Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 22
Articles | Volume 18, issue 22
https://doi.org/10.5194/gmd-18-8679-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-8679-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 22
Development and technical paper
 | 
18 Nov 2025
Development and technical paper |  | 18 Nov 2025

A computationally efficient method to model similar and alternate stratospheric aerosol injection experiments using prescribed aerosols in a lower-complexity version of the same model: a case study using CESM(CAM) and CESM(WACCM)

Jasper de Jong, Daniel Pflüger, Simone Lingbeek, Claudia E. Wieners, Michiel L. J. Baatsen, and René R. Wijngaard

Viewed

Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.

Total article views: 2,073 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,058 0 15 2,073 0 0
  • HTML: 2,058
  • PDF: 0
  • XML: 15
  • Total: 2,073
  • BibTeX: 0
  • EndNote: 0
Views and downloads (calculated since 22 Apr 2025)
Cumulative views and downloads (calculated since 22 Apr 2025)

Viewed (geographical distribution)

Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.

Total article views: 2,073 (including HTML, PDF, and XML) Thereof 2,000 with geography defined and 73 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2025
Download
Short summary
Injection of reflective sulfate aerosols high in the atmosphere is a proposed method to mitigate global warming. Climate simulations with injection are more expensive than standard future projections. We propose a method that dynamically scales the forcing fields based on pre-existing full-complexity data. This opens up possibilities for ensemble generation, new scenarios and higher resolution runs. We show that our method works for multiple model versions, injection scenarios and resolutions.
Read more
Share