The cry wolf effect and weather-related decision making.

Area of Science:

• Meteorology
• Decision Science
• Human-Computer Interaction

Background:

• Public noncompliance with extreme weather warnings persists despite forecasting advancements.
• Past experiences with false alarms may significantly influence public trust and adherence to weather warnings.

Purpose of the Study:

• To investigate the impact of false alarm rates in weather warnings on public decision-making.
• To evaluate the effectiveness of probabilistic uncertainty estimates in improving compliance with weather warnings.

Main Methods:

• Participants made decisions on road treatment based on overnight low-temperature forecasts and a decision aid over multiple trials.
• The rate of false alarms from the decision aid was manipulated across different participant groups.
• Probabilistic uncertainty estimates were introduced to assess their effect on decision quality and compliance.

Main Results:

• Both very high and very low false alarm rates led to poorer decision-making.
• Slightly reducing the false alarm rate did not significantly improve compliance or decision quality.
• Incorporating probabilistic uncertainty estimates in forecasts enhanced both compliance and decision quality.

Conclusions:

• The frequency of false alarms critically impacts the effectiveness of weather warnings.
• Communicating forecast uncertainty is a more effective strategy than solely focusing on reducing false alarms to improve public response to weather warnings.