Meteorological services are increasingly moving away from issuing weather warnings based on the exceedance of meteorological thresholds (e.g. windspeed), towards 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 likelihood of occurrence and potential impact severity. However, while 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 judgements of likelihood, severity, concern, trust in forecast and intention to take protective action. In a mixed-factorial online experiment 550 UK residents from two regions with different weather profiles were randomly assigned to 1 of 3 warning format conditions (Colour-only, Text, Risk Matrix), and presented with three warnings: high-probability/moderate-impact (amber HPMI); low-probability/high-impact (amber LPHI); high-probability/high-impact (red HPHI). 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 high-probability/moderate-impact 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 behavioural intention, even though potential impacts could be severe. We discuss the practical implications of this for weather warning communication.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)