Short-term (0-2hr) Automated Growth Forecast of Multi-Cellular Convective Systems associated with Large-scale, Daytime Forcing

Preliminary case-study analysis of large multi-cellular storm systems show that a majority initiate and grow in association with synoptic scale (fronts) and meso-scale features (such as dry-lines) that are resolved by the RUC model. However, the RUC does a poor job of providing good short-term forecast of precipitation. Further RUC areas favorable for convective development based on fields such as CAPE, CIN, EPT, etc. tend to be very large. Data from radar and satellite are needed to help pin-point the location of storm development. However, past studies have shown that thunderstorm trend forecast based on radar data, does not improve over straight extrapolation. In this paper, we explore automated techniques to forecast growth of multi-cellular storms systems based on RUC, satellite, and national radar mosaics. This effort is part of work being done under the FAA Aviation Weather Research (AWR) Program's Convective Weather Product development team. The Convective Weather team consist of participants from MIT Lincoln Laboratory, the National Severe Storms Laboratory, and the National Center for Atmospheric Research (NCAR).

The RUC data are used to determine the location of large scale forcing and environmental conditions associated with the forcing. Subsequently the satellite and radar data are monitored in the locations favorable for storm initiation and growth. Trends of storm growth as defined by satellite and radar data coverage are used to provide a forecast. Storm motion vectors are determined based on the speed of the front. Data from 8 cases are shown to determine if trending of storm growth in regions of synoptic forcing improves over extrapolation forecast.