Yet in his Vox piece, David Roberts notes this:
Basically, it’s difficult to predict anything, especially regarding sprawling systems like the global economy and atmosphere, because everything depends on everything else. There’s no fixed point of reference.
Grappling with this kind of uncertainty turns out to be absolutely core to climate policymaking. Climate nerds have attempted to create models that include, at least in rudimentary form, all of these interacting economic and atmospheric systems. They call these integrated assessment models, or IAMs, and they are the primary tool used by governments and international bodies to gauge the threat of climate change. IAMs are how policies are compared and costs are estimated.
So it’s worth asking: Do IAMs adequately account for uncertainty? Do they clearly communicate uncertainty to policymakers?
The answer to those questions is almost certainly “no.” But exactly why IAMs fail at this, and what should be done about it, is the subject of much debate.
Or to put it another way: Think about how insane it is to try to predict what’s going to happen in 2100.
In the view of these researchers, the quest to predict what climate change (or climate change mitigation) will cost through 2100 ought to be abandoned. It is impossible, computationally intractable, and the IAMs that pretend to do it only serve to distract and confuse.