Marine low-level clouds are key to the Earth’s energy budget due to their expansive coverage over global oceans and their high reflectance of incoming solar radiation. Their responses to anthropogenic aerosol perturbations remain the largest source of uncertainty in estimating the anthropogenic radiative forcing of climate. A major challenge is the quantification of the cloud water response to aerosol perturbations. In particular, the presence of feedbacks through microphysical, dynamical, and thermodynamical pathways at various spatial and temporal scales could augment or weaken the response. Central to this problem is the temporal evolution in cloud adjustment, governed by entangled feedback mechanisms. Using a large ensemble of (300+) diurnal large-eddy simulations (LES) of marine stratocumulus and a novel conditional Monte Carlo sampling technique, I demonstrate that solar heating as a key factor buffering cloud responses after sunrise, underscoring the importance of timing for aerosol seeding in MCB scenarios.

The Science I apply an innovative conditional Monte Carlo subsampling approach to a large ensemble of diurnal large-eddy simulation of non-precipitating marine stratocumulus. I find a persistent negative trend in this relationship at night, confirming that the role of microphysically enhanced cloud-top entrainment. After sunrise, the evolution in this relationship appears buffered and converges to ~-0.2 in the late afternoon. This buffering effect is attributed to a strong dependence of cloud-layer shortwave absorption on cloud liquid water path. These diurnal cycle characteristics further demonstrate a tight connection between cloud brightening potential and the relationship between cloud water and droplet number at sunrise, which has implications for the impact of the timing of advertent aerosol perturbations.

The Impact This study underscores the critical role of solar heating in modulating cloud responses, acting as a buffering mechanism with direct implications to Marine Cloud Brightening (MCB) strategies. Furthermore, the conditional Monte Carlo sampling framework introduced here could be readily extended to observational datasets and General Circulation Model (GCM) Perturbed Parameter Ensembles (PPEs).

  • J. Zhang, Y.-S. Chen, T. Yamaguchi, and G. Feingold (2024): Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli. Atmos. Chem. Phys., 24(18), 10425–10440. doi:10.5194/acp-24-10425-2024

  • Y.-S. Chen, J. Zhang, F. Hoffmann, T. Yamaguchi, and G. Feingold (2024): Diurnal evolution of non-precipitating marine stratocumuli in a large-eddy simulation ensemble. Atmos. Chem. Phys., 24(22), 12661–12685. doi:10.5194/acp-24-12661-2024