Quantifying the temperature-independent effect of stratospheric aerosol geoengineering on global-mean precipitation in a multi-model ensemble

This is the final version of the article. Available from the publisher via the DOI in this record.The reduction in global-mean precipitation when stratospheric aerosol geoengineering is used to counterbalance global warming from increasing carbon dioxide concentrations has been mainly attributed to the temperature-independent effect of carbon dioxide on atmospheric radiative cooling. We demonstrate here that stratospheric sulphate aerosol itself also acts to reduce global-mean precipitation independent of its effects on temperature. The temperature-independent effect of stratospheric aerosol geoenginering on global-mean precipitation is calculated by removing temperature-dependent effects from climate model simulations of the Geoengineering Model Intercomparison Project (GeoMIP). When sulphate aerosol is injected into the stratosphere at a rate of 5 Tg SO2 per year the aerosol reduces global-mean precipitation by approximately 0.2 %, though multiple ensemble members are required to separate this effect from internal variability. For comparison, the precipitation reduction from the temperature-independent effect of increasing carbon dioxide concentrations under the RCP4.5 scenario of the future is approximately 0.5%. Thetemperature-independent effect of stratospheric sulphate aerosol arises from the aerosol's effect on tropospheric radiative cooling. Radiative transfer calculations show this is mainly due to increasing downward emission of infrared radiation by the aerosol, but there is also a contribution from the stratospheric warming the aerosol causes. Our results suggest climate model simulations of solar dimming can capture the main features of the global-mean precipitation response to stratospheric aerosol geoengineering.Natural Environment Research Council (NERC)Engineering and Physical Sciences Research Council (EPSRC)We thank Hugo Lambert and Mat Collins for useful discussions, and Ulrike Niemeier for extensive help with data access. A Ferraro was supported by the Natural Environment Research Council PROBEC grant (NE/K016016/1). H Griffiths was supported by the Engineering and Physical Sciences Research Council Vacation Bursary Scheme. We thank all the climate modelling groups for conducting the GeoMIP simulations and making their output available. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in table 1 of this paper) for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portal