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UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations

Yang, Songru et al.
arXiv (All) · Papers
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machine-learning
Global In-situ Observation (GIO) provides fine-scale, direct records of the global weather system from sparse point stations, making it an indispensable source for capturing localized and transient dynamics beyond the reach of satellite gridded data, and playing a critical role in key fields such as
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