Articles | Volume 19, issue 1
https://doi.org/10.5194/gmd-19-27-2026
https://doi.org/10.5194/gmd-19-27-2026
Development and technical paper
 | 
05 Jan 2026
Development and technical paper |  | 05 Jan 2026

Increasing resolution and accuracy in sub-seasonal forecasting through 3D U-Net: the western US

Jihun Ryu, Hisu Kim, Shih-Yu (Simon) Wang, and Jin-Ho Yoon

Model code and software

W-US-BCSR/IRnAF: 1.0 Initial Release (v1.0) J. Ryu et al. https://doi.org/10.5281/zenodo.14776781

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Short summary
Using a neural network model, county-level weather forecasts was achieved in the Western US. By combining traditional forecasting data with actual weather observations, the AI system achieved better temperature predictions at local scales. While showed promise for temperature forecasting, it still had difficulty accurately predicting extreme rainfall events. The research advances weather forecasting capabilities, potentially helping communities prepare for severe weather conditions.
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