Collaborative Research: Communicating Hurricane Information to Local Officials for Protective Active Decision Making

在过去的30年里，飓风预报的许多方面都取得了重大进展，但关于沿海居民如何解读向他们传达的天气信息的系统研究很少。到目前为止，对飓风信息的大多数评估都包括反应标准(询问潜在用户是否喜欢显示器)，而不是学习(测试用户是否理解显示器)或性能(显示器是否改变用户？决定)标准。然而，越来越多的轶事证据表明，许多人误解了气象学家提供的显示。为了更好地了解人们如何解读飓风预报以及这些预报中的不确定性，这项研究将通过对现有的和新的飓风信息显示进行评估，系统地检查飓风跟踪所涉及的认知过程。第一个任务将评估用户如何解释风暴路径信息的三个基本元素--风暴的拖尾路径(风暴曾经在哪里)、预测路径(风暴最有可能去到哪里)和路径不确定性(它偏离预测路径的可能性有多大)。不同实验条件下的参与者将观察到由这三个基本要素描述的模拟飓风。一些参与者将只获得关于一个基本要素的信息(例如，仅提供预报轨迹)，其他参与者将获得有关两个基本要素组合的信息(例如，预测轨迹和不确定性锥体)，一些参与者将获得关于所有三个基本要素的信息。通过比较这些信息条件下的参与者，研究团队将能够深入了解这三个基本因素是如何影响人们的--S随着时间的推移对风暴路径的期望。第二项任务将集中在飓风轨迹信息的第三个基本元素(轨迹不确定性)上，通过比较传统的不确定性锥体和五种可选的轨迹不确定性显示-数字概率、颜色编码概率、地形编码概率、箭头字形和动态轨迹。比较这六种信息条件的数据将使我们能够确定是否有任何替代显示提供了传达轨迹不确定性的更好方式。最后，第三个任务将使用前两个任务的结果来设计和评估可视化风暴信息的新方法。这项拟议的研究将对飓风跟踪涉及的认知过程进行严格评估。因此，它对复杂动态任务的认知心理学(尤其是判断和决策)具有重要意义。此外，该项目将对教学产生影响，因为很少有研究解决培训成年人执行很少执行但关键的判断任务(如飓风跟踪)的问题。该项目将让气象学家更好地了解人们解读飓风预报的方式，以及这些预报中的不确定性。这种更好的理解将使他们能够更有效地与沿海人口沟通，并降低在偏离预报路径的飓风中丧生的可能性。

The past 30 years have seen major advances in many aspects of hurricane forecasting, but there has been little systematic research on the way coastal populations interpret the weather information that is communicated to them. To date, most evaluations of hurricane information have comprised reaction criteria (asking whether potential users like a display) rather than learning (testing whether users understand a display) or performance (whether a display changes users? decisions) criteria. However, there is a growing body of anecdotal evidence that many people misunderstand the displays meteorologists are providing. To better understand how people interpret hurricane forecasts and the uncertainties in those forecasts, this research will systematically examine the cognitive processes involved in hurricane tracking by conducting an evaluation of existing and novel hurricane information displays. The first task will assess the ways in which users interpret three basic elements of storm track information?the trailing track (where the storm has been), the forecast track (where it is most likely to go), and track uncertainty (how likely it is to deviate from the forecast track). Participants in different experimental conditions will observe simulated hurricanes described by these three basic elements. Some participants will be given information about only one basic element (e.g., forecast track only), others will be given information about two basic elements in combination (e.g., forecast track and uncertainty cone), and some will be given information about all three basic elements. By comparing participants in these information conditions, the research team will be able to gain insight into how each of the three basic elements affects people?s expectations about storm tracks over time. The second task will focus on the third basic element of hurricane track information (track uncertainty) by comparing a conventional uncertainty cone with five alternative track uncertainty displays?numeric probabilities, color-coded probabilities, terrain coded probabilities, arrow glyphs, and dynamic tracks. Comparing the data from these six information conditions will allow us to determine if any of the alternative displays provides a better way of conveying track uncertainty. Finally, the third task will use the findings from the first two tasks to design and evaluate new ways of visualizing storm information. The proposed research will provide a rigorous assessment of the cognitive processes involved in hurricane tracking. Accordingly, it has implications for the cognitive psychology (especially judgment and decision making) of complex dynamic tasks. In addition, the project will have implications for instruction because there is very little research that addresses the problems of training adults to perform rarely performed, but critical, judgment tasks such as hurricane tracking. The project will provide meteorologists with a better understanding of the ways in which people interpret hurricane forecasts and the uncertainties in those forecasts. This improved understanding will allow them to communicate more effectively with coastal populations and reduce the probability that lives will be lost in hurricanes that deviate from their forecast tracks.