Kelsey N. Ellis

Association of weekly suicide rates with temperature anomalies in two different climate types

Annual suicide deaths outnumber the total deaths from homicide and war combined. Suicide is a complex behavioral endpoint, and a simple cause-and-effect model seems highly unlikely, but relationships with weather could yield important insight into the biopsychosocial mechanisms involved in suicide deaths. This study has been designed to test for a relationship between air temperature and suicide frequency that is consistent enough to offer some predictive abilities. Weekly suicide death totals and anomalies from Toronto, Ontario, Canada (1986–2009) and Jackson, Mississippi, USA (1980–2006) are analyzed for relationships by using temperature anomaly data and a distributed lag nonlinear model. For both analysis methods, anomalously cool weeks show low probabilities of experiencing high-end suicide totals while warmer weeks are more likely to experience high-end suicide totals. This result is consistent for Toronto and Jackson. Weekly suicide totals demonstrate a sufficient association with temperature anomalies to allow some prediction of weeks with or without increased suicide frequency. While this finding alone is unlikely to have immediate clinical implications, these results are an important step toward clarifying the biopsychosocial mechanisms of suicidal behavior through a more nuanced understanding of the relationship between temperature and suicide.

Heat and Humidity in the City: Neighborhood Heat Index Variability in a Mid-Sized City in the Southeastern United States

Daily weather conditions for an entire city are usually represented by a single weather station, often located at a nearby airport. This resolution of atmospheric data fails to recognize the microscale climatic variability associated with land use decisions across and within urban neighborhoods. This study uses heat index, a measure of the combined effects of temperature and humidity, to assess the variability of heat exposure from ten weather stations across four urban neighborhoods and two control locations (downtown and in a nearby nature center) in Knoxville, Tennessee, USA. Results suggest that trees may negate a portion of excess urban heat, but are also associated with greater humidity. As a result, the heat index of locations with more trees is significantly higher than downtown and areas with fewer trees. Trees may also reduce heat stress by shading individuals from incoming radiation, though this is not considered in this study. Greater amounts of impervious surfaces correspond with reduced evapotranspiration and greater runoff, in terms of overall mass balance, leading to a higher temperature, but lower relative humidity. Heat index and relative humidity were found to significantly vary between locations with different tree cover and neighborhood characteristics for the full study time period as well as for the top 10% of heat index days. This work demonstrates the need for high-resolution climate data and the use of additional measures beyond temperature to understand urban neighborhood exposure to extreme heat, and expresses the importance of considering vulnerability differences among residents when analyzing neighborhood-scale impacts.

Summer temperature variability across four urban neighborhoods in Knoxville, Tennessee, USA

The urban heat island (UHI) is a well-documented effect of urbanization on local climate, identified by higher temperatures compared to surrounding areas, especially at night and during the warm season. The details of a UHI are city-specific, and microclimates may even exist within a given city. Thus, investigating the spatiotemporal variability of a city’s UHI is an ongoing and critical research need. We deploy ten weather stations across Knoxville, Tennessee, to analyze the city’s UHI and its differential impacts across urban neighborhoods: two each in four neighborhoods, one in more dense tree cover and one in less dense tree cover, and one each in downtown Knoxville and Ijams Nature Center that serve as control locations. Three months of temperature data (beginning 2 July 2014) are analyzed using paired-sample t tests and a three-way analysis of variance. Major findings include the following: (1) Within a given neighborhood, tree cover helps negate daytime heat (resulting in up to 1.19 ∘C lower maximum temperature), but does not have as large of an influence on minimum temperature; (2) largest temperature differences between neighborhoods occur during the day (0.38–1.16 ∘C difference), but larger differences between neighborhoods and the downtown control occur at night (1.04–1.88 ∘C difference); (3) presiding weather (i.e., air mass type) has a significant, consistent impact on the temperature in a given city, and lacks the differential impacts found at a larger-scale in previous studies; (4) distance from city center does not impact temperature as much as land use factors. This is a preliminary step towards informing local planning with a scientific understanding of how mitigation strategies may help minimize the UHI and reduce the effects of extreme weather on public health and well-being.

Spatiotemporal patterns of extreme hurricanes impacting US coastal cities

US coastal cities are regularly subjected to destruction by tropical cyclones. The risk of tropical cyclone winds varies along the length of the coastline. We analyze landfalling North Atlantic basin tropical cyclones whose intensities are considered extreme relative to their landfall location. To be considered extreme, a tropical cyclone’s wind speed must exceed the 50-year return level for a given city. Of interest is the spatial and temporal patterns of these extreme hurricane wind events for fifteen coastal cities, which are organized into four coastal regions: Northeast Atlantic, Southeast Atlantic, Florida, and Gulf. Findings suggest that extreme hurricanes along the Florida and Atlantic coasts cluster in time, specifically decades, while there is no temporal clustering detected along the Gulf. Atlantic coast hurricane clusters are in part due to the likelihood of one intense hurricane impacting multiple coastal cities, which is unlikely to happen along the Gulf due to the alignment of the coast. It is also unlikely for an intense hurricane to impact multiple Florida cities as an extreme hurricane, suggesting a physical mechanism enables the temporal clustering seen here. The results of this work advocate for annual and decadal hurricane risk to include: (1) the likelihood of temporal clusters of extreme hurricanes along the Atlantic and Florida coasts and (2) extreme hurricanes impacting multiple cities along the Atlantic coast.

Experiences of Urban Environmental Conditions in Socially and Economically Diverse Neighborhoods

ABSTRACT Environmental conditions can vary widely in urban areas. Temperature, green space, air quality, and other parameters may have different patterns among and within cities. These conditions may also be experienced and perceived by residents in different ways, with implications for community development and social justice in the context of environmental change. This study examines in-depth interviews (N = 20) with residents from socially and economically diverse neighborhoods to understand this variability at a more meaningful scale than typically examined in the literature. Implications for social work, community development, and multidisciplinary efforts in the pressing area of environmental change are discussed.

Tennessee tornado climate: a comparison of three cities

Tornado frequency characteristics and human vulnerability are assessed within 100 km of three major Tennessee cities (Nashville, Memphis, and Knoxville) between 1950 and 2013. Focusing on cities and their surrounding areas provides insight on tornado characteristics across different longitudinal portions of the state while also diminishing bias due to underreported tornadoes in rural areas. Nashville reported the most tornadoes between 1950 and 2013 (426), followed by Memphis (390), and Knoxville (176). Knoxville and Nashville tornadoes occurred on fewer days, while Memphis’s tornadoes were spread across more tornado days. Spring was the most active season for tornadoes, but Memphis still experienced approximately 25 percent of tornadoes in the winter, a season prone to nocturnal tornadoes. Memphis also averages the most tornado-related fatalities (four per year). Future work should investigate if social factors are the primary cause of increased vulnerability in Memphis, or if the higher number of tornado days, especially during the winter, plays a role in the increased fatalities seen there. The occurrence of more tornadoes across fewer days and increased winter activity may impact human preparedness and response.

Using Synthetic Tropical Cyclones to Characterize Extreme Hurricanes Affecting Charleston, South Carolina

AbstractThe characteristics and conditions favoring extreme hurricanes remain largely unknown because of their small number in the observational record. Synthetic tracks are capable of providing a large, representative sample of these events, which provides an opportunity to further understanding of extreme characteristics as compared with those of more common tropical cyclones. The authors compare 300 synthetic extreme (100-yr event, ≥48.9 m s−1) and 300 common (5-yr event, ≤33.6 m s−1) tropical cyclones for Charleston, South Carolina, for differences in spatial, temporal, and other characteristics. Results suggest that extreme hurricanes have a more-defined spatial and temporal behavior, generally forming off the coast of Africa and making a direct landfall at Charleston. Common tropical cyclones sometimes make prior landfalls, may approach from either the Gulf of Mexico or the Atlantic Ocean, and often decay well before reaching Charleston. They are likely to occur through much of the hurricane season,...

Hurricane risk variability along the Gulf of Mexico Coastline

Hurricane risk characteristics are examined across the U. S. Gulf of Mexico coastline using a hexagonal tessellation. Using an extreme value model, parameters are collected representing the rate or λ (frequency), the scale or σ (range), and the shape or ξ (intensity) of the extreme wind distribution. These latent parameters and the 30-year return level are visualized across the grid. The greatest 30-year return levels are located toward the center of the Gulf of Mexico, and for inland locations, along the borders of Louisiana, Mississippi, and Alabama. Using a geographically weighted regression model, the relationship of these parameters to sea surface temperature (SST) is found to assess sensitivity to change. It is shown that as SSTs increase near the coast, the frequency of hurricanes in these grids decrease significantly. This reinforces the importance of SST in areas of likely tropical cyclogenesis in determining the number of hurricanes near the coast, along with SSTs along the lifespan of the storm, rather than simply local SST. The range of hurricane wind speeds experienced near Florida is shown to increase with increasing SSTs (insignificant), suggesting that increased temperatures may allow hurricanes to maintain their strength as they pass over the Florida peninsula. The modifiable areal unit problem is assessed using multiple grid sizes. Moran’s I and the local statistic G are calculated to examine spatial autocorrelation in the parameters. This research opens up future questions regarding rapid intensification and decay close to the coast and the relationship to changing SSTs.

Tornado Warnings at Night: Who Gets the Message?

AbstractNocturnal tornadoes are a public health threat, over twice as likely to have fatalities as tornadoes during the day. While tornado warning receipt is an important factor in models of indivi...

Health Impacts of Extreme Weather Events: Exploring Protective Factors with a Capitals Framework

ABSTRACT Purpose: Extreme weather events are increasing with climate change. The physical and mental health of people served by social workers may be especially at risk from these hazards. This exploratory study examines if specific types of human, financial, physical, and social capital are associated with health impacts from excessive summer heat and extreme winter weather. Method: Data from resident surveys (N = 424) in low- and moderate-income areas of a Southeastern US city are analyzed with descriptive statistics and logistic regression. Results: Key findings are that health status and social cohesion are negatively associated with health impacts of summer heat and winter extremes. Conclusion: Further study is needed of how specific types of capital may help people cope with a changing climate. Social capital may be a particularly relevant area for social work to address within the pressing issue of climate, weather, and the health of vulnerable groups.