Visualizing Uncertainty in Hurricane Forecasts with Animated Risk Trajectories

IF 1.9 4区 地球科学 Q3 ENVIRONMENTAL STUDIES
J. Witt, Z. Labe, Amelia C Warden, Benjamin A. Clegg
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Abstract

Hurricane forecasts are often communicated through visualizations depicting the possible future track of the storm. The Cone of Uncertainty (COU) is a commonly used visualization, but the graphic is prone to misinterpretation such as thinking only locations contained within the cone’s boundary are at risk. In this study, we investigated the utility of conveying hurricane forecast tracks using a set of animated icons, each representing an instance of a possible storm path. We refer to this new visualization as Animated Risk Trajectories (ARTs). We measured non-experts’ perception of risk when viewing simplified, hypothetical hurricane forecasts presented as ARTs or COUs. To measure perception of risk for each visualization type, we designed experiments to have participants make decisions to evacuate individual towns at varying distances from the most likely forecast path of a storm. The ARTs led to greater risk perception in areas that fell beyond the cone’s boundaries. Non-experts’ interpretation of risk was impacted by the visual properties of the ARTs, such as the distribution of the icons, including their density and whether the distribution was unimodal or bimodal. This supports the suggestion that ARTs can have value in communicating spatial-temporal uncertainty.
用动画风险轨迹可视化飓风预报中的不确定性
飓风预报通常通过描绘风暴未来可能轨迹的可视化来传达。不确定性圆锥体(COU)是一种常用的可视化方法,但图形很容易被误解,例如认为只有圆锥体边界内的位置才有风险。在这项研究中,我们研究了使用一组动画图标传达飓风预报轨迹的效用,每个图标都代表一个可能的风暴路径实例。我们将这种新的可视化称为动画风险轨迹(ARTs)。我们在查看以ARTs或COU表示的简化假设飓风预报时,测量了非专家对风险的感知。为了测量每种可视化类型的风险感知,我们设计了实验,让参与者决定疏散距离最有可能预测的风暴路径不同距离的各个城镇。ARTs在锥体边界以外的区域导致了更大的风险感知。非专家对风险的解释受到ART的视觉特性的影响,例如图标的分布,包括其密度,以及分布是单峰还是双峰。这支持了ARTs在传达时空不确定性方面具有价值的说法。
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来源期刊
Weather Climate and Society
Weather Climate and Society METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
3.40
自引率
13.60%
发文量
95
审稿时长
>12 weeks
期刊介绍: Weather, Climate, and Society (WCAS) publishes research that encompasses economics, policy analysis, political science, history, and institutional, social, and behavioral scholarship relating to weather and climate, including climate change. Contributions must include original social science research, evidence-based analysis, and relevance to the interactions of weather and climate with society.
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