weather prediction seems to me like a terrific use of machine learning aka statistics. The challenge I suppose is in the data. To get perfect predictions you'd need to have a mapping of what conditions were like 6 hours, 12 hours, etc before, and what the various outcomes were, which butterflies flapped their wings and where (this last one is a joke about how hard this data would be). Hard but not impossible. Maybe impossible. I know very little about weather data though. Is there already such a format?
It's been a while since I was a grad student but I think the raw station/radiosonde data is interpolated into a grid format before it's put into the standard models.
This was also in the article. It splits the sphere surface in to 1M grids (not actually grids in the cartesian sense of a plane, these are radial units). Then there's 37 altitude layers.
So there's radial-coordinate voxels that represent a low resolution of the physical state of the entire atmosphere.
