Communicating Probability Information in Weather Forecasts: Findings and Recommendations from a Living Systematic Review of the Research Literature

Ripberger, Joseph T.; Bell, Andrew J.; Fox, Andrew S.; Forney, Aarika; Livingston, W.; Gaddie, Cassidy; Silva, Carol L.; Jenkins‐Smith, Hank C.

doi:10.1175/wcas-d-21-0034.1

Cited by 9 publications

(3 citation statements)

References 171 publications

(138 reference statements)

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“…This finding concludes that an objective measure like PoP can be subjectively interpreted (or misinterpreted), indicating that the vast efforts exploring the communication and interpretation of probabilistic information should continue (Ripberger et al, 2022), potentially even focusing on best practices for communicating probabilistic information on weather apps. Understanding interpretation by the public is vital to having appropriate messaging that avoids communicating inaccurate expectations.…”

Section: Discussionmentioning

confidence: 97%

That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps

Vaughn,

Sherman‐Morris,

Brown

et al. 2024

Meteorological Applications

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The usage of weather apps for forecast information has increased dramatically over the last 10–15 years. Ensuring that consumers value and trust weather apps is important to the integrity of weather forecasting. Public perception of weather app forecast accuracy and consistency undergirds the apps' value and trustworthiness. With app forecasts being interpreted solely by the app user, misunderstanding and consequent false expectations could jeopardize the public's perception of accuracy and consistency. Furthermore, weather apps often offer excessively—and potentially unrealistically—detailed forecasts on time and spatial scales, extending far into the future without sufficient disclaimers regarding the confidence level associated with such detailed forecasts. A survey of the public found perceived app accuracy and consistency to be positively correlated with the trust in an app. Participants indicated that they take at least modest consideration of uncertainty and spatial variability when assessing specific and longer range forecasts. On average, participants had low to moderate confidence in forecasts beyond 10 days, and a significant majority did not perceive a precipitation forecast as inaccurate, even when no rain occurred at their location, as long as it rained nearby. We tested for misinterpretation using a common expression of uncertainty in weather apps, namely probability of precipitation (PoP). A majority of participants made a correct interpretation of the two PoP values given, although, depending on the percentage, some misinterpreted the values as indicating precipitation intensity, totals, or duration. Overall, these findings offer encouragement for a society heavily reliant on weather apps while also encouraging more research on weather information interpretation.

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Section: Discussionmentioning

confidence: 97%

That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps

Vaughn,

Sherman‐Morris,

Brown

et al. 2024

Meteorological Applications

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show abstract

“…However, as these participants were only provided with the warning color for their region, this may be due to the absence of information on likelihood and severity. Nonetheless, other studies examining perceptions of likelihood and severity have found that when warned for events are more severe they tend to be perceived as more likely to occur (see Ripberger et al, 2022;Weber & Hilton, 1990).…”

Section: Probability and Judgments About Weather Riskmentioning

confidence: 99%

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

Taylor,

Summers,

Domingos

et al. 2023

Risk Analysis

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Meteorological 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.

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“…Finding ways to communicate uncertainty in different weather products has been a priority of the weather enterprise for over a decade [95][96][97][98][99]. The 3A and 4E approaches involve different kinds of uncertainty depending on present or future timeframes.…”

Section: Uncertaintymentioning

confidence: 99%

Digital Weather Information in an Embodied World

Stewart

Bolton

2023

Informatics

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We review the emergence of digital weather information, the history of human embodied knowing about weather, and two perspectives on cognition, one of which is symbolic (amodal, abstract, and arbitrary) and the other being embodied (embodied, extended, embedded, and enacted) to address the question: Beyond the general weather information they provide, to what extent can digital devices be used in an embodied way to extend a person’s pick-up of weather information? This is an interesting question to examine because human weather information and knowledge has a long past in our evolutionary history. Our human ancestors had to pick-up immediate information from the environment (including the weather) to survive. Digital weather information and knowing has a comparatively short past and a promising future. After reviewing these relevant topics, we concluded that, with the possible exception of weather radar apps, nothing currently exists in the form of digital products than can extend the immediate sensory reach of people to alert them about just-about-to-occur weather—at least not in the embodied forms of information. We believe that people who are weather salient (i.e., have a strong psychological attunement to the weather) may be in the best position going forward to integrate digital weather knowing with that which is embodied.

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Communicating Probability Information in Weather Forecasts: Findings and Recommendations from a Living Systematic Review of the Research Literature

Cited by 9 publications

References 171 publications

That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps

That's not what my app says: Perceptions of accuracy, consistency, and trust in weather apps

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

Digital Weather Information in an Embodied World

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