Early Satellite Detection and Subsequent Radar Tracking of Thunderstorms

Signal-based information systems are dominating many fields today, including meteorology. Satellite and radar have, over the years, helped improve forecast accuracy as well as warning lead-times for severe convective weather events. In relation to short-term forecasting, or nowcasting, using both sets of data can help to focus attention on the primary threat areas of storm development and intensification. Combining the two fields could lead to earlier automated detection of new thunderstorms compared to using radar alone, yet a stable blended data field has to be generated first. Moreover, tests must ensure that the fields can actually be combined in a reliable way. Using three products: the National Severe Storm Lab's (NSSL) Merged Composite Reflectivity and Reflectivity on the -10°C isosurface, and the University of Wisconsin's Convective Initiation algorithm (UWCI), a new trackable field was created. Three different combination methods were tested to see which method produced the most accurate and reliable field. Two methods used a weighted equation technique on the fields. The other used a comparative maximum value approach. Storm cells are detected and tracked in the blended fields using a K-Means clustering and tracking program. This is similar to the WSR-88D Storm Cell Identification and Tracking algorithm in that the tracking is object oriented, but the clusters are determined by an area around an average value in the K-Means algorithm. Outputs were then viewed using the Warning Decision Support System – Integrated Information (WDSS-II) display. Results from this study reveal that successfully combining the fields can result in earlier detection time for storm cells in some cases.