]> The Lorenz Model

# The Lorenz Model

Edward Lorenz was a meteorologist who, around the time I was born, noticed that weather models were highly sensitive to tiny perturbations in their initial conditions – he discovered the so-called butterfly effect. We now look back on this as the first serious study of what are now termed chaotic systems – and we now know that dynamical systems whose models using first-order differential equations aren't linear (i.e. the rate at which one of the variables is changing isn't simply a sum of the various variables each scaled by a constant, but involves other functions of those variables) commonly are chaotic if they have more than three free variables. In any case, back when I was still a child, Lorenz came up with the following simple little system that exhibits chaotic behaviour:

• d[U, V, W]/dt = [s.(U −V), U.(r −W) −V, U.V −b.W]

in which s, r and b are some constants and U, V, W are quantities that vary with time, t. I learned of this (and the following is influenced by) Sabine Hossenfelder's video How can climate be predictable if weather is chaotic?, which I can happily recommend to anyone interested in the subject. The point of the video is that, while small perturbations in the input lead to subsequent histories that are routinely far apart, one can make clear statistical predictions about each solution spending quite definite proportions of its time behaving in each of two common behaviours, and likewise statistically characterise what any solution is typically doing the rest of the time. So the details are hard to pin down but the general character of (nearly) all solutions can be quite plainly described, all the same.

That aside, I've created this page in the vague thought that I might some day actually study this system of equations in more detail. I haven't done that yet, but at least I've got the equations written down somewhere I can easily find them.

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