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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.

Open access
K. Fagiewicz, P. Churski, T. Herodowicz, P. Kaczmarek, P. Lupa, J. Morawska-Jancelewicz, and A. Mizgajski

Abstract

This study determines the conditions and provides a recommendation for fostering cocreation for climate change adaptation and mitigation (CCA&M). In postulating that insufficient cocreation by stakeholders in the quadruple helix model is an important factor contributing to the low effectiveness of climate actions in the regions, we have focused our research on identifying real stakeholder engagement in climate action and identifying the needs, barriers, and drivers for strengthening the cocreation process. We identified the needs for action highlighted by stakeholders as having an impact on reducing barriers and stimulating drivers. We treated the identified needs for action as deep leverage points (intent and design) focused on three realms—knowledge, values, and institutions—in which engagement and cocreation can be strengthened and have the potential to increase the effectiveness of climate action taken by stakeholders within our quadruple helix. We recommend knowledge-based cocreation, which puts the importance of climate action in the value system and leads to paradigm reevaluation. The implementation of the identified needs for action requires the support of institutions, whereby they develop standards of cooperation and mechanisms for their implementation as a sustainable framework for stakeholder cooperation. The research has proved how the quadruple helix operates for climate action in the Poznań Agglomeration. We believe that this case study can be a reference point for regions at a similar level of development, and the methods used and results obtained can be applied in similar real contexts to foster local stakeholders in climate action.

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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 (NEB) during the period from 1993 to 2013. Initially, we analyzed the spatial pattern of the incidence of events; subsequently, generalized additive models for location, scale, and shape were used to identify and estimate the magnitude of associations between factors. Results showed that droughts are the predominant disasters in 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, that is, 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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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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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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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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