Visibility-derived aerosol optical depth over global land from 1959 to 2021

Hao, Hongfei; Wang, Kaicun; Zhao, Chuanfeng; Wu, Guocan; Li, Jing

doi:https://doi.org/10.5194/essd-16-3233-2024

Articles | Volume 16, issue 7

https://doi.org/10.5194/essd-16-3233-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-16-3233-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 7

Data description paper

|

12 Jul 2024

Data description paper |

| 12 Jul 2024

Visibility-derived aerosol optical depth over global land from 1959 to 2021

Hongfei Hao, Kaicun Wang, Chuanfeng Zhao, Guocan Wu, and Jing Li

Data sets

Visibility-derived aerosol optical depth over global land from 1959 to 2021 Hongfei Hao et al. https://doi.org/10.11888/Atmos.tpdc.300822

Short summary

In this study, we employed a machine learning technique to derive daily aerosol optical depth from hourly visibility observations collected at more than 5000 airports worldwide from 1959 to 2021 combined with reanalysis meteorological parameters.