High sensitivity of simulated fog properties  to parameterized aerosol activation  in case studies from ParisFog

Ghosh, Pratapaditya; Boutle, Ian; Field, Paul; Hill, Adrian; Jones, Anthony; Mazoyer, Marie; Evans, Katherine J.; Mahajan, Salil; Kang, Hyun-Gyu; Xu, Min; Zhang, Wei; Asch, Noah; Gordon, Hamish

doi:https://doi.org/10.5194/acp-25-11129-2025

Articles | Volume 25, issue 18

https://doi.org/10.5194/acp-25-11129-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-25-11129-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 18

Research article

|

24 Sep 2025

Research article |

| 24 Sep 2025

High sensitivity of simulated fog properties to parameterized aerosol activation in case studies from ParisFog

Pratapaditya Ghosh, Ian Boutle, Paul Field, Adrian Hill, Anthony Jones, Marie Mazoyer, Katherine J. Evans, Salil Mahajan, Hyun-Gyu Kang, Min Xu, Wei Zhang, Noah Asch, and Hamish Gordon

Supplement

https://doi.org/10.5194/acp-25-11129-2025-supplement

Data sets

High sensitivity of simulated fog properties to parameterized aerosol activation in case studies from ParisFog Pratapaditya Ghosh et al. https://doi.org/10.5281/zenodo.15671189

Model code and software

metomi/rose: 2019.01.3 Matt Shin et al. https://doi.org/10.5281/zenodo.3800775

cylc/cylc-flow: cylc-7.8 Hilary James Oliver et al. https://doi.org/10.5281/zenodo.4638360

cylc/cylc-flow: cylc-flow-8.3.3 Hilary James Oliver et al. https://doi.org/10.5281/zenodo.12801923

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Short summary

We study aerosol–fog interactions near Paris using a weather and climate model with high spatial resolution. We show that our model can simulate the fog life cycle effectively. We find that the fog droplet number concentrations, the amount of liquid water in the fog, and the vertical structure of the fog are highly sensitive to the parameterization that simulates droplet formation and growth. The changes we propose could improve fog forecasts significantly without increasing computational costs.