SuperdropNet: A Stable and Accurate Machine Learning Proxy for Droplet‐Based Cloud Microphysics
Abstract Cloud microphysics has important consequences for climate and weather phenomena, and inaccurate representations can limit forecast accuracy. While atmospheric models increasingly resolve storms and clouds, the accuracy of the underlying microphysics remains limited by computationally expedi...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
American Geophysical Union (AGU)
2025-06-01
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| Series: | Journal of Advances in Modeling Earth Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024MS004279 |
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