To comprehensively address the goal for all possible environmental factor combinations at a lower computational expense, a synergistic use of idealized cloud-resolving model simulations and an advanced statistical algorithm has been made. In this study, six atmospheric factors including moisture, instability, and wind profiles and five geophysical factors including soil moisture, air-surface temperature difference, and latitude were considered. Through a Latin Hypercube sampling method which allows simultaneous variation of all the selected factors, 143 idealized simulations have been designed to investigate moist sea breeze convection over a coastal tropical rainforest. This is representative of equatorial coastal regions such as the coast of Cameroon. Using the Regional Atmospheric Modeling System (RAMS), all simulations have been performed in which combinations of the eleven environmental factors were perturbed.
Ultimately, regimes in which a subset of environmental factors exerts the largest and least control over the surface aerosol concentration ahead of and behind the sea-breeze front has been distinguished through variance-based sensitivity analysis. The results of this analysis will be presented. Mechanisms responsible for the redistribution of aerosol at each regime will also be demonstrated.