Non-expert interpretations of hurricane forecast uncertainty visualizations

Ruginski, Ian T.; Boone, Alexander P.; Padilla, Lace; Le, Liu; Heydari, Nahal; Kramer, Heidi; Hegarty, Mary; Thompson, William B.; House, Donald H.; Creem-Regehr, Sarah H.

doi:10.1080/13875868.2015.1137577

Cited by 111 publications

(147 citation statements)

References 23 publications

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“…The amount of uncertainty inferred was equal between the fan plot and worded probability at 50%. This result suggests that, similar to previous literature with more familiar natural‐hazard forecasts (e.g., tornado, temperature, hurricane; Ash et al ., ; Ruginski et al ., ; Tak et al ., ), interpretations of forecast information can be different when given different forecast representations for an unfamiliar hazard. Interpreting uncertainty differently depending on differing forecast representations could be problematic in real‐life decision‐making situations; for example, increasing coastal protection as an adaption to sea‐level rise.…”

Section: Discussionmentioning

confidence: 99%

Designing environmental uncertainty information for experts and non‐experts: Does data presentation affect users’ decisions and interpretations?

Mulder

Lickiss

Black

et al. 2019

Meteorological Applications

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Uncertainty information in natural hazard forecasts is increasingly being communicated explicitly. This study was designed to determine whether different ways of communicating uncertainty graphically affects the decisions and interpretations of forecasts and if expertise was a factor in the decisions and interpretations from forecasts explicitly showing uncertainty. In a hypothetical decision‐making task regarding ice thickness and shipping, 138 experts and non‐experts received ice‐thickness forecasts in four different presentations expressing uncertainty: worded probability, spaghetti plot, fan plot and box plot. These forecasts contained no measures of central tendency. There was no consistent difference in decision or best‐guess forecast (deterministic ice thickness forecast based on the forecast representation) between the different forecast representations. However, participants interpreted different amounts of uncertainty across the different forecast representations. Experts made significantly more economically rational decisions than non‐experts, interpreted lower best‐guess forecasts and inferred significantly more uncertainty than non‐experts. These results suggest that care be taken in choosing how uncertainty is represented in forecasts, especially between expert and non‐expert audiences.

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Section: Discussionmentioning

confidence: 99%

Designing environmental uncertainty information for experts and non‐experts: Does data presentation affect users’ decisions and interpretations?

Mulder

Lickiss

Black

et al. 2019

Meteorological Applications

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show abstract

“…Further complicating storm preparation decisions is the challenge of visually communicating probabilistic storm information [34,35]. Images such as the "cone of uncertainty," used by the National Hurricane Center, attempt to communicate a range of paths the storm might take; there is a 2/3 chance that the eye of the hurricane will fall within the cone [36].…”

Section: Objective Versus Subjective Probability Estimatesmentioning

confidence: 99%

Decision Science Perspectives on Hurricane Vulnerability: Evidence from the 2010–2012 Atlantic Hurricane Seasons

et al. 2018

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Abstract:Although the field has seen great advances in hurricane prediction and response, the economic toll from hurricanes on U.S. communities continues to rise. We present data from Hurricanes Earl (2010), Irene (2011), Isaac (2012), and Sandy (2012 to show that individual and household decisions contribute to this vulnerability. From phone surveys of residents in communities threatened by impending hurricanes, we identify five decision biases or obstacles that interfere with residents' ability to protect themselves and minimize property damage: (1) temporal and spatial myopia, (2) poor mental models of storm risk, (3) gaps between objective and subjective probability estimates, (4) prior storm experience, and (5) social factors. We then discuss ways to encourage better decision making and reduce the economic and emotional impacts of hurricanes, using tools such as decision defaults (requiring residents to opt out of precautions rather than opt in) and tailoring internet-based forecast information so that it is local, specific, and emphasizes impacts rather than probability.

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“…Ruginski et al . found that the wider cone demarcating the future path of tropical cyclones may induce a sharp gradient of perceived risk such that those inside the cone react more strongly than those just outside the forecast cone . Additionally, the wider cone may give the (potentially) false impression that a tropical cyclone is expected to increase in size over time .…”

Section: Literature Reviewmentioning

confidence: 99%

Tornado Warning Perception and Response: Integrating the Roles of Visual Design, Demographics, and Hazard Experience

Schumann

Ash

Bowser³

2017

Risk Analysis

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Recent advancements in severe weather detection and warning dissemination technologies have reduced, but not eliminated, large-casualty tornado hazards in the United States. Research on warning cognition and behavioral response by the public has the potential to further reduce tornado-related deaths and injuries; however, less research has been conducted in this area compared to tornado research in the physical sciences. Extant research in this vein tends to bifurcate. One branch of studies derives from classic risk perception, which investigates cognitive, affective, and sociocultural factors in relation to concern and preparation for uncertain risks. Another branch focuses on psychological, social, and cultural factors implicated in warning response for rapid onset hazards, with attention paid to previous experience and message design. Few studies link risk perceptions with cognition and response as elicited by specific examples of warnings. The present study unites risk perception, cognition, and response approaches by testing the contributions of hypothesized warning response drivers in one set of path models. Warning response is approximated by perceived fear and intended protective action as reported by survey respondents when exposed to hypothetical tornado warning scenarios. This study considers the roles of hazard knowledge acquisition, information-seeking behaviors, previous experience, and sociodemographic factors while controlling for the effects of the visual warning graphic. Findings from the study indicate the primacy of a user's visual interpretation of a warning graphic in shaping tornado warning response. Results also suggest that information-seeking habits, previous tornado experience, and local disaster culture play strong influencing roles in warning response.

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Non-expert interpretations of hurricane forecast uncertainty visualizations

Cited by 111 publications

References 23 publications

Designing environmental uncertainty information for experts and non‐experts: Does data presentation affect users’ decisions and interpretations?

Designing environmental uncertainty information for experts and non‐experts: Does data presentation affect users’ decisions and interpretations?

Decision Science Perspectives on Hurricane Vulnerability: Evidence from the 2010–2012 Atlantic Hurricane Seasons

Tornado Warning Perception and Response: Integrating the Roles of Visual Design, Demographics, and Hazard Experience

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