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YingLan: A Multimodal Ocean Foundation Model for Unified Representation Learning from Heterogeneous Observations
Multimodal ocean modeling remains challenging due to substantial heterogeneity in data structures, physical semantics, and spatiotemporal characteristics across satellite imagery, gridded oceanographic fields, and buoy observations. Existing approaches largely focus on task-specific ocean modeling,
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