A Numerical Case Study of Convection Initiation along Colliding Convergence Boundaries in Northeast Colorado

Abstract

A numerical cloud model has been used to simulate convective storm development on 17 July 1987 in northeast Colorado. The study involves the simulation of convergence along atmospheric boundaries and the subsequent development of convection. The model was initialized using observed conditions for this case day from the Convection Initiation and Downburst Experiment (CINDE). A two-dimensional version of the Clark NCAR nested grid model is employed. Results indicate that convection in boundary line collision cases can be successfully simulated by using actual observed atmospheric data. Gradual deepening of the moisture layer in the convergence zone was shown to destabilize the local atmosphere leading to the initiation of deep convection on this day. The modeled storm approximated the depth and intensity of the observed storms and displayed many of the features of the actual event. Sensitivity studies revealed that the timing and intensity of convection along boundaries is greatly affected by alterations in cross-line values of boundary-layer moisture or convergence and by variations in the vertical wind-shear profile within and above the boundary layer. Increasing the low-level moisture created a much stronger and taller modeled storm that developed much more rapidly. Variations in boundary-layer convergence were shown to affect the timing and character of the modeled storm. Horizontal vorticity in the boundary layer, associated with low-level vertical wind shear, was important for the production of deep convection. When the two air masses collided, deeper lifting was obtained if the opposing vorticity of the moving boundaries was balanced than if one of the vorticity sources was significantly stronger than the other. A threshold value of shear above the boundary layer was shown to inhibit the convective development of the modeled storm. These sensitivity studies emphasize the importance of considering the mesoscale variability of these key parameters in nowcasting convection.