A low-dimensional recursive deep learning model for El Niño-Southern Oscillation simulation
Abstract In this study, we develop a low-dimensional recursive model using deep learning (DL) to understand the dynamics of the El Niño-Southern Oscillation (ENSO). Unlike most existing research that relies on Coupled General Circulation Models (CGCMs), we explore a DL technique as an alternative ap...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-025-01053-5 |
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