Physics-guided machine learning approach for reconstructing air temperature in warm permafrost on the Qinghai‒Xizang Plateau
High-resolution air temperature data are essential for quantifying eco-hydrological processes in climate-sensitive regions like the Qinghai‒Xizang Plateau. However, in-situ observations are frequently interrupted by extended data gaps. To address this, we developed a physics-guided machine learning...
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| Główni autorzy: | , , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
KeAi Communications Co., Ltd.
2026-08-01
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| Seria: | Advances in Climate Change Research |
| Hasła przedmiotowe: | |
| Dostęp online: | http://www.sciencedirect.com/science/article/pii/S1674927826001012 |
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