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When forecasts for a major weather event begin days in advance, updates may be more accurate but inconsistent with the original forecast. Evidence suggests that resulting inconsistency may reduce user trust. However, adding an uncertainty estimate to the forecast may attenuate any loss of trust due to forecast inconsistency, as has been shown with forecast inaccuracy. To evaluate this hypothesis, this experiment tested the impact on trust of adding probabilistic snow-accumulation forecasts to single-value forecasts in a series of original and revised forecast pairs (based on historical records) that varied in both consistency and accuracy. Participants rated their trust in the forecasts and used them to make school-closure decisions. One-half of the participants received single-value forecasts, and one-half also received the probability of 6 in. or more (decision threshold in the assigned task). As with previous research, forecast inaccuracy was detrimental to trust, although probabilistic forecasts attenuated the effect. Moreover, the inclusion of probabilistic forecasts allowed participants to make economically better decisions. Surprisingly, in this study inconsistency increased rather than decreased trust, perhaps because it alerted participants to uncertainty and led them to make more cautious decisions. Furthermore, the positive effect of inconsistency on trust was enhanced by the inclusion of probabilistic forecast. This work has important implications for practical settings, suggesting that both probabilistic forecasts and forecast inconsistency provide useful information to decision-makers. Therefore, members of the public may benefit from well-calibrated uncertainty estimates and newer, more reliable information.

The purpose of this study was to clarify how explicit uncertainty information and forecast inconsistency impact trust and decision-making in the context of sequential forecasts from the same source. This is important because trust is critical for effective risk communication. In the absence of trust, people may not use available information and subsequently may put themselves and others at greater-than necessary risk. Our results suggest that updating forecasts when newer, more reliable information is available and providing reliable uncertainty estimates can support user trust and decision-making.

 

Many individual states and localities have loosened or eliminated mitigation measures as the COVID-19 pandemic has evolved. Individuals who wish to mitigate their risk of contracting COVID-19 must decide on effective strategies in environments that may have returned to pre-pandemic norms. Individuals must assess their level of risk and risk tolerance amid different mitigation measures, regulations, and metrics across states and localities. The public is also exposed to misinformation and disinformation through social and mainstream media—all occurring within a politically polarized environment. 

There are lingering questions about the effectiveness of the watch, warning, and advisory system (WWA) used to convey weather threats in the United States. Recently there has been a shift toward alternative communication strategies such as the impact-based forecast. The study reported here compared users’ interpretation of a color-coded impact-based prototype designed for email briefings, to a legacy WWA format. Participants, including emergency managers and members of the public, saw a weather briefing and rated event likelihood, severity, damage, and population affected. Then they recommended emergency response actions. Each briefing described the severity of the weather event and the degree of impact on population and property. In one condition a color-coded impacts scale was added to the text description. In another, an advisory and/or warning was added to the text description. These were compared with the text-only control. Both emergency managers and members of the public provided higher ratings for event likelihood, severity, damage, and population affected and recommended a greater response for higher impact levels regardless of format. For both groups, the color-coded format decreased ratings for lower-impact events. Among members of the public, the color-coded format also led to increases for many ratings and greater response at higher levels relative to the other two conditions. However, the highest ratings among members of the public were in the WWA condition. Somewhat surprisingly, the only effect of the WWA format on emergency managers was toreduceaction recommendations, probably because of the inclusion of the “advisory” in some briefings.