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Transcript of Disaster Research Center Jenniffer Santos-Hernández Disaster Research Center University of Delaware...
Disaster Research Center
Jenniffer Santos-Hernández Disaster Research Center
University of Delaware
Developing Informed Radar Technology: The social dimensions of risk communication
This work was supported by the Engineering Research Centers (ERC) Program of the National Science Foundation under NSF Cooperative Agreement No. EEC-0313747. Any opinions, findings and conclusions, or recommendations expressed in this material are
those of the authors and do not necessarily reflect those of the National Science Foundation.
The CASA Project
Inter-disciplinary, Multi-institution research effort
ERC Director: Dr. David McLaughlin, UMASS, Amherst
Director of Industry, Government, and End User Partnerships: Brenda Phillips
Senior Social Science Faculty: Havidán Rodríguez and Walter Díaz
Other faculty associated to the DRC-CASA project: William Donner and Joseph Trainor
DRC-CASA Graduate students: Jenniffer M. Santos-Hernández
DRC-CASA Undergraduate students: Claudia Flores, Paige Mikstas, Yesenia Rodríguez, Spencer Schargorodski, Kathleen Shea, Stephen Shinn, Jasmine Wynn
Social Scientists in CASA
How improved forecasting can reduce the exposure and vulnerability of individuals and property to every-day and extreme weather events?
What factors inform weather related decisions at different levels?
How are warnings communicated to the general population?
Under what conditions are these warnings interpreted correctly?
Through the use of field research, focus groups, in-depth interviews, and surveys, we are examining how the end-user community, particularly emergency managers and the general public, access, interpret, utilize, and respond to weather forecasts
Use of both qualitative and quantitative approaches
Research Efforts Survey of emergency managers’ access and use of weather
information In-depth interviews with emergency managers, weather
forecasters, and other emergency management related personnel to understand the processes by which emergency managers acquire, manage, and use weather information (Oklahoma and Puerto Rico)
Quick-response research after Hurricane Katrina Quick-response research after tornado warnings Phone Survey on response to tornado warnings Social Vulnerability Index for Puerto Rico Online GIS integrated platform – Disaster Decision Support
Tool Evaluation of the implementation of FEMAs CERT program
in Puerto Rico
Objectives – Public Response Phone Survey
Explore and describe public response and the household decision making process following a severe weather warning or a hazard event
Using Computer Assisted Telephone Interviewing (CATI), explore the public’s response to severe weather warning/events in communities in Oklahoma, Kansas, Minnesota, Illinois, Mississippi, Tennessee and Alabama in 2008 and 2009.
Develop quantitative and predictive models, which are based on initial extensive qualitative research with emergency managers and the general public following severe weather events
DRC-CATIDeployment
Grounded Approach: Qualitative – Quantitative Quick Response – Phone Surveys. Two-Step Sampling Process
County Selection Criteria
Demographic and Socio-Economic Characteristics
RaceIncome
EducationAge
Event Characteristics
NWS ProductMagnitudeDamage
Media Coverage
Event Characteristics
NWS ProductMagnitudeDamage
Media Coverage
Inside of Test Bed Scenarios
- Severe Weather- Tornados
- Event with Watch/Warning
- Event NO Watch/Warning- False Alarm
Outside of Test Bed Scenarios
- Tornadoes- Event with Warning- Event NO Warning
Methodology
Questionnaire
127 questions in total yielding about 429 variables:
• Damage to home, business, or other property • Shelter availability and preferences• Social Vulnerability• Social Networks• Insurance coverage • Effectiveness of Siren Systems• Behavioral outcomes of lead time • Social and environmental cues• Protection of possessions and pets• Reception of warnings and watches• Understanding of warnings and watches• Questions on false alarms • Geographic warning specificity• Past experience with other disasters
Methodology
GENESYS Sampling Systems: Genesys provided samples based on DRC sampling requests in the impacted areas
Over 600 interviews completed in counties in Oklahoma, Minnesota, Kansas, Illinois, Mississippi, Tennessee and Alabama.
Average duration of interviews: 35 minutes Calls were made 1-3 weeks after event
Demographic Characteristics
Male Female Refused0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
30.50%
69.00%
0.50%
Gender
Demographic Characteristics
81.00%
10.50%
1.00%
3.00%2.00%
2.50%
Racial Composition
WhiteBlackPacificAmerican IndianOtherRefused
Demographic Characteristics
18-24
25-34
35-44
45-54
55-64
65 and u
p0%
5%
10%
15%
20%
25%
30%
35%
40%
3%7%
10%
21%25%
35%
Age
Demographic Characteristics
Less
than $24,9
99
$25,000 to
$49,999
$50,000 to
$74,999
$75,000 to
$99,999
$100,000 to
$149,999
More th
an $150,000
0%
5%
10%
15%
20%
25%
30%
19%
25%23%
12%14%
7%
Annual Income
Were you aware that a tornado or severe storm had been observed in the surrounding area before it got to your town?
Yes84%
No 12%
Don’t know3%
Did you receive a warning or notification of a tornado or severe storm in your region?
No Yes Don’t Know0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
9.30%
85.85%
4.85%
NoYesDon’t Know
From whom did you receive this information?
53.8%
42.3%
Parents
Siblings
Friends
Neighbors
Fire Department
Emergency Manager
Hospital
Mass Media
Other: Siren
11% 4%
5%
40%
25%
6%
2%
2% 5%
After receiving the warning or notification, what did you do?
Sought more informationLooked outside a windowContinued what they were doingTook shelterProtective ActionsProtected private goodsProtected petCalled othersOther
When you first found out a tornado or severe storm was present inside or near your town or city, about
how many minutes did it take before it hit your neighborhood? (Average = 27.9 minutes)
0_5 6_10 11_15 16_20 21_25 26_30 36+0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
9.6%
22.9%
10.8%
14.5%
1.2%
20.5% 20.5%
Did the tornado sirens in your community go off?
Yes No There are no sirens
Don’t know0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%72.80%
13.60%9.40%
4.20%
Did you look outside to verify whether the tornado or severe storm was coming?
Yes No0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
66.90%
33.10%
Did you receive information from the Internet during the last 30 minutes before the tornado or severe storm arrived?
Yes No Don’t know0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
14%
85%
1%
Series1
Why did you not receive information from the internet?
8%8.9%
2.7%
57.1%
9.8%
3.6%8.1% 1.8%
Power OutageDo not have access to the Internet Already seeking shelterComputer offNo access to computerEnough Information
Did you receive information from television during the last 30 minutes before the tornado or severe storm arrived?
No Yes Don’t Know0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
16.10%
84.00%
0.90%
Did you take any actions to protect yourself, your family, or your property from the hazard event?
Yes No Don’t Know0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
58.60%
41.15%
0.25%
What information led you to seek shelter?
Personally saw tornado approaching
Saw tornado or storms approaching on TV
Somebody called me
NWS specific information about what action to take
Local TV gave specific information about what action to take
Radio gave specific information about what action to take
Sirens
Tornado warning
Other
Don’t Know
Refused
0.0% 10.0% 20.0% 30.0% 40.0% 50.0%
6.4%
12.4%
2.0%
3.2%
40.8%
11.6%
34.0%
6.0%
19.2%
0.8%
0.4%
70%
8%
3%4%
13% 2%
1 (Never)
2
3
4
5 (V. Frequently)
Don’t know
How often would you say you listen to a NOAA radio for information about
tornadoes or severe storms?
Tornado Watch & Warningand False Alarms
Respondents appear to have difficulty in understanding the differences between watches and warnings and what is a false alarm
Participants seem to understand that watches and warnings represent some type of danger, but they are unable to clearly differentiate between these two concepts
Watch Definition: Examples “I think the watch is the more dangerous one” “Same as a warning” “When the TV flashes yellow” “They put it up on the TV and tell you what
time it will be in your area and when to take shelter”
“They feel like there’s one [tornado] in our vicinity”
“A tornado is on the ground near your house” “Tornado was been sighted in my area” “Watch for the tornado coming to you”
Watch Definition
Agrees with NWS definition
47%
Disagrees: confuses watch with warning
13%
Dis-agrees:
Scientific terms13%
Disagrees with NWS definition
27%
Could you please describe what you think a tornado watch is?
Warning Definition
Agrees with NWS definitions
43%
Disagrees: confuses watch with warning
9%
Disagrees: Scientific terms
8%
Disagrees with NWS definitions
40%
Could you please describe what you think a tornado warning is?
False Alarm Definition
Agrees with NWS definition
13%
Common Use19%
Disagrees: Scientific
terms3%
Disagrees with NWS definition
65%
Could you please describe what a false alarm is?
In your opinion, how trustworthy are the weather forecasts provided in your region?
1 2 3 4 5 Don’t Know Refused0
50
100
150
200
250
Not Trustworthy Very Trustworthy
Next StepsContinue CATI Survey; expand sample
size and geographic areas
Develop predictive models on protective action:Binary logistic model to predict protective action
following severe weather warning or a hazard event
Estimate the probability that the dependent variable will assume a certain value (e.g., take protective action or not) based on a number of independent variables
Canon (1994) asserts that technology is not socially neutral and that we must have an understanding of the context in which it is implemented.
Technology matters, but what really matters is the application of the substantive knowledge that we generate regarding how individuals respond (or not) to severe weather events and how can we improve their response in order to minimize the devastating impacts associated with these events.
Technology and the social dimensions of risk communication