Colorful Language: Investigating Public Interpretation of the Storm Prediction Center Convective Outlook

Author:

Ernst Sean1,Ripberger Joe1,Krocak Makenzie J.1,Jenkins-Smith Hank1,Silva Carol1

Affiliation:

1. a University of Oklahoma, Center for Risk and Crisis Management, Norman, Oklahoma

Abstract

AbstractAlthough severe weather forecast products, such as the Storm Prediction Center (SPC) convective outlook, are much more accurate than climatology at day-to-week time scales, tornadoes and severe thunderstorms claim dozens of lives and cause billions of dollars in damage every year. While the accuracy of this outlook has been well documented, less work has been done to explore the comprehension of the product by non-expert users like the general public. This study seeks to fill this key knowledge gap by collecting data from a representative survey of U.S. adults in the lower 48 states about their use and interpretation of the SPC convective outlook. Participants in this study were asked to rank the words and colors used in the outlook from least to greatest risk, and their answers were compared through visualizations and statistical tests across multiple demographics. Results show that the US public ranks the outlook colors similarly to their ordering in the outlook but switch the positions of several of the outlook words as compared to the operational product. Logistic regression models also reveal that more numerate individuals more correctly rank the SPC outlook words and colors. These findings suggest that the words used in the convective outlook may confuse non-expert users, and that future work should continue to use input from public surveys to test potential improvements in the choice of outlook words. Using more easily understood words may help to increase the outlook’s decision support value and potentially reduce the harm caused by severe weather events.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference74 articles.

1. Understanding emergency manager forecast use in severe weather events;Ernst;J. Oper. Meteor.,2018

2. Grundstein andJ So Should severe weather graphics wear uniforms ? Understanding the effects of inconsistent convective outlook graphics on members of the public th Symp on Societal Applications Policy Research Practice Meteor Soc https ams confex com ams;Williams,2020

3. andR Skilled decision theory : From intelligence to numeracy and expertise The Cambridge Handbook of Expertise and Expert Performance Ericsson University;Cokely,2018

4. andF Time line of Storm Prediction accessed https www spc noaa gov history timeline html;Edwards,2020

5. A tornado watch scale to improve public response;Mason;Wea. Climate Soc.,2015

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