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Adam M. Rainear and Carolyn A. Lin

Abstract

When attempting to communicate flood risk, trust in and perceptions toward risk information dissemination as well as individual efficacy factors can play a significant role in affecting risk-mitigation motivation and intention. This study seeks to examine how risk communication, risk perception, and efficacy factors affect evacuation motivation and behavioral intentions in response to a presumed flood risk, as based on a conceptual framework guided by protection motivation theory. An online survey was administered to college students (N = 239) from a region that is subject to sea level rise and storm surges. Path analysis results indicate that, while less information-source trust predicts greater risk perception, greater information-source trust predicts greater mitigation-information-seeking intention, lower self-efficacy, and stronger response efficacy. As lower mitigation-information-seeking intention similarly predicts greater risk perception, greater mitigation-information-seeking intention also predicts stronger response efficacy. Significant predictors of evacuation motivation include lower risk perception as well as greater information-source trust, severity perception, and response efficacy. Implications of these findings are discussed in terms of information dissemination channels, messaging strategies, and recent severe flooding events.

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Morgan E. Gorris, James E. Neumann, Patrick L. Kinney, Megan Sheahan, and Marcus C. Sarofim

Abstract

Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000–15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were $400,000 per case, and the annual average total cost was $3.9 billion per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost $620,000 per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change–attributable damages in the United States.

Open access
Chen Su, Jessica N. Burgeno, and Susan Joslyn

Abstract

People access weather forecasts from multiple sources [mobile telephone applications (“apps”), newspapers, and television] that are not always in agreement for a particular weather event. The experiment reported here investigated the effects of inconsistency among forecasts on user trust, weather-related decisions, and confidence in user decisions. In a computerized task, participants made school-closure decisions on the basis of snow forecasts from different sources and answered a series of questions about each forecast. Inconsistency among simultaneous forecasts did not significantly reduce trust, although inaccuracy did. Moreover, inconsistency may convey useful information to decision-makers. Not only do participants appear to incorporate the information provided by all forecasts into their own estimates of the outcome, but our results also suggest that inconsistency gives rise to the impression of greater uncertainty, which leads to more cautious decisions. The implications for decisions in a variety of domains are discussed.

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Rachel E. Riley

Abstract

Decision-makers who have little to no formal training in atmospheric science are increasingly accessing and interpreting climate data and information within planning contexts. Many climate decision support tools (DSTs) have been developed to support decision-making across a variety of sectors and scales, but evaluation of such tools has only recently begun to take place. This study conducted a summative evaluation of the utility of a decision-maker-driven climate hazard assessment tool, the Simple Planning Tool (SPT), a climate DST. The SPT was inspired by and codeveloped with emergency managers, planners, and a boundary organization in two south-central U.S. states. The SPT’s target audience was surveyed to assess the tool’s utility, including its saliency, credibility, trustworthiness, and reasons for and impact of information use on decision-making. A high utility was found despite a relatively limited user base at the time of the study. In addition, SPT users represented a range of jurisdictional sizes, geographical scales, and years of experience. Although the small user sample limits generalizability of the study, it is likely a realistic reflection of the number of emergency managers and planners in the two states who are actively and regularly incorporating climate hazards into planning. The data also indicate that climate boundary organizations and climate service providers should work toward utilizing trusted information sources, channels, and procedures within the sectors to which their tool applies to help increase decision-maker awareness and use of their tool.

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Johnathan W. Sugg

Abstract

Americans remain polarized about climate change. However, recent scholarship reveals a plurality of climate change opinions among the public, with nontrivial support for a range of awareness, risk perceptions, and policy prescriptions. This study uses publicly available opinion estimates to examine the geographic variability of American climate change opinions and maps them as regions that share similarities or differences in the character of their beliefs. The exploratory geovisual environment of a self-organizing map is used to compare the support for 56 different climate opinions across all counties in the United States and arrange them into a spatially coherent grid of nodes. To facilitate the exploration of the patterns, a statistical cluster analysis groups together counties with the most similar climate beliefs. Choropleth maps visualize the clustering results from the self-organizing map. This study finds six groups of climate beliefs in which member counties exhibit a distinct regionality across the United States and share similarities in the magnitude of support for specific opinions. Groups that generally exhibit high or low levels of support for climate change awareness, risk perceptions, and policy prescriptions vary in their relative support for specific opinions. The results provide a nuanced understanding of different types of climate change opinions and where they exist geographically.

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Talardia Gbangou, Erik Van Slobbe, Fulco Ludwig, Gordana Kranjac-Berisavljevic, and Spyridon Paparrizos

Abstract

Improved weather and climate forecast information services are important to sustain small-scale crop production in many developing countries. Previous studies recognized the value of integrating local forecasting knowledge (LFK) with scientific forecasting knowledge (SFK) to support farmers’ decision-making. Yet, little work has focused on proper documentation, quality verification, and integration techniques. The skills of local and scientific forecasts were compared, and new integration approaches were derived over the coastal zone of Ghana. LFK indicators were documented, and farmers were trained to collect indicators’ observations and record rainfall in real time using digital tools and rain gauges, respectively, in 2019. Dichotomous forecasts verification metrics were then used to verify the skills of both local and scientific forecasts against rainfall records. Farmers use a diverse set of LKF indicators for both weather and seasonal climate time-scale predictions. LFK indicators are mainly used to predict rainfall occurrence, amount of seasonal rainfall, dry spell occurrence, and onset and cessation of the rainy season. The average skill of a set of LFK indicators in predicting one-day rainfall is higher than individual LFK indicators. Also, the skills of a set of LFK indicators can potentially be higher than the forecasts given by the Ghana Meteorological Agency for the Ada District. The results of the documentation and skills indicate that approaches and methods developed for integrating LFK and SFK can contribute to increasing forecast resolution and skills and reducing recurring tensions between the two knowledge systems. Future research and application of these methods can help improve weather and climate information services in Ghana.

Open access
Jacob R. Reed and Jason C. Senkbeil

Abstract

The extended forecast graphic (EFG) is a popular graphic used by meteorologists to convey weather information, but it is poorly understood by the public. Deficiencies in the format, content, and presentation of the EFG contribute to a decrease in the efficacy of this graphic and reduce the comprehension of weather information. The format of the EFG has largely gone unchanged since the graphic first became popular more than four decades ago. The goal of this research was to modify the format of the existing EFG to address current limitations that inhibit understanding and create confusion among the public. Data were gathered from an online survey of the public (n = 885). Four modified versions of the EFG were developed, evaluated, and compared with the existing EFG. Removing probability of precipitation (PoP) information, reducing the number of days shown, and switching to a horizontal layout featuring timing and intensity information resulted in higher percentages for comprehension of weather information and positive comments when compared with the current version. A majority of participants responded that forecasters could accurately predict the weather 3 days out, providing justification for the reduction in number of days shown in the modified EFGs. Results suggest that agencies and members of the meteorological community should continue evaluating and discussing the most effective ways to use graphics to convey weather information to their audiences.

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I. Gómez, S. Molina, J. Olcina, and J. J. Galiana-Merino

Abstract

This quantitative study evaluates how 71 Spanish undergraduate students perceive and interpret the uncertainty inherent to deterministic forecasts. It is based on several questions that asked participants what they expect given a forecast presented under the deterministic paradigm for a specific lead time and a particular weather parameter. In this regard, both normal and extreme weather conditions were studied. Students’ responses to the temperature forecast as it is usually presented in the media expect an uncertainty range of ±1°–2°C. For wind speed, uncertainty shows a deviation of ±5–10 km h−1, and the uncertainty range assigned to the precipitation amount shows a deviation of ±30 mm from the specific value provided in a deterministic format. Participants perceive the minimum night temperatures as the least-biased parameter from the deterministic forecast, while the amount of rain is perceived as the most-biased one. In addition, participants were then asked about their probabilistic threshold for taking appropriate precautionary action under distinct decision-making scenarios of temperature, wind speed, and rain. Results indicate that participants have different probabilistic thresholds for taking protective action and that context and presentation influence forecast use. Participants were also asked about the meaning of the probability-of-precipitation (PoP) forecast. Around 40% of responses reformulated the default options, and around 20% selected the correct answer, following previous studies related to this research topic. As a general result, it has been found that participants infer uncertainty into deterministic forecasts, and they are mostly used to take action in the presence of decision-making scenarios. In contrast, more difficulties were found when interpreting probabilistic forecasts.

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Scott C. Sheridan, P. Grady Dixon, Adam J. Kalkstein, and Michael J. Allen

Abstract

Much research has shown a general decrease in the negative health response to extreme heat events in recent decades. With a society that is growing older, and a climate that is warming, whether this trend can continue is an open question. Using eight additional years of mortality data, we extend our previous research to explore trends in heat-related mortality across the United States. For the period 1975–2018, we examined the mortality associated with extreme-heat-event days across the 107 largest metropolitan areas. Mortality response was assessed over a cumulative 10-day lag period following events that were defined using thresholds of the excess heat factor, using a distributed-lag nonlinear model. We analyzed total mortality and subsets of age and sex. Our results show that in the past decade there is heterogeneity in the trends of heat-related human mortality. The decrease in heat vulnerability continues among those 65 and older across most of the country, which may be associated with improved messaging and increased awareness. These decreases are offset in many locations by an increase in mortality among men 45–64 (+1.3 deaths per year), particularly across parts of the southern and southwestern United States. As heat-warning messaging broadly identifies the elderly as the most vulnerable group, the results here suggest that differences in risk perception may play a role. Further, an increase in the number of heat events over the past decade across the United States may have contributed to the end of a decades-long downward trend in the estimated number of heat-related fatalities.

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Lynda E. Chambers, Roan D. Plotz, Siosinamele Lui, Faapisa Aiono, Tile Tofaeono, David Hiriasia, Lloyd Tahani, ‘Ofa Fa’anunu, Seluvaia Finaulahi, and Albert Willy

Abstract

Traditional calendars document seasonal cycles and the communities’ relationships to their biophysical environment and are often used by communities, particularly subsistence farmers, to synchronize their livelihood activities with the timing of ecological processes. Because the timing of these ecological processes is not always consistent from year to year, the use of traditional seasonal calendars can help communities to cope with climate variability, particularly when biophysical phenomena become less predictable in relation to the Gregorian calendar, as has been observed in relation to climate change. Although the structure and content of seasonal calendars vary across the Pacific Ocean region, for many indigenous communities, knowledge of seasonal calendars can increase their capacity to cope with climate variability and change. To increase the effectiveness of their products and enhance their relevance to and uptake by the community, several Pacific meteorological services are now using traditional seasonal calendars in their climate communication and education, including in forecasts and warnings. The use of a participatory approach resulted in strong relationships and improved dialogues. Local communities appreciated assistance in enabling their knowledge to become available to future generations, and its inclusion in meteorological service products makes these products more accessible and relevant to community members.

Open access