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The effect of likelihood and impact information on public response to severe weather warnings

2023Journal article Open access
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dc.contributor.authorTaylor, Andrea
dc.contributor.authorSummers, Barbara
dc.contributor.authorDomingos, Samuel
dc.contributor.authorGarrett, Natalie
dc.contributor.authorYeomans, Sophie
dc.date.accessioned2024-04-23T17:48:19Z
dc.date.available2024-04-23T17:48:19Z
dc.date.issued2023
dc.description.abstractMeteorological services are increasingly moving away from issuing weather warnings based on the exceedance of meteorological thresholds (e.g., windspeed), toward risk-based (or “impact-based”) approaches. The UK Met Office’s National Severe Weather Warning Service has been a pioneer of this approach, issuing yellow, amber, and red warnings based on an integrated evaluation of information about the likelihood of occurrence and potential impact severity. However, although this approach is inherently probabilistic, probabilistic information does not currently accompany public weather warning communications. In this study, we explored whether providing information about the likelihood and impact severity of forecast weather affected subjective judgments of likelihood, severity, concern, trust in forecast, and intention to take protective action. In a mixed-factorial online experiment, 550 UK residents from 2 regions with different weather profiles were randomly assigned to 1 of 3 Warning Format conditions (Color-only, Text, Risk Matrix) and presented with 3 warnings: high-probability/moderate-impact (amber HPMI); low-probability/high-impact (amber); high-probability/high-impact (red). Amongst those presented with information about probability and impact severity, red high-likelihood/high-impact warnings elicited the strongest ratings on all dependent variables, followed by amber HPMI warnings. Amber low-likelihood/high-impact warnings elicited the lowest perceived likelihood, severity, concern, trust, and intention to take protective responses. Taken together, this indicates that UK residents are sensitive to probabilistic information for amber warnings, and that communicating that severe events are unlikely to occur reduces perceived risk, trust in the warning, and behavioral intention, even though potential impacts could be severe. We discuss the practical implications of this for weather warning communication.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTaylor, A., Summers, B., Domingos, S., Garrett, N., & Yeomans, S. (2023). The effect of likelihood and impact information on public response to severe weather warnings. Risk Analysis: An International Journal, 1. https://doi.org/10.1111/risa.14222pt_PT
dc.identifier.doi10.1111/risa.14222pt_PT
dc.identifier.issn15396924
dc.identifier.urihttp://hdl.handle.net/10400.12/9740
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWiley-Blackwell Publishing Ltdpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectImpact based forecastspt_PT
dc.subjectRisk communicationpt_PT
dc.subjectRisk perceptionpt_PT
dc.subjectWeather riskpt_PT
dc.subjectWeather warningspt_PT
dc.titleThe effect of likelihood and impact information on public response to severe weather warningspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceUnited Kingdompt_PT
oaire.citation.endPage1253pt_PT
oaire.citation.issue5pt_PT
oaire.citation.startPage1237pt_PT
oaire.citation.titleRisk Analysispt_PT
oaire.citation.volume44pt_PT
person.familyNameTaylor
person.familyNameSummers
person.familyNameDomingos
person.givenNameAndrea
person.givenNameBarbara
person.givenNameSamuel
person.identifier.orcid0000-0002-8949-1234
person.identifier.orcid0000-0002-9294-0088
person.identifier.orcid0009-0004-0822-7573
person.identifier.scopus-author-id56197299000
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationcd28d93c-26ae-4be1-803c-942cd3f8f842
relation.isAuthorOfPublication68470f76-e370-4918-958b-104902387295
relation.isAuthorOfPublication90f4e6ca-9344-4cf5-a40c-6be43a65f3a8
relation.isAuthorOfPublication.latestForDiscovery68470f76-e370-4918-958b-104902387295

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