Correcting dry/wet classification bias in precipitation downscaling via generative adversarial networks
Accurately downscaling precipitation from coarse to high spatial resolutions remains a critical challenge in climate and hydrometeorological modeling. A key limitation is the frequent misclassification of dry and wet regions, which compromises the realism and reliability of high-resolution outputs....
Guardado en:
| Autores principales: | , , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
Cambridge University Press
2026-01-01
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| Colección: | Environmental Data Science |
| Materias: | |
| Acceso en línea: | https://www.cambridge.org/core/product/identifier/S2634460226100399/type/journal_article |
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