Unexpected Results are Usually Wrong, but Often Interesting

Abstract:

In climate modeling, an unexpected result is usually wrong, arising from some sort of mistake. Despite the fact that we all bemoan uncertainty in climate, the field is underlain by a robust, successful body of theory and any properly conducted modeling experiment is posed and conducted within that context. Consequently, if results from a complex climate model disagree with theory or from expectations from simpler models, much skepticism is in order. But, this exposes the fundamental tension of using complex, sophisticated models. If simple models and theory were perfect there would be no reason for complex models--the entire point of sophisticated models is to see if unexpected phenomena arise as emergent properties of the system.

In this talk, I will step through some paleoclimate examples, drawn from my own work, of unexpected results that emerge from complex climate models arising from mistakes of two kinds. The first kind of mistake, is what I call a 'smart mistake'; it is an intentional incorporation of assumptions, boundary conditions, or physics that is in violation of theoretical or observational constraints. The second mistake, a 'dumb mistake', is just that, an unintentional violation. Analysis of such mistaken simulations provides some potentially novel and certainly interesting insights into what is possible and right in paleoclimate modeling by forcing the reexamination of well-held assumptions and theories.