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Basanta Raj Adhikari

Abstract

Lightning is one of the most devastating hazards in Nepal because of a large amount of atmospheric water vapor coming from the Indian Ocean and a large orographic lifting of this moist air. In 2019, a total of 2884 people were affected, with loss of USD 110,982, and the fatality number was the highest (94) in reported lightning events since 1971. The long-term analysis of this hazard is very scanty in Nepal. Therefore, this study analyzes lightning fatality events, fatality rates, and economic loss from 1971 to 2019 collected from the DesInventar dataset and the Disaster Risk Reduction portal of the government of Nepal using Statistical Package for Social Sciences (SPSS) and geographic information system (ArcGIS) tools. The analysis shows that the overall countrywide lightning fatality rate of the entire period is 1.77 per million per year. District lightning fatality rates range from 0.10 to 4.83 per million people per year, and the Bhaktapur district has the highest fatality density (0.067). Furthermore, there were a total of 2501 lightning fatality events in which 1927 people lost their lives and 20 569 people were affected. The increase in lightning fatality events in recent years is due to internet penetration and other measures of information gathering that result in lightning fatality reports reaching agencies collecting information. The high and low concentrations of loss and damage are mainly due to geographic distribution, population density, and economic activities. This study recommends the establishment of lightning early warning systems in the Nepal Himalayas to save life and property.

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Ronald L. Holle, William A. Brooks, and Kenneth L. Cummins

Abstract

National park visitors travel primarily to view natural features while outdoors; however, visits often occur in warmer months when lightning is present. This study uses cloud-to-ground flashes from 1999 to 2018 and cloud-to-ground strokes from 2009 to 2018 from the National Lightning Detection Network to identify lightning at the 46 contiguous United States national parks larger than 100 km2. The largest density is 6.10 flashes per kilometer squared per year within Florida’s Everglades, and the smallest is near zero in Pinnacles National Park. The six most-visited parks are Great Smoky Mountains, Grand Canyon, Rocky Mountain, Zion, Yosemite, and Yellowstone. For each of these parks, lightning data are described by frequency and location as well as time of year and day. The four parks west of the Continental Divide have most lightning from 1 July to 15 September and from 1100 to 1900 LST. Each park has its own spatial lightning pattern that is dependent on local topography. Deaths and injuries from lightning within national parks have the same summer afternoon dominance shown by lightning data. Most casualties occur to people visiting from outside the parks’ states. The most common activities and locations are mountain climbing, hiking, and viewing canyons from overlooks. Lightning fatality risk, the product of areal visitor and CG flash densities, shows that many casualties are not in parks with high risk, while very small risk indicates parks where lightning awareness efforts can be minimized. As a result, safety advice should focus on specific locations such as canyon rims, mountains, and exposed high-altitude roads where lightning-vulnerable activities are engaged in by many visitors.

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Majid Shafiee-Jood, Tatyana Deryugina, and Ximing Cai

Abstract

Forecast valuation studies play a key role in understanding the determinants of the value of weather and climate forecasts. Such understanding provides opportunities to increase the value that users can obtain from forecasts, which can in turn increase the use of forecasts. One of the most important factors that influences how users process forecast information and incorporate forecasts into their decision-making is trust in forecasts. Despite the evidence from empirical and field-based studies, modeling users’ trust in forecasts has not received much attention in the literature and is therefore the focus of our study. We propose a theoretical model of trust in information, built into a forecast valuation framework, to better understand 1) the role of trust in users’ processing of drought forecast information and 2) the dynamic process of users’ trust formation and evolution. Using a numerical experiment, we show that considering the dynamic nature of trust is critical in more realistic assessment of forecast value. We find that users may not perceive a potentially valuable forecast as such until they trust it enough, implying that exposure to even highly accurate forecasts may not immediately translate into forecast use. Ignoring this dynamic aspect could overestimate the economic gains from forecasts. Furthermore, the model offers hypotheses with regard to targeting strategies that can be tested with empirical and field-based studies and used to guide policy interventions.

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Manishka De Mel, William Solecki, Radley Horton, Ryan Bartlett, Abigail Hehmeyer, Shaun Martin, and Cynthia Rosenzweig

Abstract

Integrating climate risk information into resilience-building activities in the field is important to ensure that adaptation is based on the best available science. Despite this, many challenges exist when developing, communicating, and incorporating climate risk information. There are limited resources on how stakeholders perceive risks, use risk information, and what barriers exist to limit knowledge integration. This paper seeks to define the following: 1) What do conservation stakeholders consider to be the most significant climate risks they face now and possibly in the future? 2) What have been the most significant barriers to their using climate risk information? 3) What sources and types of knowledge would be most useful for these managers to overcome these barriers? A survey was conducted among stakeholders (n = 224) associated with World Wildlife Fund projects in tropical and subtropical countries. A very high proportion of stakeholders used climate risk information and yet faced integration-related challenges, which included too much uncertainty and the lack of a relevant scale for planning. The main factors preventing the use of climate risk information in decision-making were unavailability of climate risk information, no or limited financial or human resources available to respond, lack of organizational mandate or support, and no or limited institutional incentives. Comparing perceived current and future risks revealed a decline in concern for some future climate hazards. Survey respondents identified scientific reports, climate scientists, and online sources as the most useful information sources of climate risk information, while (i) maps and illustrations; (ii) scenarios format; and (iii) data tables, graphs, and charts were identified as user-friendly formats.

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Inez Z. Ponce de Leon

Abstract

Supertyphoon Haiyan hit the Philippines in 2013, causing massive damage and loss of lives. The media blamed the government for faulty warnings, including using the term “storm surge,” which people reportedly did not understand. As a result, the national agency tasked with disaster risk management recommended translating the term for better response in future storms. Such an approach shortchanges the complexity of risk construction and dismisses the possibility that different communities also have different understandings of risk. In this study, the researcher examined the special case of Coron, Palawan: a major tourist destination that is rarely hit by storms but that became the site of Haiyan’s last landfall. Guided by encoding–decoding theory, the researcher interviewed local government officials and carried out focus group discussions with representatives of two communities (whose names have been hidden under pseudonyms for this study): Central, close to the municipal center, and Island, a coastal village far away from potential aid and rescue. The researcher found a portrait of contrasts that split Coron: a mayor who surrendered all control and a risk management officer who planned for long-term hazard response—Island waiting for government instructions despite knowing about storm behavior and Central taking the initiative to create long-term solutions. Island also knew what storm surges were and did not need translation of the term. These findings show that risk constructions can differ even at the municipal level, which should prompt further research into the role of local knowledge in understanding risk and hazard warnings.

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Kelley M. Murphy, Eric C. Bruning, Christopher J. Schultz, and Jennifer K. 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 with tolerability thresholds to issue lightning warnings. These warnings were compared with warnings created for the same dataset using a more standard lightning safety approach that was based on National Lightning Detection Network (NLDN) total lightning within 5 n mi (1 n mi = 1.852 km) 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 (10 min)−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, whereas median down times were shorter for risk (10 min)−1 and risk (15 min)−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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Yajie Li, Amanda Lee Hughes, and Peter D. Howe

Abstract

Message diffusion and message persuasion are two important aspects of success for official risk messages about hazards. Message diffusion enables more people to receive lifesaving messages, and message persuasion motivates them to take protective actions. This study helps to identify win–win message strategies by investigating how an underexamined factor, message content that is theoretically important to message persuasion, influences message diffusion for official risk messages about heat hazards on Twitter. Using multilevel negative binomial regression models, the respective and cumulative effects of four persuasive message factors—hazard intensity, health risk susceptibility, health impact, and response instruction—on retweet counts were analyzed using a dataset of heat-related tweets issued by U.S. National Weather Service accounts. Two subsets of heat-related tweets were also analyzed: 1) heat warning tweets about current or anticipated extreme heat events and 2) tweets about nonextreme heat events. This study found that heat-related tweets that mentioned more types of persuasive message factors were retweeted more frequently, and so were two subtypes of heat-related tweets. Mentions of hazard intensity also consistently predicted increased retweet counts. Mentions of health impacts positively influenced message diffusion for heat-related tweets and tweets about nonextreme heat events. Mentions of health risk susceptibility and response instructions positively predicted retweet counts for tweets about nonextreme heat events and tweets about official extreme heat warnings, respectively. In the context of natural hazards, this research informs practitioners with evidence-based message strategies to increase message diffusion on social media. Such strategies also have the potential to improve message persuasion.

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Julia Linder and Victoria Campbell-Arvai

Abstract

In the midwestern United States, intensifying impacts from climate change necessitate adaptation by the agricultural sector. Tree fruit agriculture is uniquely vulnerable to climate change due to the long-lived nature of perennial systems, yet very few studies have addressed how fruit growers perceive climate change and are responding to climate risks. For this study, 16 semistructured interviews were conducted with Michigan tree fruit growers to understand how their climate change beliefs, beliefs about adaptive actions, and climate-related risk perceptions influence adaptation behaviors. While there was a great deal of uncertainty about the anthropogenic nature of climate change, growers generally agreed that unprecedented changes in climate and weather patterns were occurring. Because of a perception of little control over future climate impacts, most growers reactively adapted to climate risks that negatively impacted their orchards by implementing measures such as frost protection, irrigation, pesticides, and crop insurance. This study highlighted that while proactive adaptations such as crop diversification, planting new varieties, and improving soil health will be necessary to increase farm resilience in the future, growers were unable to justify making these changes due to their uncertainty about future climate changes. The findings from this study highlight the need for future outreach efforts by university extension agents, private agricultural advisors, and federal and state agency advisors to provide educational information on the long-term impacts of climate change in order to help growers increase the resilience of their farm in the face of future climate impacts.

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Abdulrahman Khamaj, Amin G. Alhashim, Vincent T. Ybarra, and Azham Hussain

Abstract

Communicating weather forecasts from the public perspective is essential for meeting people’s needs and enhancing their overall experiences. Because of the lack of cited work on the public’s behavior and perception of weather data and delivery sources in Middle Eastern countries such as Saudi Arabia (KSA), this study employs a cross-sectional questionnaire to fill the gap and apply the protective action decision model to non-Western individuals. The questionnaire examined respondents’ opinions about 1) the importance of weather forecast accessibility, 2) crucial weather features, and 3) available features on existing smartphone weather applications (apps) in KSA. The results showed that nearly all participants reported that their decisions of daily lives and activities were highly dependent on weather forecasts. Most participants thought weather forecast features are necessary. Although the most commonly used source for weather forecasts in KSA was smartphone apps, many participants responded that these apps were lacking specific weather functionalities (e.g., giving weather alerts to their exact location). Regression analyses found that KSA individuals who do not believe that weather forecasts are important are predicted by 1) not wanting any new features added to weather applications and 2) thinking that weather forecasts do not impact lives or property. This study’s findings can guide governmental and private weather agencies in KSA and other Middle Eastern or developing countries to better understand how to meet and communicate people’s weather needs.

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