Location, Location, Location: Preempting the Answer to One of the Most Common Forecast Questions Asked By the Public

The National Weather Service has been placing more emphasis on explicit use of probabilistic information in forecasts. However, one of the biggest challenges facing forecasters centers around best practices for geographically depicting probabilistic information. For example, it is not possible or reasonable to expect that forecasters include every city or town in their messaging and graphics. With that in mind, researchers at IPPRA developed an experiment as part of the ongoing Tropical Cyclones and Society Survey (TC24) series to study how individuals interpret probabilistic forecasts for point locations. Survey participants were shown a simulated social media post that contained a wind speed probability graphic with Locations A, B, and C marked. Respondents were randomly assigned to one of five treatment groups based on the text of the post — no text, text giving the wind speed probability at Location A, text giving the wind speed probability at Locations A and C, text giving the wind speed probability at Location B, text giving the wind speed probability at all locations, or text giving the range of wind speed probabilities depicted on the map. Respondents were then asked to identify the probability of experiencing hurricane-force winds at Location B, regardless of the text they saw. Results from this work will help inform best practices for geographically depicting probabilistic forecast information by highlighting effective messaging strategies that forecasters might use to help their audiences more quickly interpret graphics to understand the forecast for their individual contexts.