This study examines the relationship of feeder clouds to severe weather. Using visible satellite imagery, an attempt is made to establish a correlation between the occurrence of feeder clouds and severe weather reports. The purpose here is to discover if any relationship exists between the two, and to evaluate the utility of feeder cloud signatures in predicting severe weather. The Mesocyclone Detection Algorithm (MDA) output from WSR-88D observations is also assessed in a similar manner for a select subset of the satellite case days. Statistics are developed from the satellite and radar observations which address the relationship between the occurrence of feeder clouds and severe weather, and estimate not only the effectiveness of using feeder cloud signatures as sole predictors of severe weather, but also the potential utility of combining feeder cloud signatures with the radar's MDA output. The purpose of the latter test is to evaluate whether adding feeder cloud signatures to the list of nowcast tools currently used during severe weather situations (which includes the MDA) might improve short term forecast skill in the warning decision making process.
Results of the study suggest that the formation of feeder clouds is likely a response to rapid intensification in a thunderstorm. Results also indicate that feeder cloud signatures have low skill in predicting all severe weather. However if feeder clouds are observed in a storm, there is a 77% chance that severe weather will occur within 30 min of the observation. It is also shown that the MDA (using a selected radar data subset) is a more effective predictor of severe weather. Finally, results show that combined detections (feeder clouds plus mesocyclone detections) outperform both feeder cloud signatures and the MDA as separate predictors by 10-20%. It is suggested that utilizing feeder cloud signatures observed on visible imagery during warning operations may be a useful adjunct to the MDA in diagnosing a storm's potential to produce severe weather.