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- Author or Editor: Jason Schatz x
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Abstract
Spatial and temporal variation in the urban heat island (UHI) effect from March 2012 through October 2013 was characterized using continuous temperature measurements from an array of up to 151 fixed sensors in and around Madison, Wisconsin, an urban area of population 407 000 surrounded by lakes and a rural landscape of agriculture, forests, wetlands, and grasslands. Spatially, the density of the built environment was the primary driver of temperature patterns, with local modifying effects of lake proximity and topographic relief. Temporally, wind speed, cloud cover, relative humidity, soil moisture, and snow all influenced UHI intensity, although the magnitude and significance of their effects varied by season and time of day. Seasonally, UHI intensities tended to be higher during the warmer summer months and lower during the colder months. Seasonal trends in monthly average wind speed and cloud cover tracked annual trends in UHI intensity, with clearer, calmer conditions that are conducive to the stronger UHIs being more common during the summer. However, clear, calm summer nights still had higher UHI intensities than clear, calm winter nights, indicating that some background factor, such as vegetation, shifted baseline UHI intensities throughout the year. The authors propose that regional vegetation and snow-cover conditions set seasonal baselines for UHI intensity and that factors like wind and clouds modified daily UHI intensity around that baseline.
Abstract
Spatial and temporal variation in the urban heat island (UHI) effect from March 2012 through October 2013 was characterized using continuous temperature measurements from an array of up to 151 fixed sensors in and around Madison, Wisconsin, an urban area of population 407 000 surrounded by lakes and a rural landscape of agriculture, forests, wetlands, and grasslands. Spatially, the density of the built environment was the primary driver of temperature patterns, with local modifying effects of lake proximity and topographic relief. Temporally, wind speed, cloud cover, relative humidity, soil moisture, and snow all influenced UHI intensity, although the magnitude and significance of their effects varied by season and time of day. Seasonally, UHI intensities tended to be higher during the warmer summer months and lower during the colder months. Seasonal trends in monthly average wind speed and cloud cover tracked annual trends in UHI intensity, with clearer, calmer conditions that are conducive to the stronger UHIs being more common during the summer. However, clear, calm summer nights still had higher UHI intensities than clear, calm winter nights, indicating that some background factor, such as vegetation, shifted baseline UHI intensities throughout the year. The authors propose that regional vegetation and snow-cover conditions set seasonal baselines for UHI intensity and that factors like wind and clouds modified daily UHI intensity around that baseline.
Abstract
Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks.
Significance Statement
Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location.
Abstract
Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks.
Significance Statement
Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location.
