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https://doi.org/10.5194/egusphere-2026-2916
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2026-2916
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Preprints
11 Jun 2026
 | 11 Jun 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

JAX-SCM v1.0: a modern atmospheric single-column model for boundary layer research

Maximilian Pierzyna

Abstract. We present JAX-SCM v1.0, an open-source atmospheric single-column model for boundary layer research, implemented in Python using the JAX computing library. The model solves for horizontal wind, potential temperature, and specific humidity, combined with prognostic turbulent kinetic energy and turbulent statistics parameterized by the Mellor-Yamada-Nakanishi-Niino level~2.5 (MYNN-2.5) turbulence closure. We verify the implementation against three well-established benchmark cases covering neutral (turbulent Ekman layer), stable (GABLS1), and convective (Wangara Day~33) conditions. Close agreement with reference solutions is demonstrated across all regimes. By building on JAX, the model benefits from just-in-time compilation and native GPU support. While JAX-SCM is not yet fully differentiable, basing it on JAX also lays the foundation for future integration with machine learning components. The model is designed for simplicity and modularity, lowering the barrier to entry for users and developers alike.

How to cite. Pierzyna, M.: JAX-SCM v1.0: a modern atmospheric single-column model for boundary layer research, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-2916, 2026.
Received: 20 May 2026 – Discussion started: 11 Jun 2026
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Maximilian Pierzyna

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Maximilian Pierzyna

Model code and software

JAX-SCM v1.0: a modern atmospheric single-column model for boundary layer research Maximilian Pierzyna https://doi.org/10.5281/zenodo.20314409

Maximilian Pierzyna
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Short summary
We present JAX-SCM, a modern one-dimensional atmospheric model implemented in Python and JAX, a package for fast numerical computations. We demonstrate that the model accurately represents the atmosphere at night, during the day, and in between. By using a modern programming language, we aim to make JAX-SCM accessible to a broad scientific audience. JAX-SCM also runs efficiently on fast graphical processing units (GPUs) and can be extended to support machine learning, making it future-proof.
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