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Paul Butke and Scott C. Sheridan

Abstract

This study investigated the relationship between weather and aggressive crime for the period from 1999 through 2004 for the city of Cleveland, Ohio. The majority of the analysis focused on meteorological summer (June–August), because this is the time when the most oppressive conditions occur. Citywide analysis (nonspatial) was performed for many temporal variations, which accounted for season, time of day, and day of week (weekend or weekday). The linear regression model explored the relationship between apparent temperature and aggressive crime counts. Results show that summer has the highest aggressive crime counts, while winter has the lowest crime counts. Aggressive crime generally increases linearly as apparent temperature increases, with nonaggravated assaults and domestic violence assaults having the largest response as the weather becomes hotter. The midday and early night hours (i.e., 0300–1200 LT) have the greatest significant findings relating apparent temperature to aggressive crime.

Further analysis was performed at the subcity level. A threshold of mean apparent temperature of 24°C was used in order to investigate spatial patterns of aggressive crime when it is “hot” compared to when it is “cold.” Overall, the spatial patterns of crime counts are minimally influenced by hotter weather. Despite the numerous different spatial analyses that were performed, there was no significant evidence suggesting that spatial patterns of aggressive crime are greatly affected by hotter weather. Rather, it appears that warmer weather brings relatively similar percentage increases in aggressive crime activity citywide. Further exploration and analysis of the weather–crime relationship could be of significant benefit to law enforcement officials and emergency response personnel, who increasingly use geographic information system (GIS)-based tools in their work to assist in determining where and when intervention is most beneficial.

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Wes P. Kent and Scott C. Sheridan

Abstract

Although it is often suggested that direct sunlight may affect a player’s vision, no published studies have analyzed this interaction. In this research, a variety of statistical tests were utilized to study how baseball variables respond to different cloud cover conditions. Data from more than 35 000 Major League Baseball games, spanning the seasons from 1987 through 2002, were studied. Eleven baseball variables covering batting, pitching, and fielding performance were included. Overall responses were analyzed, as well as individual responses at 21 different stadiums. Home and away team performances were evaluated separately. This study then synthesized the synergistic differences in offensive production, pitching performance, and fielding performance into changes in the “home field advantage.”

Offensive production generally declines during clearer-sky daytime games compared to cloudy-sky daytime games, while pitching performance increases as conditions become clearer. Strikeouts show the strongest response in the study, increasing from 5.95 per game during cloudy-sky conditions to 6.40 per game during clear-sky conditions. The number of errors per game increases during clear-sky daytime games compared to cloudy-sky daytime games, while fly outs increase and ground outs decrease between daytime and nighttime games, regardless of the amount of cloud cover. Results at individual stadiums vary, with some stadiums displaying a very strong association between baseball performance and changes in cloud cover, while others display a weak association. All of these impacts affect the home field advantage, with the home team winning 56% of the games played under clear skies compared to 52.3% of the games played under cloudy skies.

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Scott C. Sheridan and Laurence S. Kalkstein

Among all atmospheric hazards, heat is the most deadly. With such recent notable heat events as the Chicago Heat Wave of 1995, much effort has gone into redeveloping both the methods by which it is determined whether a day will be “oppressive,” as well as the mitigation plans that are implemented when an oppressive day is forecast to occur.

This article describes the techniques that have been implemented in the development of new synoptic-based heat watch–warning systems. These systems are presently running for over two dozen locations worldwide, including Chicago, Illinois; Toronto, Ontario, Canada; Rome, Italy; and Shanghai, China; with plans for continued expansion. Compared to traditional systems based on arbitrary thresholds of one or two meteorological variables, these new systems account for the local human response by focusing upon the identification of the weather conditions most strongly associated with historical increases in mortality. These systems must be constructed based on the premise that weather conditions associated with increased mortality show considerable variability on a spatial scale. In locales with consistently hot summers, weather/mortality relationships are weaker, and it is only the few hottest days each year that are associated with a response. In more temperate climates, relationships are stronger, and a greater percentage of days can be associated with an increase in mortality.

Considering the ease of data transfer via the World-Wide Web, the development of these systems includes Internet file transfers and Web page creation as components. Forecasts of mortality and recommendations to call excessive-heat warnings are available to local meteorological forecasters, local health officials, and other civic authorities, who ultimately determine when warnings are called and when intervention plans are instituted.

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Scott C. Sheridan, John F. Griffiths, and Richard E. Orville

Abstract

This study examines the relationship between cloud-to-ground (CG) lightning and surface precipitation using observations from six regions (each on the order of 10000 km2), April through October (1989–93), in the south-central United States. The relationship is evaluated using two different methods. First, regression equations are fit to the data, initially for only the CG lightning flash density and precipitation, and then with additional atmospheric and lightning parameters. Second, days are categorized according to differences in the precipitation-to-CG lightning ratio; the same additional parameters are then examined for differences occurring within each category.

Results show that the relationship between CG lightning and surface precipitation is highly variable; r2 coefficients range from 0.121 in Baton Rouge to 0.601 in Dallas. A measure of the positive CG lightning flash density is the best addition to the model, statistically significant in all regions. When days are categorized, the percentage of lightning that is positive shows the most significant differences between categories, ranging from <4% on days with a “low” precipitation-to-CG lightning ratio, to 12%–36% on days with a “high” ratio. Other lightning parameters give less significant results; however, three atmospheric parameters (CAPE, lifted index, and Showalter index) do show a significant trend suggesting that there is much less instability in the atmosphere on “high” ratio days than on “low” ratio days.

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Scott C. Sheridan, Douglas E. Pirhalla, Cameron C. Lee, and Varis Ransibrahmanakul

Abstract

Coastal ocean ecosystems are impacted by atmospheric conditions and events, including episodic severe systems such as hurricanes as well as more regular seasonal events. The complexity of the atmosphere–ocean relationship makes establishing concrete connections difficult. In this paper, this relationship is assessed through synoptic climatological methods, a technique well established in applied climatological research but heretofore rarely used in assessing coastal ocean water quality and ecological status. Historical sea level pressure data are used to define 10 circulation patterns across the southeastern United States and adjacent Gulf of Mexico, based on the spatial pattern of sea level pressure, which can then be associated with the presence of cyclones, precipitation, and wind stress. The frequency of these patterns, and their deviation from climatological means, is then compared with Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chlorophyll observations over the Florida Bay and south Florida shelf for the period 1997–2010. Several circulation patterns indicative of cyclonic activity over the broader region are associated with increased chlorophyll levels in the study area, while several other patterns, indicative of anticyclonic conditions, are associated with decreased chlorophyll levels. These relationships are spatially and temporally variable, generally with stronger correlations observed in winter and spring, and farther north in the study region when compared with more southern locations near the Florida Keys. The results here demonstrate the potential of using synoptic analysis and derived statistics for tracking and modeling changes in chlorophyll and other indicators related to water quality and biological health.

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Douglas E. Pirhalla, Cameron C. Lee, Scott C. Sheridan, and Varis Ransibrahmanakul

Abstract

Anomalous sea levels along the mid-Atlantic and South Atlantic coasts of the United States are often linked to atmosphere–ocean dynamics, remote- and local-scale forcing, and other factors linked to cyclone passage, winds, waves, and storm surge. Herein, we examine sea level variability along the U.S. Atlantic coast through satellite altimeter and coastal tide gauge data within the context of synoptic-scale weather pattern forcing. Altimetry data, derived from sea level anomaly (SLA) data between 1993 and 2019, were compared with self-organizing map (SOM)-based atmospheric circulation and surface wind field categorizations to reveal spatiotemporal patterns and their interrelationships with high-water-level conditions at tide gauges. Regional elevated sea level patterns and variability were strongly associated with synergistic patterns of atmospheric circulation and wind. Recurring atmospheric patterns associated with high-tide flooding events and flood risk were identified, as were specific regional oceanographic variability patterns of SLA response. The incorporation of combined metrics of wind and circulation patterns further isolate atmospheric drivers of high-tide flood events and may have particular significance for predicting future flood events over multiple spatial and temporal scales.

Significance Statement

Mean sea level and minor to moderate coastal flood events, also called blue-sky or high-tide floods, are increasing along many U.S. coastlines. While the drivers of such events are numerous, here we identified key contributing weather patterns and environmental factors linked to increased risk of regional and local high-water conditions along the Atlantic coast. Our results indicate that the predictability of elevated sea levels and high-tide floods is highly dependent upon atmospheric drivers including wind and circulation patterns and, if applied in a tested modeling framework, may prove useful for predicting future floods at various time scales.

Open access
Scott C. Sheridan, P. Grady Dixon, Adam J. Kalkstein, and Michael J. Allen

Abstract

Much research has shown a general decrease in the negative health response to extreme heat events in recent decades. With a society that is growing older, and a climate that is warming, whether this trend can continue is an open question. Using eight additional years of mortality data, we extend our previous research to explore trends in heat-related mortality across the United States. For the period 1975–2018, we examined the mortality associated with extreme-heat-event days across the 107 largest metropolitan areas. Mortality response was assessed over a cumulative 10-day lag period following events that were defined using thresholds of the excess heat factor, using a distributed-lag nonlinear model. We analyzed total mortality and subsets of age and sex. Our results show that in the past decade there is heterogeneity in the trends of heat-related human mortality. The decrease in heat vulnerability continues among those 65 and older across most of the country, which may be associated with improved messaging and increased awareness. These decreases are offset in many locations by an increase in mortality among men 45–64 (+1.3 deaths per year), particularly across parts of the southern and southwestern United States. As heat-warning messaging broadly identifies the elderly as the most vulnerable group, the results here suggest that differences in risk perception may play a role. Further, an increase in the number of heat events over the past decade across the United States may have contributed to the end of a decades-long downward trend in the estimated number of heat-related fatalities.

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Melissa C. K. Phillips, Adam B. Cinderich, Jennifer L. Burrell, Jennifer L. Ruper, Rachel G. Will, and Scott C. Sheridan

Abstract

Climate change is currently a topic of debate that is discussed not only within the physical science community but also by those in policy. Outside of these communities lies the American public, often not seeking out climate change research, but rather ingesting information interpreted by a third party, most likely through a political lens. Given the increased attention to natural disasters, one area of concern is the possible relationship between climate change and natural disasters. An assessment of the public’s opinion on this relationship has seen minimal research and none regarding college students. College students are a unique subset of the populace for their age, media sensitivity, and possible future in policy or research. This study surveyed college students in geography courses at Kent State University regarding their opinion of the effect of climate change on various natural disasters, while given examples of recently occurring natural disasters. The natural disasters included both atmospheric-related and nonatmospheric-related phenomena. The results show similar responses for those natural disasters that are atmospheric related. However, disparities exist between atmospheric-related and nonatmospheric-related natural disasters, illustrating a lack of knowledge between climate change and nonatmospheric natural disasters, especially tsunamis. Finally, females were found more likely to agree with the effect of climate change on natural disasters, while males were more likely to disagree.

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Erik T. Smith, Cameron C. Lee, Brian B. Barnes, Ryan E. Adams, Douglas E. Pirhalla, Varis Ransibrahmanakul, Chuanmin Hu, and Scott C. Sheridan

Abstract

A historical water clarity index (K d index or KDI) was developed through the use of satellite-derived and validated diffuse light attenuation (K d; m−1) for each of the Great Lakes (and subbasins) on a daily level from 1998 to 2015. A statistical regionalization was performed with monthly level KDI using k-means clustering to subdivide the Great Lakes into regions with similar temporal variability in water clarity. The KDI was then used to assess the relationship between water clarity and atmospheric circulation patterns and stream discharge. An artificial neural-network-based self-organized map data reduction technique was used to classify atmospheric patterns using four atmospheric variables: mean sea level pressure, 500-hPa geopotential heights, zonal and meridional components of the wind at 10 m, and 850-hPa temperature. Stream discharge was found to have the strongest relationship with KDI, suggesting that sediments and dissolved matter from land runoffs are the key factors linking the atmosphere to water clarity in the Great Lakes. Although generally lower in magnitude than stream discharge, atmospheric circulation patterns associated with increased precipitation tended to have stronger positive correlations with KDI. With no long-range forecasts of stream discharge, the strong relationship between atmospheric circulation patterns and stream discharge may provide an avenue to more accurately model water clarity on a subseasonal-to-seasonal time scale.

Free access
David R. Perkins IV, Jennifer Vanos, Christopher Fuhrmann, Michael Allen, David Knight, Cameron C. Lee, Angela Lees, Andrew Leung, Rebekah Lucas, Hamed Mehdipoor, Sheila Tavares Nascimento, Scott Sheridan, and Jeremy Spencer
Open access