A Machine Learning‐Based Observation Operator for FY‐4B GIIRS Brightness Temperatures Considering the Uncertainty of Label Data
Abstract The increasing volume of satellite data, particularly hyperspectral infrared data, combined with the real‐time monitoring requirements of numerical weather prediction (NWP) systems, has heightened the demand for computational efficiency and accuracy in radiative transfer models (RTM). Machi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-03-01
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| Series: | Journal of Geophysical Research: Machine Learning and Computation |
| Online Access: | https://doi.org/10.1029/2024JH000449 |
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