Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 8
Articles | Volume 18, issue 8
https://doi.org/10.5194/gmd-18-2427-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-2427-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 8
Model description paper
 | 
24 Apr 2025
Model description paper |  | 24 Apr 2025

TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions

Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You

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Latest update: 31 Oct 2025
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Short summary
Our research presents a novel deep learning approach called "TemDeep" for downscaling atmospheric variables at arbitrary time resolutions based on temporal coherence. Results show that our method can accurately recover evolution details superior to other methods, reaching 53.7 % in the restoration rate. Our findings are important for advancing weather forecasting models and enabling more precise and reliable predictions to support disaster preparedness, agriculture, and sustainable development.
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