Articles | Volume 19, issue 14
https://doi.org/10.5194/gmd-19-6451-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-6451-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
17 Jul 2026
Model description paper |
| 17 Jul 2026
| 17 Jul 2026
JCM v1.1: a differentiable, intermediate-complexity atmospheric model
Ellen H. Davenport
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
J. Varan Madan
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Rebecca Gjini
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Cecil H. and Ida M. Green Institute of Geophysics and Planetary Physics, University of California San Diego, La Jolla, USA
Jared Brzenski
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Benjamin Crawford
Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, USA
Nick Ho
Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
Tien-Yiao Hsu
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Yueshan Liang
Department of Bioengineering, University of California San Diego, La Jolla, USA
Zhixing Liu
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Veeramakali Manivannan
Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
Eric Pham
Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, USA
Rohith Vutukuru
Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
Andrew I. L. Williams
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Zhiqi Yang
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Rose Yu
Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
Nicholas J. Lutsko
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Stephan Hoyer
Google Research, Mountain View, CA, USA
Duncan Watson-Parris
CORRESPONDING AUTHOR
Scripps Institution of Oceanography, University of California San Diego, La Jolla, USA
Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, USA
Data sets
JCM v1.1 Supplementary Data E. Davenport et al. https://doi.org/10.5281/zenodo.20140142
Model code and software
JAX Circulation Model J. V. Madan et al. https://doi.org/10.5281/zenodo.20140172
Short summary
We introduce version 1.1 of the JAX Circulation Model (JCM), an open-source atmosphere model. JCM is written in JAX, a framework for high-performance Python code that supports automatic differentiation (automated calculation of how sensitive any program output is to any input). JCM's differentiability and modular design make it easier to train, test, and combine physical-theory-based and data-driven model components, thus providing a flexible and modern platform to facilitate climate research.
We introduce version 1.1 of the JAX Circulation Model (JCM), an open-source atmosphere model....
