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> physical models are the most reliable basis for prediction Simpler models can yield better predictions than complex ones, even when the complex model is more
by sieste 3y ago
> physical models are the most reliable basis for prediction
Simpler models can yield better predictions than complex ones, even when the complex model is more "realistic". The many tunable parameters and complex feedback loops can increase uncertainty compared to a simple model.
See for example "To explain or to predict?" by Shmueli (2010, https://doi.org/10.1214/10-STS330 https://doi.org/10.1214/10-STS330)
- braaannigan 3y agoMany of the physical models are of similar complexity to the model in this paper - the sort of analytical model that you run in a few minutes on your laptop, not on a super-computer. It's not a question of complexity it's about whether a statistical model that is not constrained by well-understood constraints is a high-value model
- sieste 3y agoAgreed. Also I'm not here to defend their particular model. Just saying that "physical" does not always equal "better predictions". Their model equation (1) has 4 parameters. Do you have any papers at hand that model AMOC in a more physically constrained way, with a similar number of tunable parameters?