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https://essopenarchive.org/doi/full/10.22541/essoar.170785861.15326368/v1

*Authors*
Jared Farley¹,Douglas G Macmartin¹, Daniele Visioni, Ben Kravitz

*13 Feb 2024*

*Cite as*: Jared Farley¹, Douglas G Macmartin¹, Daniele Visioni, et al.
Emulating Inconsistencies in Stratospheric Aerosol Injection. ESS Open
Archive . February 13, 2024.

DOI: 10.22541/essoar.170785861.15326368/v1

*Abstract*
Stratospheric Aerosol Injection (SAI) would involve the addition of sulfate
aerosols in the stratosphere in order to reflect part of the incoming solar
radiation, thereby cooling the climate. Studies trying to explore the
impacts of SAI have often focused on idealized scenarios without explicitly
introducing what we call “inconsistencies” in a deployment. A concern often
discussed is what would happen to the climate system after an abrupt
termination of its deployment, whether inadvertent or deliberate. However,
there is a much wider range of plausible inconsistencies in deployment than
termination that should be evaluated to better understand associated risks.
In this work, we simulate a few representative inconsistencies in a
pre-existing SAI scenario: an abrupt termination, a decade-long gradual
phase-out, and 1-year and 2-year temporary interruptions of deployment.
After examining their climate impacts, we use these simulations to train an
emulator, and use this to project global mean temperature response for a
broader set of inconsistencies in deployment. Our work highlights the
capacity of a finite set of explicitly-simulated scenarios that include
inconsistencies to inform an emulator that is capable of expanding the
space of scenarios that one might want to explore far more quickly and
efficiently.

*Source: ESS*

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