Obviously one of the major themes of the M&M articles is the remarkable lack of robustness of MBH98. BàÆà⻲ger and Cubasch, hot off the press at GRL, asks the following question:
whether or not the MBH98 and relative approaches are robust, including the predictor selection issues as argued by McIntyre and McKitrick [2005a], is the subject of the current study.
Without a model error estimate and without techniques to keep it small, it is not clear how these methods can be salvaged to become robust.
They cite both our 2005 articles approvingly.
They introduce the issue as follows:
a number of methodological issues [were] left unsettled in the original version [of MBH98], and which after several critical remarks [cf. McIntyre and McKitrick, 2003] led to the publication of a corrigendum. The discussion, nevertheless, continued [von Storch et al., 2004, McIntyre and McKitrick, 2005a, 2005b; Rutherford et al., 2005; BàÆà⻲ger et al., 2005], indicating that several issues are still unsettled, all related to the problem of reproducibility and robustness. For instance, assertions made by MBH98 and later about certain steps (such as rescaling) being “Å”Åinsensitive” to the method were hard to quantify and thus of little help. BàÆà⻲ger et al.  showed that the method is, on the contrary, highly sensitive to the variation of 5 independent standard criteria (as we call the steps here), resulting in an entire spectrum of possible climate histories.
They conclude as follows:
Any robust, regression-based method of deriving past climatic variations from proxies is therefore inherently trapped by variations seen at the training stage, that is, in the instrumental period. The more one leaves that scale and the farther the estimated regression laws are extrapolated the less robust the method is. The described error growth is particularly critical for parameter-intensive, multi-proxy climate field reconstructions of the MBH98 type. Here, for example, colinearity and overfitting induce considerable error already in the estimation phase. To salvage such methods, two things are required: First, a sound mathematical derivation of the model error and, second, perhaps more sophisticated regularization schemes that can keep this error small. This might help to select the best among the 64, and certainly many more possible variants. In view of the relatively short verifiable period not much room is left.
I wonder how long it will take realclimate to break the bad news.
BàÆà⻲ger, G., and U. Cubasch (2005), Are multiproxy climate reconstructions robust?, Geophys. Res. Lett., 32, L23711, doi:10.1029/2005GL024155.