The Geographic Distribution of Extreme Weather and Climate Risk Perceptions in the United States

Weather and climate disasters pose and increasing risk to life and property in the United States. In 2017, there were 16 weather and climate disasters with losses exceeding $1 billion each. More significant than the number of events was the cumulative cost of $309.5 billion, the most in U.S. history. Managing this risk requires objective information about the nature of the threat and subjective information about how people perceive it. Meteorologists and climatologists have a relatively firm grasp of the objective risk. We know, for example which parts of the U.S. are most likely to experience drought, heat waves, flooding, snow or ice storms, tornadoes, and hurricanes. We know less, by comparison, about the geographic distribution of the perceived risks of meteorological events and trends. Is drought a prominent concern in some places and not others? What about heat waves or flooding? Do perceptions align with objective risk? These questions are difficult to answer because analysts have yet to develop a comprehensive and spatially consistent methodology for measuring risk perceptions across geographic areas in the U.S. In this project, we propose a methodology that uses multilevel regression and poststratification (MRP) to estimate extreme weather and climate risk perceptions by geographic area (i.e., region, state, forecast area, county). We apply this methodology using a unique dataset from the Severe Weather and Society Survey, an annual national survey that is conducted by the Center for Risk and Crisis Management at the University of Oklahoma. Doing so allows us to measure, map, and compare perceptions of risk from extreme high winds, extreme rain storms, extreme heat waves, drought, extreme cold temperatures, extreme snow (or ice) storms, tornadoes, floods, hurricanes, and wildfires in geographic areas across the country.