Articles | Volume 18, issue 2
https://doi.org/10.5194/gmd-18-529-2025
https://doi.org/10.5194/gmd-18-529-2025
Development and technical paper
 | 
30 Jan 2025
Development and technical paper |  | 30 Jan 2025

Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes

Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli

Related authors

Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025,https://doi.org/10.5194/gmd-18-33-2025, 2025
Short summary
Impact of climate change on snow avalanche activity in the Swiss Alps
Stephanie Mayer, Martin Hendrick, Adrien Michel, Bettina Richter, Jürg Schweizer, Heini Wernli, and Alec van Herwijnen
The Cryosphere, 18, 5495–5517, https://doi.org/10.5194/tc-18-5495-2024,https://doi.org/10.5194/tc-18-5495-2024, 2024
Short summary
Revealing the dynamics of a local Alpine windstorm using large-eddy simulations
Nicolai Krieger, Heini Wernli, Michael Sprenger, and Christian Kühnlein
EGUsphere, https://doi.org/10.5194/egusphere-2024-3461,https://doi.org/10.5194/egusphere-2024-3461, 2024
Short summary
The importance of diabatic processes for the dynamics of synoptic-scale extratropical weather systems – a review
Heini Wernli and Suzanne L. Gray
Weather Clim. Dynam., 5, 1299–1408, https://doi.org/10.5194/wcd-5-1299-2024,https://doi.org/10.5194/wcd-5-1299-2024, 2024
Short summary
Frequency anomalies and characteristics of extratropical cyclones during extremely wet, dry, windy and calm seasons in the extratropics
Hanin Binder and Heini Wernli
EGUsphere, https://doi.org/10.5194/egusphere-2024-2936,https://doi.org/10.5194/egusphere-2024-2936, 2024
Short summary

Related subject area

Atmospheric sciences
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025,https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025,https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025,https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025,https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025,https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary

Cited articles

Adams, S. V., Ford, R. W., Hambley, M., Hobson, J., Kavčič, I., Maynard, C. M., Melvin, T., Müller, E. H., Mullerworth, S., Porter, A. R., Rezny, M., Shipway, B. J., and Wong, R.: LFRic: Meeting the challenges of scalability and performance portability in Weather and Climate models, J. Parallel Distr. Com., 132, 383–396, https://doi.org/10.1016/j.jpdc.2019.02.007, 2019. a
Afanasyev, A., Bianco, M., Mosimann, L., Osuna, C., Thaler, F., Vogt, H., Fuhrer, O., VandeVondele, J., and Schulthess, T. C.: GridTools: A framework for portable weather and climate applications, SoftwareX, 15, 100707, https://doi.org/10.1016/j.softx.2021.100707, 2021. a, b
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational convective-scale numerical weather prediction with the COSMO model: Description and sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/mwr-d-10-05013.1, 2011. a
Bauer, P., Quintino, T., Wedi, N. P., Bonanni, A., Chrust, M., Deconinck, W., Diamantakis, M., Dueben, P. D., English, S., Flemming, J., Gillies, P., Hadade, I., Hawkes, J., Hawkins, M., Iffrig, O., Kühnlein, C., Lange, M., Lean, P., Maciel, P., Marsden, O., Müller, A., Saarinen, S., Sarmany, D., Sleigh, M., Smart, S., Smolarkiewicz, P. K., Thiemert, D., Tumolo, G., Weihrauch, C., and Zanna, C.: The ECMWF scalability programme: Progress and plans, ECMWF Technical Memo No. 857, https://doi.org/10.21957/gdit22ulm, 2020. a, b
Bauer, P., Dueben, P. D., Hoefler, T., Quintino, T., Schulthess, T. C., and Wedi, N. P.: The digital revolution of Earth-system science, Nature Comput. Sci., 1, 104–113, https://doi.org/10.1038/s43588-021-00023-0, 2021. a
Download
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.