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Kathleen Sherman-Morris
and
S. M. Asger Ali

Abstract

In-depth analysis of the content of broadcast tornado warning coverage is limited. Such analysis is important due to local television’s role as a key source for tornado warning information. This study attempts to fill gaps in our knowledge regarding broadcast coverage of tornado warnings by demonstrating how local television news stations’ coverage of tornadic events can be systematically analyzed to better understand this element of warning communication. We reviewed both visual and verbal content for information such as the prominence of specific radar products, the geographic scale of warning communication, and common themes in verbal communication. A combination of deductive and inductive coding approaches was used to summarize the verbal content of the broadcasts. We found that the stations heavily used radar products with reflectivity and velocity surpassing correlation coefficient. The geographic scale of mapped products (street, city/county, and state level) appeared to be related to the rural or urban nature of the area warned, which may have implications for how readily rural residents would be able to personalize tornado threats. Verbal content was very similar between the two stations. The theme of monitoring and updating conditions, which included processes such as zooming in and out, making adjustments, reinforcing conditions, and providing damage reports was the most frequent communication type, likely because weathercasters use these processes to both communicate the warning and also to help themselves understand the situation. The results can inform future studies examining the influence of specific elements of broadcast warning coverage on risk perception and protective actions.

Significance Statement

Television is a key source for receiving or confirming tornado warnings, but few studies have examined the content of broadcast warnings in depth. This study examined the visual and verbal content of broadcast tornado warnings on two local television stations. Radar products were used heavily, and street-level coverage was more common when a tornado affected a metropolitan area. Coverage was most common at the city/county level. Verbal content included many elements of effective warning communication but at times included jargon that may not be understood by viewers. The results can serve as a springboard for future research on the impacts of these elements on risk perception and response. It can also serve future research by distinguishing what viewers of severe weather broadcasts are exposed to that nonviewers are not.

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Zhi Li
,
Theresa Tsoodle
,
Mengye Chen
,
Shang Gao
,
Jiaqi Zhang
,
Yixin Wen
,
Tiantian Yang
,
Farina King
, and
Yang Hong

Abstract

Climate change has posed inequitable risks to different communities. Among communities of color in the United States, Native Americans stand out because 1) they desire resources to sustain resilient nations and 2) they have developed nature-based solutions through experiences with local climate-related challenges, which can provide deep insight for the whole society. Projection of climate risks for Native Americans is essential to assess future risks and support their climate-ready nations, yet there has been lack of useable information. In this study, we projected three climate hazards—heavy rainfall, 2-yr floods, and flash floods—for tribal nations in Oklahoma. To break down into tribal jurisdictions, we utilize a coupled regional climate model at 4 km and flash-flood forecast model at 1 km. A hazard–exposure–vulnerability risk framework is applied to integrate both climate and demographic changes in a high-emissions scenario. It is found that 1) Indigenous people are the most vulnerable community in Oklahoma; 2) heavy rainfall and 2-yr floods have marked increases in risks at 501.1% and 632.6%, respectively, while flash floods have a moderate increase (296.4%); 3) Native Americans bear 68.0%, 64.3%, and 64.0% higher risks in heavy rainfall, 2-yr flooding, and flash flooding, respectively, than the general population in Oklahoma; 4) in comparing climate and demographic changes, it is seen that population growth leads to greater climate hazard risks than does climate change; and 5) emerging tribal nations are projected to have 10 times as much population, resulting in great exposures to climate extremes. This study can raise awareness of the impact of climate changes and draw attention to address climate injustice issues for minoritized communities.

Significance Statement

This study examines the impact of climate change on a marginalized community—Native Americans in Oklahoma, home to 39 federally recognized tribal nations. We utilized the high-resolution climate simulation at 4-km resolution and hydrologic simulation at 1-km resolution to aggregate three climate extremes to tribal jurisdictions. We find that climate and demographic changes disproportionately put many Native Americans at risk. The heavy rainfall, 2-yr floods, and flash floods are all projected to have increased risks by 501.1%, 632.6%, and 296.4%, respectively. Those risks are 68.0%, 64.3%, and 64.0% higher than the state average for the general population, respectively. We urge proper attention to tribal nations to address climate injustice issues as a whole with the acknowledgment of their distinct relationships to their homelands as sovereign peoples.

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Elisabeth Kago Ilboudo Nébié
,
Alexandra Brewis
,
Amber Wutich
,
Yogo Pérenne
, and
Kadidiatou Magassa

Abstract

One of the most pressing and immediate climate concerns globally is inadequate and unsafe household water. The livelihoods of smallholder crop and livestock farmers are especially vulnerable to these challenges. Past research suggests that water insecurity is highly gendered, and women are theorized to be more aware of and impacted by water insecurity than men. Our study reengages this literature through a livelihood lens, comparing gendered perception of household water insecurity across crop and livestock subsistence modalities in a semiarid region of Burkina Faso in the Sahel region of West Africa, where water insecurity is closely intertwined with both seasonality and rainfall unpredictability. Our mixed-methods ethnographic study sampled matched men and women in households with water insecurity data collected from 158 coresident spousal pairs who engaged primarily in pastoralism or agriculture. Contrary to predictions from the existing literature, men engaged in livestock husbandry perceived greater water insecurity than matched women in the same household. We suggest this reflects men’s responsibility for securing water for the animals—which consume most of the household’s water among livestock farmers. In contrast, men engaged in cropping perceive less water insecurity than women in the same household, aligning with predictions from past research. Our findings suggest that the relationship between gender and water insecurity is more highly nuanced and related to livelihood strategies than previously recognized, with significant implications for how water insecurity is conceptualized theoretically and methodologically in the contexts of people’s everyday management and experience of the most immediate and proximate climate-related challenges.

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Daniela de Oliveira Maionchi
,
Adriano Carvalho Nunes e Araújo
,
Walter Aguiar Martins Jr.
,
Junior Gonçalves da Silva
, and
Danilo Ferreira de Souza

Abstract

Brazil presents the highest number of lightning-related deaths in the world. This study aimed to identify the key victims’ characteristics associated with such fatalities in Brazil and to develop a model that predicts the number of deaths as function of the victims’ data. The dataset provided by the Department of Informatics of the Unified Health System in Brazil (DATASUS) was analyzed and machine learning regression techniques were applied. The gradien-boosting regressor (GBR) model was found to be the most effective, achieving a prediction accuracy of 97%. Through the analysis of 34 initial variables, 10 variables were identified as having the greatest influence on the model’s outcomes. These variables included race, gender, age group, occupational accidents, education, and location of death. Understanding these characteristics is crucial for implementing targeted prevention and safety strategies in various regions, helping to mitigate the risk of lightning-related deaths worldwide. Additionally, the methodology used in this study can serve as a framework for similar research in different locations, allowing for the identification of important factors specific to each region. By adapting the machine learning regression techniques and incorporating local datasets, researchers can gain valuable insights into the determinants of lightning-related fatalities, enabling the development of effective prevention and safety measures tailored to specific geographical areas.

Significance Statement

This study presents a machine learning approach using the gradient-boosting regressor (GBR) method to estimate the weekly number of lightning-related deaths with an impressive 97% prediction accuracy. The research includes a comprehensive analysis of various factors, such as race, gender, age group, occupational accidents, education, and location of death, providing valuable insights for targeted preventive strategies and safety measures. The findings significantly contribute to understanding lightning-related fatalities in Brazil. The proposed machine learning model demonstrates a robust and accurate fit to the data, allowing for a comprehensive understanding of patterns and underlying trends in lightning fatalities.

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Ayobami Badiru Moreira
,
Ranyére Silva Nóbrega
,
Lucas Suassuna de A. Wanderley
, and
Andreas Matzarakis

Abstract

This study introduces the urban heat island vulnerability index (UHIVI) for Recife, Brazil, the center of the most populated metropolitan area in the Northeast region. The index, encompassing sensitivity, adaptive capacity, and exposure, integrates demographic data through factor analysis to derive a social vulnerability index (SVI). Urban heat island (UHI) intensity data addresses exposure, enabling a comprehensive analysis of both the physical and social dimensions of the city. Results reveal heightened UHI exposure in the city center and coastal areas, correlating with higher urbanization density. However, populations in most areas of these regions demonstrated higher adaptive capacities, translating to lower UHI vulnerability. Conversely, less-discussed areas in traditional UHI approaches, with limited adaptive capacity and heightened sensitivity, emerge, shedding light on previously overlooked urban vulnerabilities. Regions near the city center featuring irregular settlements prove most susceptible to UHI. Illiteracy, aging demographics, and local environmental conditions emerge as the three main factors contributing to UHIVI. The index’s application unveils spatial complexities and inequalities, offering urban planners a nuanced understanding of the city. This comprehensive insight aids in policy development and decision-making, empowering planners to address urban disparities effectively. The UHIVI thus emerges as a valuable tool for understanding the challenges of urban planning, fostering more resilient and equitable urban development.

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Anuska Narayanan
,
Brad G. Peter
, and
David Keellings

Abstract

In recent decades, changes in precipitation, temperature, and air circulation patterns have led to increases in the occurrences of extreme weather events. These events can have devastating effects on communities causing destruction to property and croplands, as well as negative impacts on public health. As changes in the climate are projected to continue throughout the remainder of the twenty-first century, the ability for a community to plan for extreme weather events is essential to its survival. In this paper, we introduce a new index for examining the potential impacts of climate extremes on community resilience throughout the conterminous United States at the county level. We use an established disaster resilience index (baseline resilience indicators for communities) together with a revised version of the U.S. climate extremes index to create a combined measure of climate resilience—the climate extremes resilience index (CERI). To demonstrate the index, we test it on the 2021 Pacific Northwest heat wave, a 1000-yr weather event made 150 times as likely by climate change. To promote the use of the index, we also introduce a Google Earth Engine web app to calculate and map the CERI for the CONUS. By developing a web application for calculating the CERI, we expand the use of climate-resilience indices beyond theoretical applications. We anticipate that this tool and the CERI could be useful for policy makers to plan for climate-related disasters, as well as help the public with understanding and visualizing the impacts of extreme climatic events.

Open access
Brittany S. Harris
,
Mark Brunson
, and
Peter D. Howe

Abstract

Domestic climate migration is likely to increase in the future, but we know little about public perceptions and attitudes about climate migrants and migration. Understanding how perceptions and attitudes are formed is a critical task in assessing public support for assistance policies and developing effective messaging campaigns. In this paper, we aim to better understand how the U.S. public perceives domestic climate migrants. We use novel survey data to identify the relationship between climate change risk perceptions and awareness of “climate migrants,” belief that domestic climate migration is currently happening in the United States, perceived voluntariness of domestic climate migrant relocation, and support for the development of assistance programs for domestic climate migrants. We utilize a large, nationally representative panel of U.S. adults (N = 4074) collected over three waves in 2022. We find that climate change risk perceptions and perceptions of whether migration is voluntary are key drivers of perceptions and attitudes toward domestic climate migrants. We provide key suggestions to policy makers and decision-makers to improve outcomes for host and migrant communities.

Significance Statement

This study illuminates factors that influence the how the public forms perceptions and attitudes about domestic climate migrants in the United States. For the first time, we offer insight into the drivers of public opinion toward domestic climate migrants and migration. Our results indicate that the various perceptions of climate migrants are largely driven by preexisting climate change risk perceptions and respondent characteristics. Our findings create a new connection with the existing literature on climate change risk perceptions and offer an opportunity for decision-makers and policy makers to create effective messaging campaigns on topics related to domestic climate migration in the United States.

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Jennifer Collins
,
Elizabeth A. Dunn
,
Rashida K. Jones
,
Amy Polen
,
Nagashree R. Rao
,
Stephen Murphy
, and
Mark Welford

Abstract

During peak disease transmission in 2021, the compounding threat posed by the pandemic and hurricane season required coastal states to understand evacuation behaviors during a major hurricane to inform the planning process. While research relating to hurricane evacuation behavior and perceptions of risk has increased since the start of the pandemic, there is minimal understanding of how perceptions have changed now the COVID-19 vaccine is available. A total of 1075 individuals across seven U.S. coastal states participated in a study on evacuation intentions postvaccine availability. Findings revealed that most survey participants (50.9%) preferred to stay home if a major hurricane threatened their area, and only 3.9% would evacuate to a public shelter. Approximately half (56.2%) of individuals viewed the risk of being in a shelter as more dangerous than enduring hurricane hazards. When considering shelter use, nearly half of respondents (49.4%) stated they would evacuate to a shelter before the pandemic; now, only one-third (34.3%) would consider evacuating to a shelter during the pandemic. Statistically significant findings include the relationship between those who lived in evacuation zones A or B (25.5%) and the choice to shelter in place at home (40.5%) or evacuate to a hotel (36.9%). There was a statistically significant relationship between the level of education and choosing to evacuate to a hotel. Additionally, the influence of pet ownership on evacuation decision-making was found to be statistically significant. Officials can use the results of this study to strengthen community preparedness and planning strategies across diverse populations.

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Free access
Renie Oelviani
,
Witono Adiyoga
,
I Gede Mahatma Yuda Bakti
,
Tota Suhendrata
,
Afrizal Malik
,
Chanifah Chanifah
,
Samijan Samijan
,
Dewi Sahara
,
Himawan Arif Sutanto
,
Munir Eti Wulanjari
,
Budi Utomo
,
Arif Susila
,
Ratih Kurnia Jatuningtyas
, and
Yennita Sihombing

Abstract

Climate change has negatively affected agricultural productivity in Indonesia. This study conducted a bibliometric analysis of the literature on soil salinity caused by climate change, discussed the impact of soil salinity on Indonesian agriculture, examined various strategies for adaptation to salinity, and delivered some ideas for future research. An analysis of 39 identified Scopus articles related to farmers’ vulnerability, adaptation, and practices was carried out. This study was performed in November 2022 and employed Bibliometrix R package and VOSviewer software. Findings show that salinity has left Indonesia’s agriculture vulnerable to reduced food production, especially for small-scale farmers losing crop yields and land. Various adaptation measures have been initiated, such as restoring soil fertility and using saline-resistant varieties. Irrigation facilities improvements have also been carried out to reduce the risks of soil salinity expansion. Farmers also try social action measures, such as selling assets, borrowing money for daily needs, and even changing jobs. However, for farmers to survive and sustain their businesses, any such measures need to produce satisfactory results. A review of the existing literature reveals a lack of soil salinity studies in Indonesia, which simultaneously points to research gaps not only on the issue of the impact of salinity on income and the vulnerability of small farmers but also on the development of adaptation strategies to address salinity due to climate change.

Significance Statement

Soil salinization caused by climate change is a disastrous problem in Indonesia’s coastal areas that presents a major challenge to the productivity of rice agriculture and difficulties in addressing sustainable food security. To provide researchers with a clear understanding of the current emphasis and future trends in climate change–induced salinity research, systematically analyzing the relevant literature in the existing research area is necessary. The bibliometric analysis in this study shows that research on salinity due to climate change in Indonesia still needs to be completed. Further comprehensive studies to find a focus for managing coastal soil salinity are urgently required to reduce vulnerability and increase adaptation to salinity due to climate change.

Open access