Event-Specific Human Perception and Response Data for Early Warning System Research

Early warning systems (EWS) for hazardous weather integrate human expertise, science, technology, and policy to identify hazard risk and disseminate warnings to groups and individuals. This talk will address an important gap in warning system research: the lack of event-specific data on how individuals perceive and respond to hazardous weather events. Many warning system analyses rely on outcome data -- deaths, injuries, rescues, 911 calls -- to represent human response. While important, outcome data does not provide insights on how individuals process and respond to environmental, social and warning information as they experience a hazardous weather event. Additional insights into the factors which influence individual decision-making have important impacts on future directions warning system research. Through an interdisciplinary case study of an urban flash flooding event in Fort Worth, Texas which resulted in three vehicle-related fatalities, we evaluate the effectiveness of the flash flood early warning system (FFEWS) focusing on the interdependencies among hazard detection, risk communication, emergency response, and motorist behavior. To characterize the FFEWS, this study uses environmental and organizational data, and surveys of the public gathered through the CASA Dallas-Fort Worth (DFW) Living Lab (LL), a platform for advancing severe weather warning paradigms where research is conducted in the context of actual events and close collaborations with stakeholders.