It looks to me like it's "upscaling" ENS data to high resolution. Global general circulation models work with somewhat low-resolution data about terrain, and this model has found a function mapping the low-resolution weather predictions back to a prediction on high-resolution terrain.
(ed.: true also, but to a lesser extent, for "mesoscale" models (e.g. of just North America with boundary conditions to a global model))
If it did learn longer-range predictions (or the next model does?), I would hazard the model had achieved speedup by internalising the patterns of certain large-scale weather connections, e.g. the jet streams, Walker circulation, ENSO, Gulf stream... which I think will be fine for 99% of cases, the 1% being if these established patterns break somehow. ("freak weather")
At that point you would have to return to a general circulation model. When you take away the long-lived circulatory features that are familiar to us, and that are particular to Earth, predicting the weather is "just" fluid dynamics.
These are both just wild guesses, though