine wave plus added noise. Mathematically the difference is that in the first case the autocovariance function tends to zero at infinite lag and this is not something that can always be decided experimentally from a time series of finite length.
So any attempt to discuss "stochasticity vs. determinism" by simply looking at the spectrum is completely meaningless. The distinction between the two is always a matter of taste, and not a fundamental one.
So does God play dice with the Universe? Einstein seemed to think it was fairly fundamental.
I believe the author should read some textbook on this subject before writing a scientific paper.
See below.
Furthermore, in practice, the "continuous or discrete" nature of a spectrum is linked to the hypothesis made on the time series at infinity (is it a finite time series or a periodic one). This is always an assumption, not a result. So it is not possible to distinguish a "continuous spectrum" from a "discontinuous" one from data analysis. This is of course particularly true when the data series is short, as often in paleoclimatic situations (we are dealing here with a 100 kyr periodicity on a 400 kyr time series ! There is no chance to find out if this is "periodic" or "pure chance").
Perhaps the Reviewer could propose an alternative, deterministic model which leads to the observed n=2 power law spectrum.
The whole discussion pages 6 to 8 is completely meaningless.
If the Reviewer cannot understand the arguments presented he should not have agreed to review the paper in the first place.
A list of several other MAJOR flaws of this manuscript:
 FFT (or any fourier transform algorithm) is not a suitable algorithm for spectral
analysis. This problem is actually THE central problem of spectral analysis
(again, please look at a basic textbook on this subject) since it is too unstable...
Statistically significant spectra require some "spectral smoothing" using one or
another technique. BlackmanTukey is one of them.
This is the most revealing statement in this review. Blackman and Tukey (1959) “The Measurement of Power Spectra from the point of view of Communications Engineering.”(B&T) is an early text book in the field of signal processing. It predates the computer age and describes a crude but computationally efficient method for computing power spectra with a hand calculator. The resulting spectral estimates are highly distorted by the process.
It is more than a bit awkward to state that FFT (Cooley et al. 1965) is a recent
technique of spectral analysis (which is actually not the case), when many recent
papers have proposed new (true spectral analysis) ones (MTM, SSA, ...).
Spectral analysis is a bit more than a Fourier transform.
Well at least the FFT is slightly more recent than B&T. The idea that the FFT “is not a suitable tool for spectral analysis .. because it is too unstable” has also been around since the 1960’s. I cannot find an original reference to this idea. Perhaps it is a tearoom myth rather than a peerreviewed hypothesis. In any case it is incorrect. The term “unstable” comes from signal processing.
An inverse square law red spectrum is the outcome of integrating a white noise process. If the original process includes a cyclic component which was added prior to integration then whitening by taking first differences is a sensible thing to do. If, on the other hand, the cyclic components were added after the integration then it would be incorrect to attenuate these components by differencing.
Most geophysical time series analysis are envisioned the opposite way: the signal is in the red part of the spectrum, because we are not dealing with perfectly periodic signals.
Yes, the thrust of the paper is to place an upper limit on periodic signals which should be evident in the spectra if the Milankovic hypothesis is correct.
All current models of glacialinterglacial cycles are non linear (and even strongly nonlinear). Their spectral response is usually not "sharp" but is often quite "redish", in particular when the time window is as short as 400 kyr which is not sufficient to resolve potential fine structures in the spectrum. In practice, fine structures are meaningless for nonstationary signals.
So Reviewer B is saying that even if orbital forcing were true, we would not expect to find evidence for it in the data because of the nonstationarity of the process and the nonlinearity of proposed mechanisms.
I therefore do not understand the author's desire to isolate these spectral lines, that are probably non existent and certainly not relevant.
The absence of spectral lines representing cyclical forcing of climate is highly relevant. It is called "hypothesis testing". It is an important aspect of the scientific method.
Again, an AR(2) process can also be described as a "deterministic" oscillator in some circumstances since there is already some physics into it (two time constants).
What on earth is he talking about? An autoregressive process is a stochastic process by definition.
In contrast to the author's view, Physics does extend beyond linear systems and simple linear techniques can be misleading.  there is a clear misunderstanding of the paleoclimatic records as highlighted by the 10Be discussion.
Granted 10Be flux can be influenced by climate, and perhaps I should have made mention of that, but that does not explain why the 10Be flux is well correlated with DansgaardOeschger events between 20 and 40 ky BP, but not with the most recent termination and the Younger Dryas between 10 and 15 ky BP as seen in my Figure 7 (below)
 it is quite well known within the climate community that there is no simple
relationship between the insolation forcing and the glacialinterglacial cycles. This
"finding" of the author is not really a news. The litterature on the subject is vast. It strikes me that, except for the data sources, the references given by the author
are quite old (about 10 to 20 years old). Apparently, the author is not up to date
on the litterature on the subject. The most recent cited paper concerning the
dynamics of glacial cycles is Milankovitch (1941)...
I thought it appropriate to reference the scientist who first proposed the theory. This was the earliest reference I could find although I believe Milankovic thought of it as early as 1912.
 it seems very strange that the slope of the red spectrum is "exactly" 2.
The 2 slope is an experimental result, not a preconception. It can clearly be seen in the spectral estimate in Figure 2 of my paper (top of page, right).
The 1.64 slope is a result that points to nonlinear dynamics.
How exactly? Has anyone proposed a nonlinear model which predicts such a power law? If so there is no reference to it in Huybers and Curry’s paper.
I could add many more points that indicate why this manuscript is not suitable for
a publication in Journal of Climate, but I will stop here. In summary, there is no
new scientific content in this manuscript, the authors is not mastering the
question he is trying to address, and the conclusions are either obvious or wrong.
"And he is not one of us."
