DRU: A Multi-disciplinary Approach to Communicating Weather Forecast Uncertainty

除降水概率外，公众天气预报很少传达有关不确定性的信息，尽管这可能会改善与天气有关的决策，产生重要的经济和安全后果。国家研究委员会最近的一份报告发现，评估、传达和传播预报不确定性信息给最终用户是天气预报界迄今尚未解决的最大任务。这个项目的目的是通过一个由心理学家、大气科学家、统计学家和应用物理学家组成的多学科团队的努力来弥合这一差距。该项目将确定非专家用户在现实环境中理解和使用天气预报不确定性所涉及的心理过程。将进行研究，以确定提供信息的其他方法的影响，包括口头解释以及视觉图像和图表。这项研究的结果将被应用于制作一个史无前例的天气预报网站原型，向公众呈现完全概率的预报。它将给出温度、降水和风速的不确定预测。它还将为极端事件提供警告信息，如大风、极端温度和极端降雨量。尽管这种警告具有重要的安全影响，但致力于产生或传播这种信息的方法的研究很少。这将需要开发创新的方法来分析和显示极端事件的概率信息。该项目还将开发和提供图表，将过去的概率预报与观测值进行比较，向用户证明，虽然观测值可能并不总是与单值预报相匹配，但它们往往在概率范围内。这一功能将增强对预测的概率性质的理解，并改善用户信任。

With the exception of the probability of precipitation, information about uncertainty is rarely communicated in public weather forecasts, even though it could improve weather-related decisions with important economic and safety consequences. A recent National Research Council report found that assessing, communicating and disseminating forecast uncertainty information to the end-user is the largest as yet unaddressed task before the weather forecasting community. The purpose of this project is to bridge that gap with the efforts of a multi-disciplinary team of psychologists, atmospheric scientists, statisticians, and applied physicists. This project will define the psychological processes involved in understanding and using weather forecast uncertainty in realistic contexts among non-expert users. Research will be conducted to determine the impact of alternative methods of presenting information, including verbal explanations as well as visual images and graphs. The results of this research will be applied to producing an unprecedented prototype weather forecasting website that presents forecasts to the public that are entirely probabilistic. It will give uncertainty-bracketed forecasts for temperature, precipitation and wind speed. It will also provide warning information for extreme events, such as high winds, extreme temperatures and extreme amounts of rainfall. Although such warnings have important safety implications, there has been very little research devoted to the methods for producing or communicating this information. This will require the development of innovative methods of analyzing and displaying probabilistic information for extreme events.The project will also develop and provide graphics that compare past probabilistic forecasts to observed values, to demonstrate to users that although observed values may not always match single value forecasts, they are often within the boundaries of the probability range. This feature will enhance understanding of the probabilistic nature of the forecast as well as improving user trust.