Visualization techniques have been widely used by the U.S National Hurricane Center to enhance viewers’ understanding of hurricane forecasts and their underlying uncertainty. The track forecast cone is the one almost universally adopted by the general public, the news media, and governmental officials. However, current research has experimentally shown that it has limitations that result in misconceptions of the uncertainty included. Most importantly, the area covered by the cone tends to be misinterpreted as the region affected by the hurricane. In addition, the cone summarizes forecasts for the next three days into a single representation and, thus, makes it difficult for viewers to accurately determine crucial time-specific information. To address these limitations, this research proposes novel alternative visualizations. The work reported here began by proposing a technique that generates and smoothly interpolates robust statistics from ensembles of hurricane predictions, thus developing visualizations that inherently include the spatial uncertainty by displaying three levels of positional storm strike risk at a specific point in time. To address the misconception of the area covered by the cone, this research develops time-specific visualizations depicting spatial information based on a sampling technique that selects a representative subset from an ensemble of points. It also allows depictions of such important storm characteristics as size and intensity. We collaborated on a cognitive study that indicates that these visualizations are more accurate than the track forecast cone because they enhance the viewers’ ability to understand the predictions.