Abstract

Stratospheric aerosol injection (SAI) is the theoretical deployment of sulphate particles into the stratosphere to reflect incoming solar radiation and trigger a cooling impact at the Earth’s surface. This study assessed the potential impact of SAI geoengineering on temperature and precipitation extremes over South Africa (SAF) and its climatic zones in the future (2075–2095) using simulations from the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) project. We analyse three different experiments from the GLENS project, each of which simulate stratospheric SO2 injection under the representative concentration pathway 8.5 (RCP8.5) emissions scenario: (i) tropical injection around 22.8–25 km altitude (GLENS), (ii) tropical injection around 1 km above the tropopause (GLENS_low), and (iii) injection near the equator around 20–25 km (GLENS_eq). The study used a set of the Expert Team on Climate Change Detection and Indices describing temperature and rainfall extremes to assess the impact of the three SAI experiments on extreme weather in the future over SAF. The results of this study indicate that, relative to the baseline period (2010–2030), all three SAI experiments are mostly over-effective in offsetting the projected RCP8.5 increase in the frequency of hot (up to −60%) and decrease (up to +10%) in cold temperature extremes over SAF and its climatic zones. These findings suggest that SAI could cause over-cooling in SAF. However, SAI impact on precipitation extremes is less linear and varies across the country’s climatic zones. For example, SAI could reinforce the projected decrease in precipitation extremes across most of SAF, although it could exacerbate heavy precipitation over the KwaZulu-Natal Coast. These findings are consistent across SAI experiments except in magnitude, as GLENS_eq and GLENS_low could cause larger decreases in precipitation extremes than GLENS. These findings imply that SAI could alleviate heat stress on human health, agriculture, and vulnerable communities while simultaneously decreasing infrastructure and crops’ vulnerability to flooding. It is, however, essential to interpret these findings cautiously as they are specific to the SAI experiments and modelling settings considered in the GLENS project.

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