Evaluation of deep convective transport in storms from different convective regimes during the DC3 field campaign using WRF‐Chem with lightning data assimilation

Deep convective transport of surface moisture and pollution from the planetary boundary layer to the upper troposphere and lower stratosphere affects the radiation budget and climate. This study analyzes the deep convective transport in three different convective regimes from the 2012 Deep Convective Clouds and Chemistry field campaign: 21 May Alabama air mass thunderstorms, 29 May Oklahoma supercell severe storm, and 11 June mesoscale convective system (MCS). Lightning data assimilation within the Weather Research and Forecasting (WRF) model coupled with chemistry (WRF‐Chem) is utilized to improve the simulations of storm location, vertical structure, and chemical fields. Analysis of vertical flux divergence shows that deep convective transport in the 29 May supercell case is the strongest per unit area, while transport of boundary layer insoluble trace gases is relatively weak in the MCS and air mass cases. The weak deep convective transport in the strong MCS is unexpected and is caused by the injection into low levels of midlevel clean air by a strong rear inflow jet. In each system, the magnitude of tracer vertical transport is more closely related to the vertical distribution of mass flux density than the vertical distribution of trace gas mixing ratio. Finally, the net vertical transport is strongest in high composite reflectivity regions and dominated by upward transport. Key Points Lightning data assimilation improves model simulations of storm location and vertical structure Rear inflow jets within mesoscale convective systems may weaken boundary layer trace gas vertical transport The tracer vertical transport is more controlled by the vertical gradient of mass flux than the vertical gradient of trace gas