A fast physics-based perturbation generator of machine learning weather model for efficient ensemble forecasts of tropical cyclone track
Abstract Traditional ensemble forecasting based on numerical weather prediction (NWP) models, is constrained by the need for massive computational resources, resulting in limited ensemble sizes. Although emerging artificial intelligence (AI)-based weather models offer high forecast accuracy and impr...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-03-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-025-01009-9 |
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