Preprints
https://doi.org/10.5194/egusphere-2025-4808
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-4808
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
14 Oct 2025
| 14 Oct 2025
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Toward Exascale Climate Modelling: A Python DSL Approach to ICON’s (Icosahedral Non-hydrostatic) Dynamical Core (icon-exclaim v0.2.0)
Abstract. A refactored atmospheric dynamical core of the ICON model implemented in GT4Py, a Python-based domain-specific language designed for performance portability across heterogeneous CPU-GPU architectures, is presented. Integrated within the existing Fortran infrastructure, the GT4Py core achieves throughput slightly exceeding the optimized OpenACC version, reaching up to 213 simulation days per day when using a quarter of CSCS’s ALPS GPUs.
A multi-tiered testing strategy has been implemented to ensure numerical correctness and scientific reliability of the model code. Validation has been performed through global aquaplanet and prescribed sea-surface temperature simulations to demonstrate model’s capability to simulate mesoscale and its interaction with the larger-scale at km-scale grid spacing. This work establishes a foundation for architecture-agnostic ICON global climate and weather model, and highlights poor strong scaling as a potential bottleneck in scaling toward exascale performance.
How to cite. Dipankar, A., Bianco, M., Bukenberger, M., Ehrengruber, T., Farabullini, N., Gopal, A., Hupp, D., Jocksch, A., Kellerhals, S., Kroll, C. A., Lapillonne, X., Leclair, M., Luz, M., Müller, C., Ong, C. R., Osuna, C., Pothapakula, P., Röthlin, M., Sawyer, W., Serafini, G., Vogt, H., Weber, B., and Schulthess, T.: Toward Exascale Climate Modelling: A Python DSL Approach to ICON’s (Icosahedral Non-hydrostatic) Dynamical Core (icon-exclaim v0.2.0), EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4808, 2025.
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Anurag Dipankar
CORRESPONDING AUTHOR
Center for Climate System Modelling C2SM, ETH Zürich, Switzerland
Mauro Bianco
Swiss National Supercomputing Centre CSCS, ETH Zürich, Switzerland
Mona Bukenberger
Institute for Atmospheric and Climate Sciences IAC, ETH Zürich, Switzerland
Till Ehrengruber
Swiss National Supercomputing Centre CSCS, ETH Zürich, Switzerland
Nicoletta Farabullini
Center for Climate System Modelling C2SM, ETH Zürich, Switzerland
Abishek Gopal
NSF National Center for Atmospheric Research, Boulder, Colorado
Daniel Hupp
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
Andreas Jocksch
Swiss National Supercomputing Centre CSCS, ETH Zürich, Switzerland
Samuel Kellerhals
Center for Climate System Modelling C2SM, ETH Zürich, Switzerland
Clarissa A. Kroll
Institute for Atmospheric and Climate Sciences IAC, ETH Zürich, Switzerland
Xavier Lapillonne
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
Matthieu Leclair
Center for Climate System Modelling C2SM, ETH Zürich, Switzerland
Magdalena Luz
Center for Climate System Modelling C2SM, ETH Zürich, Switzerland
Christoph Müller
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
Chia Rui Ong
Center for Climate System Modelling C2SM, ETH Zürich, Switzerland
Carlos Osuna
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
Praveen Pothapakula
Institute for Atmospheric and Climate Sciences IAC, ETH Zürich, Switzerland
Matthias Röthlin
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
William Sawyer
Swiss National Supercomputing Centre CSCS, ETH Zürich, Switzerland
Giacomo Serafini
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
Hannes Vogt
Swiss National Supercomputing Centre CSCS, ETH Zürich, Switzerland
Ben Weber
Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland
Thomas Schulthess
Swiss National Supercomputing Centre CSCS, ETH Zürich, Switzerland
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.
Climate models are becoming more detailed and accurate by simulating weather at scales of just a...