Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 20
Articles | Volume 19, issue 20
https://doi.org/10.5194/gmd-19-10263-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-10263-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 20
Development and technical paper
 | 
28 Oct 2026
Development and technical paper |  | 28 Oct 2026

GPU-accelerated three-dimensional variational data assimilation with automatic differentiation for WRF-Chem

Hancheng Ye, Zengliang Zang, Wei You, Yiwen Hu, Ning Liu, and Yi Li

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Short summary
Our study pioneers a PyTorch-based atmospheric pollutant assimilation system that leverages automatic differentiation and Graphics Processing Unit (GPU) acceleration to achieve order-of-magnitude speedups, while maintaining analysis accuracy consistent with the traditional Fortran-based system.
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