Subseasonal Prediction of Regional Antarctic Sea Ice by a Deep Learning Model
Abstract Antarctic sea ice concentration (SIC) prediction at seasonal scale has been documented, but a gap remains at subseasonal scale (1–8 weeks) due to limited understanding of ice‐related physical mechanisms. To overcome this limitation, we developed a deep learning model named Sea Ice Predictio...
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| 主要な著者: | , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Wiley
2023-09-01
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| シリーズ: | Geophysical Research Letters |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1029/2023GL104347 |
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