Effective Visualizations of the Uncertainty in Hurricane Forecasts

The track forecast cone developed by the U.S. National Hurricane Center is the one most universally adopted by the general public, the news media, and governmental officials to enhance viewers\u27 understanding of the forecasts and their underlying uncertainties. However, current research has experimentally shown that it has limitations that result in misconceptions of the uncertainty included. Most importantly, the area covered by the cone tends to be misinterpreted as the region affected by the hurricane. In addition, the cone summarizes forecasts for the next three days into a single representation and, thus, makes it difficult for viewers to accurately determine crucial time-specific information. To address these limitations, this research develops novel alternative visualizations. It begins by developing a technique that generates and smoothly interpolates robust statistics from ensembles of hurricane predictions, thus creating visualizations that inherently include the spatial uncertainty by displaying three levels of positional storm strike risk at a specific point in time. To address the misconception of the area covered by the cone, this research develops time-specific visualizations depicting spatial information based on a sampling technique that selects a small, representative subset from an ensemble of points. It also allows depictions of such important storm characteristics as size and intensity. Further, this research generalizes the representative sampling framework to process ensembles of forecast tracks, selecting a subset of tracks accurately preserving the original distributions of available storm characteristics and keeping appropriately defined spatial separations. This framework supports an additional hurricane visualization portraying prediction uncertainties implicitly by directly showing the members of the subset without the visual clutter. We collaborated on cognitive studies that suggest that these visualizations enhance viewers\u27 ability to understand the forecasts because they are potentially interpreted more like uncertainty distributions. In addition to benefiting the field of hurricane forecasting, this research potentially enhances the visualization community more generally. For instance, the representative sampling framework for processing 2D points developed here can be applied to enhancing the standard scatter plots and density plots by reducing sizes of data sets. Further, as the idea of direct ensemble displays can possibly be extended to more general numerical simulations, it, thus, has potential impacts on a wide range of ensemble visualizations

Visualizing Uncertainty for Non-Expert End Users: The Challenge of the Deterministic Construal Error

There is a growing body of evidence that numerical uncertainty expressions can be used by non-experts to improve decision quality. Moreover, there is some evidence that similar advantages extend to graphic expressions of uncertainty. However, visualizing uncertainty introduces challenges as well. Here, we discuss key misunderstandings that may arise from uncertainty visualizations, in particular the evidence that users sometimes fail to realize that the graphic depicts uncertainty. Instead they have a tendency to interpret the image as representing some deterministic quantity. We refer to this as the deterministic construal error. Although there is now growing evidence for the deterministic construal error, few studies are designed to detect it directly because they inform participants upfront that the visualization expresses uncertainty. In a natural setting such cues would be absent, perhaps making the deterministic assumption more likely. Here we discuss the psychological roots of this key but underappreciated misunderstanding as well as possible solutions. This is a critical question because it is now clear that members of the public understand that predictions involve uncertainty and have greater trust when uncertainty is included. Moreover, they can understand and use uncertainty predictions to tailor decisions to their own risk tolerance, as long as they are carefully expressed, taking into account the cognitive processes involved

Multiple Hazard Uncertainty Visualization Challenges and Paths Forward

Making decisions with uncertainty is challenging for the general public, policymakers, and even highly trained scientists. Nevertheless, when faced with the need to respond to a potential hazard, people must make high-risk decisions with uncertainty. In some cases, people have to consider multiple hazards with various types of uncertainties. Multiple hazards can be interconnected by location, time, and/or environmental systems, and the hazards may interact, producing complex relationships among their associated uncertainties. The interaction between multiple hazards and their uncertainties can have nonlinear effects, where the resultant risk and uncertainty are greater than the sum of the risk and uncertainty associated with individual hazards. Effectively communicating the uncertainties related to such complicated systems should be a high priority because the frequency and variability of multiple hazard events due to climate change continue to increase. However, the communication of multiple hazard uncertainties and their interactions remains largely unexplored. The lack of practical guidance on conveying multiple hazard uncertainties is likely due in part to the field’s vast expanse, making it challenging to identify entry points. Here, we offer a perspective on three critical challenges related to uncertainty communication across various multiple hazard contexts to galvanize the research community. We advocate for systematic considerations of multiple hazard uncertainty communication that focus on trade-offs between complexity and factors, including mental effort, trust, and usability

Visualizations Out of Context: Addressing Pitfalls of Real-Time Realistic Hazard Visualizations

Realistic 3D hazard visualizations based on advanced Geographic Information Systems (GIS) may be directly driven by hydrodynamic and wind model outputs (e.g., ADCIRC, the ADvanced CIRCulation Model) and hazard impact modeling (e.g., predicting damage to structures and infrastructure). These methods create new possibilities for representing hazard impacts and support the development of near-real-time hazard forecasting and communication tools. This paper considers the wider implications of using these storm visualizations in light of current frameworks in the context of landscape and urban planning and cartography that have addressed the use of realistic 3D visualizations. Visualizations used outside of engagement processes organized by experts risk misleading the public and may have consequences in terms of feelings of individual self-efficacy or perception of scientists behind the visualizations. In addition to summarizing the implications of using these visualizations outside of recommended practices, a research agenda is proposed to guide the development of real-time realistic and semi-realistic visualizations for future use in hazard communication. Development of a clearer use-case for real-time visualization capabilities is an essential first step if such work is to continue

Visualization of 40 Years of Tropical Cyclone Positions and Their Rainfall

Correos de investigadores: [email protected] || [email protected] || [email protected] || [email protected] article focuses on a visualization of tropical cyclone track data occurring over a 40- year period (1970–2010) and their relationship with (extremely) heavy rainfall reported by 88 Central American weather stations. The purpose of the visualization is to associate the paths of tropical cyclones in oceanic areas with heavy rainfall inland. Thus, the potential for producing a set of rainfall patterns might somehow help in predicting where different impacts like flooding might occur when tropical cyclones develop in specific oceanic regions. The visualization will serve as a key tool for CIGEFI scientists to apply in their work to determine critical positions of the tropical cyclones associated with extremely heavy rainfall events at daily timescales.Universidad de Costa Rica/[805-B9-454]/UCR/Costa RicaUniversidad de Costa Rica/[805-C0-610]/UCR/Costa RicaUniversidad de Costa Rica/[EC-497]/UCR/Costa RicaUniversidad de Costa Rica/[805-A4-906]/UCR/Costa RicaUniversidad de Costa Rica/[805-C0-074]/UCR/Costa RicaUniversidad de Costa Rica/[805-A1-715]/UCR/Costa RicaUniversidad de Costa Rica/[805-B0-810]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela de FísicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR

Visualizing volcanic ash forecasts: scientist and stakeholder decisions using different graphical representations and conflicting forecasts

During volcanic eruptions, Volcanic Ash Advisory Centres issue ash advisories for aviation showing the forecasted outermost extent of the ash cloud. During the 2010 Icelandic volcano Eyjafjallajökull eruption, the UK Met Office produced supplementary forecasts of quantitative ash concentration, due to demand from airlines. Additionally, satellite retrievals of estimated volcanic ash concentration are now available. To test how these additional graphical representations of volcanic ash affect flight decisions, whether users infer uncertainty in graphical forecasts of volcanic ash, and how decisions are made when given conflicting forecasts, a survey was conducted of 25 delegates representing UK research and airline operations dealing with volcanic ash. Respondents were more risk-seeking with safer flight paths and risk-averse with riskier flight paths when given location and concentration forecasts compared to when given only the outermost extent of the ash. Respondents representing operations were more risk-seeking than respondents representing research. Additionally, most respondents' hand-drawn no-fly zones were larger than the areas of unsafe ash concentrations in the forecasts. This conservatism implies that respondents inferred uncertainty from the volcanic ash concentration forecasts. When given conflicting forecasts, respondents became more conservative than when given a single forecast. The respondents were also more risk-seeking with high-risk flight paths and more risk-averse with low-risk flight paths when given conflicting forecasts than when given a single forecast. The results show that concentration forecasts seem to reduce flight cancellations while maintaining safety. Open discussion with the respondents suggested that definitions of "uncertainty" may differ between research and operations

Understanding representations of uncertainty, an eye-tracking study – Part 2: The effect of expertise

As the ability to make predictions regarding uncertainty information representing natural hazards increases, an important question for those designing and communicating hazard forecasts is how visualizations of uncertainty influence understanding amongst the intended, potentially varied, target audiences. End-users have a wide range of differing expertise and backgrounds, possibly influencing the decision-making process they undertake for a given forecast presentation. Our previous, Part 1 study (Mulder et al., 2023) examined how the presentation of uncertainty information influenced end-user decision making. Here, we shift the focus to examine the decisions and reactions of participants with differing areas of expertise (meteorology, psychology, and graphic-communication students) when presented with varied hypothetical forecast representations (boxplot, fan plot, or spaghetti plot with and without median lines) using the same eye-tracking methods and experiments. Participants made decisions about a fictional scenario involving the choices between ships of different sizes in the face of varying ice thickness forecasts. Eye movements to the graph area and key and how they changed over time (early, intermediate, and later viewing periods) were examined. More fixations (maintained gaze on one location) and more fixation time were spent on the graph and key during early and intermediate periods of viewing, particularly for boxplots and fan plots. The inclusion of median lines led to less fixations being made on all graph types during early and intermediate viewing periods. No difference in eye movement behaviour was found due to expertise; however, those with greater expertise were more accurate in their decisions, particularly during more difficult scenarios. Where scientific producers seek to draw users to the central estimate, an anchoring line can significantly reduce cognitive load, leading both experts and non-experts to make more rational decisions. When asking users to consider extreme scenarios or uncertainty, different prior expertise can lead to significantly different cognitive loads for processing information, with an impact on one's ability to make appropriate decisions.</p

A Study of Visual Communication: Cyclones, Cones, and Confusion

Visuals are at the forefront of providing information in today's society. They are on the front page of newspapers, the evening news, the Internet, and textbooks. They are particularly important in explaining risk and scientific processes such as the intricacies of climate change or the risks of cancer treatments. These visuals do not simply appear in the newspaper or on television without thought but often have distinct objectives or purposes given to them by their designer. The original objective of the graphic may not be achieved, however, if viewers misunderstand or misinterpret the graphic. Misinterpretations of risk visuals, such as hurricane track graphics, may have especially harmful consequences. Therefore, it is critically important to understand how scientific intent translates through visuals to evoke public understanding of science and risk assessment, a process that I call visual validity. To do attain scientific validity, the scientist?s objective for the graphic must be known as well as the public's interpretation of the graphic. This thesis looks at the concept of visual validity from the scientist?s point of view using a graphic called the ?cone of uncertainty,? a highly visible hurricane track graphic. Using a grounded theory approach, I conducted 19 in-depth interviews with forecasters and meteorologists from a variety of government and private sector institutions including the National Weather Service, the National Hurricane Center, The Weather Channel, and Weatherbug. I found that the cone of uncertainty has four main message objectives: (1) to communicate uncertainty, (2) to emphasize risks and impacts, (3) to show confidence in the forecast, and lastly, (4) to encourage individuals to listen to their emergency managers. The results suggest that a complicated relationship exists between the design of a visual and its many message objectives. Additionally, two potential characteristics of achieving visual validity emerged out of the data. First, the role of transactional communication between the designer of a visual and its intended audience appears to play a role in accurate understanding and risk assessment. Second, supplementing a visual with an explanation also appears to play a role in attaining visual validity. These findings have implications for the visual literacy process, as well as the extent to which an individual understands complex science and risk visuals. Future research to seek out additional potential characteristics of the visual validity process will include the public?s interpretation of the cone of uncertainty