First, as I’ve mentioned before, there is a Reddit “As Me Anything” (AMA) going on right now with Stephan Lewandowsky, and if you are into Reddit AMA’s and climate change related issues you should check it out. Lewandowsky is a co-author of the famous Frontiers Retracted paper, though the subjects being discussed at the AMA range far beyond that particular issue.
Second, there is new paper out that looks very interesting. I’m still trying to absorb it and I’ve asked the author for some clarifications on some issues, but already the Global Warming Deialosphere is all over it, so it must have some merit!
From the press release:
Is global warming just a giant natural fluctuation?
An analysis of temperature data since 1500 all but rules out the possibility that global warming in the industrial era is just a natural fluctuation in the earth’s climate, according to a new study by McGill University physics professor Shaun Lovejoy.
…Rather than using complex computer models to estimate the effects of greenhouse-gas emissions, Lovejoy examines historical data to assess the competing hypothesis: that warming over the past century is due to natural long-term variations in temperature.
“This study will be a blow to any remaining climate-change deniers,” Lovejoy says. “Their two most convincing arguments – that the warming is natural in origin, and that the computer models are wrong – are either directly contradicted by this analysis, or simply do not apply to it.”
Lovejoy’s study applies statistical methodology to determine the probability that global warming since 1880 is due to natural variability. His conclusion: the natural-warming hypothesis may be ruled out “with confidence levels great than 99%, and most likely greater than 99.9%.”
“We’ve had a fluctuation in average temperature that’s just huge since 1880 – on the order of about 0.9 degrees Celsius,” Lovejoy says. “This study shows that the odds of that being caused by natural fluctuations are less than one in a hundred and are likely to be less than one in a thousand.
“While the statistical rejection of a hypothesis can’t generally be used to conclude the truth of any specific alternative, in many cases – including this one – the rejection of one greatly enhances the credibility of the other.”