A theoretical study of the impact of anthropogenic CCN on the dynamics of deep convective clouds in the EPIC region

Clouds are important components of the climate system as they affect the Earth's albedo and they participate in the hydrological cycle. One of the largest uncertainties in climate modeling is related to the parameterization of convective processes and, in particular, the question of how anthropogenic emissions may affect the different types of clouds is still open. Most research has been devoted to warm stratocumulus clouds, and only recently some studies incorporate changes in cirrus and mixed phase clouds. Emissions of gases and particles in industrial and urban regions may affect the microphysics and dynamics of clouds developing near and downwind of said emissions.

In this study we have introduced changes in the parameterization of the autoconversion and accretion processes in the Advanced Regional Prediction System (ARPS, developed at the Center for the Analysis and Prediction of Storm at the University of Oklahoma). The CCN used in the model were obtained from in situ observations by the instrumented C-130 (NSF, operated by NCAR), during the East Pacific Investigations of Climate (EPIC). Three cases were selected, in two of which there was evidence that the CCN were modified by anthropogenic influence. The spectra were then incorporated as initial droplet distributions for the simulations. The thermodynamic soundings were obtained from radiosondes deployed from the Ron Brown oceanographic ship stationed at 10 N and 95 W, during EPIC. These results indicate that the dynamics of the deep, mixed phase clouds simulated is sensitive to the input of large concentrations of anthropogenic CCN. The precipitation development is delayed in the simulations when more CCN are included. These results are in agreement with observations of the precipitation spectra from the C-130, that had indicated the absence of large droplets in the most polluted situation. Nevertheless, some other simulations with higher instability in the environment indicate a substantially reduced sensitivity.