J. Witt, Z. Labe, Amelia C Warden, Benjamin A. Clegg
{"title":"用动画风险轨迹可视化飓风预报中的不确定性","authors":"J. Witt, Z. Labe, Amelia C Warden, Benjamin A. Clegg","doi":"10.1175/wcas-d-21-0173.1","DOIUrl":null,"url":null,"abstract":"\nHurricane 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.","PeriodicalId":48971,"journal":{"name":"Weather Climate and Society","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visualizing Uncertainty in Hurricane Forecasts with Animated Risk Trajectories\",\"authors\":\"J. Witt, Z. Labe, Amelia C Warden, Benjamin A. Clegg\",\"doi\":\"10.1175/wcas-d-21-0173.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nHurricane 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.\",\"PeriodicalId\":48971,\"journal\":{\"name\":\"Weather Climate and Society\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Weather Climate and Society\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1175/wcas-d-21-0173.1\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENVIRONMENTAL STUDIES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather Climate and Society","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/wcas-d-21-0173.1","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
Visualizing Uncertainty in Hurricane Forecasts with Animated Risk Trajectories
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.
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.