Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 18
Articles | Volume 19, issue 18
https://doi.org/10.5194/gmd-19-8673-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-8673-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 18
Development and technical paper
 | 
17 Sep 2026
Development and technical paper |  | 17 Sep 2026

An online spectral nudging-based correction system: improving physical model forecasts by incorporating large-scale circulations derived from machine learning models

Yong Su, Jincheng Wang, Xueshun Shen, Couhua Liu, Xingliang Li, Jin Zhang, Hao Jing, and Yingying Hu

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Short summary
The traditional weather prediction models improve slowly, while machine learning models struggle with extreme weather and fine details. To address these gaps, we developed an online  Spectral Nudging-based correction system that leverages a machine learning model's skillful large-scale circulation to guide a physical model. This hybrid model enhances large-scale skill while preserving small-scale features, providing a viable pathway for improving operational weather forecasting.
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