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...
Gorde:
| Egile Nagusiak: | , , , , , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Wiley
2023-09-01
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| Saila: | Geophysical Research Letters |
| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.1029/2023GL104347 |
| Etiketak: |
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