The ability to anticipate specific weather events or combination of conditions that can disrupt the distribution network of an electric utility, particularly with an overhead infrastructure, can enable proactive allocation and deployment of resources to minimize time for restoration. For predictions of such conditions to be useful, the information must be disseminated in a timely fashion that enables effective decisions to be made with confidence. Visualization is a critical means for dissemination, but it requires appropriate designs to permit almost pre-attentive interpretation as part of operational planning prior to a severe storm event. Among the design criteria include appropriate utilization of visualization elements (e.g., geometry, color), consistency with and coupling to weather forecast data, incorporation of infrastructure information concerning the distribution network, cartographic reprojection to minimize spatial distortion, and limitations with web-based deployment coordinated with the workflow and perception of the intended users. Additional extensions have been considered for derived information such as the classification of storm severity and the estimation of outages in the distribution network. These ideas have been implemented and deployed operationally as a service for the emergency management group at a major utility company in the northeastern United States. They were developed by building upon earlier efforts at the IBM Thomas J. Watson Research Center to implement and apply an operational mesoscale prediction system to business problems, dubbed “Deep Thunder”. In particular, the capabilities in the New York City metropolitan area have been extended to meet the needs of this utility company. But the approach is applicable to similar operational needs among electric and water utilities, municipal emergency management and transportation agencies, and others. We will discuss the on-going work, the design issues and rationale for particular implementation choices as well as some of the continuing challenges such as depiction of inherent uncertainty in the information. We will also present some results concerning the overall effectiveness of the visualizations for various user tasks.