During the summer months, one of the primary roles of forecasters at White Sands Missile Range (WSMR) is to monitor convective activity and warn personnel working on the range of any associated danger, including that from C-G lightning. The goal of this study is to show how various information about storms from above the freezing level can be combined with boundary layer forcing information to produce C-G lightning potential forecasts that are improved over those based on simple reflectivity information alone.

This methodology utilizes radar reflectivity information above the freezing level in conjunction with information about boundary layer convergence lines or gust fronts. The reflectivity information includes the volume of echo > 30 dBZ and the maximum reflectiviy above approximately the -10 C level for cells identified with a centroid based cell tracker. Also included is the volume growth rate and the maximum height of the 30 dBZ echo for the identified cell. The boundary layer convergence line information includes the boundary relative steering flow, which for non-synoptically forced situations that are often observed at WSMR, provides an indication of whether the cell will stay with the boundary and further intensify. The final lightning potential forecast is produced by combining this information using the NCAR Convective Weather Nowcast System, a fuzzy logic based expert system.

Example forecasts will be presented, showing how the addition of the various fields affect the forecasts. Verification results will also be provided detailing how this additional information helps the forecasts.