https://gmd.copernicus.org/articles/18/8679/2025/

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

*18 November 2025*

*Abstract*
Climate model simulations incorporating stratospheric aerosol injection
(SAI) generally require more computational resources compared to
out-of-the-box applications, due to the importance of stratospheric
chemistry. This presents a challenge for SAI research, especially because
there are numerous ways and scenarios through which SAI can be implemented.
Here, we propose a novel application of pattern-scaling techniques that
allows us to generate SAI forcing in the Community Atmosphere Model (CAM) –
a model without interactive stratospheric chemistry – using pre-existing
data from the Whole Atmosphere Community Climate Model (WACCM), a
state-of-the-art model with interactive stratospheric chemistry, but
expensive to run. In doing so, a significant portion of the computational
budget is saved. The present method requires a pre-existing dataset of a
representative SAI experiment and its corresponding control experiment,
with interactive stratospheric chemistry. The data is converted into a set
of relations to determine the forcing fields given any required optical
depth of the aerosol field. The present method is suitable for applications
that use dynamical feedback controllers and is intended to aid impact
research into the tropospheric and (sub)surface climate changes due to SAI.
The results of climate simulations with aerosols prescribed by the present
procedure are in close agreement with those from the full-complexity model,
even for different model versions, horizontal resolutions and SAI forcing
scenarios.

*Source: EGU*

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