Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 21, issue 17
Articles | Volume 21, issue 17
https://doi.org/10.5194/acp-21-13149-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-13149-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 17
Research article
 | 
06 Sep 2021
Research article |  | 06 Sep 2021

Forecasting and identifying the meteorological and hydrological conditions favoring the occurrence of severe hazes in Beijing and Shanghai using deep learning

Chien Wang

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Short summary
Haze caused by abundant atmospheric aerosols has become a serious environmental issue in many countries. An innovative deep-learning machine has been developed to forecast the occurrence of hazes in two Asian megacities (Beijing and Shanghai) and has achieved good overall accuracy. Using this machine, typical regional meteorological and hydrological regimes associated with haze and non-haze events in the two cities have also been, arguably for the first time, successfully categorized.
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