Nonlinear Processes in Geophysics
Nonlinear Processes in Geophysics
NPG
Articles | Volume 32, issue 4
Articles | Volume 32, issue 4
https://doi.org/10.5194/npg-32-397-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/npg-32-397-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 32, issue 4
Research article
 | 
20 Oct 2025
Research article |  | 20 Oct 2025

Improving dynamical climate predictions with machine learning: insights from a twin experiment framework

Zikang He, Julien Brajard, Yiguo Wang, Xidong Wang, and Zheqi Shen

Viewed

Total article views: 1,330 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,128 155 47 1,330 43 61
  • HTML: 1,128
  • PDF: 155
  • XML: 47
  • Total: 1,330
  • BibTeX: 43
  • EndNote: 61
Views and downloads (calculated since 17 Feb 2025)
Cumulative views and downloads (calculated since 17 Feb 2025)

Viewed (geographical distribution)

Total article views: 1,330 (including HTML, PDF, and XML) Thereof 1,291 with geography defined and 39 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Dec 2025
Download
Short summary
Climate prediction is challenging due to systematic errors in traditional climate models. We addressed this by training a machine learning model to correct these errors and then integrating it with the traditional climate model to form an AI-physics hybrid model. Our study demonstrates that the hybrid model outperforms the original climate model on both short-term and long-term predictions of the atmosphere and ocean.
Read more
Share
Special issue
Emerging predictability, prediction, and early-warning approaches...