Direct Radiative Impacts of Stratospheric Aerosols on the Tropical Troposphere: Clouds, Precipitation, and Circulation in Convection-Resolving and Global Simulations

TL;DR

This study investigates how stratospheric aerosols from solar geoengineering affect tropical rainfall, clouds, and circulation using multi-model simulations, revealing reduced precipitation but negligible impact on circulation, with uncertainties mainly from cloud processes.

Contribution

It provides a multi-model analysis of SAI impacts on the tropical atmosphere, clarifying mechanisms and highlighting uncertainties from cloud processes affecting predictability.

Findings

SAI reduces tropical mean precipitation

Cloud radiative heating moderates precipitation reduction

Surface-temperature-independent effects on circulation are negligible

Abstract

A concern for stratospheric aerosol injection (SAI) is that stratospheric aerosols could inadvertently alter rain and winds through mechanisms independent of the intended surface cooling. We here use a multi-model framework to investigate how the tropical troposphere responds to SAI when sea surface temperatures are held fixed. By performing convection-resolving simulations in small-domains and in mock-Walker setups, and contrasting these with global climate model simulations, we trace how stratospheric aerosols radiatively heat the troposphere, and in turn alter convection, clouds, and rainfall. Our simulations show an SAI-induced reduction in tropical mean precipitation, yet decreased cloud radiative heating moderates this effect and complicates its predictability. Regional rainfall anomalies within the tropics can be substantial. However, surface-temperature-independent effects on tropical circulation are found to be negligible, indicating that stratospheric aerosols do not inherently alter the tropical overturning circulation as previously suggested. These results clarify the mechanisms governing SAI hydroclimate impacts and show that key uncertainties arise from cloud processes that models are unable to constrain. Consequently, near-term SAI deployment would carry the risk of being implemented without the ability to reliably predict its hydroclimate impacts.