Interesting Comment On Climate Modeling By James Lovelock

There is an interesting interview of James Lovelock by Leo Hickman titled

James Lovelock on the value of sceptics and why Copenhagen was doomed [h/t/ to eric144 who posted a comment #3) in the post  Picking Cherries and Hot Fudge].

The header for this section of the interview is titled “On the over-reliance on computer modelling” and reads 

I remember when the Americans sent up a satellite to measure ozone and it started saying that a hole was developing over the South Pole. But the damn fool scientists were so mad on the models that they said the satellite must have a fault. We tend to now get carried away by our giant computer models. But they’re not complete models. They’re based more or less entirely on geophysics. They don’t take into account the climate of the oceans to any great extent, or the responses of the living stuff on the planet. So I don’t see how they can accurately predict the climate. It’s not the computational power that we lack today, but the ability to take what we know and convert it into a form the computers will understand. I think we’ve got too high an opinion of ourselves. We’re not that bright an animal. We stumble along very nicely and it’s amazing what we do sometimes, but we tend to be too hubristic to notice the limitations. If you make a model, after a while you get suckered into it. You begin to forget that it’s a model and think of it as the real world. You really start to believe it.

I have discussed climate models in several posts; e.g. see

What Are Climate Models? What Do They Do?

Q & A How Skillful Are The Global Climate Models Given The Relatively Small Radiative Human-Caused Forcing?

I agree with James Lovelock on his view of models. As I wrote in my first post listed above

“…. the IPCC and US National Assessments appropriately should be communicated as process studies in the context that they are sensitivity studies. It is a very convoluted argument to state that a projection is not a prediction. The specification to periods of time in the future (e.g., 2050-2059) and the communication in this format is very misleading to the users of this information. This is a very important distinction which has been missed by impact scientists who study climate impacts using the output from these models and by policymakers.”

Until climate modellers accept the limitations of their models, they will continue to improperly present model results to policymakers. The result will a perpetuation of the perspective presented in the excellent  Der Speigel article How the Science of Global Warming was Compromised.

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