Analysis of the NCWF shows that although the motion vectors are generally accurate, during rapid growth and dissipation of storm systems the forecast tend to be poor (Megenhardt et. al., 2000). An automated technique using RUC, satellite, and radar data to improve forecasting during the growth phase of multi-cellular convective systems associated with large-scale, daytime forcing is presented. The algorthm builds on the NCWF storm extrapolation. The RUC data are used to determine locations of large-scale frocing. These data are processed using two different algorihtms. The first utilizes fuzzy logic to determine the broad locations of large scale forcing based on the RUC surface equivalent potential temperature gradient, convergence, and vorticity fields. The second algorihtm tracks the boundary and provides motion vectors and orientation of the line. In regions of synoptic forcing, small storms are grown and clumped along the orientation of the boundary based on trending of radar and satellite data. In areas outside of the large-scale forcing the extrapolation forecast is used. This technique will be presented along with preliminary results. Future upgrades will also be discussed.