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- Author or Editor: Brenda Philips x
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Abstract
Despite considerable interest in the weather enterprise, there is little focused research on the “false alarm effect.” Within the body of research that does exist, findings are mixed. Some studies suggest that the false alarm effect is overstated, while several recent efforts have provided evidence that FAR may be a significant determinate of behavior. This effort contributes to the understanding of FAR through a sociological analysis of public perceptions and behavioral responses to tornadoes. This analysis begins by addressing public definitions of FAR and then provides two statistical models, one focused on perception of FAR and one focused on behavioral response to tornado warnings. The authors’ approach incorporates a number of sociological and other social science concepts as predictors in both of these models. Findings provide a number of important insights. Most notably, it is found that 1) there is a wide degree of variation in public definitions of false alarm, 2) actual county FAR rates do not predict perception of FAR, 3) actual county FAR rates do predict behavioral response, and 4) planning and family characteristics are also influential. Another major contribution is to illustrate the significant complexity associated with analysis of false alarms. Conclusions discuss the limits of this analysis and future direction for this type of research.
Abstract
Despite considerable interest in the weather enterprise, there is little focused research on the “false alarm effect.” Within the body of research that does exist, findings are mixed. Some studies suggest that the false alarm effect is overstated, while several recent efforts have provided evidence that FAR may be a significant determinate of behavior. This effort contributes to the understanding of FAR through a sociological analysis of public perceptions and behavioral responses to tornadoes. This analysis begins by addressing public definitions of FAR and then provides two statistical models, one focused on perception of FAR and one focused on behavioral response to tornado warnings. The authors’ approach incorporates a number of sociological and other social science concepts as predictors in both of these models. Findings provide a number of important insights. Most notably, it is found that 1) there is a wide degree of variation in public definitions of false alarm, 2) actual county FAR rates do not predict perception of FAR, 3) actual county FAR rates do predict behavioral response, and 4) planning and family characteristics are also influential. Another major contribution is to illustrate the significant complexity associated with analysis of false alarms. Conclusions discuss the limits of this analysis and future direction for this type of research.
Abstract
Emergency managers make time-sensitive decisions in order to protect the public from threats including severe weather. Simulation and questionnaires were used to capture the decision-making process of emergency managers during severe weather events. These data were combined with insights from emergency manager instructors, National Weather Service (NWS) forecasters, and experienced emergency managers to develop a descriptive decision-making model of weather information usage, weather assessments, and decisions made during severe weather. This decision-making model can be used to develop better decision support tools, improve training, and to understand how innovative weather information could potentially affect emergency managers’ role of protecting the public.
Abstract
Emergency managers make time-sensitive decisions in order to protect the public from threats including severe weather. Simulation and questionnaires were used to capture the decision-making process of emergency managers during severe weather events. These data were combined with insights from emergency manager instructors, National Weather Service (NWS) forecasters, and experienced emergency managers to develop a descriptive decision-making model of weather information usage, weather assessments, and decisions made during severe weather. This decision-making model can be used to develop better decision support tools, improve training, and to understand how innovative weather information could potentially affect emergency managers’ role of protecting the public.
Dense networks of short-range radars capable of mapping storms and detecting atmospheric hazards are described. Composed of small X-band (9.4 GHz) radars spaced tens of kilometers apart, these networks defeat the Earth curvature blockage that limits today s long-range weather radars and enables observing capabilities fundamentally beyond the operational state-of-the-art radars. These capabilities include multiple Doppler observations for mapping horizontal wind vectors, subkilometer spatial resolution, and rapid-update (tens of seconds) observations extending from the boundary layer up to the tops of storms. The small physical size and low-power design of these radars permits the consideration of commercial electronic manufacturing approaches and radar installation on rooftops, communications towers, and other infrastructure elements, leading to cost-effective network deployments. The networks can be architected in such a way that the sampling strategy dynamically responds to changing weather to simultaneously accommodate the data needs of multiple types of end users. Such networks have the potential to supplement, or replace, the physically large long-range civil infrastructure radars in use today.
Dense networks of short-range radars capable of mapping storms and detecting atmospheric hazards are described. Composed of small X-band (9.4 GHz) radars spaced tens of kilometers apart, these networks defeat the Earth curvature blockage that limits today s long-range weather radars and enables observing capabilities fundamentally beyond the operational state-of-the-art radars. These capabilities include multiple Doppler observations for mapping horizontal wind vectors, subkilometer spatial resolution, and rapid-update (tens of seconds) observations extending from the boundary layer up to the tops of storms. The small physical size and low-power design of these radars permits the consideration of commercial electronic manufacturing approaches and radar installation on rooftops, communications towers, and other infrastructure elements, leading to cost-effective network deployments. The networks can be architected in such a way that the sampling strategy dynamically responds to changing weather to simultaneously accommodate the data needs of multiple types of end users. Such networks have the potential to supplement, or replace, the physically large long-range civil infrastructure radars in use today.
The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (the Plan) is summarized. The Plan (available on the AMS website at www.ametsoc.org/boardpges/cwce/docs/BEC/ACUF/2011-02-20-ACUF-Final-Report.pdf) is based on and intended to provide a foundation for implementing recent recommendations regarding forecast uncertainty by the National Research Council (NRC), AMS, and World Meteorological Organization. It defines a vision, strategic goals, roles and respon- sibilities, and an implementation road map to guide the weather and climate enterprise (the Enterprise) toward routinely providing the nation with comprehensive, skillful, reliable, and useful information about the uncertainty of weather, water, and climate (hydrometeorological) forecasts. Examples are provided describing how hydrometeorological forecast uncertainty information can improve decisions and outcomes in various socioeconomic areas. The implementation road map defines objectives and tasks that the four sectors comprising the Enterprise (i.e., government, industry, academia, and nongovernmental organizations) should work on in partnership to meet four key, interrelated strategic goals: 1) understand social and physical science aspects of forecast uncertainty; 2) communicate forecast uncertainty information effectively and collaborate with users to assist them in their decision making; 3) generate forecast uncertainty data, products, services, and information; and 4) enable research, development, and operations with necessary information technology and other infrastructure. The Plan endorses the NRC recommendation that the National Oceanic and Atmospheric Administration and, in particular, the National Weather Service, should take the lead in motivating and organizing Enterprise resources and expertise in order to reach the Plan's vision and goals and shift the nation successfully toward a greater understanding and use of forecast uncertainty in decision making.
The American Meteorological Society (AMS) Weather and Climate Enterprise Strategic Implementation Plan for Generating and Communicating Forecast Uncertainty (the Plan) is summarized. The Plan (available on the AMS website at www.ametsoc.org/boardpges/cwce/docs/BEC/ACUF/2011-02-20-ACUF-Final-Report.pdf) is based on and intended to provide a foundation for implementing recent recommendations regarding forecast uncertainty by the National Research Council (NRC), AMS, and World Meteorological Organization. It defines a vision, strategic goals, roles and respon- sibilities, and an implementation road map to guide the weather and climate enterprise (the Enterprise) toward routinely providing the nation with comprehensive, skillful, reliable, and useful information about the uncertainty of weather, water, and climate (hydrometeorological) forecasts. Examples are provided describing how hydrometeorological forecast uncertainty information can improve decisions and outcomes in various socioeconomic areas. The implementation road map defines objectives and tasks that the four sectors comprising the Enterprise (i.e., government, industry, academia, and nongovernmental organizations) should work on in partnership to meet four key, interrelated strategic goals: 1) understand social and physical science aspects of forecast uncertainty; 2) communicate forecast uncertainty information effectively and collaborate with users to assist them in their decision making; 3) generate forecast uncertainty data, products, services, and information; and 4) enable research, development, and operations with necessary information technology and other infrastructure. The Plan endorses the NRC recommendation that the National Oceanic and Atmospheric Administration and, in particular, the National Weather Service, should take the lead in motivating and organizing Enterprise resources and expertise in order to reach the Plan's vision and goals and shift the nation successfully toward a greater understanding and use of forecast uncertainty in decision making.
