Freeman Dyson on Climate Models

One of the leading physicists on the planet, Freeman Dyson, has given a video interview to the Vancouver Sun. Whilst the paper emphasizes Dyson’s statements about the impact of more CO2 greening the Earth, there is something more fundamental that can be gleaned.

Referring to a friend who constructed the first climate models, Dyson says at about 10.45

These climate models are excellent tools for understanding climate, but that they are very bad tools for predicting climate. The reason is simple – that they are models which have very few of the factors that may be important, so you can vary one thing at a time ……. to see what happens – particularly carbon dioxide. But there are a whole lot of things that they leave out. ….. The real world is far more complicated than the models.

I believe that Climate Science has lost sight of what this understanding of what their climate models actually are literally attempts to understand the real world, but are not the real world at all. It reminds me of something another physicist spoke about fifty years ago. Richard Feynman, a contemporary that Dyson got to know well in the late 1940s and early 1950s said of theories:-

You cannot prove a vague theory wrong. If the guess that you make is poorly expressed and the method you have for computing the consequences is a little vague then ….. you see that the theory is good as it can’t be proved wrong. If the process of computing the consequences is indefinite, then with a little skill any experimental result can be made to look like an expected consequence.

Complex mathematical models suffer from this vagueness in abundance. When I see supporters of climate arguing the critics of the models are wrong by stating some simple model, and using selective data they are doing what lesser scientists and pseudo-scientists have been doing for decades. How do you confront this problem? Climate is hugely complex, so simple models will always fail on the predictive front. However, unlike Dyson I do not think that all is lost. The climate models have had a very bad track record due to climatologists not being able to relate their models to the real world. There are a number of ways they could do this. A good starting point is to learn from others. Climatologists could draw upon the insights from varied sources. With respect to the complexity of the subject matter, the lack of detailed, accurate data and the problems of prediction, climate science has much in common with economics. There are insights that can be drawn on prediction. One of the first empirical methodologists was the preeminent (or notorious) economist of the late twentieth century – Milton Friedman. Even without his monetarism and free-market economics, he would be known for his 1953 Essay “The Methodology of Positive Economics”. Whilst not agreeing with the entirety of the views expressed (there is no satisfactory methodology of economics) Friedman does lay emphasis on making simple, precise and bold predictions. It is the exact opposite of the Cook et al. survey which claims a 97% consensus on climate, implying that it relates to a massive and strong relationship between greenhouse gases and catastrophic global warming when in fact it relates to circumstantial evidence for a minimal belief in (or assumption of) the most trivial form of human-caused global warming. In relation to climate science, Friedman would say that it does not matter about consistency with the basic physics, nor how elegantly the physics is stated. It could be you believe that the cause of warming comes from the hot air produced by the political classes. What matters that you make bold predictions based on the models that despite being simple and improbable to the non-expert, nevertheless turn out to be true. However, where bold predictions have been made that appear to be improbable (such as worsening hurricanes after Katrina or the effective disappearance of Arctic Sea ice in late 2013) they have turned out to be false.

Climatologists could also draw upon another insight, held by Friedman, but first clearly stated by John Neville Keynes (father of John Maynard Keynes). That is on the need to clearly distinguish between the positive (what is) and the normative (what ought to be). But that distinction was alienate the funders and political hangers-on. It would also mean a clear split of the science and policy.

Hattips to Hilary Ostrov, Bishop Hill, and Watts up with that.


Kevin Marshall

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  1. And as if on cue come this study

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability.
    Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal.
    The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario’s forced signal, but is likely inconsistent with the steepest emission scenario’s forced signal.

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