One of the grand challenges in climate science is to reduce uncertainty in estimates of climate sensitivity, which quantifies how much Earth’s surface warms in response to a doubling of carbon dioxide relative to preindustrial levels. This uncertainty is large because climate sensitivity aggregates myriad processes, from microscale aerosol-cloud interactions to planetary-scale atmospheric and ocean circulations, into one number. Clouds, which are notoriously difficult to measure and simulate, are the main driver of the uncertainty.