Aerosols (small airborne particles) impact Earth's climate, but their extent is unknown. By running climate model simulations and using machine learning to emulate millions of additional variants with different settings, we found that natural emissions like sea spray and sulfur are key sources of uncertainty in climate predictions. Our work shows that understanding these natural processes better can help improve climate models and make future climate projections more accurate.