The product of the 3DVAR analysis was available to forecasters at 1km horizontal resolution every 5 min, with a 4-5 min latency, incorporating data from the national WSR-88D network and the North American Mesoscale (NAM) model. Four different 200x200 km domains were used to run the 3DVAR program throughout the experiment; the location of each was determined by default via an automated algorithm which moved the domains over regions of peak reflectivity throughout the continental United States, but this process could be over-ridden by forecasters/scientists using a web-map interface to focus on specific storms of interest. Initial products provided to the forecasters included: vertical velocity, synthesized (or mosaic) reflectivity, vertical vorticity, and 3D wind vectors. Following feedback from early forecaster evaluations, additional products for updraft helicity and storm-top divergence (max-divergence above 8 km) were created during the 2012 experiment. The forecasters found the vertical vorticity, storm-top divergence, and updraft products the most useful for storm interrogation and quickly visualizing storm trends, often using these tools increase the confidence in a warning decision and/or issue the warning slightly earlier. The addition of AWIPS-2 during the 2012 experiment also allowed forecasters to overlay 3D wind vectors, barbs, or streamlines on other 3DVAR or radar products at multiple levels from near the surface to storm-top. The 3DVAR analysis was most consistent and reliable when the storm mode was supercellular, though forecasters were still able to utilize the data in multiple scenarios. The analysis was also better when the storm of interest was in close proximity to one of the assimilated 88-D radars, or data from multiple radars were incorporated in the analysis. The latter was extremely useful to forecasters when helping to fill in the gaps of having to analyze multiple radars separately, especially where storms from one or more radars were in the "purple haze" of the range-folded obscuration. The largest hurdle for realtime use of 3DVAR or similar data assimilation products by forecasters is the data latency, as even 3-5 minutes reduces the utility of the products when new radar scans are already available. Future additions in the HWT include reducing the data latency, cycling the 3DVAR analysis to improve the estimates for other variables, such as temperature and water vapor, and adding a short term forecast component (0-1 hour) as computational speed increases.