Open Mind

Don’t Get Fooled, Again

September 12, 2008 · 17 Comments

In the last post we discussed MA (moving average) noise processes, and even combined them with AR (autoregressive) noise processes to define ARMA (autoregressive moving average) processes. I mentioned that global average temperature behaves approximately as a trend plus ARMA(1,1) noise, i.e., a 1st-order AR, 1st-order MA process.

Let’s put some of this to practical use; let’s create some artificial data, the sum of a steady trend at a rate of 0.018 deg.C/yr (about the rate of global average temperature), and pure ARMA(1,1) noise with AR parameter \phi = 0.8493, MA parameter \theta = -0.4123, and white-noise standard deviation \sigma_w = 0.1147. With these parameters, it’ll have just about the same structure as GISS monthly temperature data since 1975.

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Categories: Global Warming