DRMS: Improving Public Response to Weather Warnings

尽管天气预报的及时性和准确性都有所提高，但与天气有关的伤亡仍然是一个严重问题。越来越多的人认为，至少部分问题在于公众对警告本身的不信任。这个项目调查了与公众对天气预警的不信任有关的三个心理问题。第一个与不一致性有关。高影响天气事件的预报通常会提前几天发布，以便居民有时间做好准备。对同一事件的后续预测可能与先前的预测不同，给人不一致的印象。预测者倾向于假设人们不相信不一致的预测，即使有更好的信息可用，也不愿意改变预测，宁愿牺牲准确性来保持一致性。该项目测试不一致或不准确是否对信任更有害。由于预报员担心承认不确定性是无能的信号，恶劣天气事件通常被描述为确定的，这也可能产生不信任。然而，大多数人都明白天气预报有一定程度的不确定性。因此，太多的确定性似乎是不可信的。该项目测试添加不确定性估计（例如，在您所在位置发生龙卷风的概率）是否会增加或降低对警告的信任和遵从性。最后，对预警预报的不信任可能会导致为了收集更多信息而推迟采取预防行动。如果人们等待太久，他们可能没有足够的时间在恶劣天气到来之前充分保护自己。该项目将确定在天气警报中包含的适当信息，以激发信任，使人们能够及时做出决定。因此，该项目的结果将影响预报通信实践，为人们提供更好、更可靠的信息，以制定关键的天气相关决策，最终挽救生命。只有公众信任并采取相应行动，准确的天气预警才能发挥其价值。这项研究将为预警沟通程序中的“最佳实践”提供信息，以促进对预测和及时反应的信任。因此，这项工作的结果很可能改善对警告的遵守并挽救生命。研究小组在实验研究中调查了这些问题，使用现实天气相关的决策任务。在受控的实验室环境中建立对信任和决策的假设影响将允许测试预测沟通方法来解决它们。特别令人感兴趣的是包含了具体的不确定性估计。传达预测是概率性的概念可以减少不一致和不准确的影响。不确定性估计也可以通过满足对附加信息的需要来减弱超过最佳停止的延迟。然而，在动态的、时间紧迫的情况下，可能性沟通可能需要简化，因此颜色编码的风险等级也将被测试。因此，这些实验将比较相同的情况，即人们收到概率预测、颜色代码或传统警告，以确定哪种方法会带来更大的信任和更好的决策。总而言之，目标是通过仔细的实验程序，直接比较一种情况和另一种情况，以及一种交流形式和另一种交流形式，并保持所有其他因素不变，以得出关于其影响的确定结论，从而找出一系列具体但关键问题的答案。这是一种认知实验方法，迄今为止主要是用其他社会科学工具来解决的问题。这项工作将通过提供对复杂和动态预测的解释、信任和行动所涉及的认知过程的独特理论理解，在不同领域产生影响，从而使科学界受益。

Despite improvements in weather forecasts both in terms of timeliness and accuracy, weather-related injury and death remain a serious problem. There is growing consensus that at least part of the problem is public distrust in the warnings themselves. This project investigates three psychological issues related to public distrust in weather warnings. The first has to do with inconsistency. Forecasts for high-impact weather events are often made days in advance to allow residents time to prepare. Subsequent forecasts for the same event may differ from earlier forecasts, giving the impression of inconsistency. Forecasters tend to assume that people distrust inconsistent forecasts and are reluctant to change forecasts even when better information becomes available, preferring to sacrifice accuracy for consistency. This project tests whether inconsistency or inaccuracy is more injurious to trust. Distrust may also arise from the fact that severe weather events are usually presented as certain because forecasters worry that admitting uncertainty signals incompetence. Most people, however, understand that weather prediction involves some level of uncertainty. Therefore too much certainty may seem implausible. This project tests whether adding an uncertainty estimate (e.g. the probability of a tornedo at your location) increases or decreases trust and compliance with warnings. Finally, distrust in warning forecasts may lead to delaying precautionary action in order to gather more information. If people wait too long, they may not have enough time to adequately protect themselves before severe weather hits. This project will determine the appropriate information to include in weather warnings to inspire trust and allow people to make timely decisions. Thus, the results of this project will influence forecast communication practices to provide people with better and more trustworthy information upon which to base critical weather related decisions, ultimately saving lives. The value of accurate weather warnings with generous lead times will be realized only if the public trusts them and acts accordingly. This research will inform "best practices" in warning communication procedures to promote both trust in the forecast and timely responses. As such, results of this work may well improve compliance with warnings and save lives.The research team investigates these issues in experimental studies, using realistic weather-related decision tasks. Establishing the hypothesized effects on trust and decisions in a controlled laboratory environment will permit testing forecast communication methods to address them. Of particular interest is the inclusion of specific uncertainty estimates. Conveying the notion that the forecast was intended as probabilistic may reduce effects of both inconsistency and inaccuracy. Uncertainty estimates may also attenuate delay beyond optimal stopping by satisfying the need for additional information. Likelihood communication, however, may need to be simplified in dynamic, time pressured situations so color coded risk scales will also be tested. Thus, these experiments will compare identical situations in which people receive either probabilistic forecasts, color-codes or conventional warnings, to determine which method leads to greater trust and better decisions. In sum, the goal is to carve out answers to a set of specific but critical questions, using careful experimental procedures that make direct comparisons between one situation and another and one form of communication and another, holding all other factors constant to yield firm conclusions about their effects. It is a cognitive-experimental approach to what has heretofore been a problem tackled primarily with other social science tools. This work will benefit the scientific community at large by providing a unique theoretical understanding of the cognitive processes involved in interpreting, trusting and acting on complex and dynamic predictions, with implications in diverse domains.