[earthscienceman]

I'm someone working in the field with weather modelers/forecasters but not a modeler myself. Reading this discussion has been an absolute treat ...

The most fascinating thing about the concept of error in models, including in ensembles, is you can only calculate and propagate error for contributors that you can quantify. There are many unquantifiable sources of error. Imagine a physical process that you are unaware of that propagates as a bias, for example ice nucleation via aerosols. Perhaps you don't even model aerosols. How do you account for error here? What does error even mean?

Ensembles only show you intramodel variability. Which is like error, sort of, but only really represents a combination of "real" variability in initial conditions and how that propagates through your physics/parameterizations.

"models" the HN commentators make for their businesses surely have parallel concepts, but I don't see anyone talking about them. Only discussion about the errors you know when the ugliest errors are the ones that no one knows.