Articles | Volume 23, issue 1
https://doi.org/10.5194/acp-23-375-2023
© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jan 2023
Research article |
| 10 Jan 2023
| 10 Jan 2023
Capturing synoptic-scale variations in surface aerosol pollution using deep learning with meteorological data
Related authors
EGUsphere, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Atmos. Chem. Phys., 21, 17995–18010, 2021
Cited articles
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Chen, Z. H., Cheng, S. Y., Li, J. B., Guo, X. R., Wang, W. H., and Chen, D.
S.: Relationship between atmospheric pollution processes and synoptic pressure patterns in northern China, Atmos. Environ., 42, 6078–6087, https://doi.org/10.1016/j.atmosenv.2008.03.043, 2008.
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Feng, J.: Data for “Capturing synoptic-scale variations in surface aerosol pollution using deep learning with meteorological data”, Zenodo [data set], https://doi.org/10.5281/zenodo.6982879, 2022a.
Feng, J.: Animation for “Capturing synoptic-scale variations in surface aerosol pollution using deep learning with meteorological data”, Zenodo [video/audio], https://doi.org/10.5281/zenodo.6982971, 2022b.
