In some recent commentary trying to backpedal from the hockey stick, "detection and attribution" studies have been cited as alternative validations and Hegerl et al  is cited as a key example. I have not looked in detail at these studies, but some features of Hegerl at al.  struck me as so obvious that they are worth pointing out.
The most striking aspect to me is how little "explanation" of the proxy reconstruction CLH seems to be accomplished by Hegerl et al. . Look at the top panel and then look at the residuals in the bottom panel. For most of the period, the residual is about the same size as the original series and it looks to me like virtually nothing is "explained" in statistical terms. Table 1 of Hegerl et al  states that 57% of the variance is explained by the forcing model. It sure doesn’t look like it. It would be nice to see the calculations.
Original Caption: Figure 1. Detection results for the updated Crowley and Lowery  reconstruction of decadal Northern Hemispheric mean temperature (north of 30N, calendar year average). Upper panel: Paleo reconstruction (black) compared to the instrumental data (grey) and the best estimate of the combined forced response (red), middle panel: response attributed to individual forcings (thick lines) and their 5–95% uncertainty range (thin lines), lower panel: residual variability attributed to internal climate variability and errors in reconstruction and forced response. An asterisk “Å”Å*” denotes a response that is detected at the 5% significance level.
A few other comments. This study is not really "independent" of the Hockey Team. Crowley is a co-author and lead author Hegerl is his wife.
The CLH reconstruction shown in the top panel is a new version of Crowley and Lowery . It is described in the text as follows:
a modified version [T. J. Crowley et al., in preparation, "Å"ÅCLH''] of the Crowley and Lowery [2000, hereinafter referred to as CL00] reconstruction (correlation with CLH 0.94). The latter is a weighted average of 9 long decadal or decadally averaged records over the Northern Hemisphere mid-to-high latitudes (30–90 N, the records sample both the warm and cold season, with a likely bias towards the summer half year). The weights are determined from the regression coefficients of individual records with the 30–90 N annual mean instrumental record during the period of overlap [Jones et al., 1999]. The resulting paleo time series was scaled so that the regression fit with the instrumental data from 1880–1960 had a slope of 1.0 [decadal correlations of 0.81 (with trend) and 0.66 (detrended)]. For consistency, the scaling of E02 is based on the same period and also decadally filtered data.
Unfortunately, I have been unable to locate Crowley et al., in preparation. If the original data was "misplaced" during Crowley’s move from Texas (see this post) , it seems odd that they managed to create a new version. Perhaps they will be able to locate the missing data by the time of publication. The weighting of series is different than in Crowley and Lowery , as is the number of series – reduced from 15 to 9. The effect of the reduction in number of proxies is to make the 20th century peak larger than the medieval peak (which it isn’t otherwise). See my post on Crowley and Lowery . If the medieval peaks in CLH are unexplained (even in the mitigated form of CLH), how do you know that the 20th century peak isn’t something similar?
Gabriele C. Hegerl, Thomas J. Crowley, Steven K. Baum, Kwang-Yul Kim and William T. Hyde, 2003. Detection of volcanic, solar and greenhouse gas signals in paleo-reconstructions of Northern Hemispheric temperature, GEOPHYSICAL RESEARCH LETTERS, 30(5), 1242, doi:10.1029/2002GL016635. Downloaded from http://www.nicholas.duke.edu/people/faculty/hegerl/2002gl016635.pdf