Tim Curtin’s incompetence with basic statistics is the stuff of legend. Curtin has now demonstrated incompetence at a fairly new journal called The Scientific World Journal. Consider his very first “result” (emphasis mine):
I first regress the global mean temperature (GMT) anomalies against the global annual values of the main climate variable evaluated by the IPCC Hegerl et al.  and Forster et al.  based on Myhre et al. , namely, the total radiative forcing of all the noncondensing greenhouse gases [RF]
Annual(Tmean) = a + b[RF] + u(x)
The results appear to confirm the findings of Hegerl et al.  with a fairly high R^2
and an excellent t-statistic (>2.0) and P-value (<0.01) but do not pass the Durbin-Watson test (>2.0) for spurious correlation (i.e., serial autocorrelation), see Table 1. **This result validates the null hypothesis** of no statistically significant influence of radiative forcing by noncondensing GHGs on global mean temperatures.
Any first year stats student or competent peer reviewer should be able to tell you that you a statistical test cannot prove the null hypothesis. But it’s far worse than that as Tamino explains:
The DW statistic for his first regression is d = 1.749. For his sample size with one regressor, the critical values at 95% confidence are dL = 1.363 and dU = 1.496. Since d is greater than dU, we do not reject the null hypothesis of uncorrelated errors.
This test gives no evidence of autocorrelation for the residuals. But Tim Curtin concluded that it does. He further concluded that such a result means no statistically significant influence of greenhouse gas climate forcing (other than water vapor) on global temperature. Even if his DW test result were correct (which it isn’t), that just doesn’t follow. …
In other words, the regression which Curtin said fails the DW test actually passes, while the regression which he said passes, actually fails.
And — the presence of autocorrelation doesn’t invalidate regression anyway.
I have to wonder what kind of “peer-reviewed” scientific journal would publish this. Who were the referees for this paper?
And do check out Curtin’s responses in comments where he insists that he didn’t get it wrong. Curtin’s understanding of statistics is so poor that he can’t recognize his own mistakes.