In his interview with Roger Harrabin, Richard Tol said something quite interesting. He claimed:
RT: The very start of my career was about trying to show that CO2 and other greenhouse gases cause climate change. We were one of the first to establish that on a satisfactory statistical basis.
Quite a remarkable claim. So, I went and looked at Richard’s publication list and found a paper called Greenhouse Statistics-Time Series Analysis. It really is what it says in the title; simply a time series analysis. Compare various time series with the known temperture record, some with a CO2 term, some without, some with an additional linear term, and find which correlates best.
One obvious problem is, as it says in the Conclusion:
many climatologists classify this type of results as ‘correlation calculations’, which refers to the many wrong and misleading results obtained by this type of analysis.
So, yes, it might show that a time series with a CO2 correlates best with the observed temperature timeseries, but claiming that this shows that CO2 and other greenhouse gases cause climate change, seems a bit strong. However, they do state:
We have casted the hypothesis that the increase in atmospheric greenhouse gases causes global warming in a sophisticatedly simple model which enables efficient statistical testing; ….. The hypothesis of no influence is rejected. We have not found a proof or an explanation of the phenomenon though we can describe it. We have shown with much statistical care that the data are in line with the climatological hypothesis; the combination of the econometric techniques and climatological theory confirmed it in sign;
There are a couple of interesting issue relating to this. On an earlier post there was a rather acrimonious and contentious exhange between myself and Richard, mainly as a result of Richard defending Doug Keenan. Doug Keenan’s claim to fame (in the climate arena, at least) is making accusations of fraud and claiming that the surface temperture dataset is not significant. Richard said things like
The context is whether or not there is a statistically significant trend in the temperature record. That is a time series question if there ever was one.
He is correct in this case
At no point did Richard mention that he had published a time series analysis of his own, which he claims shows that CO2 and other greenhouse gases cause climate change. That would seem to be rather significant, given the context of the thread about Keenan. I wonder why he failed to mention this?
There is, however, something else interesting about Richard’s paper; it makes estimates of climate sensitivity. For a CO2 rise of 300ppm (which I assume is intended to be about a doubling since pre-industrial times) it estimates a 95% range of 2.99oC to 7.02oC for one model, and a 95% range of 3.4oC to 5.7oC for the other. Hmmm, quite a bit higher than the IPCC range, even at that time.
However, in the paper they then argue that they used CO2, rather than CO2-equivalent, which rose more than CO2 only, and that they should therefore reduce their climate sensitivity estimates accordingly. They then produced the table on the left, which shows that their estimate for climate sensitivity hovers around 3oC.
Now, there are a few things to bear in mind. Their model is simply a time series, with no real physics. They do introduce a lag of 20 years between the CO2 time series, and the temperature time series, but this still means that their climate sensitivity estimate is probably something like a mixture of an Effective Climate Sensitivity and a Transient Climate Response. Also, even though CO2-equivalent rose more than CO2 alone, when you include all the anthropogenic emissions, the anthropogenic effect is actually quite close to the CO2 only influence. Hence, maybe they shouldn’t have adjusted their estimates down.
Either way, though, we can now state that Richard Tol’s published estimate for climate sensitivity – which is based on a sophisticated time series analysis – suggests climate sensitivity is probably around 3oC, maybe even higher. Who’d thunk it? 😉