Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 17
Articles | Volume 18, issue 17
https://doi.org/10.5194/gmd-18-5605-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-18-5605-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 17
Model description paper
 | 
04 Sep 2025
Model description paper |  | 04 Sep 2025

Huge ensembles – Part 2: Properties of a huge ensemble of hindcasts generated with spherical Fourier neural operators

Ankur Mahesh, William D. Collins, Boris Bonev, Noah Brenowitz, Yair Cohen, Peter Harrington, Karthik Kashinath, Thorsten Kurth, Joshua North, Travis A. O'Brien, Michael Pritchard, David Pruitt, Mark Risser, Shashank Subramanian, and Jared Willard

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Short summary
We use machine learning emulators to create a massive ensemble of simulated weather extremes. This ensemble provides a large sample size, which is essential to characterize the statistics of extreme weather events and study their physical mechanisms. Also, these ensembles can be beneficial to accurately forecast the probability of low-likelihood extreme weather.
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Theoretical and computational aspects of ensemble design,...