An Interpretable Weather Forecasting Model With Separately‐Learned Dynamics and Physics Neural Networks
Abstract Machine learning (ML) offers a promising alternative for weather forecasting by reducing computational costs and modeling complex non‐linear atmospheric processes. While recent foundation models highlight this potential with advanced architectures, interpreting the “black‐box” nature of ML...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-07-01
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| Series: | Geophysical Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1029/2024GL114310 |
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