Toward exascale climate modelling: a python DSL   approach to ICON's (icosahedral non-hydrostatic)  dynamical core (icon-exclaim v0.2.0)

Dipankar, Anurag; Bianco, Mauro; Bukenberger, Mona; Ehrengruber, Till; Farabullini, Nicoletta; Fuhrer, Oliver; Gopal, Abishek; Hupp, Daniel; Jocksch, Andreas; Kellerhals, Samuel; Kroll, Clarissa A.; Lapillonne, Xavier; Leclair, Matthieu; Luz, Magdalena; Müller, Christoph; Ong, Chia Rui; Osuna, Carlos; Pothapakula, Praveen; Prein, Andreas; Röthlin, Matthias; Sawyer, William; Schär, Christoph; Schemm, Sebastian; Serafini, Giacomo; Vogt, Hannes; Weber, Ben; Wills, Robert C. Jnglin; Gruber, Nicolas; Schulthess, Thomas C.

doi:10.5194/gmd-19-713-2026

Articles | Volume 19, issue 2

https://doi.org/10.5194/gmd-19-713-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-19-713-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 2

Model description paper

|

22 Jan 2026

Model description paper |

| 22 Jan 2026

Toward exascale climate modelling: a python DSL approach to ICON's (icosahedral non-hydrostatic) dynamical core (icon-exclaim v0.2.0)

Anurag Dipankar, Mauro Bianco, Mona Bukenberger, Till Ehrengruber, Nicoletta Farabullini, Oliver Fuhrer, Abishek Gopal, Daniel Hupp, Andreas Jocksch, Samuel Kellerhals, Clarissa A. Kroll, Xavier Lapillonne, Matthieu Leclair, Magdalena Luz, Christoph Müller, Chia Rui Ong, Carlos Osuna, Praveen Pothapakula, Andreas Prein, Matthias Röthlin, William Sawyer, Christoph Schär, Sebastian Schemm, Giacomo Serafini, Hannes Vogt, Ben Weber, Robert C. Jnglin Wills, Nicolas Gruber, and Thomas C. Schulthess

Data sets

Data for the article "Toward Exascale Climate Modelling: A Python DSL Approach to ICON's (Icosahedral Non-hydrostatic) Dynamical Core (icon-exclaim v0.2.0)'' Anurag Dipankar et al. https://doi.org/10.5281/zenodo.17317423

Model code and software

EXCLAIM use cases Anurag Dipankar https://doi.org/10.5281/zenodo.17250248

Source code and scripts for publication "The ICON-based coupled Earth System Model for Climate Predictions and Projections (ICON XPP)'' (3.1) Wolfgang A. Müller et al https://doi.org/10.17617/3.UUIIZ8

Short summary

Climate models are becoming more detailed and accurate by simulating weather at scales of just a few kilometers. Simulating at km-scale is computationally demanding requiring powerful supercomputers and efficient code. This work presents a refactored dynamical core of a state-of-the-art climate model using a Python-based approach. The refactored code has passed through a sequence of verification and validation demonstrating its usability in performing km-scale global simulations.