Aerosols, often emitted alongside greenhouse gases, can brighten clouds and cause significant cooling. However, the uncertainty associated with aerosol-cloud interactions (ACI) is large and potentially significant enough to mask a sizable portion of greenhouse gas-related warming. A higher aerosol concentration generally suppresses rainfall and increases the abundance of droplets in clouds passing over Graciosa Island in the Azores, where an Atmospheric Radiation Measurement (ARM) site provides continuous ground measurements of aerosol and cloud properties. Satellite data shows that cloud drops remain affected by elevated concentrations of aerosol for several days when tracked across thousands of kilometers. Earth system model simulations show good agreement with observations, but differences remain despite model modification.
Researchers developed a Lagrangian framework that tracks the ACI along the trajectories of air parcels and applied it to the Energy Exascale Earth System Model (E3SM). This framework utilizes geostationary satellite measurements of clouds throughout their lifetime, thereby providing a new constraint needed to quantify and understand highly non-linear causal connections among cloud water, precipitation, and aerosols. New results reveal that clouds contain more cloud droplets that persist for several days when polluted. These responses are simulated in E3SM, but the polluted clouds modeled by E3SM are not thick enough. These findings provide insights into model strengths and weaknesses, which are useful for model development efforts to improve cloud-controlling processes so that future climate change projections are better understood and quantified.
A series of E3SM experiments with variations of precipitation parameterization were carried out to determine whether the sensitivity of aerosol-affecting warm rain modifies cloud properties at multiple scales. In general, the results showed only small changes, known as the Twomey effect, in the size of cloud droplets during experiments. The researchers saw larger effects on adjustments about the amount of water and cloud size. While E3SM predicts a similar Twomey effect as the observations, it does so due to compensating errors through the strong positive bias in cloud droplet number concentration, or Nd, (decreases the Twomey effect) and the large increase in Nd (larger effect) between clean and polluted conditions. These effects on larger-scale cloud properties lead to a radiative effect. While the Twomey-related estimates agree with satellite observations reasonably well, E3SM simulations of water content and size adjustments produce too much radiative warming because polluted clouds are thinner in E3SM than in observations. A new framework suggests that aerosol activation, warm-rain processes, and or turbulence representations may require further modification to achieve better agreement with base state variables (such as cloud droplet concentration and liquid water amount) as well as with satellite and ARM observations.