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
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Related subject area
Subject: Aerosols | Research Activity: Machine Learning | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
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Atmos. Chem. Phys., 23, 10313–10324, 2023
Cited articles
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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.
