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Multimodal
NIVA: A Multimodal Foundation Model for Actionable Earth System Intelligence
arXiv:2606.28546v1 Announce Type: new Abstract: Recent advances in AI-driven weather and climate modeling have improved forecast skill while reducing computational cost. However, existing data-driven approaches are limited in their ability to model coupled Earth system dynamics, which is required for extending predictability beyond the ~2-week horizon. To address this, we introduce NIVA, a multimodal foundation model designed to learn unified representations across Earth system components. While...
arXiv cs.LG
·Anisha Pal, Aodhan Sweeney, Kyle Heyblom, Kalai Ramea
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