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https://www.frontiersin.org/articles/10.3389/fenvs.2023.1205515/abstract


*Authors*
 Lauren Wheeler, Todd Zeitler, Sarah Brunell, Jessica Lien, Lyndsay Shand,
Benjamin Wagman, Erika Roesler, Carianne Martinez, Kevin Potter

*21 November 2023*

*Abstract*
As the prospect of exceeding global temperature targets set forth in the
Paris Agreement becomes more likely, methods of climate intervention are
increasingly being explored. With this increased interest there is a need
for an assessment process to understand the range of impacts across
different scenarios against a set of performance goals in order to support
policy decisions. The methodology and tools developed for Performance
Assessment (PA) for nuclear waste repositories shares many similarities
with the needs and requirements for a framework for climate intervention.
Using PA, we outline and test an evaluation framework for climate
intervention, called Performance Assessment for Climate Intervention (PACI)
with a focus on Stratospheric Aerosol Injection (SAI). We define a set of
key technical components for the example PACI framework which include
identifying performance goals, the extent of the system, and identifying
which features, events, and processes are relevant and impactful to
calculating model output for the system given the performance goals. Having
identified a set of performance goals, the performance of the system,
including uncertainty, can then be evaluated against these goals. Using the
Geoengineering Large Ensemble (GLENS) scenario, we develop a set of
performance goals for monthly temperature, precipitation, drought index,
soil water, solar flux, and surface runoff. The assessment assumes that
targets may be framed in the context of risk-risk via a risk ratio, or the
ratio of the risk of exceeding the performance goal for the SAI scenario
against the risk of exceeding the performance goal for the RCP8.5 scenario.
This is a provisional file, not the final typeset article From regional
responses, across multiple climate variables, it is then possible to assess
which pathway carries lower risk relative to those goals. The assessment is
not comprehensive but rather a demonstration of the evaluation of an SAI
scenario. Future work is needed to develop a more complete assessment that
would provide additional simulations to cover parametric and aleatory
uncertainty and enable a deeper understanding of impacts, informed scenario
selection, and allow further refinements to the approach.

*Source: Frontiers *

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