Editorial Type:
Article
Article Type:
Research Article

Characteristics of Winter-Precipitation-Related Transportation Fatalities in the United States

Alan W. Black Department of Geography, The University of Georgia, Athens, Georgia

Search for other papers by Alan W. Black in
Current site
Google Scholar
PubMed Close
and
Thomas L. Mote Department of Geography, The University of Georgia, Athens, Georgia

Search for other papers by Thomas L. Mote in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Apr 2015
DOI:
https://doi.org/10.1175/WCAS-D-14-00011.1
Page(s):
133–145
Restricted access

Abstract

Winter precipitation can be very disruptive to travel by aircraft and by motor vehicles. Vehicle fatalities due to winter precipitation are considered “indirect” and are not counted in Storm Data, the publication commonly used to evaluate losses from meteorological hazards. The goal of this study is to examine the spatial and temporal characteristics of these indirect transportation fatalities that involve winter precipitation for the period 1975–2011. Motor vehicle fatalities were gathered from the National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS) database, while aviation fatalities were collected from the National Transportation Safety Board’s (NTSB) Aviation Accident database. Statistical analysis and geographic information systems (GIS) were used to assess the spatial and temporal characteristics of these deaths. Most winter-precipitation-related motor vehicle fatalities occur during the daylight hours. Fatal motor vehicle accident rates are higher than expected in the Northeast and Great Lakes regions, while winter-precipitation-related aviation fatalities are most common in the western United States. Vehicle fatality counts due to winter weather are compared to fatality counts for various hazards from Storm Data to highlight the differences between the datasets. Because of the exclusion of vehicle fatalities, Storm Data underestimates by an order of magnitude the number of fatalities that involve winter weather each year. It is hoped that a better understanding of winter precipitation mortality can be applied in order to reduce fatalities in the future.

Corresponding author address: Alan Black, Department of Geography, University of Georgia, 210 Field St., Room 204, Athens, GA 30602. E-mail: awblack@uga.edu

Abstract

Winter precipitation can be very disruptive to travel by aircraft and by motor vehicles. Vehicle fatalities due to winter precipitation are considered “indirect” and are not counted in Storm Data, the publication commonly used to evaluate losses from meteorological hazards. The goal of this study is to examine the spatial and temporal characteristics of these indirect transportation fatalities that involve winter precipitation for the period 1975–2011. Motor vehicle fatalities were gathered from the National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS) database, while aviation fatalities were collected from the National Transportation Safety Board’s (NTSB) Aviation Accident database. Statistical analysis and geographic information systems (GIS) were used to assess the spatial and temporal characteristics of these deaths. Most winter-precipitation-related motor vehicle fatalities occur during the daylight hours. Fatal motor vehicle accident rates are higher than expected in the Northeast and Great Lakes regions, while winter-precipitation-related aviation fatalities are most common in the western United States. Vehicle fatality counts due to winter weather are compared to fatality counts for various hazards from Storm Data to highlight the differences between the datasets. Because of the exclusion of vehicle fatalities, Storm Data underestimates by an order of magnitude the number of fatalities that involve winter weather each year. It is hoped that a better understanding of winter precipitation mortality can be applied in order to reduce fatalities in the future.

Corresponding author address: Alan Black, Department of Geography, University of Georgia, 210 Field St., Room 204, Athens, GA 30602. E-mail: awblack@uga.edu
Save
Cover Weather, Climate, and Society
Weather, Climate, and Society

  • Andrey, J., 2010: Long-term trends in weather-related crash risks. J. Transp. Geogr., 18, 247–258, doi:10.1016/j.jtrangeo.2009.05.002.

    • Search Google Scholar
    • Export Citation

  • Andrey, J., Mills B. , Leahy M. , and Suggett J. , 2003: Weather as a chronic hazard for road transportation in Canadian cities. Nat. Hazards, 28, 319–343, doi:10.1023/A:1022934225431.

    • Search Google Scholar
    • Export Citation

  • Anselin, L., 1995: Local Indicators of Spatial Association—LISA. Geogr. Anal., 27, 93–115, doi:10.1111/j.1538-4632.1995.tb00338.x.

  • Ashley, W. S., 2007: Spatial and temporal analysis of tornado fatalities in the United States: 1880–2005. Wea. Forecasting, 22, 1214–1228, doi:10.1175/2007WAF2007004.1.

    • Search Google Scholar
    • Export Citation

  • Ashley, W. S., and Black A. W. , 2008: Fatalities associated with nonconvective high-wind events in the United States. J. Appl. Meteor. Climatol., 47, 717–725, doi:10.1175/2007JAMC1689.1.

    • Search Google Scholar
    • Export Citation

  • Ashley, W. S., and Gilson C. W. , 2009: A reassessment of U.S. lightning mortality. Bull. Amer. Meteor. Soc., 90, 1501–1518, doi:10.1175/2009BAMS2765.1.

    • Search Google Scholar
    • Export Citation

  • Belcastro, C. M., and Foster J. V. , 2010: Aircraft loss-of-control accident analysis. AIAA Guidance, Navigation and Control Conf., Toronto, ON, Canada, AIAA, AIAA 2010-8004, doi:10.2514/6.2010-8004.

  • Black, A. W., and Ashley W. S. , 2010: Nontornadic convective wind fatalities in the United States. Nat. Hazards, 54, 355–366, doi:10.1007/s11069-009-9472-2.

    • Search Google Scholar
    • Export Citation

  • Borden, K. A., and Cutter S. L. , 2008: Spatial patterns of natural hazards mortality in the United States. Int. J. Health Geogr., 7, 64, doi:10.1186/1476-072X-7-64.

    • Search Google Scholar
    • Export Citation

  • Changnon, D., and Changnon S. A. , 2007: Snowstorm dimensions across the central and eastern United States. Phys. Geogr., 28, 218–232, doi:10.2747/0272-3646.28.3.218.

    • Search Google Scholar
    • Export Citation

  • Changnon, S. A., 2007: Catastrophic winter storms: An escalating problem. Climatic Change, 84, 131–139, doi:10.1007/s10584-007-9289-5.

    • Search Google Scholar
    • Export Citation

  • Changnon, S. A., 2008: Climatology of sleet in the United States. Phys. Geogr., 29, 195–207, doi:10.2747/0272-3646.29.3.195.

  • Changnon, S. A., and Karl T. R. , 2003: Temporal and spatial variations of freezing rain in the contiguous United States: 1948–2000. J. Appl. Meteor., 42, 1302–1316, doi:10.1175/1520-0450(2003)042<1302:TASVOF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Changnon, S. A., Changnon D. , and Karl T. R. , 2006: Temporal and spatial characteristics of snowstorms in the contiguous United States. J. Appl. Meteor. Climatol., 45, 1141–1155, doi:10.1175/JAM2395.1.

    • Search Google Scholar
    • Export Citation

  • Cutter, S. L., 1996: Vulnerability to environmental hazards. Prog. Hum. Geogr., 20, 529–539, doi:10.1177/030913259602000407.

  • Eckley, D. C., and Curtin K. M. , 2013: Evaluating the spatiotemporal clustering of traffic incidents. Comput. Environ. Urban Syst., 37, 70–81, doi:10.1016/j.compenvurbsys.2012.06.004.

    • Search Google Scholar
    • Export Citation

  • Eisenberg, D., and Warner K. E. , 2005: Effects of snowfalls on motor vehicle collisions, injuries, and fatalities. Amer. J. Public Health, 95, 120–125, doi:10.2105/AJPH.2004.048926.

    • Search Google Scholar
    • Export Citation

  • Gall, M., Borden K. A. , and Cutter S. L. , 2009: When do losses count? Six fallacies of natural hazard loss data. Bull. Amer. Meteor. Soc., 90, 799–809, doi:10.1175/2008BAMS2721.1.

    • Search Google Scholar
    • Export Citation

  • Lawson, A. B., 2001: Disease map reconstruction. Stat. Med., 20, 2183–2204, doi:10.1002/sim.933.

  • Marshall, R. J., 1991: Mapping disease and mortality rates using empirical Bayes estimators. J. Appl. Roy. Stat. Soc.,40C, 283–294.

  • Meza, J. L., 2003: Empirical Bayes estimation smoothing of relative risks in disease mapping. J. Stat. Plann. Inference, 112, 43–62, doi:10.1016/S0378-3758(02)00322-1.

    • Search Google Scholar
    • Export Citation

  • NHTSA, 2013a: Fatality Analysis Reporting System (FARS) analytical user’s manual 1975–2011. National Highway Traffic Safety Administration, U.S. Department of Transportation Doc. DOT HS 811 693, 607 pp. [Available online at http://www-nrd.nhtsa.dot.gov/Pubs/811693.pdf.]

  • NHTSA, 2013b: Traffic safety facts 2011: A compilation of motor vehicle crash data from the Fatality Analysis Reporting System and the General Estimates System. National Highway Traffic Safety Administration, U.S. Department of Transportation Doc. DOT HS 811 754, 217 pp. [Available online at http://www-nrd.nhtsa.dot.gov/Pubs/811754AR.pdf.]

  • NOAA, 2007: Storm data preparation. National Weather Service Instruction 10-1605, 97 pp. [Available online at http://www.weather.gov/directives/sym/pd01016005curr.pdf.]

  • NTSB, 2013: Aviation Accident database and synopses. Accessed 23 May 2013. [Available online at http://www.ntsb.gov/_layouts/ntsb.aviation/index.aspx.]

  • Rasmussen, R., and Coauthors, 1992: Winter Icing and Storms Project (WISP). Bull. Amer. Meteor. Soc., 73, 951–974, doi:10.1175/1520-0477(1992)073<0951:WIASP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • van Es, G. W. H., Roelen A. L. C. , Kruijsen E. A. C. , and Giesberts M. K. H. , 1998: Safety aspects of aircraft performance on wet and contaminated runways. Netherlands National Research Laboratories NLR Tech. Rep. NLR-TP-2001-216, 31 pp.

  • Wilson, J. L., and Buescher P. A. , 2002: Mapping mortality and morbidity rates. Statistical Primer 15, North Carolina Department of Health and Human Services, 11 pp. [Available online at http://www.schs.state.nc.us/schs/pdf/sp15.pdf.]

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 3243 1472 95
PDF Downloads 1055 190 7