Poster's note:  not sure how this got missed.

Authors
D. G. MacMartin, D. Visioni  B. Kravitz, and M. Sugiyama

https://www.pnas.org/doi/full/10.1073/pnas.2202230119

Significance
The benefits and risks of solar radiation modification (SRM; also known as
solar geoengineering) need to be evaluated in context with the risks of
climate change and will depend on choices such as the amount of cooling.
One challenge today is a degree of arbitrariness in the scenarios used in
current SRM simulations, making comparisons difficult both between SRM and
non-SRM cases and between different SRM scenarios. We address this gap by
1) defining a set of plausible scenarios capturing a range of choices and
uncertainties, and 2) providing simulations of these scenarios that can be
broadly used for comparative impact assessment. This is an essential
precursor to any international assessment by, e.g., the Intergovernmental
Panel on Climate Change.

Abstract
Making informed future decisions about solar radiation modification (SRM;
also known as solar geoengineering)—approaches such as stratospheric
aerosol injection (SAI) that would cool the climate by reflecting
sunlight—requires projections of the climate response and associated human
and ecosystem impacts. These projections, in turn, will rely on simulations
with global climate models. As with climate-change projections, these
simulations need to adequately span a range of possible futures, describing
different choices, such as start date and temperature target, as well as
risks, such as termination or interruptions. SRM modeling simulations to
date typically consider only a single scenario, often with some unrealistic
or arbitrarily chosen elements (such as starting deployment in 2020), and
have often been chosen based on scientific rather than policy-relevant
considerations (e.g., choosing quite substantial cooling specifically to
achieve a bigger response). This limits the ability to compare risks both
between SRM and non-SRM scenarios and between different SRM scenarios. To
address this gap, we begin by outlining some general considerations on
scenario design for SRM. We then describe a specific set of scenarios to
capture a range of possible policy choices and uncertainties and present
corresponding SAI simulations intended for broad community use.
Source: PNAS

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