Characterizing the magnitute and evolution of cloud water adjustment to aerosol perturbations is crucial to understand aerosol effects on clouds (i.e., brightening or darkening). Using a large ensemble of (300+) diurnal large-eddy simulations (LES) of marine stratocumulus and a novel conditional Monte Carlo sampling technique, I demonstrated that solar heating as a key factor buffering cloud responses after sunrise, underscoring the importance of timing for aerosol seeding in MCB scenarios. The conditional Monte Carlo sampling approach has the potential to be applied to also observational datasets and GCM Perturbed Parameter Ensembles (PPEs).

[LEFT] Diurnal cycle of the Nd–LWP regression slope, separated by colors representing different values at sunrise (large dots). Mean values of the 50 times, 25-member conditional Monte Carlo subsampling approach are shown. [RIGHT] Diurnal cycle of the Nd–SWreflected regression slope, separated by colors representing aerosol perturbations ("seeding") at different times before sunrise.

This work not only illustrates a (solar heating) buferring mechanism with direct implications for Marine Cloud Brightening (MCB) proposals, but also demonstrates the usefulness of an innovative conditional Monte Carlo (cMC) sampling technique for testing hypotheses with simulation ensembles (e.g., 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