Using Visualization Science to Improve Expert and Public Understanding of Probabilistic Temperature and Precipitation Outlooks
Using Visualization Science to Improve Expert and Public Understanding of Probabilistic Temperature and Precipitation Outlooks
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利用可视化科学提高专家和公众对概率温度和降水展望的理解
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
D. Dewitt
中科院分区：
文献类型：
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作者：
M. Gerst;M. Kenney;A. Baer;A. Speciale;J. Wolfinger;J. Gottschalck;S. Handel;Matthew Rosencrans;D. Dewitt
以视觉方式传达温度和降水气候前景图形具有挑战性，因为它要求观看者熟悉概率并具有解释地理空间预报不确定性的视觉素养。此外，可视化科学文献还提出了哪些视觉设计选择最有效地表达不确定预测的多维性的问题，这使得设计师缺乏具体的指导。本研究采用两阶段实验设置，展示了如何使用最近开发的可视化诊断指南来迭代诊断、重新设计和测试美国国家海洋和大气管理局 (NOAA) 气候预测中心 (CPC) 气候展望的可理解性。在第一阶段，可视化诊断指南与访谈和焦点小组结合使用，以确定温度和降水前景中现有视觉惯例的可理解性挑战。接下来，在随机对照与实验治疗设置中，通过对最终用户和公众的在线调查制作并测试了一些图形修改。结果表明，总体而言，最终用户对前景表现出更好的理解，但某些类型的概率颜色映射被最终用户和公众误解，这是诊断指南所预测的。修改使最终用户和公众对气候前景的了解显着增加，为使用可视化诊断通知的控制测试与治疗测试的效用提供了额外的证据。
Visually communicating temperature and precipitation climate outlook graphics is challenging because it requires the viewer to be familiar with probabilities as well as to have the visual literacy to interpret geospatial forecast uncertainty. In addition, the visualization scientific literature has open questions on which visual design choices are the most effective at expressing the multidimensionality of uncertain forecasts, leaving designers with a lack of concrete guidance. Using a two-phase experimental setup, this study shows how recently developed visualization diagnostic guidelines can be used to iteratively diagnose, redesign, and test the understandability the U.S. National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) climate outlooks. In the first phase, visualization diagnostic guidelines were used in conjunction with interviews and focus groups to identify understandability challenges of existing visual conventions in temperature and precipitation outlooks. Next, in a randomized control versus experimental treatment setup, several graphic modifications were produced and tested via an online survey of end users and the general public. Results show that, overall, end users exhibit a better understanding of outlooks, but some types of probabilistic color mapping are misunderstood by both end users and the general public, which was predicted by the diagnostic guidelines. Modifications lead to significant gains in end-user and general public understanding of climate outlooks, providing additional evidence for the utility of using control versus treatment testing informed by visualization diagnostics.