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Climatic Change (2014) 127:381–389
DOI 10.1007/s10584-014-1253-6
LETTER
Mapping the shadow of experience of extreme weather
events
Peter D. Howe & Hilary Boudet & Anthony Leiserowitz &
Edward W. Maibach
Received: 30 June 2014 / Accepted: 10 September 2014 / Published online: 13 October 2014
# Springer Science+Business Media Dordrecht 2014
Abstract Climate change will increase the frequency and/or intensity of certain extreme
weather events, and perceived experience with extreme weather may influence climate change
beliefs, attitudes, and behaviors. However, the aspects of extreme events that influence
whether or not people perceive that they have personally experienced them remain unclear.
We investigate (1) the correspondence of reported experience of extreme weather events with
documented events, and (2) how characteristics of different extreme events shape the geographic area within which people are likely to report they have experienced it—the event’s
perceived “shadow of experience.” We overlay geocoded survey responses indicating personal
experience with hurricanes, tornadoes, and drought—from a 2012 nationally representative
survey (N=1,008) of U.S. residents—on maps of recorded event impacts. We find that
reported experiences correspond well with recorded event impacts, particularly for hurricanes
and tornadoes. Reported experiences were related to event type, proximity, magnitude and
duration. The results suggest locations where disaster preparedness efforts and climate change
education campaigns could be most effective after an extreme weather event.
1 Introduction
Extreme weather events—events that are rare for a particular place and time of year—can
serve as teachable moments about climate change (Marx et al. 2007; Spence et al. 2011; Myers
P. D. Howe (*)
Department of Environment and Society, Quinney College of Natural Resources, Utah State University,
5215 Old Main Hill, Logan 84322 UT, USA
e-mail: [email protected]
H. Boudet
Department of Sociology, School of Public Policy, Oregon State University, Corvallis, OR, USA
e-mail: [email protected]
A. Leiserowitz
School of Forestry and Environmental Studies, Yale University, New Haven, CT, USA
e-mail: [email protected]
E. W. Maibach
Center for Climate Change Communication, George Mason University, Fairfax, VA, USA
e-mail: [email protected]
382
Climatic Change (2014) 127:381–389
et al. 2013; Rudman et al. 2013). But what types and scales of events are the best teachers?
And how near must a person be relative to the event for it to create a teaching opportunity? As
climate change increases the frequency and/or intensity of certain extreme weather events
(Coumou and Rahmstorf 2012; Peterson et al. 2012), these are important questions not only
for climate educators trying to understand where to devote limited time and resources, but also
for risk managers hoping to encourage disaster preparedness.
Personal experience plays an important role in individual risk perceptions of future events
as well as preparedness and mitigation behaviors, although the effect of experience is likely to
be contingent on situation-specific aspects of the event (e.g., type, magnitude, distance),
individual factors (e.g., knowledge, values, attitudes, emotions) and social context (e.g., media
reports, peer influences, culture) (McGee et al. 2009; Zaalberg et al. 2009; Wachinger et al.
2013; Silver and Andrey 2014). Moreover, the effect of experience on perceptions and
attitudes can create “windows of opportunity” for policy change (Tierney 2007; McGee
et al. 2009).
These findings from natural hazards research are similar to findings about the influence of
weather experience on beliefs and actions related to climate change. Perceptions of changes in
local weather (e.g., rising temperatures, flood experience) play an important role in beliefs,
attitudes and behaviors related to climate change (Spence et al. 2011; Hamilton and Stampone
2013; Akerlof et al. 2013; Zaval et al. 2014) and vice versa (Goebbert et al. 2012; Howe and
Leiserowitz 2013). Using direct measures of weather changes, studies have linked local
weather and climate fluctuations to beliefs and attitudes, particularly for those with less
entrenched beliefs (Egan and Mullin 2012; Goebbert et al. 2012; Howe et al. 2013; Howe
and Leiserowitz 2013; Hamilton and Stampone 2013; Akerlof et al. 2013; Zaval et al. 2014).
Recent research, however, has focused on variations in temperature and precipitation as
opposed to extreme weather events, yet extreme weather events, particularly when they result
in fatalities, may have a larger and longer term impact on climate change attitudes (Brody et al.
2008). Indeed, recent research has shown that personal experience with Hurricanes Irene and
Sandy increased both pro-environmental beliefs and support for politicians who support
climate change mitigation (Rudman et al. 2013).
We analyze an important aspect of the relationship between exposure to extreme weather
and people’s beliefs that they have personally experienced climate change: the characteristics
of extreme weather events that influence how members of the public perceive that they have
personally experienced extreme weather. To date, there has been limited research on how
different extreme event types, magnitudes, durations or proximity influence public perceptions
of extreme weather experience.
Our goal is to investigate the geographic correspondence of subjective personal experience
of extreme weather events with the recorded locations of events. In so doing, we will examine
the effect of proximity on personal experience to characterize the events’ “shadows of
experience.” While the concept of a risk perception shadow was originally created to map
risk perceptions of technological hazards associated with siting hazardous facilities, we believe
it useful in the context of extreme weather risk. Adapting a definition offered by Stone (2001),
we define a shadow of experience as the geographic area within which a population perceives
itself to have experienced an extreme weather event. This area may extend beyond the location
where the event actually occurred, for example via indirect experience from friends or
relatives, or social and environmental cues. Based on previous research (Stoffle et al. 1991)
that has outlined the factors that may be important in mapping risk perception shadows, we
analyze the type of event, proximity or directness of impacts, significance or magnitude of
impacts, and duration of impacts on people’s tendency to report personal experience with the
extreme weather event. Moreover, this analysis represents a novel application of spatial
Climatic Change (2014) 127:381–389
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relative risk mapping—a technique adapted from spatial epidemiology—and statistical models
to characterize the relationship between extreme weather events and individual perceptions.
2 Methods
Data on extreme weather perceptions were obtained from a national survey of U.S. adults (ages
18 or older) conducted in April 2012 using an online panel recruited by Knowledge Networks
(N=1,008; completion rate=54.1 %; cumulative response rate=5.2 %). Response rate metrics
for online panel surveys are still under development, and do not compare directly to telephone
or mail surveys. A cumulative response rate may be calculated as the product of the panel’s
recruitment rate, profile rate (the proportion of respondents who completed the initial profile
survey to become panel members) and completion rate (Callegaro and DiSogra 2008). While
the cumulative response rate appears low compared to telephone surveys, studies show that the
accuracy of probability-based Internet surveys meets or exceeds that of telephone interviews,
with the optimal combination of both sample composition and response accuracy (Chang and
Krosnick 2009). Knowledge Networks recruits participants using random digit dialing and
provides small incentives as well as a free netbook and Internet service to those without
computers to ensure they are represented in the panel. Survey responses were based on a series
of yes/no questions which asked the respondent: “In the past year have you personally
experienced each of the extreme weather events or natural disasters listed below?” and
included eleven types of extreme weather events (extreme snow storm, extreme cold temperature, extreme high winds, extreme rain storm, extreme heat wave, flood, wildfire, hurricane,
drought, tornado, other unusual weather). Only those who provided an answer are included in
the analysis. We focused our analysis on perceptions of tornadoes, hurricanes and droughts as
examples of hazards with varying spatial extents, magnitudes, and rates of onset.
We mapped the spatial pattern of perceived experience of each hazard by creating a relative
risk surface for each survey item, depicting the probability density of each response relative to
other responses and accounting for spatial inhomogeneity in the underlying population. Kernel
density estimation was performed in R using the spatstat (Baddeley and Turner 2005) and
sparr (Davies et al. 2011) packages, which use an isotropic kernel smoother with bandwidths
selected by cross-validation. Positive concentrations of responses were identified after calculating asymptotic p-value surfaces, with positive concentrations at the 95 and 99 % confidence
level represented as contours superimposed on the relative risk surface.
We conducted a spatial nearest neighbor analysis to characterize the relationship between
proximity to recorded extreme events and the probability that respondents would report
personal experience with the event. We calculated the great-circle distance between each
respondent and: (1) the nearest recorded tornado track of each category on the Enhanced
Fujita scale between January 2011 and March 2012 and (2) the nearest record of property
damage, injuries, or fatalities due to a hurricane between January 2011 and March 2012.
Tornado tracks were obtained from the NOAA Storm Prediction Center (SPC 2013) and
hurricane records were obtained from the National Climatic Data Center Storm Events
Database (NCDC 2013). Records were included if they were categorized as a hurricane/
tropical storm event, or if they were categorized as a coastal flood, storm surge, or flood event
related to a hurricane/tropical storm. We included events beginning in January 2011 because
our survey question asked about events “in the past year,” which may have been interpreted as
referring to events either within the last 12-month period or within the previous calendar year.
The Storm Events Database georeferences hydro-meteorological events to the point, county, or
weather forecast zone. In the case of events referenced only to a county or weather forecast
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zone, the events were assigned to the centroid of the county or zone. This method generates
some locational uncertainty at the lower bound of the nearest-neighbor analysis.
We counted the number of respondents within successive 1-km distance bands from the
nearest event and calculated the proportion of respondents who reported experiencing a
particular type of event within each distance band. Using a chi-square test we then tested
the difference between the proportion of respondents reporting personal experience
within each distance band and the national baseline proportion of respondents
reporting personal experience with each type of event. To examine the relationship
between perceptions and experiences of drought, we calculated the duration of severe
drought (Category 2 or higher) at the county level during the 15 months prior to the
survey. We then extracted these county-level data based on respondent locations for
use in logistic regression analysis.
3 Results
In a nationally representative survey conducted in April 2012, a large majority of Americans
(82 %) said they had personally experienced one or more types of extreme weather or natural
disasters in the past year (Leiserowitz et al. 2012). Here we focus on three hazards that differ in
spatial scale, rate of onset, magnitude, and relationship to climate change: tropical cyclones/
hurricanes, tornadoes, and drought. Hurricanes are moderate-onset events (with a typical
advance warning of days) that affect large areas and are projected to increase in severity as
the climate changes, but possibly decrease in frequency (IPCC 2012). Tornadoes are fast-onset
events (with a typical advance warning of minutes) that affect relatively small areas, but it
remains unclear whether climate change will affect the frequency or severity of tornadoes
(IPCC 2012). Droughts are slow-developing events, but affect large areas, are often longlasting, and are projected to increase in frequency and severity in the Western U.S. as a result
of climate change (IPCC 2012). In April 2012, 16 % of Americans reported experiencing a
hurricane, 21 % reported experiencing a tornado, and 34 % reported experiencing a drought in
the prior year.
The spatial distribution of recorded tropical cyclone activity, tornado tracks, and drought
corresponded with the distribution of people’s reports of personal experience with each event
(see Fig. 1). The analysis of hurricane experience was limited to one event, since Irene was the
only hurricane to affect the contiguous U.S. during the study period, making landfall in North
Carolina in August 2011 as a Category 1 hurricane and later making a second landfall in New
Jersey as a tropical storm. Mapping the relative distribution of reported hurricane experience
showed that respondents from eastern North Carolina through northern New England
were significantly more likely than respondents elsewhere in the country to report
experiencing a hurricane, with a rate ranging from 20 to 35 % (as compared to less
than 5 % in the West). This region corresponds to the area affected by Hurricane
Irene. Although rainfall from Tropical Storm Lee caused flooding in the Southeast
through Mid-Atlantic regions in 2011, respondents in those areas did not show an
elevated probability of reporting hurricane experience—possibly because the storm
was never classified as a hurricane.
The study period was an abnormally active tornado year in the U.S., with seven major
tornado outbreaks, 1,691 confirmed tornadoes, 551 deaths, and over one billion dollars in
damages (NCDC 2012). In contrast to the analysis of hurricane experience, the analysis of
tornadoes includes many events with different characteristics. Mapping the relative distribution
of reported tornado experience showed that respondents in the southern Midwest and
385
0.8
0.6
0.4
0.2
p < 0.05
Track of Hurricane (Tropical Storm) Irene
Tornado-related disaster declarations
p < 0.01
Yes
No
Presidential disaster declaration
Personally experienced tornado (n=187)
1
0.6
0.4
0.2
p < 0.01
Personally experienced drought (n=316)
Severe drought duration
0
0.8
p < 0.05
Tornado track
0
65
1
52
0.8
39
0.6
Weeks
26
0.4
13
0.2
1
0
p < 0.05
p < 0.01
Pr(hurricane experience)
No
Presidential disaster declaration
Yes
1
Pr(tornado experience)
Personally experienced hurricane (n=128)
Hurricane-related disaster declarations
Pr(drought experience)
Climatic Change (2014) 127:381–389
0
Fig. 1 Spatial distribution of recorded extreme weather events (left) and reported personal experience (right)
Southeast were significantly more likely than the national average to report that they had
experienced a tornado, ranging from 25 to 35 % (as compared to less than 5 % in the Pacific
Northwest). The region of reported experience of tornadoes corresponds with the
region that suffered the highest rate of deaths and property damage from tornadoes
in 2011.
Drought also affected large areas of the U.S. in 2011 through spring 2012, with 56 % of the
U.S. in abnormally dry conditions and 19 % of the U.S. in severe drought as of March 27,
2012. Drought was concentrated in the Southwest, Southern Plains, and Southeast. These
regions corresponded with areas where respondents were significantly more likely than the
national average to report that they had experienced a drought. For example, 75 % of
respondents in southern Texas reported that they had experienced a drought, compared to less
than 20 % of respondents in the Northeast.
We compared the distances among respondents and the nearest recorded impacts of the
different types of extreme weather events to identify the spatial extent of the shadow of
experience—the area in which people are more likely to report experiencing an event.
Figure 2a shows the probability that a respondent reported experiencing a hurricane versus
their distance from locations affected by Hurricane/Tropical Storm Irene, as compared to the
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Probability of reported personal experience by event type, distance to nearest event, & magnitude
Local probability (95% CI)
b
1.0
0.8
0.4
0.2
0.0
0
800
50
100
150
200
250
0
Nearest tornado track, EF0-EF5 (km)
e
f
Tornado (EF3-5)
Pr (tornado experience)
0.6
0.4
Pr (tornado experience)
100
150
200
Nearest tornado track, EF2-EF5 (km)
250
200
250
Tornado (EF4-5)
0.2
0.2
0.0
0.0
50
150
0.8
0.8
1.0
0.8
0.6
0.4
0.2
0.0
0
100
Nearest tornado track, EF1-EF5 (km)
1.0
Tornado (EF2-5)
50
1.0
600
0.6
400
Tornado (EF1-5)
0.6
Pr (tornado experience)
0.4
0.6
Pr (tornado experience)
0.2
0.0
200
Nearest tropical cyclone record (km)
Pr (tornado experience)
c
0.8
1.0
0.8
0.6
0.4
Pr (hurricane experience)
0.2
0.0
0
d
Baseline probability
Tornado (EF0-5)
1.0
Hurricane
0.4
a
0
50
100
150
200
Nearest tornado track, EF3-EF5 (km)
250
0
50
100
150
200
250
Nearest tornado track, EF4-EF5 (km)
Fig. 2 Probability of reported personal experience by distance to nearest event record, as compared to national
baseline, for hurricanes (a) and tornadoes of magnitude EF0-5 (b), EF 1–5 (c), EF 2–5 (d), EF 3–5, and EF 4–5
(f). Note the difference in the x-axis between (a) and (b–e). Shaded areas represent 95 % confidence intervals of
the proportion of respondents who reported personal within each distance band
unweighted national baseline. The shadow of experience for Irene extended beyond the area
directly affected by the storm: respondents within 820 km of locations with recorded impacts
were significantly more likely (up to 3.3 times greater than the national baseline) to report that
they had experienced a hurricane (p<0.05). However, even within areas directly affected by
Irene, no more than 45 % of respondents reported that they had experienced a hurricane,
possibly due to the fact that it weakened from a hurricane to a tropical storm just prior to its
second landfall.
Figure 2b–f depict the probability that a respondent reported experiencing a tornado as a
function of their distance from the nearest tornado track for varying sets of tornadoes of
increasing magnitude, as compared to the unweighted national baseline. For tornadoes, the
shadow of experience grows with the magnitude of the event. For example, respondents within
71 km of an EF 0–5 tornado track were significantly more likely to report (p<0.05) that they
had experienced a tornado, whereas the distance band increased to 121 km for an EF1-5
tornado track, 207 km for an EF 2–5 tornado track, 504 km for an EF 3–5 tornado track, and
1,150 km for an EF 4–5 tornado.
To examine the effects of drought duration on perceived experience, we fit a logit model
predicting perceived drought experience as a function of the duration of severe drought at the
county level during the 15 months prior to the survey. As shown in Fig. 3, the probability of
reported experience increases with the duration of exposure to drought (β=0.05, std. error=
0.01, p<0.001). On average, each week of severe drought increases the chance of perceived
drought experience by about 1 %. However, only in areas exposed to at least 25 weeks of
severe drought conditions were the majority of people (>50 %) likely to report that they had
experienced a drought.
Climatic Change (2014) 127:381–389
387
0.8
0.6
0.4
0.2
0.0
Pr (drought experience)
1.0
Perceived experience with drought
0
10
20
30
40
50
60
Number of weeks in drought category 2 or higher
Fig. 3 Probability of reported personal experience with drought by duration of exposure to drought. Shaded area
indicates 95 % confidence interval
4 Discussion and conclusions
Our results suggest that the public tends to accurately recall and report experiences with
extreme weather, particularly discrete events like hurricanes and tornadoes that tend to have
large impacts and attract media coverage. The distributions of perceived experiences reported
by survey respondents follow the same spatial patterns as the records of actual events. As one
might expect, people located closer to recorded events are more likely to report experiencing
them. This proximity effect may be explained by an increased likelihood of personally
suffering harm or property damage as one approaches the site of the event, as well as
environmental cues (e.g. dark clouds or high winds) and social cues (e.g. tornado sirens or
warnings) that are more likely to be present closer to the event. We find that the shadow of
experience—in terms of the distance within which people are more likely to report that they
have experienced extreme events—increases as the magnitude of an event increases, as shown
by our analysis of experience with tornadoes of different magnitudes. As disaster events
increase in magnitude, they become more likely to cause not only direct damages and loss
of life, but indirect damages through disruption of services, utilities, businesses, social
networks, and local economies. These indirect effects are one likely cause for the tendency
of people to report personally experiencing events even if they live many kilometers away and
did not suffer direct personal damages.
Our analysis of personal experiences with drought presents a contrast to the moderate- to
fast-onset hazards of tornadoes and hurricanes. Drought is particularly challenging for individuals to perceive because it is a slow-onset hazard with a long time horizon, broad spatial
extent and diverse set of conceptual and operational definitions. Indeed, only after 25 weeks of
severe drought do a majority of people consider themselves to have personally experienced the
drought.
Our findings are consistent with previous research showing that perceptions are consistent
with observations of phenomena such as seasonal temperature anomalies, average temperature
change, and seasonal rainfall patterns and timing (e.g. Marin 2010; Hartter et al. 2012; Howe
et al. 2013; Howe and Leiserowitz 2013). The correlation of proximity with personal experience is consistent with a study of perceptions of local extreme temperatures (Ruddell et al.
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2012), which found that perceptions were related to local rather than distant environmental
factors.
These findings have important implications for disaster preparedness efforts and efforts to
educate people about climate change in the context of extreme weather events. By mapping the
shadows of experience of extreme weather, we highlight where disaster preparedness and climate
education efforts could be the most effective after an event, since people who did not previously
accept the reality of climate change sometimes change their minds when they are personally
affected by extreme events (Rudman et al. 2013). TV weathercasters, for example, can provide
important climate change context for extreme weather events; many are interested in doing so
(Maibach et al. 2011), and when they do, their viewers learn important climate information (Zhao
et al. 2014). For slow-onset events like drought, communication efforts may need to focus on
encouraging public recognition of the phenomenon as well as preparedness behaviors.
We note that our data are limited to retrospective assessments of personal experiences over
one year for several extreme weather events, and our findings depict only a rough map of the
shadow of experience for these extreme weather events (Stone 2001). We used a simplified
yes/no measure of personal experience, and future research should address the different ways
in which people may experience extreme events. For example, the effect of proximity on
personal experience may be due to a combination of different types of experience such
environmental cues, social cues, indirect experience via social networks and media coverage,
affective responses, and direct impacts. Future research should also investigate the contours of
these shadows of experience in more detail, analyze their durability over time, explore how
they aggregate across multiple events, and examine different types of hazards with different
spatial and temporal characteristics to better understand the mechanisms that convert any one
event into a memorable experience that shapes subsequent perceptions and behavior.
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