Today on C-Span 2:
Doomage.
wha’ i can’t wait to see
is how the u.s. democrap media
spins the brains of tv viewers
from global warming cycle
to global cooling cycle!
si.
He reports a linear upward trend in temperature on page 4 but does not provide the statistics that tell you how likely it is that the trend is different than zero. I ran the actual regression numbers for two of the series, the one with the strongest trend (NASA GISS) and the one with the weakest trend (HadCRUT3). The results appear below after the text.
The bottom line is that neither of the "trends" comes even close to the normal p-value required to be considered statistically different from NO TREND. Generally p<0.05 is regarded as the threshold. His p-values, had he reported them, would have been about 0.17 (HadCRUT3) and 0.67 (NASA GISS).
This omission is really embarrassing--especially when reporting the p-values makes his "trends" meaningless. From glancing through the article, he almost certainly knows enough statistics to know that his "trends" are statistically meaningless and he almost certainly knows better than to compute a regression "trend" and not report the p-value for the regression. That he did not was, imho, almost surely intentional.
In formal terms, none of the series reported on page four of the article give any reason to reject the null hypothesis at the 95% (the standard), the 90% or even the 85% confidence level. The null hypothesis would be that there is NO trend in temperature between 1998 and 2007.
If this were a normal scientific paper, the reviewers would have required him to report that, as a result of his data, he could not reject the null hypothesis that there is NO TREND in temperature.
*******************
For hadCrut3 Series
TEMP = a*Year + b
Coefficients:
Value Std. Error t value Pr(>|t|)
(Intercept) -7.7865 18.6444 -0.4176 0.6872
Year 0.0041 0.0093 0.4396 0.6718
Residual standard error: 0.08852 on 8 degrees of freedom
Multiple R-Squared: 0.02359
F-statistic: 0.1933 on 1 and 8 degrees of freedom, the p-value is 0.6718
********************
For NASA GISS Series
TEMP = a*Year + b Value Std. Error t value Pr(>|t|)
(Intercept) -39.6009 27.0090 -1.4662 0.1808
V2 0.0204 0.0135 1.5092 0.1697
Residual standard error: 0.1282 on 8 degrees of freedom
Multiple R-Squared: 0.2216
F-statistic: 2.278 on 1 and 8 degrees of freedom, the p-value is 0.1697
Just one more note. What is also interesting in this paper is that noone is discussing the fact that the 1999 and on numbers (which this AGW’er accepts as correct) are way below the IPCC forecasts.
Assessing just how badly the IPCC did is difficult because of the sloppiness of the IPCC forecasts—you really can’t tell what the meaning of their “confidence intervals” are. But if they are typical confidence intervals (95%) bands, the probability that the IPCC forecasts are too high is very large (I ran those numbers about a month ago and was suprised that noone is talking about just how far off the IPCC was.)
Even if you toss the IPCC confidence intervals and use the IPCC temperature forecasts only, it is still highly probable that the IPCC forecasts are too high.
I’ll try to find these numbers and post them here.
Syria reached -22F this winter and Antarctica is 2C below the mean. Do you want to hear about China's recent coldest winter in 100 years?
Forget El Nino, the error bars from 1995 and the 2008 overlap which means there has been no statistically significant warming during that time. So says Richard Lindzen. And I think he is absolutely correct.