Textual Environmental Context and Spatial Graphs for LLM-Based Regional SST Forecasting
This work forms forecasting as conditional numerical generation: historical SST and anomaly sequences, date-aligned environmental records, and static ocean knowledge form a textual context, while regional spatial state is supplied through continuous graph-derived prefixes.