Emergency Manager Interpretation of Probabilistic Snowfall Forecasts and Graphics

An effective forecast communicates the full range of likely weather scenarios and impacts. Consistently, winter weather events put this idea to the test, with forecasts ahead of storm impacts balancing different precipitation types and precipitation amounts. Probabilistic National Weather Service (NWS) products exist to communicate these scenarios and any associated uncertainty. Given this new paradigm, understanding the effectiveness of these probabilistic winter weather graphics becomes an important question. The University of Oklahoma’s Institute for Public Policy Research and Analysis’ Extreme Weather and Emergency Management Survey seeks to answer how some of the NWS’s most critical partners, emergency managers (EMs), respond to probabilistic winter weather graphics. Using a recent nationwide survey of Emergency Managers, researchers ask for EMs’ preference on the presentation of probabilistic information, namely high confidence in a small range of impacts or low confidence in a wide range of impacts. The survey also asks questions about EMs’ confidence in the continued use of probabilistic graphics given a range of forecast outcomes, how they interpret the information presented in the graphics, and whether or not they would share the graphics with different audiences (e.g., jurisdictional leadership, colleagues, members of the public, etc.). The results of this survey will be analyzed and discussed, furthering the conversation about the future of probabilistic graphics within the NWS.