Fig Leaves, Fudge Factors And Global Warming

When scientists use computer models -- whether it's for predicting the effects of development on an endangered species or what the global temperature will be in 2027 -- things can go wrong. And usually do.

And when they do, scientists do what anyone does -- they defend their position until long after it's reasonable to do so. They're not pugilistic about it; they're formulaic. Specifically, they keep applying and re-applying their formulas (called "fig leaves" by certain wags, hence our lovely model). It's the scientific counterpart to the old AA saying, "Insanity is doing the same thing over and over again and expecting a different result."

Fig leaves, fudge factors and kamikaze approaches are all terms used by Orrin Pilkey and his daughter Linda Pilkey-Jarvis in their book on the dangers of assuming scientific models can be trusted, Useless Arithmetic: Why Environmental Scientists Can't Predict the Future.

Warmie scientists should read the book, but of course they won't. Doing so would mean they would have to remove their fig leaves. Ick.

But Cornelia Dean read it for the NYT and wrote a lauding review -- another step, I hope, in the gradual destruction of the credibility of the Warmie movement. Climate change is one of the big topics on the Pilkey book, and it's pretty shocking:

Two issues, the authors say, illustrate other problems with modeling. One is climate change, in which, they say, experts’ justifiable caution about model uncertainties can encourage them to ignore accumulating evidence from the real world.

Got that? Weather forecasters who never step outside to check the weather! It's already happening in the young art of climate hysteria, as earlier, short-term models are found to over-predict everything from ice melt to temperature change. The response? More models.

It won't work because models fail. Pilkey's early work on modeling sand movement on beaches -- models that were exquisitely elegant but perputually useless -- gave him the answer why:

Among other things, participants concluded that beach modelers applied too many fixed values to phenomena that actually change quite a lot. For example, “assumed average wave height,” a variable crucial for many models, assumes that all waves hit the beach in the same way, that they are all the same height and that their patterns will not change over time. But, the authors say, that’s not the way things work.

Their solution? Well, there's a bunch of ideas about how to work smarter with models, but the idea I like the most is this: Throw 'em all out.

It sounds radical, but think a moment. If you throw out the models, you will have to observe what's going on, think it through, try a solution, observe if it works, adjust, observe, adjust again. If you have any life experience at all, you know that's a superior solution.

Scientists complain about it. It'll be too expensive, too time consuming, too much time outside our comfortable labs. But whoa up there, Dr. Partner. With the Stern Report predicting the cost of stopping global warming at $400 billion a year, scrapping the models and funding actual research, analysis and planning seems like a much more sensible approach, since funds would be committed only when a need was found and verified, and a plan of action was designed.

The haphazard de-industrialization of the planet and heartless ignoring of more pressing human needs (AIDS, malaria, education, opportunity) all because a model tells us to is worse than useless arithmetic -- it's immoral arithmetic.

Hat-tip: Neil