Gambling at 19-1
The IPCC report is out. We know the earth has been getting hotter: that’s just simple data analysis. The report says
It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together. The best estimate of the human induced contribution to warming is similar to the observed warming over this period.
Here, “extremely likely” is defined as 95-100% confidence. Since we (fortunately) don’t get a long series of potential climate catastrophes to average over, the probabilities have to be interpreted in terms of (reasonable) degrees of belief rather than relative frequency, which can be made concrete by equivalents to investment or gambling.
That is, the panel concludes no-one should be betting against a human cause for climate change unless they get better than 19-1 odds (and possibly much better, depending on where in the 95-100% range they are). Suppose we have an opportunity to reduce greenhouse gas concentrations, which will cost $20 million, and that the money is completely wasted if the climate models are basically wrong, but which will bring in $21 million, for a $1 million profit, if the models are basically right. The evaluation as “extremely likely” means we should take these opportunities. Investments that have, say, a net loss of $10 million if there isn’t anthropogenic warming and a net saving of $1 million if there is, are very good value. For mitigation efforts, the odds are even more favourable: the world unquestionably has been warming, so mitigation is likely to be worthwhile even if the reason isn’t CO2.
I don’t think current policies are anywhere near the 19-1 threshold. I’d be surprised if a lot of them even made sense if the climate was offering even money.
Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »