This paper will explore alternative methods for assessing the goodness of NWS severe thunderstorm and tornado warnings. One motivation behind this study was to evaluate the results of springtime experiments at the NOAA Hazardous Weather Testbed (HWT). During real-time severe weather events in the HWT, visiting NWS forecasters issued experimental warnings while evaluating multiple-radar and multiple sensor (MRMS) severe weather applications developed by the National Severe Storms Laboratory. To get a more robust picture of warning goodness, verification data sets were created on a 1-km grid by using a combination of actual reports (which are sparse) and MRMS radar proxies for hail and mesocyclone/tornado paths. Hail verification grids are bias-corrected with actual reports. Mesocyclone/tornado paths, determined from ground truth and MRMS data, are converted to verification grids with varying degrees of splatting to allow for a degree of spatial tolerance for tornado warnings. After converting the warning polygons to 1 km grids, we can calculate hits, misses, false alarms, and lead time for each grid point and each time interval. Gridded warning and verification data also allow for the calculation of aggregate false alarm areas and false alarm times, departure times, and times under valid warnings. The HWT experimental warnings are compared to the official NWS warnings for the same events to determine whether or not the experimental severe weather applications offered improvements in warning goodness.