Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-23T05:54:40.743Z Has data issue: false hasContentIssue false
  • English
  • Français

Predictors for the Number of Warning Information Sources During Tornadoes

Part of: Tornadoes collection

Published online by Cambridge University Press:  23 June 2016

Zhen Cong ,
Jianjun Luo ,
Daan Liang  and
Ali Nejat
Zhen Cong*
Affiliation:
Department of Human Development and Family Studies, Boston, Massachusetts
Jianjun Luo
Affiliation:
AIR Worldwide, Boston, Massachusetts
Daan Liang
Affiliation:
National Wind Institute, Texas Tech University, Lubbock, Texas
Ali Nejat
Affiliation:
Department of Civil, Environmental, and Construction Engineering, Texas Tech University, Lubbock, Texas.
*
Correspondence and reprint requests to Zhen Cong, Department of Human Development and Family Studies, Texas Tech University, Box 41230, Lubbock, TX, 79416 (e-mail: [email protected]).
Get access Rights & Permissions [Opens in a new window]

Abstract

People may receive tornado warnings from multiple information sources, but little is known about factors that affect the number of warning information sources (WISs). This study examined predictors for the number of WISs with a telephone survey on randomly sampled residents in Tuscaloosa, Alabama, and Joplin, Missouri, approximately 1 year after both cities were struck by violent tornadoes (EF4 and EF5) in 2011. The survey included 1006 finished interviews and the working sample included 903 respondents. Poisson regression and Zero-Inflated Poisson regression showed that older age and having an emergency plan predicted more WISs in both cities. Education, marital status, and gender affected the possibilities of receiving warnings and the number of WISs either in Joplin or in Tuscaloosa. The findings suggest that social disparity affects the access to warnings not only with respect to the likelihood of receiving any warnings but also with respect to the number of WISs. In addition, historical and social contexts are important for examining predictors for the number of WISs. We recommend that the number of WISs should be regarded as an important measure to evaluate access to warnings in addition to the likelihood of receiving warnings. (Disaster Med Public Health Preparedness. 2017;11:168–172)

Keywords

tornadoesdisasterswarning information sourcesJoplinTuscaloosa
Type
Brief Reports
Information
Disaster Medicine and Public Health Preparedness , Volume 11 , Issue 2 , April 2017 , pp. 168 - 172
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Hoekstra, S, Klockow, K, Riley, R, et al. A preliminary look at the social perspective of warn-on-forecast: preferred tornado warning lead time and the general public’s perceptions of weather risks. Weather Clim Soc. 2011;3(2):128-140.Google Scholar
2. Coleman, TA, Knupp, KR, Spann, J, et al. The history (and future) of tornado warning dissemination in the United States. B Am Meteorol Soc. 2011;92(5):567-582.Google Scholar
3. Durage, SW, Wirasinghe, S, Ruwanpura, J. Comparison of the Canadian and US tornado detection and warning systems. Nat Hazards. 2013;66(1):117-137.Google Scholar
4. Benight, C, Gruntfest, E, Sparks, K. Colorado wildfires 2002: Natural Hazards Center quick response program report No. QR167. Boulder, CO: Natural Hazards Center, 2004.Google Scholar
5. Luo, J, Cong, Z, Liang, D. Number of warning information sources and decision-making during tornadoes. Am J Prev Med. 2015;48(3):334-337.Google Scholar
6. National Weather Service central region service assessment Joplin, Missouri, Tornado - May 22, 2011 2011. National Weather Service website. http://www.nws.noaa.gov/om/assessments/pdfs/Joplin_tornado.pdf. Accessed May 20, 2016.Google Scholar
7. Drabek, TE. Understanding disaster warning responses. Soc Sci J. 1999;36(3):515-523.Google Scholar
8. Rodríguez, H, Quarantelli, EL, Dynes, RR. eds. Handbook of disaster research. New York: Springer; 2007.Google Scholar
9. Storm events database 2013. National Oceanic and Atmospheric Administration’s National Climatic Data Center website. http://www.ncdc.noaa.gov/stormevents/. Accessed May 20, 2016.Google Scholar
10. Simmons, K, Daniel, S. Deadly season: analysis of the 2011 tornado outbreaks. Boston, MA: American Meteorological Society; 2013.Google Scholar
11. Service assessment-the historic tornadoes of April 2011. National Weather Service website. http://www.nws.noaa.gov/om/assessments/pdfs/historic_tornadoes.pdf. Accessed May 20, 2016.Google Scholar
12. Simmons, KM, Sutter, D. Economic and societal impacts of tornadoes. Boston, Massachusetts: American Meteorological Society; 2011.Google Scholar
13. Hayden, MH, Drobot, S, Radil, S, et al. Information sources for flash flood warnings in Denver, CO and Austin, TX. Environ Hazards. 2007;7(3):211-219.Google Scholar
14. Papathanassopoulos, S, Coen, S, Curran, J, et al. Online threat, but television is still dominant: a comparative study of 11 nations’ news consumption. Journalism Pract. 2013;7(6):690-704.Google Scholar