According to Megan McArdle in a Bloomberg View opinion piece we cannot trust computer models of the climate because economists have failed when they tried to model complex economic systems.
Leaving aside the fundamental fact that the ‘atoms’ of physics (molecules, humidity, etc.) are consistent in their behaviour, whereas the ‘atoms’ of economics (humans) are fickle and prone to ‘sentiment’, this is a failed form of denialism.
You do not have to be Champagne maker Taittinger investing in sparkling wine production in Kent (England), for example, to know that global warming is real, because there are thousands of scientifically observed and published indicators of a warming world. Most of these receive little attention in the media compared to the global average surface temperature (important though it is).
In her article she repeats something I believe is a key confusion in her piece:
“This lesson from economics is essentially what the “lukewarmists” bring to discussions about climate change. They concede that all else equal, more carbon dioxide will cause the climate to warm. But, they say that warming is likely to be mild unless you use a model which assumes large positive feedback effects.”
Matt Ridley is also often railing against the fact that the feedback from increased humidity turns a warming of 1C (from doubling CO2 from pre-industrial levels) into closer to 3C (as the mean predicted level of warming).
This has nothing to do with the inherent complexity in the climate models as it is derived from basic physics (the Infra-Red spectra of CO2 and H2O; the Clausius–Clapeyron relation that determines the level of humidity when the atmosphere warms; some basics of radiative transfer; etc.). Indeed, it is possible to get to an answer on the basic physics with pencil and paper, and the advanced computer models come to broadly the same conclusion (what the models are increasingly attempting to do is to resolve more details on geographic scales, time scales and within different parts of the Earth system, such as that big block of ice called Antarctica).
But even in the unlikely event that Megan McArdle were to accept these two incontrovertible points (the world is warming and the central feedback, from H2O, are not in any way compromised by some hinted at issue of ‘complexity’), she might still respond with something like:
“oh, but we do rely on complex models to make predictions of the future and things are too chaotic for this to be reliable.”
Well, we have learned from many great minds like Ilya Prigogine that there is complex behaviour in simple systems (e.g. the orbit of Pluto appears on one level to perform according to simple Newtonian mechanics, but in addition, has apparently random wobbles). One needs therefore to be careful at specifying at what level of order ‘chaotic behaviour’ exists. Pluto is both ordered and chaotic.
Whereas for other system that are complex (e.g. the swirling atmosphere of Jupiter) they can display ’emergent’ ordered behaviour (e.g. the big red spot). We see this all around us in the world, and ‘complexity theory’ is now a new branch of science addressing many phenomena that were otherwise inaccessible to pencil and paper: the computer is an essential tool in exploring these phenomena.
Complexity is therefore not in itself a reason for casting out a lazy slur against models, that predictability is impossible. There is often an ability to find order, at some level, in a system, however complex it is.
Yet, it can also be very simple.
At its most basic, adding energy to the climate system as we are doing by adding heat-trapping gases to the atmosphere, tends to warm things up, because of well established basic physics.
In a similar way, printing too much money in an economy tends to lead to inflation, despite the irreducible random factors in human nature.
It ain’t rocket science and you don’t need to be an expert in complexity theory to understand why we are a warming world.