Twitter, can be succinct
Damn well better, but Steve Easterbrook has a nice explanation of what GCMs are and are not. As he points out,@E__Strobel @CColose @ClimateOfGavin @AdamFrank4 Explicative value is strong, predictive only in the long run— eli rabett (@EthonRaptor) June 9, 2015
you don’t actually need a computer model to predict climate change. The first predictions of what would happen if we keep on adding carbon dioxide to the atmosphere were produced over 120 years ago. That’s fifty years before the first digital computer was invented. And those predictions were pretty accurate – what has happened over the twentieth century has followed very closely what was predicted all those years ago. Scientists also predicted, for example, that the arctic would warm faster than the equatorial regions, and that’s what happened. They predicted night time temperatures would rise faster than day time temperatures, and that’s what happened.
So in many ways, the models only add detail to what we already know about the climate. They allow scientists to explore “what if” questions. For example, you could ask of a model, what would happen if we stop burning all fossil fuels tomorrow. And the answer from the models is that the temperature of the planet will stay at whatever temperature it was when you stopped. For example, if we wait twenty years, and then stopped, we’re stuck with whatever temperature we’re at for tens of thousands of years. You could ask a model what happens if we dig up all known reserves of fossil fuels, and burn them all at once, in one big party? Well, it gets very hot.
Post Script: Isaac Held has some essays on the speakable and unspeakable in climate models. Last The quality of the large scale flow simulated in GCMs, instructions on How Not to Evaluate Climate Models, and a bug-a-boo of Eli's, Addicted to Global Mean Temperature.