Articles | Volume 19, issue 3
https://doi.org/10.5194/gmd-19-1103-2026
https://doi.org/10.5194/gmd-19-1103-2026
Model description paper
 | 
03 Feb 2026
Model description paper |  | 03 Feb 2026

LEX v1.6.0: a new large-eddy simulation model in JAX with GPU acceleration and automatic differentiation

Xingyu Zhu, Yongquan Qu, and Xiaoming Shi

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Short summary
By using the newly developed Python library JAX, we developed a fast and differentiable large-eddy simulation model, named LEX. Evaluated with a warm bubble case, LEX maintains high accuracy as the Cloud Model 1. With the hardware acceleration and better numerical stability, LEX can be quite faster. To report its differentiability, we further trained a deep learning-based parameterization scheme. The newly trained model can surpass the conventional scheme and get proper forecast results.
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