Aerosol transport and wet scavenging in deep convective clouds: A case study and model evaluation using a multiple passive tracer analysis approach

Abstract

Wet scavenging of aerosols by continental deep convective clouds is studied for a supercell storm complex observed over Oklahoma during the Deep Convective Clouds and Chemistry campaign. A new passive-tracer-based transport analysis framework is developed to characterize convective transport using vertical profiles of several passive trace gases. For this case, the analysis estimates that observed passive gas mixing ratios in the upper troposphere convective outflow consist of 47% low level (<3km) inflow air, 32% entrainedmidtroposphere air, and 21% upper troposphere air. The new analysis framework is used to estimate aerosol wet scavenging efficiencies. Observations yield high overall scavenging efficiencies of 81% for submicron aerosol mass. Organic, sulfate, and ammonium aerosols have similar wet scavenging efficiencies (80%-84%). The apparent scavenging efficiency for nitrate aerosol is much lower (57%), but the scavenging efficiency for nitrate aerosol plus nitric acid combined (84%) is close to the other species. Scavenging efficiencies for aerosol number are high for larger particles (84%for 0.15-2.5 µmdiameter) but are lower for smaller particles (64% for 0.03-0.15 µm). The storm is simulated using the chemistry version of the Weather Research and Forecasting model. Compared to the observation-based analysis, the standard model strongly underestimates aerosol scavenging efficiencies by 32% and 41% in absolute differences for submicron mass and number. Adding a new treatment of secondary activation significantly improves simulated aerosol scavenging, producing wet scavenging efficiencies that are only 7% and 8% lower than observed efficiencies. This finding emphasizes the importance of secondary activation for aerosol wet removal in deep convective storms.