Building My Own Tiny AI Weather Model

The author builds a small graph neural network weather model inspired by Graphcast, using a 5 GB subset of ERA5 data (North Atlantic/Europe, 2003–2016 training, 2017–2019 evaluation) and an encode-process-decode architecture with an icosahedral mesh. The model has about 200k weights and trains in 45 minutes on a five-year-old gaming PC, outperforming the persistence baseline for all nine variables at lead times up to +72 h, though its RMSE is roughly 5x worse than Graphcast at 24 h and 10x worse at 72 h.