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Marcos Samuel Matias Ribeiro, Lara de Melo Barbosa Andrade, Maria Helena Constantino Spyrides, Kellen Carla Lima, Pollyane Evangelista da Silva, Douglas Toledo Batista, and Idemauro Antônio Rodrigues de Lara

Abstract

The occurrence of environmental disasters affects different social segments, impacting health, education, housing, economy and the provision of basic services. Thus, the objective of this study was to estimate the relationship between the occurrence of disasters and extreme climate, sociosanitary and demographic conditions in the Northeast region of Brazil during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events and, subsequently, generalized additive models for location, scale and shape were used in order to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in the NEB representing 81.1% of the cases, followed by events triggered by excessive rainfall such as flash floods (11.1%) and floods (7.8%). Climate conditions presented statistically significant associations with the analyzed disasters, in which indicators of excess rainfall positively contributed to the occurrence of flash floods and floods, but negatively contributed to the occurrence of drought. Sociosanitary factors, such as percentage of households with inadequate sewage, waste collection and water supply, were also positively associated with the model’s estimations, i.e., contributing to an increase in the occurrence of events, with the exception of floods, which were not significantly influenced by sociosanitary parameters. A decrease of 19% in the risk of drought occurrence was estimated, on average. On the other hand, events caused by excessive rainfall increased by 40% and 57%, in the cases of flash floods and floods, respectively.

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Kelley Murphy, Eric Bruning, Christopher J. Schultz, and Jennifer Vanos

Abstract

A lightning risk assessment for application to human safety was created and applied in 10 West Texas locations from 2 May 2016 to 30 September 2016. The method combined spatial lightning mapping data, probabilistic risk calculation adapted from the International Electrotechnical Commission Standard 62305-2, and weighted average interpolation to produce risk magnitudes that were compared to tolerability thresholds to issue lightning warnings. These warnings were compared to warnings created for the same dataset using a more standard lightning safety approach based on National Lightning Detection Network (NLDN) total lightning within 5 nautical miles of each location. Four variations of the calculation as well as different units of risk were tested to find the optimal configuration to calculate risk to an isolated human outdoors.

The best performing risk configuration using risk 10min−1 or larger produced the most comparable results to the standard method, such as number of failures, average warning duration, and total time under warnings. This risk configuration produced fewer failures than the standard method, but longer total time under warnings and higher false alarm ratios. Median lead times associated with the risk configuration were longer than the standard method for all units considered, while median down times were shorter for risk 10min−1 and risk 15min−1. Overall, the risk method provides a baseline framework to quantify the changing lightning hazard on the storm-scale, and could be a useful tool to aid in lightning decision support scenarios.

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Ross Westoby, Rachel Clissold, and Karen E. McNamara

Abstract

As climate change accelerates, effective adaptation is an urgent and unavoidable priority. Bottom-up approaches such as community-based adaptation have been portrayed as the panacea. Recent studies are, however, highlighting the ongoing and inherent issues with normative “community” conceptualizations that assume a geographically bound, temporally fixed, and harmonious unit. Despite documentation on the negative impact these problematic assumptions can have on adaptation outcomes, adaptation at the community scale remains the preferred option for project delivery in highly exposed places such as the Pacific Islands region. More creative entry points that are less charged with problematic assumptions are needed at the local scale. This paper draws from three examples in Vanuatu to offer compelling alternative entry points for adaptation: 1) a rural technical college embedded within an Anglican mission village, 2) a whole-of-island approach, and 3) the “collective of vendors” at marketplaces. We offer hope by identifying ways to expand on and complement existing, restricted notions of community and, through this, to improve adaptation outcomes.

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Mary McRae, Ross A. Lee, Scott Steinschneider, and Frank Galgano

Abstract

Increases in maximum and minimum air temperatures resulting from anthropogenic climate change will present challenges to aircraft performance. Elevated density altitude (DA) reduces aircraft and engine performance and has a direct impact on operational capabilities. The frequency of higher DA will increase with the combination of higher air temperatures and higher dewpoint temperatures. The inclusion of dewpoint temperature in DA projections will become increasingly critical as minimum air temperatures rise. High DA impacts aircraft performance in the following ways: reduction in power because the engine takes in less air; reduction in thrust because a propeller is less efficient in less dense air; reduction in lift because less dense air exerts less force on the airfoils. For fixed-wing aircraft, the performance impacts include decreased maximum takeoff weight and increased true airspeed, which results in longer takeoff and landing distance. For rotary-wing aircraft, the performance impacts include reduced power margin, reduced maximum gross weight, reduced hover ceiling, and reduced rate of climb. In this research, downscaled and bias-corrected maximum and minimum air temperatures for future time periods are collected and analyzed for a selected site: Little Rock Air Force Base, Arkansas. Impacts corresponding to DA thresholds are identified and integrated into risk probability matrices enabling quantifiable comparisons. As the magnitude and frequency of high DA occurrences are projected to increase as a result of climate change, it is imperative for military mission planners and acquisition officers to comprehend and utilize these projections in their decision-making processes.

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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