I didn't read the paper but the linked post seems to say otherwise? It mentions it used the supercomputer output to impute data during training. But for prediction it just needs:

> For inputs, GraphCast requires just two sets of data: the state of the weather 6 hours ago, and the current state of the weather. The model then predicts the weather 6 hours in the future. This process can then be rolled forward in 6-hour increments to provide state-of-the-art forecasts up to 10 days in advance.