Doing It With Models

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The Coyote describes how they are doing it with models:

I seldom trust a computer model I did not build and I NEVER trust a model I did build (because I know the flaws and assumptions and plug variables all too well).

By the way, the mention of plug variable reminds me of one of the most interesting studies I have seen on climate modeling, by Kiel in 2007.  It was so damning that I haven't seen anyone do it since (at least get published doing it).  I wrote about it in 2011 at Forbes:

My skepticism was increased when several skeptics pointed out a problem that should have been obvious. The ten or twelve IPCC climate models all had very different climate sensitivities -- how, if they have different climate sensitivities, do they all nearly exactly model past temperatures? If each embodies a correct model of the climate, and each has a different climate sensitivity, only one (at most) should replicate observed data. But they all do. It is like someone saying she has ten clocks all showing a different time but asserting that all are correct (or worse, as the IPCC does, claiming that the average must be the right time). 

The answer to this paradox came in a 2007 study by climate modeler Jeffrey Kiehl. To understand his findings, we need to understand a bit of background on aerosols. Aerosols are man-made pollutants, mainly combustion products, that are thought to have the effect of cooling the Earth's climate. 

What Kiehl demonstrated was that these aerosols are likely the answer to my old question about how models with high sensitivities are able to accurately model historic temperatures. 

When simulating history, scientists add aerosols to their high-sensitivity models in sufficient quantities to cool them to match historic temperatures. Then, since such aerosols are much easier to eliminate as combustion products than is CO2, they assume these aerosols go away in the future, allowing their models to produce enormous amounts of future warming. 

Specifically, when he looked at the climate models used by the IPCC, Kiehl found they all used very different assumptions for aerosol cooling and, most significantly, he found that each of these varying assumptions were exactly what was required to combine with that model's unique sensitivity assumptions to reproduce historical temperatures. In my terminology, aerosol cooling was the plug variable.

When I was active doing computer models for markets and economics, we used the term "plug variable."  Now, I think "goal-seeking" is the hip word, but it is all the same phenomenon.