A Hybrid Offline–Online Kalman–RBF Framework for Accurate Relative Humidity Forecasting
Accurate humidity forecasts are crucial for environmental and operational applications, yet Numerical Weather Prediction systems frequently exhibit systematic and random errors. To address this problem, this study introduces a modified hybrid post-processing approach that extends a previously develo...
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| Główni autorzy: | , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
MDPI AG
2026-01-01
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| Seria: | Atmosphere |
| Hasła przedmiotowe: | |
| Dostęp online: | https://www.mdpi.com/2073-4433/17/2/162 |
| Etykiety: |
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