Print Email Facebook Twitter Public understanding of visual representations of uncertainty in temperature forecasts Title Public understanding of visual representations of uncertainty in temperature forecasts Author Tak, S.W. Toet, A. van Erp, J.B.F. Publication year 2015 Abstract Multiday weather forecasts often include graphical representations of uncertainty. However, visual representations of probabilistic events are often misinterpreted by the general public. Although various uncertainty visualizations are now in use, the parameters that determine their successful deployment are still unknown. At the same time, a correct understanding of possible weather forecast outcomes will enable the public to make better decisions and will increase their trust in these predictions. We investigated the effects of the visual form and width of temperature forecast visualizations with uncertainty on estimates of the probability that the temperature could exceed a given value. The results suggest that people apply an internal model of the uncertainty distribution that closely resembles a normal distribution, which confirms previous findings. Also, the visualization type appears to affect the applied internal model, in particular the probability estimates of values outside the depicted uncertainty range. Furthermore, we find that perceived uncertainty does not necessarily map linearly to visual features, as identical relative positions to the range are being judged differently depending on the width of the uncertainty range. Finally, the internal model of the uncertainty distribution is related to participants numeracy. We include some implications for makers or designers of uncertainty visualizations. © Human Factors and Ergonomics Society. Subject Human & Operational ModellingPCS - Perceptual and Cognitive SystemsELSS - Earth, Life and Social SciencesInformaticslaboratory studymethodstopicstopicsuncertaintyuser evaluation studyvisualizationBalloonsFlow visualizationForecastingNormal distributionUncertainty analysisVisualizationLaboratory studiesmethodstopicsuncertaintyUser evaluationsWeather forecasting To reference this document use: http://resolver.tudelft.nl/uuid:96c9a969-176f-4ab3-9753-30a59f29d2ba DOI https://doi.org/10.1177/1555343415591275 TNO identifier 527987 Publisher SAGE Publications Inc. ISSN 1555-3434 Source Journal of Cognitive Engineering and Decision Making, 9 (3), 241-262 Document type article Files To receive the publication files, please send an e-mail request to TNO Library.