An Inconvenient Truth

I saw it this weekend, and must say, it was magnificent. My timing is certainly appropriate given the release of the IPCC report on Friday.

To me the two things that stood out the most were the Greenland melting, and the emphatic point that reducing carbon emission is probably an opportunity for immense economic growth, not a burden. I guess I have more faith in Yankee ingenuity and the free market than the critics do; at any rate the counterargument by Gore using automobile standards in China vs the US (specifically California) was utterly devastating. Excellent additional reading is the Stern Review Report on the economics of climate change.

I'm going to buy this DVD; it's that good. And I'll chip in another ten bucks to the Draft Gore ActBlue page besides.

I'd appreciate any link to "response" pieces by critics, as long as they actually address the specific arguments and don't try to do an end-run by attempting to ad-hominem the scientific process itself.

UPDATE: just because it's so good, this comment about numerical simulations and climate models from Good Math Bad Math:

Even if we accept what [a partisan hack who claims to be a scientist] says at face value: that there are multiple variables in a simulation which need to be considered separately in terms of probability - he's quite deliberately ignoring the correct way of combining those probabilities. In fact, he's really just trying to play the inverse of a classic "big numbers" game - he wants to artificially combine things to make the probability look as untrustworthy as possible. The trick is in pretending that all 50 (or whatever) variables in the simulation are independent. In real climate simulations, the kinds of things that become variables are not independent. To give a couple of examples, real climatalogical simulations will include a parameter to describe the humidity of airmasses based on temperature; and simulation to describe the viscosity of airmasses based on temperature and humidity. Those are not independent - the viscosity of the airmass is determined in part by its humidity; the ability of the airmass to pick up more moisture while over the ocean is determined in part by its viscosity. The probabilities of these things being correct are not independent - if one is right, the other is almost certainly right; and if one is wrong, the other is almost certainly wrong - because each depends on the correctness of the other. Dependent variables get treated very differently in a probability calculation that independent variables - that's what Bayes theorem is all about.

But it's much worse than just making a misleading probability argument. He's very deliberately mischaracterizing how we model the accuracy of a simulation. The accuracy of simulation is based on its performance and the known accuracy of the fundamental model which it's based on. So, for example, most airplane manufacturers no longer use wind tunnels - computational fluid dynamics simulations generate better results than the wind tunnel (Do a websearch on "Boeing" and "Tranair"). The reliability of the simulation is based on two things. One is a long history of measuring things on instrumented aircraft, and comparing the measurements to the predictions from the simulations; the other is the known accuracy of the Navier Stokes equations, and the computational methods used to implement NS systems. On the basis of those two, we come up with results about how accurate we believe the models to be.

And further - we look at simulations based on multiple models. If 20 different models, generated in 20 different ways, all of which have strong track records for accuracy - if all 20 of them have been been implemented by simualations whose quality has been demonstrated - and all of them generate nearly the same result, and no system/model with a proven track record disagrees, then we consider the results of those simulations to be very strong evidence.