Drivers of reduced permafrost cooling efficacy of equatorial stratospheric aerosol injection in the Eastern Arctic compared to a moderate emission pathway - Preprint

[Geoengineering News]

https://essopenarchive.org/doi/full/10.22541/essoar.177100420.06303100/v1

Authors: Isaline Businger, Rhonda Müller, Raleigh Grysko, Jacqueline Oehri, Jin-Soo Kim, Gabriela Schaepman-Strub

13 February 2026

Abstract

The Arctic is warming about four times faster than the global average, with permafrost thaw representing a potential global climate tipping element. Given the insufficient rate of carbon emission reductions, stratospheric aerosol injection (SAI) has emerged as a strategy to abate climate warming. However, its effects on permafrost thaw drivers remain uncertain. The G6sulfur experiment, part of the Geoengineering Model Intercomparison Project (GeoMIP6), aims to reduce radiative forcing in the high-emission scenario (ssp585) to levels comparable to those in the moderate-emission scenario (ssp245) by injecting stratospheric aerosols near the equator. Analyzing the G6sulfur results, we find that this intervention alters atmospheric circulation, modifying winds, cloud properties, and the North Atlantic Oscillation, which affect temperature patterns and longwave radiation. These changes shift the relative importance of mechanisms driving summer permafrost thaw, resulting in a distinct spatial pattern: increased thaw depth in the Eastern Hemisphere (+0.51 ± 0.07 m) and decreased thaw in the Western Hemisphere (-0.26 ± 0.06 m), compared to the ssp245 scenario targeted by the intervention. While G6sulfur reduces radiative forcing to levels similar to ssp245 and slows permafrost decline by 2080–2099 relative to ssp585 (+4.61 ± 0.21 × 106 km2), it fails to preserve as much permafrost area as ssp245 (-1.08 ± 0.18 × 106 km2). By altering the drivers of permafrost dynamics, G6sulfur creates spatial variations in thaw patterns, resulting in an overall reduction in permafrost area compared to ssp245. Our findings underscore the need to better understand and optimize SAI deployment to avoid unintended regional impacts.

Source: ESS Open Archive