Introducing aerosol-cloud interactions in the ECMWF model reveals new constraints on aerosol representation

Andreozzi, Paolo; Fielding, Mark D.; Hogan, Robin J.; Forbes, Richard M.; Hill, Adrian A.; Rémy, Samuel; Bohn, Birger; Löhnert, Ulrich

doi:10.5194/acp-26-11309-2026

Articles | Volume 26, issue 15

https://doi.org/10.5194/acp-26-11309-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-26-11309-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 15

Research article

|

12 Aug 2026

Research article |

| 12 Aug 2026

Introducing aerosol-cloud interactions in the ECMWF model reveals new constraints on aerosol representation

Paolo Andreozzi, Mark D. Fielding, Robin J. Hogan, Richard M. Forbes, Adrian A. Hill, Samuel Rémy, Birger Bohn, and Ulrich Löhnert

Data sets

Aerosol activation lookup table (LUT) for CAMS/IFS-COMPO CY49R1 Paolo Andreozzi https://doi.org/10.5281/zenodo.20051869

IFS-COMPO CY49R1 free-running chemistry and aerosols, years 2003-2005 ECMWF Research Department https://doi.org/10.21957/f7xh-vb32

IFS-COMPO CY49R1 free-running chemistry and aerosols, years 2006-2008 ECMWF Research Department https://doi.org/10.21957/8hr4-c209

IFS-COMPO CY49R1 free-running chemistry and aerosols, years 2009-2011 ECMWF Research Department https://doi.org/10.21957/ke91-dq34

IFS-COMPO CY49R1 free-running chemistry and aerosols, years 2012-2014 ECMWF Research Department https://doi.org/10.21957/90a6-yf93

IFS-COMPO CY49R1 free-running chemistry and aerosols, years 2015-2017 ECMWF Research Department https://doi.org/10.21957/acke-ra52

IFS-COMPO CY49R1 free-running chemistry and aerosols, years 2018-2020 ECMWF Research Department https://doi.org/10.21957/jjzh-av89

Model code and software

pandreozzz/optimind: First release of OptimiNd (Version v0.1) Paolo Andreozzi https://doi.org/10.5281/zenodo.21809161

miepython: Pure python calculation of Mie scattering (Version 3.3.0) Scott Prahl https://doi.org/10.5281/zenodo.7949263

Short summary

Aerosols significantly contribute to the Earth’s climate, but models still struggle to represent them. Here we use satellite observations of clouds to constrain aerosol processes in a weather and air-quality model. We show that African wildfires lead to overly bright simulated clouds and that the model removes too much aerosol in mixed-phase clouds. This demonstrates how cloud observations can target weakly constrained aerosol processes, with potential benefits for weather and climate modelling.