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We study the sensitivity of South Asian Summer Monsoon (SASM) precipitation to Southern Hemisphere (SH) subtropical Absorbed Solar Radiation (ASR) changes using Community Earth System Model 2 simulations. Reducing positive ASR biases over the SH subtropics impacts SASM, and is sensitive to the ocean basin where changes are imposed. Radiation changes over the SH subtropical Indian Ocean (IO) shifts rainfall over the equatorial IO northward causing 1–2 mm/day drying south of equator, changes over the SH subtropical Pacific increases precipitation over northern continental regions by 1–2 mm/day, and changes over the SH subtropical Atlantic have little effect on SASM precipitation. Radiation changes over the subtropical Pacific impacts the SASM through zonal circulation changes, while changes over the IO modify meridional circulation to bring about changes in precipitation over northern IO. Our findings suggest that reducing SH subtropical radiation biases in climate models may also reduce SASM precipitation biases. Plain Language Summary: Precipitation from South Asian Summer Monsoon (SASM) is of high significance to the livelihoods of over a billion people. As the global climate continues to evolve, it is essential to have a clear understanding of the possible future changes to the SASM. However, current state‐of‐the‐art climate models have difficulties in simulating climatological mean SASM precipitations. Here we study sensitivity of SASM precipitation to subtropical southern ocean radiation as one of the possible causes of SASM precipitation bias. Our experiments indicate that SASM precipitation is sensitive to southern hemisphere (SH) subtropical radiation changes particularly to those in subtropical Pacific. These findings imply that improving SH subtropical radiation biases might improve SASM precipitation simulations in climate models. Key Points: We test if biases in southern hemisphere shortwave radiation contributes to biases in South Asian summer monsoon precipitation in the CESM2Reducing incoming shortwave radiation in the subtropical southern hemisphere reduces dry biases over continental South AsiaThis effect is mostly due to forcing in the South Pacific, with less impact from the Atlantic or Indian Ocean [ABSTRACT FROM AUTHOR]

The magnitude of the aerosol forcing remains among the largest unknowns when assessing climate sensitivity over the historical period. Here, we quantify and explain a crucial but often overlooked source of uncertainty in aerosol forcing: the temporal variability of aerosol emissions. We show that time‐variability in biomass burning (BB) emissions weakens the time‐averaged total aerosol forcing, particularly in the Northern Hemisphere mid‐ to high‐latitudes. BB emissions variability produces weaker (less negative) mean effective radiative forcing (ERF) compared to scenarios with no interannual variability in emissions. Satellite‐estimated BB emissions (and associated variability) result in a June–September absolute ERF (relative to zero BB emissions) of −7.7 W m−2 from 50° to 70°N, compared to −10.4 W m−2 when no emissions variability is used in the Community Earth System Model version 2 (CESM2). This difference in forcing is attributable to nonlinear aerosol‐cloud interactions. Aerosol forcing will be overestimated (i.e., more negative) if emissions are temporally‐smoothed. Plain Language Summary: Aerosols are small particles in the air that can impact the climate, but we don't know exactly how much. One reason for this uncertainty is that the amount of aerosols can change a lot over time, especially when it comes from burning things like wood or plants (i.e., biomass burning emissions). When the amount of these biomass burning aerosols changes a lot from year‐to‐year, it has less of an impact on the climate. This is because clouds react less strongly when aerosol concentrations are high compared to when they are low. If we smooth out the changes in aerosol amounts over time (as is done with most Earth System Model simulations), we will overestimate their cooling impact on the climate. Key Points: The radiative forcing due to aerosols is overestimated if emissions are temporally‐smoothedInterannual variability in aerosol emissions leads to a weakened time‐average cloud radiative effectChanges in time‐average cloud radiative effect with differing aerosol variability are due to nonlinear aerosol‐cloud interactions [ABSTRACT FROM AUTHOR]