1. Societal Aspects of the 2008 Super Tuesday Tornado Outbreak Kevin Barjenbruch * and Julie Demuth ** *NWS Salt Lake City WFO **NCAR Societal Impacts Program Kevin Barjenbruch * and Julie Demuth ** *NWS Salt Lake City WFO **NCAR Societal Impacts Program IWT Workshop: Using the WAS*IS Approach January 22, 2009 IWT Workshop: Using the WAS*IS Approach January 22, 2009

2. Conducted to evaluate NWS performance during significant (high-impact) events Usually convened just once or twice a year Team composition: experts from both inside and outside the National Weather Service NWS service assessments…then

3. THEN: Inward focus on procedures, actions, equipment – Internal review of operations in National Centers, WFOs, CWSUs, RFCs – Informal external review of information with partners – Quantitative assessment Damage, verification, fatalities, injuries, etc.

4. NWS service assessments…now NOW: Inclusion of external focus via societal impacts analyses – Super Tuesday, Mother’s Day, Midwest floods – Qualitative assessment Information sources, perceptions, decision-making

5. Desired outcomes of NWS SAs Use findings, recommendations, best practices to: – Improve delivery of hazard information (format, content, media) to our customers and partners – Improve clarity of hazard information – Focus research and training – Allocate resources Provide better and more understandable weather information so that people will take action to protect life and property!

6. Impacts of the tornado outbreak 87 tornadoes – 5 EF-4 tornadoes – 1 tornado had a 122-mile long path 57 fatalities – most since May 31, 1985 – 13 th overall 350+ injuries $520M damage

7. February 5-6, 2008, tornado outbreak National Weather Service (NWS) predictions – Excellent long lead-time info: First outlook issued 6 days prior Day before, outlook mentioned “potentially strong and long- track tornadoes” – Mixed quality short lead-time info: Mean official tornado warning lead time of 18 minutes Some problems with timely downstream warnings Uncertainty wording for confirmed tornadoes 18 min 1 min T

8. Ubiquitous questions This was a well-warned event, with good information… – … why did so many people die? – … why don’t people do what they’re “supposed” to do … to make the “right” decision? We get frustrated when we put “good” weather information out there and people don’t make the “right” decisions!

9. The “right” decision … in a tornado Why might someone not take shelter from a tornado?. What is the “right” decision? Is there a “right” decision? How and why do decisions get made? What is the “right” decision? Is there a “right” decision? How and why do decisions get made?

10. Bottom line … if you want to study human beings, you’d better have a high tolerance for ambiguity!

11. Societal impacts scope The task – To try to understand why so many people died and the details of those fatalities. Can learn so much by having people walk you through their knowledge, thoughts, actions … by letting them tell you their stories!. Can learn so much by having people walk you through their knowledge, thoughts, actions … by letting them tell you their stories! An opportunity – To gather empirical information about people’s actual warning response behaviors

12. Research objectives For the fatalities, wanted to gather info about: – Age, gender, warning received, warning source, warning heeded, shelter sought, structure where they died, availability of safer shelter For the survivors, wanted to assess: – what info people had, how they interpreted it (knowledge) – how people perceived the situation (perceptions) – what decisions people made (decision-making) – what information they had about the fatalities This is a highly interdependent, iterative process

13. Methodology Semi-structured interviews with the public Targeted, convenience, and snowball sampling 41 interviews by 3 sub-teams in the 6 WFOs visited – We did 17 public interviews over 4 days in the field, another day on the phone Audio recorded with consent

14. Some of the questions When did you first realize there was a threat of a tornado? – How did you learn about the threat? (sources, environmental cues) – What were you thinking after you received that information? (trust? confusion? uncertainty? barriers to action?) – What did you do next? (confirmation?) Have you ever been in a similar type of extreme-weather situation in the past? (experience, false alarms) – Did anything from that experience influence what you did during this most recent event? – Have you ever been warned about an extreme weather event in the past that did not occur? Think back over the entire tornado event, from the time you learned there was a tornado threat through when the tornado actually occurred. – Do you feel that any of the information you received was unclear? – Is there any other information you would have liked to have had?

15. Data analysis Analyzed iteratively, cooperatively by 2 coders Coded with Excel – Pre-determined categories – Categories created inductively during analysis Caveats and considerations!! – Balance between scientific rigor and rapid operational needs – First step, hopefully leading to more related work in the future (more in-depth studies, various weather contexts, etc.)

16. Findings − knowledge People get information from multiple sources – Majority via television – Also commonly from other people (family, friends, neighbors, co-workers) People get information multiple times NOAA Weather Radio was used, but not common Tornado sirens are useful, but… – Misconceptions about sirens as a warning device Local EMs confirmed this is a problem; one is actively trying to correct this via newspaper and radio – Misconceptions about what sirens mean

17. Findings − perception Integration of seasonality, weather salience, situational awareness about the event – Majority of people associate tornado outbreaks as occurring in March or later… – … so many minimized threat because they perceived it as being outside “traditional” tornado season – … BUT, for many people, situational factors (e.g., unusually warm temps) heightened their awareness

18. Findings − perception (cont) Personalization of the threat – People often seek confirmation of the threat; a single source of info will not necessary spur protective action E.g., Atkins, AR, woman and couple – Many people recognize a risk exists, but believe that their personal risk is less or that they aren’t at risk at all (optimism bias) E.g., Hardin County, TN, family; Arkansas family

19. Findings − decision making NOT a singular event Happens numerous times throughout the warning process Implicit part of people’s gathering and interpreting weather information to evaluate their risk

20. Findings − sheltering Sheltering definitions – Safer = safer relative to one’s current location (e.g., frame home is “safer” than mobile home) – Safest = a basement, storm cellar, or safe room Decision to shelter – Vast majority of people who received warning heeded it and sought shelter in best location available to them … – … but less than half of people had a “safest” shelter available – Very few people who received a warning opted not to shelter

21. Findings − 57 fatalities Collected as much good data as we could Nearly 2/3 of victims were in mobile homes – 15 in houses, 4 in warehouse, 1 in vehicle, 1 unknown Warning and sheltering info for victims – Of the 18 people we had warning info about 11 people heeded the warning, 3 did not, unknown for 4 10 people sought shelter, 5 did not, unknown for 3 – … but most did not have an safest sheltering option 8 people did, 34 did not, unknown for 15 – … and many did not have a safer sheltering option 17 did, 21 did not, unknown for 19

22. Opportunities – National Scope Establish a ‘pool’ of societal impacts experts – Communication, sociologists, anthropologists, economists, GIS specialists, etc. Develop a common set of societal impacts survey questions, tailored as appropriate NWS should consider adding a Societal Impacts Program to operational branches of NWSH and Regions, to organize and focus these efforts

23. Opportunities – Regional/WFO Scale Gather impacts/socio-demographic data for local events Utilize academic community for research initiatives – Resource for survey methods, questions, analyses – Utilize COMET grants, NSTEP process Build partnerships! This workshop is a great first-step!

24. Broader lessons learned Value of having some exposure to quantitative and qualitative research Emergency managers are invaluable Partnerships among social scientists, research meteorologists, operational meteorologists, broadcasters, emergency managers and other practitioners, policy makers, etc. – Building this community! – Interest and willingness to work together, to listen, learn, exchange ideas!

25. Discussion questions Would more definitive wording (call to action statements) in warnings & statements may prompt better protective response? Should we continue with the watch / warning / advisory methodology? Should mandatory protective action be taken at longer lead times (e.g., evacuating mobile home parks, dismissing classes, large-venue considerations)? Should local, state, and federal governments partner (legislate?) to build local shelter facilities?

26. Acknowledgements Super Tuesday service assessment team members – Especially Mike Vescio, Daniel Nietfeld NWS NCAR Societal Impacts Program and WAS*IS Contact – Kevin Barjenbruch (kevin.barjenbruch@noaa.gov) – Julie Demuth (jdemuth@ucar.edu) www.sip.ucar.edu