Evaluating clouds, aerosols, and their interactions in three global climate models using satellite simulators and observations

Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this investigation we compare aerosols, clouds, and their interactions in three global climate models (Geophysical Fluid Dynamics Laboratory-Atmosphere Model 3 (AM3), National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5), and Goddard Institute for Space Studies-ModelE2) to Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. Modeled cloud properties are diagnosed using a MODIS simulator. Cloud droplet number concentrations (N) are computed identically from satellite-simulated and MODIS-observed values of liquid cloud optical depth and droplet effective radius. We find that aerosol optical depth (τa) simulated by models is similar to observations in many regions around the globe. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in coastal marine stratocumulus versus remote ocean regions, though modeled values, in general, are higher than observed. Aerosol-cloud interactions were computed as the sensitivity of ln(N) to ln(τa) for coastal marine liquid clouds near South Africa (SAF) and Southeast Asia where τa varies in time. AM3 and CAM5 are more sensitive than observations, while the sensitivity for ModelE2 is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the sensitivity of ln(N) to ln(τa) at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite-simulated versus standard model values of N are compared; for CAM5 in SAF, standard model values are significantly lower than satellite-simulated values with a bias of 83 cm⁻³.