Climate models are fundamentally physical, but I don't have the insight in the field to have the deep insight to make qualified opinions.
I could after significant research as suggested. But that is a significant endeavour, hence following the opinion of the field is typically sufficient.
It's like a fronted developer making comments on kernel development and vice versa. It's both fundamentally code, but different fields.
I think if you’ve looked at numerical models then you have enough knowledge to at least judge the underlying assumptions: boundary conditions, numerical stability, discretisation methods, validation methods and results.
In the same way that I can verify a SAT solution, I don’t need to know how to code a sat solver.
Unfortunately there are fundamental disagreements about most of the critical parts of climate science, so going by the opinion of the field isn’t foolproof (who to choose? How to choose?). Many fields have had false consensus beliefs before, and most of their problems weren’t 1000th the difficulty of climate modelling.
This is true, but there are no biological simulations in the mainstream models, just various correction factors with their own uncertainty. I wish they had biological data because then we would have more domains in which to measure their accuracy.
I could after significant research as suggested. But that is a significant endeavour, hence following the opinion of the field is typically sufficient.
It's like a fronted developer making comments on kernel development and vice versa. It's both fundamentally code, but different fields.