THE TORNADO WARNING PROCESS: A Review of Current Research, Challenges, and Opportunities
| By Donner, W | |
| Proquest LLC |
A review of the entire warning system, from prediction and detection to public response, reveals such fundamental needs as identifying acceptable risks, improving personal preparation, and personalizing warnings.
O ne of the scientific community's greatest achievements in meteorology during the twentieth century has been the development of a largely effective public tornado warning system. Between 1912 and 1936, tornadoes killed an average 260 persons per year, about 1.8 deaths per million people when normalized by population (Brooks and Doswell 2001). Between 1975 and 2000, that number had declined to 54 deaths per year, or 0.12 deaths per million people in 2000 (Brooks and Doswell 2001), a reduction of 93% from 1925. In 1986 the tornado warning lead time was approximately five minutes, with only 25% of tornadoes warned; by 2004, the mean lead time was 13 min, with about 75% of tor- nadoes warned (
Far from simple, the tornado warning process is a complex chain of events, encompassing institu- tional action and individual responses, that utilizes sensing technologies, conceptual models, numerical weather prediction (NWP), forecaster and emergency management (EM) decision making, warning dis- semination technologies, and public experience and education (Fig. 1). The sequential steps of this process-forecast, detection, warning decision, dissemination, and public response-are known as the Integrated Warning System (IWS; Leik et al. 1981; Doswell et al. 1999).
This article reviews the end-to-end tornado warning process and related research, considers the challenges to improving the current system, and explores possible next steps. While this article cannot provide a completely comprehensive review of all research in each specific area, the goal is to provide a broad overview of the tornado warning process and a brief summary of the many avenues of research that could contribute to improvements in the current system.
TORNADO PREDICTION. The ability to predict a tornado's precise path and intensity days in advance could allow for evacuation to take place well ahead of storm development and the predeployment of assets needed to support emergency response and recovery. While restrained to less accurate forecasts by the inherent limitations imposed by atmospheric predict- ability, the last decade has seen a growing recognition of the connection between large-scale patterns and large-scale tornado outbreaks.
As high-resolution, convection-allowing (?4-km grid resolution) NWP becomes more accurate at longer time scales, multivariate model output may be used to a greater extent in identifying and predicting tornado outbreak events. Using observational and modeling analysis, Egentowich et al. (2000a,b,c) identified a series of dynamic precursors during the 6-84 h preceding a major tornado outbreak. Shafer et al. (2009) found that
Ever faster computer processing, and increasing memory and storage capacities combined with ad- vances in parallel computing and code efficiency now enable the routine use of mesoscale forecast ensembles at high-resolution hours or even days in advance. Furthermore, analysis of model ensembles provides insight into forecast uncertainty. Stensrud and Weiss (2002) demonstrated that even a rela- tively coarse (32-km inner grid), small six-member ensemble, while underdispersive, provided some sta- tistical guidance in predicting the relative locations of expected severe weather 24 h in advance. Clark et al. (2010) have since shown that the use of convectionallowing resolutions improves the representation and prediction of severe weather features. As a predictive measure of storm severity, Clark et al. (2012) extracted proxy forecasts of tornado pathlengths from 36-h ensemble forecasts.
One official
Currently, all official NWS tornado warnings are issued based upon "detections," where an immediate tornado threat is observed either directly by spotters and media or inferred from observations (e.g., radar). However, as the accuracy and precision of short- term (0-3 h) storm predictions continue to improve, model output is expected to become an increasingly important basis upon which to issue NWS tornado warnings. This is the eventual goal of "warn on forecast" (Stensrud et al. 2009), where NWS tornado warnings may be issued based not only on detected tornadoes or observed precursors, but also on model output. Utilizing model output as the basis for some warnings could theoretically extend lead time to tornadogenesis.
Significant advances in computer processing, the utilization of new types and greater numbers of real-time weather observations (NRC 2009), and the development and adoption of new data assimilation (DA) techniques (Kalnay 2003; Park and Xu 2009) are making warn on forecast a real- ity. Computer processing capabilities continue increasing at an exponential rate, as predicted by
TORNADO DETECTION. Weather radar is the primary tool used by warning forecasters to iden- tify areas of potential tornado development. Radar ref lectivity provides forecasters with a clear view of tornadic features, such as the hook echo (Markowski 2002), and Doppler radial velocity shows horizontal wind shear, sometimes an early indicator of tornado formation (Brown et al. 1971). Radar polarimetric data provide storm microphysical information, such as hydrometeor type and shape, that can be used to identify areas of significant low-level wind shear (referred to as Z arcs) and tornado debris (Ryzhkov DR et al. 2005; Bodine et al. 2013).
To better standardize weather radar coverage across
NEXRAD deployment had an immediate and sig- nificant positive impact on tornado warning statistics (Polger et al. 1994; NRC 1995). Bieringer and Ray (1996) found that the probability of detection (POD) increased by 10%--15% and that warning lead times increased by several minutes after installation of the WSR-88D network. Analyzing all tornadoes in the conterminous
For enhanced tornado detection, automated detec- tion algorithms, such as the WSR-88D mesocyclone (Stumpf et al. 1998) and tornado detection algorithms (MDA and TDA, respectively; Mitchell et al. 1998), automatically identify radar-based tornado features and are displayed in real time within the Advanced Weather Interactive Processing System (AWIPS). Radar data can be combined with additional weather information to linearly project storm motion and extrapolate mesocyclone, tornado, and hail core movement (e.g., Smith and Elmore 2004; Lakshmanan et al. 2007; Wang et al. 2008; Ortega et al. 2009; Lakshmanan and Smith 2010; Miller et al. 2013).
Storm reports from individuals in the field can provide timely, critical information to warning officials. Trained "storm spotters" provide a valuable service to the NWS, EMs, and media by providing reliable, real-time information on storm evolution and tornado development (
Nearly as important, spotters provide much- needed postevent verification; Brotzge and
TORNADO WARNING DECISION. Once the formation of a tornado is considered likely or is re- ported already in progress, the NWS issues a tornado warning, the official NWS product used to warn the public of a tornado. The first tornado warning was issued on
The final decision by the operational forecaster on whether to issue a warning is based upon a number of complex, sometimes competing factors. These factors may include environmental data, access to real-time weather and storm spotter information, forecaster experience, knowledge, distance of event from the nearest radar, population density, population vulner- ability, tornado climatology, event anticipation, SPC guidance, and/or storm history. The interpretation of such data may be impacted by such things as personal fatigue, office staffing, and interoffice relationships. Andra et al. (2002) provides an excellent case study of warning decision making during the
Despite the difficulty of each decision, the warning forecaster strives to warn on every tornado, with as much lead time as possible, while minimizing the number of false alarm warnings. Having every tornado warned is essential for public safety; the public is much more likely to take shelter once they have received an official warning (Balluz et al. 2000). However, there is an incentive to keep the warning area size small; the use of smaller warning polygons is estimated to save over
As of 2011, the national tornado POD was 0.75, with a mean lead time of 14.6 min, and a FAR of 0.74 (NOAA 2011b). A review of the long-term trends in these statistics reveals that the POD and mean lead time have increased dramatically since the installa- tion of the WSR-88D network and NWS modern- ization program (Friday 1994), with a POD of 0.48 and a mean lead time of 7.6 min in 1994. However, nearly all of this increase in lead time was a direct result of greater numbers of tornadoes being warned (
WARNING DISSEMINATION. Warning the public remains difficult in large part because the "public" is a largely diverse population with tremen- dous variation in education, physical abilities, family support, and situational awareness. To overcome these challenges, a variety of communication alert systems are used. Warnings may reach the public directly from the NWS through the
The public most commonly receives tornado warnings from local media through television and radio (e.g., Hammer and
Emergency managers also play a critical role in disseminating weather information to the local community. As part of their responsibilities, EMs operate local warning systems, such as local out- door warning sirens or reverse 911 systems, and coordinate disaster response and recovery efforts. An instant messaging service called NWSChat was created to facilitate direct communication between the NWS and EMs and to better support EM services. However, there are few consistent criteria applied across jurisdictions for warning dissemina- tion. A number of meteorological (e.g., presence of a wall cloud) and nonweather-related (e.g., public backlash for issuing false alarms) factors influence the judgment of EMs on whether to activate warning systems (Sorensen and Mileti 1987; Stewart and Lusk 1994;
PUBLIC RESPONSE. Warning dissemination sets into motion a process of public response, a complex and multidimensional activity. While research on risk and warning response has been conducted since the 1950s, it was not until the 1990s that scholars began to systematize findings into a general model. Mileti and Sorensen (1990) and Lindell and Perry (1992) shared the common conclusion that warning response was not a single act, but a set of stages through which the public progressed in responding to disseminated warnings. Before taking action, the public must receive, understand, believe, confirm, and personalize warnings.
Reception. Community members receive warning information through formal and informal channels. Formal communication includes NWS, media, emer- gency management, and reverse 911, or any official warning system. Informal communication includes family, friends, and coworkers. Each form of commu- nication channels warning information to the public, but each does so in dramatically different ways. Formal communication tends to reach members of upper- and middle-class populations, while infor- mal communication often better serves the poor, ethnic minorities, and recent migrants. For instance, warnings issued during the 1987
Social networks may play a key role in reception. For instance, Nagarajan et al. (2012) documented the importance of warning dissemination among neigh- bors in a series of computer simulations. Frequent interaction of family members (Lardry and Rogers 1982), strong community or network involvement (Turner et al. 1979; Sorensen and Gersmehl 1980; Perry and Greene 1983; Rogers and Nehnevajsa 1987; Rogers and Sorensen 1991), regular association with a subculture or voluntary association (Perry et al. 1981), and more frequent community interaction (Scanlon and Frizzell 1979) improved the likelihood of message reception among individuals within the community.
Understanding. How recipients understand and make sense of warning information is deeply connected to human psychology and past experience. With the exception of Quarantelli (1980), research overwhelm- ingly demonstrates that long-term residents gener- ally tend to hold a better understanding of warning information (
One concern is whether individuals understand the difference between warnings and watches. In a study of
Social scientists have identified a number of social and cultural factors that account for variation in warning comprehension between individuals. Education is consistently associated with greater understanding (Turner et al. 1979), and those with a greater familiarity with science and scientific concepts generally hold a stronger understanding of warnings (Blanchard-Boehm 1998). Age, too, shows a direct correlation with understanding (Turner et al. 1979; Blanchard-Boehm 1998).
Belief. After understanding a warning message, the recipient evaluates the credibility of the message. Will there really be a tornado or is the warning a false alarm? In other words, should the message be taken seriously? Rarely, however, at this stage do recipients arrive at a concrete conclusion about whether a tornado will or will not occur. On the contrary, recipients crudely evaluate the probability of severe weather. The psychological qualities, past experiences, and unique demographic characteristics of the individual play a significant role in shaping these judgments of likelihood.
Those closer to a hazard are more likely to believe a warning (Diggory 1956; Sorensen 1982), which may be because of the greater likelihood of experiencing environmental cues (Drabek 1969; Quarantelli 1980; Sorensen 1982; Tierney 1987; Mileti and Fitzpatrick 1993; Hammer and
Demographic factors have some influence as well. Women appear more likely to believe warnings (Drabek 1969;
Confirmation. A common feature of the warning process (Mileti 1999), confirmation serves to clarify and specify warning information, but at the cost of delaying sheltering. Confirmation has been found to take place among neighbors, rather than through formal channels (Kirschenbaum 1992), with infor- mation from media sources more likely the subject of confirmation (
Personalization of risk. Risk personalization deals with whether community members believe severe weather will affect them personally. In other words, one can believe that a threat exists somewhere, but the threat is not immediate and therefore action is unnecessary. For example, residents may decide that the mountains or rivers surrounding their community protect them from tornadoes, even if they believe local reports that storms may produce tornadoes (
The psychological elements of risk personaliza- tion are well understood. Warning consistency yields greater personalization of risk (McDavid and Marai 1968; Lindell and Perry 1983). Warning specific- ity (Perry et al. 1981) and sender credibility (Perry 1979; Rogers and Nehnevajsa 1987) contribute to personalization. Geographical proximity to a threat appears to be the most important in the literature (
Demographics also play a role. As with belief, women are more likely to personalize a threat (
Action necessary and feasible. Believing that one is personally at risk sets off a process of determining whether one must and is able to do something to pro- tect oneself. Little research has been conducted in this area of the model. This stage is unique from resource availability, in that resources may be available but the potential victim either does not know about them or does not think them useful for protection.
Protection from severe weather often takes the form of sheltering. Sheltering may be broadly de- fined as either "in home" or "public." With in-home sheltering, refuge is typically sought in hallways, closets, underground basements, or, ideally, personal shelters. Those under warning may also choose to seek public shelters, which are typically set up and maintained by local government. Public shelters may be stand-alone shelters, in that their only use is as a shelter, or schools, town halls, or other municipal structures may become "shelters" during storms. Education, possibly through increased income, is most consistently associated with the availability of resources such as shelters (Edwards 1993; Balluz et al. 2000); see "Public response challenges" for more information.
NEXT STEPS. All other things being equal, as the U.S. population density increases, tornado fatalities may be expected to increase, calling for a review of the prediction, detection, and communication pro- cesses through which tornadoes are warned. Urban populations continue to rise in hazard prone regions, thereby placing greater numbers of people at risk (Brooks and Doswell 2001; Ashley 2007). In addition, the overall population is aging, with increasing numbers living alone (Gusmano and Rodwin 2006). Greater diversity among the population introduces additional challenges, such as warning dissemina- tion to non-English-speaking populations (
A fundamental question society must ask is, "How much risk are we willing to tolerate?" The answer to this dilemma will set the limit on how much money should be expended toward further research and warning infrastructure. In other words, the public must define its acceptable risks, and its willingness to provide additional resources or reduce existing services or quality to match those risks (Stallings 1990). The public's level of acceptable risk likely varies across the country as a function of the nature and extent of the risk. This variability calls for an emphasis on local-to-regional decision making, such that any top-down, one-size-fits-all strategy will likely be less than optimal. A dense observing spotter and warning dissemination network in the plains may vary in function and form from one in the Southeast, whereas neither system may be cost effective in the West or
A second essential subject often overlooked in discussions of the tornado warning process is preparation, both at the organizational and personal levels. Preparation at the organizational level may include the development of public policy regarding the use and availability of public shelters and warning systems, the availability of multilingual warnings, requirements or guidelines for shelters in mobile home parks, building codes, and sheltering proce- dures. Private preparations may include developing a family disaster plan, copying and storing critical insurance papers and photos in safety deposit boxes, or purchasing a safe room or shelter. Proper prepara- tion at the organizational level can often facilitate the speed and ease of personal decision making during a moment of crisis.
Preparation should focus on maximizing per- sonal safety, minimizing economic loss, and easing recovery efforts. While this article has focused on public safety, total damage estimates from tornadoes between 1950 and 2011 range from
Finally, the one common ingredient to a suc- cessful end-to-end tornado warning program is the personalization of the warning; to be successful, warnings must evoke a sense of specific and imme- diate risk. Even days prior to an event, the efforts of the SPC and others are spent narrowing the area of a potential threat; local WFOs narrow the threat further in time and space, issuing warnings over specific regions in time. The most effective warnings are those that communicate clearly to individuals the specific information they need to know with enough time to react. The goals of ensemble NWP, warn on forecast, phased array and gap-fill radars, and storm-based warnings are to provide more detailed data on when and where tornadoes will strike. Many new and innovative warning dis- semination tools, many developed and sold by the private sector, convey this detailed information to individuals, through the use of local media, outdoor warning sirens, NOAA Weather Radio, the Internet, smart phones, and pagers. Similarly, preparation for tornadoes needs to be personalized, and specific mitigation information provided at a household level could see potential dividends in reducing home damage and personal injury.
Social and cultural factors may inhibit personal- ization of warnings. Long lead times and high false alarm rates tend to depersonalize risk. A continuing program of research and education remains key to systematically improving public response to warnings.
A highly integrated and efficient tornado warning system does not necessarily ensure that no fatalities will ever occur, but it does set a priori standards of warning capability as a function of the community- defined level of acceptable risk, resources, and will. The effectiveness of the best tornado warning system is dependent largely upon the comprehensiveness and manner of preparedness at the organizational and personal levels. This review has demonstrated the value of research and investment at all stages of the warning process for improving the personaliza- tion of the warning. In an era of austerity, additional investments will need to be strategically focused to further prepare and personalize the tornado threat.
ACkNOWLEDGMENTS. This work is supported by the
PREDICTION CHALLENGES
Several significant challenges remain to be addressed before routine 0--3-h tornado prediction can be realized. These needs include i) faster computer processing to permit even higher-resolution NWP and more robust ensemble systems; ii) the ability to enable real-time DA of even larger volumes of data; iii) greater numbers of observations at high spatial and temporal resolutions; and iv) the ability to predict marginal, less predictable events with greater accuracy and fewer false alarms. Model grid spacing is tightly coupled with the model physics; for ex- ample,
In a similar manner, storm-scale NWP is equally sensitive to model initialization and analysis. Numerical modeling of convective storms has shown sensitivity to model initialization of low-level thermo- dynamics (Frame and Markowski 2010), low-level wind profiles (Dawson et al. 2012), surface soil moisture (
Finally, while our ability to anticipate and predict significant events is rela- tively good with a POD of nearly 90% for tornado outbreaks (Brotzge and
DETECTION CHALLENGES
The most common reasons for op- erational warning forecasters for not detecting (and thereby not warning) tornadoes prior to touchdown often can be traced to having either too little infor- mation available-because of inadequacies in existing technology (e.g., LaDue et al. 2010), limited spotter networks, and incomplete conceptual models-or too much information, that is, data overload.
As the primary tool used for detecting tornadoes, weather radar is critical for seeing low-level to midlevel rotation prior to tornadogenesis. In areas with limited low-level radar coverage, tornado detection (and prediction) is severely hampered. In a root cause analysis study of 146 unwarned tornadoes between 2004 and 2009, "radar sampling," "no radar signature," and "radar use" were listed as 3 of the top 10 reasons for failure to warn and were cited in over two-thirds of all missed events (Quoetone et al. 2009). Sampling issues were cited in 19 of 31 false alarm events evaluated. Brotzge and
Solutions to improving radar coverage include the use of lower-elevation scans, deployment of gap filling and rapid-scan radars, and an optimization of the radar network configuration. The WSr-88Ds' lowest scanning angle is 0.5° elevation, as limited by
Zrnic' et al. 2007) could provide 1-min volume scans (or faster single elevation scans), an improvement over the current 4 --6-min volume scans provided by the WSr-88Ds. In ongoing evaluations of the impact of PAr data on tornado warnings, heinselman et al. (2012, 2013) found that the use of faster scans has the potential to extend tornado warning lead times, re- duce false alarms, and increase forecaster confidence. Finally, a more rigorous, optimal radar network configuration could improve overall low-level coverage. NEXrAD radars were originally deployed to operate as single autonomous systems; however, merged, multiradar data have proven more effective for extracting severe weather information (Lakshmanan et al. 2006). geometric, statistical, and genetic algorithm techniques have been developed to optimize the low-level coverage and maximize multi-Doppler overlap (ray and Sangren 1983; de ElĂa and Zawadzki 2001; Minciardi et al. 2003; Junyent and Chandrasekar 2009; Kurdzo and Palmer 2012). Nevertheless, the addition and /or replacement of radars will require a significant financial public investment.
Storm spotters provide an equally crit- ical role to the warning forecaster. In the root cause analysis study, a lack of, con- flicting or erroneous spotter reports were cited as having contributed to warning failure in nearly two-thirds of all missed events, and a lack of reports contributed to 15 of 31 false alarms (Quoetone et al. 2009). Sustained education and coordina- tion of spotter groups requires dedicated NWS resources. Fortunately, as described previously, access to real-time informa- tion and video from the field is becoming easier, with the proliferation of new video and wireless technologies (e.g., Dixon et al. 2012).
A basic understanding of tornado dynamics is still key to good forecasting and detection. In the Quoetone et al. (2009) root cause analysis study, "not anticipated," "conceptual model failure," and "environment" were listed among the top six reasons for warning misses. Poor radar, environmental conceptual models, and environment were listed as three of the top four reasons cited for issuing tornado false alarms. "Fits radar conceptual model" was cited in 30 of the 31 false alarm events studied. Continued improvement in the conceptual models requires sustained advances in basic research. Field programs such as the Verification of the Origins of rotation in Tornadoes Experiment (VOrTEX; rasmussen et al. 1994) and the second VOrTEX project (VOrTEX2; Wurman et al. 2012) provide valuable observational data from which to study and improve understanding. Continued meteorological training and education are essential for moving research to operations.
Finally, with the plethora of new sensors and model output now avail- able to the warning forecaster, many are now experiencing data overload, which is hampering warning operations. "Workload" was cited in one-third of all missed warnings, with "distractions" cited in one-quarter of all missed warnings (Quoetone et al. 2009). One solution to this is the use of integrated, "fused" and/or assimilated sensor products (e.g., Wang et al. 2008). A second, complemen- tary solution is the advent of multisensor and three-dimensional visualization (e.g., gibson ridge
WARNING DECISION CHALLENGES
significant challenge to the forecaster is reducing the FAr while keeping the POD steady or improving (Brooks 2004). Yet the value provided by the statistical measures (POD, FAr) is ambiguous. For example, POD is dependent largely upon the level of verification. FAr fails to account for close calls (Barnes et al. 2007) and varies with parameters such as tornado order, climatology, and distance from radar (Brotzge et al. 2011). While the POD, FAr, and warning lead time are frequently cited indices for measuring our ability to warn, additional improvement in these numbers may not translate necessarily into a reduction in tornado casualty rates.
All of the deaths from the
The impact of false alarms on public response is unknown. Early research found that false alarms may unexpectedly increase the likelihood of future response (
A second emergent challenge for the warning forecaster is how to best blend information from automated algorithms, nowcasting, and NWP model output with conceptual models and human experience (Stuart et al. 2006). At least in the short term, such output have limitations (e.g., Andra et al. 2002), and their use may be limited best as a check or calibration against the conceptual model.
WARNING DISSEMINATION CHALLENGES
significant challenge in improving warning dissemination is to integrate new technologies in such a manner that those less able to afford such tools can still be warned. The Commercial Mobile Alert System (CMAS), Wireless Emergency Alerts (WEA), and Interactive NWS (iNWS) were recently created to disseminate warnings to mobile devices. however, many are ill equipped to receive text messaging, and so older warning systems, such as outdoor warning sirens, must still play a critical role within an inte- grated warning system, even as new, more informative services are made available.
The limitations of dissemination tools must be clearly recognized when building a public warning dissemination system. For example, mobile phone applications fail if and when cell phone towers and commu- nications are disabled, a frequent problem in storm-ravaged areas. Similarly, outdoor warning sirens fail when power is lost to those sirens, such as occurred in some areas during the
Another challenge for the operational forecaster is how to effectively communi- cate scientific information to the general public. Instantaneous communication and the growth of meteorological support companies have had a significant impact on the warning process (golden and Adams 2000). As a result, institutions now communicate risk with unprecedented speed. Nevertheless, problems related to the expertise of institutions may affect the process of risk communication. For example, a recent experiment simulating a tornado outbreak tasked EMs with accessing and interpreting radar data (Baumgart et al. 2008). Despite general competence, study participants experi- enced significant difficulties interpreting wind velocity data and, more importantly, synthesizing multiple forms of radar data to produce overall judgments, which affected the risk communication process.
Effective communication also entails that the public understands and makes effective use of warnings (Lazo 2012). The risk communication process is most effec- tive when those at risk hold a "perceived shared experience" with those already victimized (Aldoorya et al. 2010). When those warned could relate to victims (e.g., similar gender or race), threat acknowledg- ment and information seeking increased. Thus, risk communication may be taken more seriously if nearby communities are affected. how warnings are communi- cated also may shape risk communication. Numerical representations of risk often fail to persuade (Lipkus and hollands 1999). In an experiment on risk perception of flooding, images depicting flood damage re- inforced perceived risks (
PUBLIC RESPONSE CHALLENGES
Although the determinants of shelter seeking are well documented in the literature, little is known about the sheltering process itself. Personal shelters are ideal, in that sheltering is immediate; traveling to a public shelter may be dangerous, especially in the context of tornadoes that are rapid and violent on onset. For those in mobile homes or similar vulnerable structures without shelters, evacuation may be the only option; mobile homes comprised 7.6% of U.S. housing stock in 2000, but 43.2% of all tornado fatalities between 1985 and 2007 occurred in mobile homes (Sutter and Simmons 2010). In addition to distance, other more "human" factors may shape the use of shelters. Cola (1996) found that people were less likely to use shelters thought uncomfortable. Pet owners also may be less likely to seek shelter (heath 1999; Pfister 2002). More research is needed to understand shelter use and its relationship to lead time and social factors. Additional work needs to explore the associ- ated needs, optimal locations, and operation of public tornado shelters.
There is also the real inability by some to take shelter because of disability. In the
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AFFILIATIONS: Brotzge-
CORRESPONDING AUTHOR :
E-mail: [email protected]
The abstrac t for this article can be found in this issue, following the table of contents.
DOI:10.1175/BAMS-D-12-00147.1
In final form
©2013
| Copyright: | (c) 2013 American Meteorological Society |
| Wordcount: | 13066 |
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