Mann et al 2009 reconstructs Atlantic tropical cyclone counts resulting in a curve that looks pretty much like every other Mannian curve. Atlantic tropical cyclone counts as a linear combination of reconstructed Atlantic SST in the east tropical Atlantic "main development region" (MDR), reconstructed El Nino and reconstructed North Atlantic Oscillation, using a formula developed in (3,16) - which surprisingly enough turn out to be articles by Mann himself (Mann and Sabatelli, 2007; Sabatelli and Mann 2007) previously discussed at Climate Audit here. This is summarized in the article as follows:
An independent estimate of past tropical cyclone activity was obtained using a statistical model for Atlantic tropical cyclone counts. This previously developed and validated 3,16 statistical model conditions annual Atlantic tropical cyclone counts on three key large-scale climate state variables tied to historical variations in Atlantic tropical cyclone counts: (1) the SST over the main development region (MDR) for tropical Atlantic tropical cyclones, which reflects the favourability of the local thermodynamic environment; (2) the El Nino/Southern Oscillation (ENSO), which influences theamount of (unfavourable) vertical wind shear; and (3) the North Atlantic Oscillation (NAO), which affects the tracking of storms, determining how favourable an environment they encounter. The statistical model was driven by proxy-based reconstructions17,18 of these three state variables (Fig. 2), yielding a predicted history of Atlantic tropical cyclone counts for past centuries.One doesn't necessarily expect much clarification from Mannian methodology and this time Mann surpasses himself. Remarkably the Methods Summary is almost word-for-word the same as the article. It's actually a little less. Mann explains once again that they reconstructed hurricane counts by using reconstructions of the SST in the Atlantic Main Development Region, El Nino and the North Atlantic Oscillation, with the only new information being that they only used the North Atlantic Oscillation reconstruction over the past 500 years from Luterbacher (18), but it didn't matter. Mann again cites (3,16) Mann and Sabatelli; Sabatelli and Mann.
We used a statistical model of tropical cyclone counts as conditioned on3,16: the MDR SST, the ENSO (measured by the boreal winter Nino3 SST index), and the boreal winter NAO index The statistical model, which is trained on the modern historical record, has been shown in independent statistical validation experiments3,16 to resolve roughly 50% of the interannual and longer-term variations in Atlantic tropical cyclone counts. The model, in this study, was driven by decadally smoothed proxy reconstructions of the three required climate indices to yield predictions of tropical cyclone activity over past centuries. The MDR SST and Nino3 reconstructions were derived from proxy-based surface temperature patterns spanning the past 1,500 years17. Though an NAO reconstruction was available only for the past 500 years18, the NAO influence was found to be very minor (Supplementary Information).The Full Methods in the online version adds little additional information. Again we are told that they used a statistical reconstruction using Atlantic SST and El Nino from the enigmatic ref 17. Confidence intervals appear to be done using the recipes of Mann et al 2008 with lots of "decadally smoothed" series.
Statistical prediction of tropical cyclone counts using proxy reconstructions. Here the model was applied to decadally resolved reconstructions of MDR SST and Nino3 described by ref. 17 and the decadally smoothed winter NAO index of ref. 18. For the instrumental interval (1851 to present), standard errors due to uncertainties in the model coefficients were calculated from the residual decadal variance diagnosed from the validation residuals (standard errors were averaged for the early and late intervals of the split calibration/validation procedure). For the pre-1851 statistical model estimates, which are driven by reconstructed climate indices, there is an additional component of uncertainty due to the uncertainties in the climate indices themselves. This contribution was estimated by Monte Carlo simulations in which the statistical model was driven with an ensemble of 2000 randomly perturbed versions of the statistical predictors consistent with their estimated uncertainties17, and an additional random term due to the uncertainties in the model coefficients.The Supplementary Information sheds no light on the methodology or the proxies.
The Supplementary Information contained no data sets. The proxies used for the Mann et al submission are not even listed.
The edifice is built on the SST and Nino3 reconstructions, both of which are references to the enigmatic reference 17, which turns out to be an unpublished submission of Mann et al.
17. Mann, M. E. et al. Global signatures of the Little Ice Age and the medieval climate anomaly and plausible dynamical origins. Science (submitted).At the time that Nature published this article, there was precisely NO information available on what proxies were used in the reconstruction of Atlantic SST or El Nino or how these reconstructions were done. Did any of the Nature reviewers ask to see the other Mann submission? I doubt it. I wonder if it uses Graybill bristlecone pines.
UPDATE: Roger Pielke Jr observes below that Mann has provided a "grey" Supplementary Information at his website here holocene.meteo.psu.edu/~mann/Nature09/ , which commendably includes source code and data from the check-kited paper on i.e. we still don't know anything about the reconstruction proxies for Atlantic SST or El Nino. To my knowledge, there is no reference in the original article or Nature SI to the Supplementary SI at Mann's website; there is no link on Mann's website to the Supplementary SI and the directory hosting the Supplementary SI is not readable or searchable. Unless you know the precise name of the subdirectory, you can't there. Right now, I don't know how Roger found the Supplementary SI, but once located, the documentation looks at first glance to be very commendable.