Quantifying the Impact of Mobile Severe Weather Alerts using GIS

Research in severe weather warnings can make the biggest difference when advancements are communicated effectively to those outside the weather community. To assess communication between the weather enterprises and the general public, both scientific and societal components need to be considered. Smartphone apps have been identified as a key player in severe weather events as they are heavily relied on before storms hit and after severe storms have knocked out other forms of communication. Baron Services, Inc. in Huntsville, AL is investigating how the public receives information and how that information is interpreted; and is dedicated to improving localized weather information as part of their Critical Weather Initiative. The SAF-T-Net smart phone application developed as part of this initiative sends out user-location-specific warnings and severe weather alerts, and allows users to send information back about the impacts they observe.

This presentation will demonstrate how GIS can integrate user data from the SAF-T-Net app, National Weather Service, U.S. Census Bureau, and Emergency Managers in the state of Alabama. Geographic Information Systems (GIS) software is a powerful platform to integrate social and scientific data involved in the warning process. Geostatistical techniques including cluster, hot spot, and density analysis were used to spatially identify areas that are under-represented based on SAF-T-Net use. Social vulnerability is a measure of an individual's susceptibility to danger and harm in the event severe weather events. By including social data, the pattern of spatial coverage of warnings as related to social vulnerability was assessed. The work demonstrates both general findings for the entire state, as well as case studies of specific severe events.

Results found from this research provide insight into where users are located, how and when they receive warnings, and what sociospatial factors influence their decision making process in a severe event. This information can improve communication between forecasters, decision makers, and the public, which will save lives and property in the future.