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arXiv Machine Learning By Shiqi Zhang, Pan Mu, Cheng Huang, Hanting Yan, Yuchao Zhu, Jinglin Zhang, Shengyong Chen, Shoujuan Shu, Cong Bai

Tianmu-TC: Physics-constraints Generative Artificial Intelligence for Global Tropical Cyclone Forecasting

Read the original on arXiv Machine Learning →

Tianmu-TC is a physics‑constraints generative AI framework designed for global tropical cyclone forecasting. Trained on Western North Pacific data, it produces controllable outputs with reduced uncertainty, outperforming both deterministic and ensemble meteorological AI models as well as the ECMWF NWP system across global ocean basins. The model also demonstrates strong performance in challenging scenarios such as data sparsity, anomaly tracks, rapid intensification, and weakening, while maintaining significantly lower computational cost.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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