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Exploring Community Differences in Tornado Warning Reception, Comprehension, and Response across the United States

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  • 1 Center for Risk and Crisis Management, University of Oklahoma, and National Institute for Risk and Resilience, Norman, Oklahoma
  • | 2 Center for Risk and Crisis Management, University of Oklahoma, and National Institute for Risk and Resilience, and Cooperative Institute for Mesoscale Meteorological Studies, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
  • | 3 East Tennessee State University, Johnson City, Tennessee
  • | 4 Center for Risk and Crisis Management, University of Oklahoma, and National Institute for Risk and Resilience, Norman, Oklahoma
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Abstract

Effective risk communication in the weather enterprise requires deep knowledge about the communities that enterprise members serve. This includes knowledge of the atmospheric and climate conditions in these communities as well as knowledge about the characteristics of the people living in these communities. Enterprise members often have access to data that facilitate the first type of knowledge, but relatively little social or behavioral data on the populations they serve. This article introduces an effort to overcome these challenges by developing a database of community statistics and an interactive platform that provides dynamic access to the database. Specific emphasis is given to one set of statistics in the community database: estimates of tornado warning reception, comprehension, and response by county warning area in the contiguous United States. Exploration of these estimates indicates significant variation in reception and comprehension across communities. This variation broadly aligns with tornado climatology, but there are noticeable differences within climatologically comparable regions that underline the importance of community-specific information. Verification of the estimates using independent observations from a random sample of communities confirms that the estimates are largely accurate, but there are a few consistent anomalies that prompt questions about why some communities exhibit higher or lower levels of reception, comprehension, and response than models suggest. The article concludes with a discussion of next steps and an invitation to use and contribute to the project as it progresses.

Corresponding author: Joseph T. Ripberger, jtr@ou.edu

Abstract

Effective risk communication in the weather enterprise requires deep knowledge about the communities that enterprise members serve. This includes knowledge of the atmospheric and climate conditions in these communities as well as knowledge about the characteristics of the people living in these communities. Enterprise members often have access to data that facilitate the first type of knowledge, but relatively little social or behavioral data on the populations they serve. This article introduces an effort to overcome these challenges by developing a database of community statistics and an interactive platform that provides dynamic access to the database. Specific emphasis is given to one set of statistics in the community database: estimates of tornado warning reception, comprehension, and response by county warning area in the contiguous United States. Exploration of these estimates indicates significant variation in reception and comprehension across communities. This variation broadly aligns with tornado climatology, but there are noticeable differences within climatologically comparable regions that underline the importance of community-specific information. Verification of the estimates using independent observations from a random sample of communities confirms that the estimates are largely accurate, but there are a few consistent anomalies that prompt questions about why some communities exhibit higher or lower levels of reception, comprehension, and response than models suggest. The article concludes with a discussion of next steps and an invitation to use and contribute to the project as it progresses.

Corresponding author: Joseph T. Ripberger, jtr@ou.edu
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