The field of climate prediction has been bedeviled by the problem of how to represent the enormous complexity of clouds. The usual strategy is to peform deterministic simulations with advanced cloud models. The study outlined here concentrates on a statistical approach that is arguably better suited to determining the mean climatological state. The presented observations from a wide range of satellite platforms show that a power-law well describes frequencies of occurence of cloud sizes across a very wide range of scales, and that the exponent is robust to local climatological characteristics as surface temperature, aerosol loading, Coriolis forces, or dominant cloud type. Instead, the distribution of cloud sizes emerge simply from a competition for energy and air that occurs due to small-scale cloud mixing processes at cloud edge.

Natural aerosols have long been understood to have a substantial effect on Earth’s climate, in particular because they define a natural baseline that affects the magnitude of anthropogenic aerosol radiative forcing. In this Opinion the authors highlight the very large uncertainties in the radiative effects of aerosols particularly from fires and dust, which they estimate to exceed the magnitude of anthropogenic aerosol forcing over the entire industrial period. Rather than just defining a pre-industrial baseline for aerosol, natural emissions have changed substantially during pre-industrial times and through the industrial period, making a very poorly defined contribution to climate change. Based on the estimated large uncertainties, the authors argue for greater research efforts to narrow them.