True stochastic nature of aerosol–cloud interactions

Determine whether aerosol–cloud interactions are intrinsically stochastic at fine spatiotemporal scales, as opposed to an artifact of analysis using an observation-trained random forest regression model, by establishing the true physical nature of aerosol–cloud interactions from first-principles frameworks.

Background

The paper uses a random forest regression model trained on three years of ACTIVATE field observations to predict cloud droplet number concentration from aerosol and meteorological predictors. While the model successfully predicts climatological behavior, it fails in individual cases and short timescales, suggesting apparent stochasticity.

The authors caution that their inference of stochasticity is derived from data-driven analysis rather than first-principles physical theory, leaving open the fundamental question of whether aerosol–cloud interactions are truly stochastic in nature.