Cultures of simulations vs. cultures of calculations revisited

I find the framework presented in a previous post helpful for thinking about modeling practices in the climate field, compared to my previous experience as a computationally oriented physicist.

Multiple questions I sometimes ask myself seem to find meaningful anchoring points in this framework:

1. When I perform a climate simulation, do I actually understand what is happening inside the numerical model?
2. Is this even knowable in detail?
3. What have we actually learned after performing a simulation?

In this post I have written some loose thoughts on the first two questions above. I will return to number 3 later as that is a slightly different topic.

Global climate models and Earth system models aim for comprehensivness, and thus include a lot of interacting sub models which all again aim for comprehensiveness and include sub models of their own and amny processes which interact in complicated ways. The large number of interacting modules and the total size of the code, makes it basically impossible for one person or a small group of persons to have detailed knowledge about everything in a modern climate model. Even the developers of main parts of the codes, will generally have limited knowledge of other parts.

Users/simulationists (like me) are even less knowledgeable about the detailed workings of the specific model code we are building our scientific practices on than the developers. We often come to the simulation field with the theoretical

Setting up a climate model simulation and running it is actually just a small part of the climate model user’s job. If using a modern climate model like CESM and not deviating too much (too is doing some work here) from the pre-configured setups, making a simulation case and running it is reasonably simple.