Phoenix Regional Heat and Air Quality Knowledge Repository

The urban thermal environment varies not only from its rural surroundings but also within the urban area due to intra-urban differences in land-use and surface characteristics. Understanding the causes of this intra-urban variability is a first step in improving urban planning and development. Toward this end, a method for quantifying causes of spatial variability in the urban heat island has been developed. This paper presents the method as applied to a specific test case of Portland, Oregon. Vehicle temperature traverses were used to determine spatial differences in summertime ~2 m air temperature across the metropolitan area in the afternoon. A tree-structured regression model was used to quantify the land-use and surface characteristics that have the greatest influence on daytime UHI intensity. The most important urban characteristic separating warmer from cooler regions of the Portland metropolitan area was canopy cover. Roadway area density was also an important determinant of local UHI magnitudes. Specifically, the air above major arterial roads was found to be warmer on weekdays than weekends, possibly due to increased anthropogenic activity from the vehicle sector on weekdays. In general, warmer regions of the city were associated with industrial and commercial land-use. The downtown core, whilst warmer than the rural surroundings, was not the warmest part of the Portland metropolitan area. This is thought to be due in large part to local shading effects in the urban canyons.

This study addresses a classic sustainability challenge—the tradeoff between water conservation and temperature amelioration in rapidly growing cities, using Phoenix, Arizona and Portland, Oregon as case studies. An urban energy balance model— LUMPS (Local-Scale Urban Meteorological Parameterization Scheme)—is used to represent the tradeoff between outdoor water use and nighttime cooling during hot, dry summer months. Tradeoffs were characterized under three scenarios of land use change and three climate-change assumptions. Decreasing vegetation density reduced outdoor water use but sacrificed nighttime cooling. Increasing vegetated surfaces accelerated nighttime cooling, but increased outdoor water use by ~20%. Replacing impervious surfaces with buildings achieved similar improvements in nighttime cooling with minimal increases in outdoor water use; it was the most water-efficient cooling strategy. The fact that nighttime cooling rates and outdoor water use were more sensitive to land use scenarios than climate-change simulations suggested that cities can adapt to a warmer climate by manipulating land use.