One of the big frustrations with trying to follow the debate on climate change is that most of the key questions are best answered with large, complicated models. Learning enough to assess these models in one subject area, even in general terms, is a huge task, and learning the details of any particular model is a full-time occupation. But, if we are going to make any real progress, we need numbers we can understand. It seems hopeless, but it isn’t entirely so. One thing I learned very early on about modelling is that, for almost any large complicated model, there’s a small simple model that gives much the same answers to the key questions of interest, if you use it correctly, and choose input parameters consistent with those in the big model. The big model (if it’s a good one) imposes consistency conditions you might miss in a simple model, and also gives detailed answers to lots of more specific questions, but a lot of the time, you can do without that. I’m writing a paper at the moment, trying to answer some of the important in a way anyone can check without spending years mastering a big model.
The biggest question of the moment is: what is the right price for carbon? I’m going to look at this question for the world as a whole, disregarding national differences and so on. If you’ve read the title of the post, you’ll know what answer I reach.