Plus I didn’t see this one before, it has a table in it with predictions based on the above method. Sorry if you all know this already,

ADVANCED SPECTRAL METHODS FOR CLIMATIC
TIME SERIES
M. Ghil,1 M. R. Allen,2 M. D. Dettinger,3 K. Ide,1
D. Kondrashov,1 M. E. Mann,4 A. W. Robertson,1
A. Saunders,1 Y. Tian,1 F. Varadi,1 and P. Yiou5
Received 28 August 2000; revised 3 July 2001; accepted 18 September 2001; published XX Month 2001.

[1] The analysis of univariate or multivariate time series
provides crucial information to describe, understand,
and predict climatic variability. The discovery and implementation
of a number of novel methods for extracting
useful information from time series has recently
revitalized this classical field of study. Considerable
progress has also been made in interpreting the information
so obtained in terms of dynamical systems theory.
In this review we describe the connections between
time series analysis and nonlinear dynamics, discuss signal-
to-noise enhancement, and present some of the
novel methods for spectral analysis. The various steps, as
well as the advantages and disadvantages of these methods,
are illustrated by their application to an important
climatic time series, the Southern Oscillation Index. This
index captures major features of interannual climate variability
and is used extensively in its prediction. Regional
and global sea surface temperature data sets are used to
illustrate multivariate spectral methods. Open questions
and further prospects conclude the review. INDEX TERMS:
1620 Climate dynamics (3309); 3220 Nonlinear dynamics;
4522 El NinËœo; 9820 Techniques applicable in three
or more fields; KEYWORDS: climate; dynamical systems; El
NinËœo; prediction; spectral analysis; time series

You ask how this stuff passed “peer review”? WEll, it didn’t just pass review – stadiums of climate scientists reviewed for IPCC TAR and none of them understood what he did either. What makes me more irritated is that I asked the NAS panel to find out – it was relevant to their mandate but they didn’t. Any business auditor would have.

How did it pass peer review?

Those who have frequented this site over the past couple of years would know that the climate scientists’ ‘golden seal of quality’ is ‘peer review’. If it is ‘peer reviewed’ it is A OK in the team and the IPCC clique who represent themselves as the ‘consensus of scientists’.

The term ‘peer review’ is represented as meaning that the papers have been quality checked by appropriately qualified, and independent, peer reviewers and have been approved of as being up to golden seal of quality standard.

Unfortunately, the reality is, as has been clearly exposed on this site, that for the team, ‘peer review’ actually appears to mean that a mate or colleague has cast his eye over the paper and pronounced that it is A OK. Peer reviewers apparently didn’t bother to really check the work for soundness. Nor did they check that basic requirements of sound science such as use of good quality statistics, proper archiving of data and methods etc have been met. When a truly independent peer reviewer turns up, and starts asking awkward questions, he is frozen out of the process.

It has become abundantly clear that the term ‘peer review’ in climate science means very little.

This exercise has been repeated using many different climate models, with the same qualitative result: one cannot simulate the evolution of the climate over last 30 years without including in the simulations mankind’s influence on sulfate aerosols and greenhouse gases.

So, we have two choices:

1) use Mann’s robust method (chops the peak of AR1 with p close to one. Then you’ll need the A in AGW

2) Forget Mann’s statistical signal processing, use AR1 with p=0.93, and then you can simulate the evolution of the climate over last 30 years. Without A.

Why 1) is better than 2) ? I’ve read many Mann’s papers so I would choose 2), if these arguments are the best they can give.

#183

I think that reproducing figure 3 b would help to solve that problem. But the not so surprising fact is that Jean’s code that reproduces fig 2 doesn’t reproduce fig 3 b. I think is very hard to find something that is correctly calculated in MBH9X. No smiley here.

The positive aspect of MannLees 96 paper is the number of equations that are presented. Almost all the reconstruction papers I have read contain only a few unnumbered equations or none. References are provide for the methodology/equations and after chasing down the references one finds no equations or detailed discussion there either. Very frustrating, as it make it difficult or impossible to follow or replicate the results.
The devil is in the detail.