Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 26, issue 4
Articles | Volume 26, issue 4
https://doi.org/10.5194/acp-26-3025-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-3025-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 4
Research article
 | 
27 Feb 2026
Research article |  | 27 Feb 2026

From column to surface: connecting the performance in simulating aerosol optical properties and PM2.5 concentrations in the NASA GEOSCCM

Caterina Mogno, Peter R. Colarco, Allison B. Collow, Sampa Das, Sarah A. Strode, Vanessa Valenti, Michael E. Manyin, Qing Liang, Luke Oman, Stephen D. Steenrod, and K. Emma Knowland

Supplement

https://doi.org/10.5194/acp-26-3025-2026-supplement

Data sets

MODIS Atmosphere L2 Aerosol Product, NASA MODIS Adaptive Processing System R. Levy and C. Hsu https://doi.org/10.5067/MODIS/MOD04_L2.006

MODIS Atmosphere L2 Aerosol Product, NASA MODIS Adaptive Processing System R. Levy and C. Hsu https://doi.org/10.5067/MODIS/MYD04_L2.006

Model code and software

GEOSagcm-Icarus-3_2_p9_MEM_22x Global Modeling and Assimilation Office (GMAO) and Atmospheric Chemistry and Dynamics Laboratory https://doi.org/10.5281/zenodo.18716695

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Short summary
We investigated a climate model's ability to simulate atmospheric aerosols focusing on the relationship between mass and optical properties, by comparing predictions with observations. Our analysis revealed that model errors in aerosol scattering primarily stem from inaccurate particle mass concentrations and relative humidity, rather than flawed optical property assumptions in the model. These findings point out improvements for enhancing the accuracy for aerosols representation in our model.
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