Data · dataset · 2026
Collecting longitudinal, perishable social science observations during hurricanes
Listed in National Center for Atmospheric Research
A hurricane is highly dynamic, evolving over minutes, hours, and days.
Description
It can change in intensity, track, and translational speed, all of which can change the hazards from wind, tornado, storm surge, and inland flooding. A sophisticated meteorological observation network exists to observe hurricanes over time, to monitor, understand, and forecast their evolution.
It is reasonable to think that people also are dynamic, evolving in response to evolving hurricane risks. Yet, very little is known about how people perceive and respond to hurricane risks over time because developing such knowledge requires collecting social science observational data repeatedly from the same set of individuals in real time during a real-world hurricane event. We describe the methodology we developed and implemented to collect such longitudinal, perishable social science observations for three hurricane events: Laura and Marco in 2020, Henri in 2021, and Ian in 2022.
Read the rest (2 more)
With these data, we examined whether, when, and how people’s amount of forecast information obtained and risk perceptions changed during each of these events. A key finding is that people were dynamic, updating their perceptions and behaviors over time as the hurricanes evolved rather than anchoring on early knowledge and assessments. Moreover, the ways people were dynamic varied based on their predicted exposure to different hurricane hazards and across the hurricane events.
Based on the novel insights this research yields, we advocate scaling and expanding this methodology to collect such data for additional hurricanes and for different high-impact and extreme weather hazards.
Links
Get the data
- Publisher page n2t.net/ark:/85065/d73f4v1v ↗
documentation · download · from data ucar edu
Where it is published
- data.ucar.edu /dataset/collecting-longitudinal-perishable-social-science-obse… ↗
National Center for Atmospheric Research dataset page
landing page · from data ucar edu
Catalogue records · 1
- CKAN API data.ucar.edu/api/3/action/package_show?id=073df2f4-fe31-48bd-a007-3c7206884… ↗
metadata API · from data ucar edu
Topics
- From keywords
- Earth & Environmental Science · Ocean & Atmospheric Science
- Inferred from text
- Longitudinal study 65%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| National Center for Atmospheric Research | 073df2f4-fe31-48bd-a007-3c720688424d | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| concepts[method].local:method:longitudinal-study | enrichment · data ucar edu | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| description | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /notes |
| publication_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 | |
| title | source · data ucar edu | connector:data_ucar_edu@1.0.0 | /title |
| updated_date | source · data ucar edu | connector:data_ucar_edu@1.0.0 |