Susan Joslyn

Uncertainty Forecasts Improve Weather-Related Decisions and Attenuate the Effects of Forecast Error

Although uncertainty is inherent in weather forecasts, explicit numeric uncertainty estimates are rarely included in public forecasts for fear that they will be misunderstood. Of particular concern are situations in which precautionary action is required at low probabilities, often the case with severe events. At present, a categorical weather warning system is used. The work reported here tested the relative benefits of several forecast formats, comparing decisions made with and without uncertainty forecasts. In three experiments, participants assumed the role of a manager of a road maintenance company in charge of deciding whether to pay to salt the roads and avoid a potential penalty associated with icy conditions. Participants used overnight low temperature forecasts accompanied in some conditions by uncertainty estimates and in others by decision advice comparable to categorical warnings. Results suggested that uncertainty information improved decision quality overall and increased trust in the forecast. Participants with uncertainty forecasts took appropriate precautionary action and withheld unnecessary action more often than did participants using deterministic forecasts. When error in the forecast increased, participants with conventional forecasts were reluctant to act. However, this effect was attenuated by uncertainty forecasts. Providing categorical decision advice alone did not improve decisions. However, combining decision advice with uncertainty estimates resulted in the best performance overall. The results reported here have important implications for the development of forecast formats to increase compliance with severe weather warnings as well as other domains in which one must act in the face of uncertainty.

Directed forgetting of autobiographical events

Two diary experiments demonstrated directed forgetting (DF) of autobiographical events, previously observed only for less complex memory items. Using a 2-week diary paradigm, we compared recall between a group of participants who were directed to forget Week 1 memories (forget group) and a group who did not receive a forget instruction (remember group). In Experiment 1, the forget group remembered fewer items from Week 1 than did the remember group. The effect was observed for negative and positive valence events, as well as for high and low emotional intensity events. The effect was replicated in Experiment 2 despite a memorable holiday (Valentine’s Day) that occurred during the manipulation week. Forget participants remembered fewer low emotional intensity items in Experiment 2. We conclude that intentional forgetting is a plausible explanation for the loss of some autobiographical memories.

Probability of Precipitation: Assessment and Enhancement of End-User Understanding

Abstract The results of three psychological studies suggest that many people did not understand probability of precipitation (PoP) despite the fact that participants were college undergraduates in the Pacific Northwest, an area with frequent precipitation forecasts. The misunderstanding concerned the class of events to which the probability refers. The combined results reported here suggest that some participants thought that the percentage, indicating chance of precipitation, referred instead to the proportion of area or time that precipitation would be observed. More participants chose to take an umbrella or wear a hooded jacket who mistakenly interpreted the forecast as indicating precipitation for more than half of the area or time as compared to those who do not hold this misunderstanding. In addition, performance only improved significantly when PoP was accompanied by a phrase expressing the probability of no precipitation. This suggests a deep-seated misunderstanding that converts the probabilistic...

The Effect of Uncertainty Visualizations on Decision Making in Weather Forecasting

Peoples reasoning with uncertainty information is often flawed. Visual representations can help, but little is known about what is the best way to present such information. Two studies investigated the effect of visualizations on the understanding and use of wind speed forecast uncertainty. Participants varied in expertise from novices in weather forecasting (Experiment 1) to professional forecasters (Experiment 2). The authors investigated three visualizations: (a) a chart showing the amount of uncertainty, (b) a chart showing the worst-case scenario, and (c) a box plot of likely wind speeds. Participants were asked to determine the relative uncertainty in the forecast, predict wind speed, and decide whether to post a high-wind warning advisory. The results for novices and professional forecasters were similar. The uncertainty chart enhanced awareness of the degree of uncertainty associated with the forecast, box plots improved reading accuracy, and presenting a visualization of the worst-case scenario introduced bias in the deterministic wind speed forecast. An interactive display (e.g., a combination of an uncertainty chart with a box plot display) may be optimal to convey uncertainty information.

Uncertainty Forecasts Improve Decision Making Among Nonexperts

The objective of this research was to evaluate the impact of weather uncertainty information on decision making in naturalistic settings. Traditional research often reveals deficits in human decision making under uncertainty as compared with normative models of rational choice. However, little research has addressed the question of whether people in naturalistic settings make better decisions when they have uncertainty information as compared with when they have only a deterministic forecast. Two studies investigated the effect of several types of weather uncertainty information on the quality of decisions to protect roads against icing and on temperature predictions and compared them with a control condition that provided deterministic forecast only. Experiment 1 was a Web-based questionnaire that included a single trial. Experiment 2, conducted in lab, included 120 trials and provided outcome feedback and a reward based on performance. Both studies indicated enhanced performance with uncertainty information. The best kind of uncertainty information tested here was the one that provided the probability at the threshold for the task at hand. We conclude that uncertainty information can be used advantageously, even when it does not result in perfectly rational performance, and that uncertainty can be communicated effectively to nonexpert end users, resulting in improved decision making.

The "Cry Wolf" Effect and Weather-Related Decision Making

Despite improvements in forecasting extreme weather events, noncompliance with weather warnings among the public remains a problem. Although there are likely many reasons for noncompliance with weather warnings, one important factor might be peoples past experiences with false alarms. The research presented here explores the role of false alarms in weather-related decision making. Over a series of trials, participants used an overnight low temperature forecast and advice from a decision aid to decide whether to apply salt treatment to a towns roads to prevent icy conditions or take the risk of withholding treatment, which resulted in a large penalty when freezing temperatures occurred. The decision aid gave treatment recommendations, some of which were false alarms, i.e., treatment was recommended but observed temperatures were above freezing. The rate at which the advice resulted in false alarms was manipulated between groups. Results suggest that very high and very low false alarm rates led to inferior decision making, but that lowering the false alarm rate slightly did not significantly affect compliance or decision quality. However, adding a probabilistic uncertainty estimate in the forecasts improved both compliance and decision quality. These findings carry implications about how weather warnings should be communicated to the public.

The Effect of Probabilistic Information on Threshold Forecasts

Abstract The study reported here asks whether the use of probabilistic information indicating forecast uncertainty improves the quality of deterministic weather decisions. Participants made realistic wind speed forecasts based on historical information in a controlled laboratory setting. They also decided whether it was appropriate to post an advisory for winds greater than 20 kt (10.29 m s−1) during the same time intervals and in the same geographic locations. On half of the forecasts each participant also read a color-coded chart showing the probability of winds greater than 20 kt. Participants had a general tendency to post too many advisories in the low probability situations (0%–10%) and too few advisories in very high probability situations (90%–100%). However, the probability product attenuated these biases. When participants used the probability product, they posted fewer advisories when the probability of high winds was low and they posted more advisories when the probability of high winds was hi...

Decisions With Uncertainty: The Glass Half Full

Each of us makes important decisions involving uncertainty in domains in which we are not experts, such as retirement planning, medical treatment, and precautions against severe weather. Often, reliable information about uncertainty is available to us, although how effectively we incorporate it into the decision process remains in question. Previous research suggests that people are error-prone when reasoning with probability. However, recent research in weather-related decision making is more encouraging. Unlike earlier work that compares people’s decisions with a rational standard, this research compares decisions made by people with and without uncertainty information. The results suggest that including specific numeric uncertainty estimates in weather forecasts increases trust and gives people a better idea of what to expect in terms of both the range of possible outcomes and the amount of uncertainty in the particular situation, all of which benefit precautionary decisions. However, the advantage for uncertainty estimates depends critically on how they are expressed. It is crucial that the expression is compatible with both the decision task and cognitive processes of the user.

Memory for memory

Participants read short passages and 1 day later they answered questions via telephone about the passages (text facts) and about the experimental session (event facts). They were telephoned again 6 weeks later and answered the same questions about text and event facts. They also answered new questions about whether they remembered the answers they had given in the initial telephone interview (recall for prior memory performance). Although participants accurately remembered the majority of past memory successes, they were poor at remembering past memory failures. After being provided with the correct answer and tested again, the participants’ performance improved somewhat, especially for memory failures. This suggests that some errors in recalling past forgetting might have been due to correctly remembering the answer previously given, but failing to realize that it had been wrong. These findings have implications for a variety of situations in which people are queried about past memory performance.

Methods for Communicating the Complexity and Uncertainty of Oil Spill Response Actions and Tradeoffs

ABSTRACT Complexity and uncertainty influence opinions, beliefs, and decisions about health, safety, and other kinds of risk, as demonstrated in research on health, climate change, storm forecasts, pandemic disease, and in other domains. Drawing from this research, this article summarizes insights into how people understand and process uncertain or complex information and explores key oil spill and oil spill response-relevant issues regarding the communication of complexity and uncertainty—from the presentation of uncertainties around forecast parameters to the deployment of online oil spill response simulation tools. Recommended practices from this article include (a) to continue to develop and evaluate interactive Web-based oil spill response simulations to help users explore tradeoffs in response decisions, (b) to take how people simplify information into account in designing communications processes and products (and evaluate), (c) to provide numbers along with verbal probability descriptions, and (d) if using graphics, to communicate probability or uncertainty, using simple graphics and testing them, as effects may not be predictable and some kinds of graphics are easier to understand than others, depending on context, numeracy, and graphicacy.