Big HPC area. Yesterday, all the forecast models had us getting ~1.5 inches (about 4cm) of snow with rain/ice afterwords.
We got (locally by me) 12+ inches (30+cm).
Ok. I don’t mind if there are large error bars. Really I don’t. But this ?
I don’t know enough about the models to be able to say anything terribly intelligent about their intrinsic accuracy, or if the omit anything, under/over predict anything … I do know enough to say that they weren’t in the same ballpark as what we got.
Part of this is HPC. More computing over more accurate grids, with better models, would (I would hope) have a better accuracy. This isn’t always the case, especially if there is a process that doesn’t start getting important until you shrink your scales and thus up your data intensity. Error accumulation to be sure, will be quite different. You might need a different renormalization technique. As with molecular dynamics, small errors calculating in delta V’s of particles/air masses will accumulate their error differently than a potential energy function … one is positive definite, one may change sign, so you have to be careful about Hamiltonian-like formalisms (not sure if they are used here, I should look).
But more computing is indicated.
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