Hi dean,

“So, they basically assumed a result and built a “model” around it? Am I missing something?”

Sort of. They looked at the temperature record from ice cores and decided that it looked stable. They then said that if an electronic engineer were to build a stable circuit, then they would choose a circuit with a certain gain factor. Therefore the climate has this effective gain factor.

Bigger values of the gain are still “stable”, but Monckton et al. chose a range that gives a small warming. Because they say that’s how circuits are designed.

Researchers have used the same palaeoclimate data and they actually calculated values relevant for climate change. The results from palaeoclimate studies contradict the Monckton team’s assumptions. I can only guess that the Monckton team didn’t know about these studies or maybe they forgot to cite them and explain why their assumptions differ from measurement-based calculations.

Figure 1b shows the M15 model with the parameters they estimate for the IPCC. We pointed out in our paper that the model did much better when using parameters inferred from the IPCC. We then used linear regression to estimate the product of feedbacks and transient fraction, showing that the Monckton assumed value was outside of the confidence intervals. There’s also some discussion in there about the complexities of response time and how this should be considered to get useful things out of the EBM approach.

We ended up using “M15 model” to refer to “M15 parameterisation of the energy balance model” because it was shorter and we had to say it a lot!

However. figure 1a shows that the model is useful, as long as the parameters are properly set. This is a Nit pic I know. but it is important to separate modelling errors from parameter setting errors. For example, I can make a GCM look like crap by fiddling with certain parameters. The model is useful when the parameters are set using good methods.

total surface warming = 1.5 C per trillion tons of carbon emitted, with 5-95% confidence levels of 1.0 and 2.1 C.

https://andthentheresphysics.files.wordpress.com/2015/03/cumulativeemissions.jpg

“The proportionality of global warming to cumulative carbon emissions,” H. Damon Matthews et al, Nature v459, 11 June 2009, pp 829-832.
doi:10.1038/nature08047

I can think of a sensible definition for the term: a model with zero free parameters would be “irreducibly simple”. But I don’t think it means what Monckton et al. think it means. And situations where a model with zero free parameters is actually useful are rare; atmospheric circulation certainly isn’t one of them.

Monckton et al rely on the assumption that the Earth’s surface temperature varies by only 1% around a long term (810,000 year) average.

That would be about 3 K. Some of the ice age excursions were close to that level, but there have been larger excursions than that in geological history, e.g., tropical plants once grew at what today are subarctic latitudes, and further back there was a “snowball Earth” period. So this assumption seems to be false. They might fare better if they require something close to the current continental configuration (IIRC global climate became significantly colder once the isthmus connecting the Americas developed), but then that would not be an irreducibly simple model–and they also have to ignore the extreme forcing of CO2.