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Alexander J. Ross, Ryan C. Grow, Lauren D. Hayhurst, Haley A. MacLeod, Graydon I. McKee, Kyle W. Stratton, Marissa E. Wegher, and Michael D. Rennie

Abstract

Groundhog Day is a widespread North American ritual that marks the onset of spring, with festivities centered around animals that humans believe have abilities to make seasonal predictions. Yet, the collective success of groundhog Marmota monax prognosticators has never been rigorously tested. Here, we propose the local climate-predicted phenology of early blooming spring plants (Carolina spring beauty, or Claytonia caroliniana, which overlaps in native range with groundhogs) as a novel and relevant descriptor of spring onset that can be applied comparatively across a broad geographical range. Of 530 unique groundhog-year predictions across 33 different locations, spring onset was correctly predicted by groundhogs exactly 50% of the time. While no singular groundhog predicted the timing of spring with any statistical significance, there were a handful of groundhogs with notable records of both successful and unsuccessful predictions: Essex Ed (Essex, Connecticut), Stonewall Jackson (Wantage, New Jersey), and Chuckles (Manchester, Connecticut) correctly predicted spring onset over 70% of the time. By contrast, Buckeye Chuck (Marion, Ohio), Dunkirk Dave (Dunkirk, New York), and Holland Huckleberry (Holland, Ohio) made incorrect predictions over 70% of the time. The two most widely recognized and long-tenured groundhogs in their respective countries—Wiarton Willie (Canada) and Punxsutawney Phil (United States)—had success rates of 54% and 52%, respectively, despite over 150 collective guesses. Using a novel phenological indicator of spring, this study determined, without a shadow of a doubt, that groundhog prognosticating abilities for the arrival of spring are no better than chance.

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Zoe Schroder and James B. Elsner

Abstract

Environmental variables are routinely used in estimating when and where tornadoes are likely to occur, but more work is needed to understand how tornado and casualty counts of severe weather outbreak vary with the larger-scale environmental factors. Here the authors demonstrate a method to quantify “outbreak”-level tornado and casualty counts with respect to variations in large-scale environmental factors. They do this by fitting negative binomial regression models to cluster-level environmental data to estimate the number of tornadoes and the number of casualties on days with at least 10 tornadoes. Results show that a 1000 J kg−1 increase in CAPE corresponds to a 5% increase in the number of tornadoes and a 28% increase in the number of casualties, conditional on at least 10 tornadoes and holding the other variables constant. Further, results show that a 10 m s−1 increase in deep-layer bulk shear corresponds to a 13% increase in tornadoes and a 98% increase in casualties, conditional on at least 10 tornadoes and holding the other variables constant. The casualty-count model quantifies the decline in the number of casualties per year and indicates that outbreaks have a larger impact in the Southeast than elsewhere after controlling for population and geographic area.

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Brooke Fisher Liu and Anita Atwell Seate

Abstract

Since the tragic tornado outbreaks in central Alabama and Joplin, Missouri, in 2011, the National Weather Service (NWS) has increasingly emphasized the importance of supporting community partners who help to protect public safety. Through impact-based decision support services (IDSS), NWS forecasters develop relationships with their core partners to meet their partners’ decision-making needs. IDSS presents a fundamental shift in NWS forecasting through highlighting the importance of connecting with partners instead of simply providing partners with forecasts. A critical challenge to the effective implementation of IDSS is a lack of social science research evaluating the success of IDSS. This paper addresses this gap through a cross-sectional survey with 119 NWS forecasters and managers in the central and southern regions of the United States. Findings uncover how NWS forecasters and management team members evaluate the importance of IDSS. Findings also provide a new instrument for NWS field offices to assess and improve their relationships with core partners.

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Adrian Brügger, Christina Demski, and Stuart Capstick

Abstract

The proportion of the world’s population exposed to above-average monthly temperatures has been rising consistently in recent decades and will continue to grow. This and similar trends make it more likely that people will personally experience extreme weather events and seasonal changes related to climate change. A question that follows from this is to what extent experiences may influence climate-related beliefs, attitudes, and the willingness to act. Although research is being done to examine the effects of such experiences, many of these studies have two important shortcomings. First, they propose effects of experiences but remain unclear on the psychological processes that underlie those effects. Second, if they do make assumptions about psychological processes, they do not typically corroborate them with empirical evidence. In other words, a considerable body of research in this field rests on relatively unfounded intuitions. To advance the theoretical understanding of how experiences of climate change could affect the motivation to act on climate change, we introduce a conceptual framework that organizes insights from psychology along three clusters of processes: 1) noticing and remembering, 2) mental representations, and 3) risk processing and decision-making. Within each of these steps, we identify and explicate psychological processes that could occur when people personally experience climate change, and we formulate theory-based, testable hypotheses. By making assumptions explicit and tying them to findings from basic and applied research from psychology, this paper provides a solid basis for future research and for advancing theory.

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Hua He, Guorong Chai, Yana Su, Yongzhong Sha, Shengliang Zong, and Hairong Bao

Abstract

This study assessing the lag and interactive effects between the daily average temperature and relative humidity on respiratory disease (RD) morbidity in Lanzhou, China, using data from daily outpatient visits for RD between 2014 and 2017 and meteorological and pollutant data during the same period analyzed with Poisson generalized linear model and distributed lag nonlinear models; the effects are further explored by classifying the RD by gender, age, and disease type. The results showed that the effect of temperature and relative humidity on outpatient visits of different populations and types of RD is nonlinear, with a significant lag effect. Relative to 11°C, every 1°C decrease in temperature is associated with 10.98% [95% confidence interval (CI): 9.87%–12.11%] increase for total RD. Chronic obstructive pulmonary disease is affected only by low temperature, upper respiratory tract infection is affected by both low and high temperatures, and asthma is influenced by high temperature. When the relative humidity is less than 32%, every 1% decrease in relative humidity is associated with 6.00% (95% CI: 3.00%–9.11%) increase for total RD; relative humidity has different effects on the outpatient risk of different types of RD. Temperature and relative humidity have an obvious interactive effect on different types and populations of RD: when both temperature and humidity are at low levels, the number of outpatient visits for RD is higher. When the relative humidity is ≤50% and the temperature is ≤11°C, total RD outpatient visits increase by 4.502% for every 1°C drop in temperature; that is, a dry environment with low temperature has the most significant impact on RD.

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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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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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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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