Investigating the relationship between water vapour convergence and severe convection using the WRF model at 1km resolution

Severe convection is often preceded by low-level water vapor convergence. Observations of water vapor convergence can potentially increase the lead-time and knowledge of locations for nowcasting severe weather. In this study, we examine results of high-resolution numerical simulations of severe convection to determine the relationship between low-level water vapor convergence and severe convection. Three cases are selected from the period of the the Bow-Echo and Mesoscale Convective Vortex Experiment (BAMEX), each of different convective-system mode; a bow-echo system, a line of supercells and a leading-line Mesoscale Convective System (MCS). The Weather Research and Forecasting (WRF) model is used with one-way nesting to simulate the pre-convective environment, convection initiation and mesoscale organization at 1km horizontal grid-spacing.

For the range of convective situations, low-level water vapor convergence evolves on two timescales; a slow increase on synoptic/mesoscale timescales in the hours before convection followed by a fast increase close to the onset of severe convection. The rapid increase of water vapor (and its associated moisture convergence) can serve as a useful precursor to severe convection. Our results show a significant increase of water vapor convergence occurs prior to severe convection, with lead-times in the range of 20 to 40 minutes. This relationship appears to be quite robust for grid spacing smaller than 30km and temporal interval of 30 minutes or smaller. Based on these results, we conclude that a satellite remote sensing instrument capable of providing a 10 min repeat cycle and at a resolution of 10km would be able to detect significant moisture convergence, and provide useful warning for the possibility of severe convection.