A new and content-free model

In his article “A New and Effective Climate Model”, Stephen Wilde (guest posting on Anthony Watts’ blog) states his dissatisfaction with current climate models, and proposes another “model” for climate which he hopes will improve the state of climate modeling in general. In the article he has items like:

  1. Solar surface turbulence increases causing an expansion of the Earth’s atmosphere.
  2. Resistance to outgoing longwave radiation reduces, energy is lost to space faster.
  3. The stratosphere cools. Possibly also the number of chemical reactions in the upper atmosphere increases due to the increased solar effects with faster destruction of ozone.
  4. The tropopause rises.
  5. etc…

This list continues for 26 points, not an equation in the mix. So why am I so hooked on equations? Take the first item, and call “Solar surface turbulence” T, and the size of the atmosphere, A. Saying T goes up, so A goes up, could be like:


which would predict a nice linear response. What about this:


or this?


Each of these is a translation of “when T goes up, A goes up”, but they have radically different forms, and they have radically different effects. You can’t build a proper scientific model in words alone. Words are not precise, and there are many different ways to translate them into something that is precise, that can actually make meaningful predictions.

A model of just words is not really a model, in the scientific sense. Lord Kelvin said it best:

“In physical science the first essential step in the direction of learning any subject is to find principles of numerical reckoning and practicable methods for measuring some quality connected with it. I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind; it may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of Science, whatever the matter may be.”


About brianblais

I am a professor of Science and Technology at Bryant University in Smithfield, RI, and a research professor in the Institute for Brain and Neural Systems, Brown University. My research is in computational neuroscience and statistics. I teach physics, meteorology, astonomy, theoretical neuroscience, systems dynamics, artificial intelligence and robotics. My book, "Theory of Cortical Plasticity" (World Scientific, 2004), details a theory of learning and memory in the cortex, and presents the consequences and predictions of the theory. I am an avid python enthusiast, and a Bayesian (a la E. T. Jaynes), and love music.
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2 Responses to A new and content-free model

  1. Stephen Wilde says:

    Thank you for your kind attention, Professor.

    That model does appear to describe the correct sequence of events as they occur in the real world, unlike existing more formal models.

  2. bblais says:

    Perhaps my attention wasn't all too kind for your model ( 🙂 ), but I really do appreciate the comment. You say that your model describes the correct sequence of events. The problem as I see it is that we are dealing with a complex system, and the statements made in your model are either impossible to verify, or are going to be true to some extent no matter what. Because things in the model are stated in such an imprecise way it is impossible to make any real specific predictions.

    Could you, for example, take the following approach: from your first statement, “Solar surface turbulence increases causing an expansion of the Earth’s atmosphere.” can you make an approximation of the size of this effect? We know solar activity reasonably well for the past 50 years, so could you be specific on the relationship? If you can, then that would be the start of a simplified model. If you can't, then how can you estimate the next statement “Resistance to outgoing longwave radiation reduces, energy is lost to space faster”, and even get any answer to the problem that you're posing? Since each item follows from the next, the problem becomes worse the farther you go.

    If you have, qualitatively, written down the right sequence then you “may be the beginning of knowledge, but you have scarcely in your thoughts advanced to the state of Science”, as Kelvin said. Is there another value to the type of description you are calling a model here?

    I'm not just trying to be negative, and I am certainly not a total believer in the formal computer models used in climate these days, but I have seen too many “models” that do not have any real substance in the form of specific predictions.

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