Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 16
Articles | Volume 17, issue 16
https://doi.org/10.5194/gmd-17-6379-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-6379-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 16
Model description paper
 | 
29 Aug 2024
Model description paper |  | 29 Aug 2024

AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states

Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam

Viewed

Total article views: 1,375 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,117 203 55 1,375 26 24
  • HTML: 1,117
  • PDF: 203
  • XML: 55
  • Total: 1,375
  • BibTeX: 26
  • EndNote: 24
Views and downloads (calculated since 02 Feb 2024)
Cumulative views and downloads (calculated since 02 Feb 2024)

Viewed (geographical distribution)

Total article views: 1,375 (including HTML, PDF, and XML) Thereof 1,353 with geography defined and 22 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Read more