I'd like to commend to readers a couple of postings on the subject of statistical significance in the temperature records.
Last week a little visited website called Real Climate had an article by climatologist Stefan Rahmstorf, which addressed many of the issues discussed here in recent months. What I found interesting was that there was a measure of agreement:
...the confidence intervals (and claims of statistical significance) do not tell us whether a real warming has taken place, rather they tell us whether the warming that has taken place is outside of what might have happened by chance.
You will hear no dispute of that sentiment from this quarter. However, as readers here know, it is hard to demonstate that the post-industrial warming is outside the range of natural variability, a subject that the Rahmstorf article rather glosses over, instead preferring to focus on the pause:
...the question the media love to debate is not: can we find a warming trend since 1998 which is outside what might be explained by natural variability? The question being debated is: is the warming since 1998 significantly less than the long-term warming trend? Significant again in the sense that the difference might not just be due to chance, to random variability? And the answer is clear: the 0.116 since 1998 is not significantly different from those 0.175 °C per decade since 1979 in this sense.
It goes on to look at a changepoint analysis of the data performed by Niamh Cahill, a postgraduate student from Dublin.
The optimal solution found for the global temperature data is 3 change points, approximately in the years 1912, 1940 and 1970. There is no way you can get the model to produce 4 change points, even if you ask it to – the solution does not converge then, says Cahill. There simply is no further significant change in global warming trend, not in 1998 nor anywhere else.
And so if she is to be believed we are just seeing long-term warming with natural variability superimposed. However, Ms Cahill's conclusions have been challenged at WUWT, where reader Jeff Paterson seems less than impressed:
[Cahill's] basic thesis is that since a CPA analysis detects no significant recent change in the slope of the GISS dataset there is no pause. Unfortunately, the analysis is of no value because, as is commonly known, the CPA cannot be used on auto-regressive time series.
I am insufficiently expert to be able to say who is right here. Ms Cahill lists time series analysis as one of her areas of expertise so I am dumbfounded if she really has made the error Paterson says she has.
Do any readers here know the answer?