To further evaluate the factors influencing public heat and air-quality health, a characterization of how urban areas affect the thermal environment, particularly in terms of the air temperature, is necessary. To assist public health agencies in ranking urban areas in terms of heat stress and developing mitigation plans or allocating various resources, this study characterized urban heat in California and quantified an urban heat island index (UHII) at the census-tract level (~1 km²). Multi-scale atmospheric modeling was carried out and a practical UHII definition was developed. The UHII was diagnosed with different metrics and its spatial patterns were characterized for small, large, urban-climate archipelago, inland, and coastal areas. It was found that within each region, wide ranges of urban heat and UHII exist. At the lower end of the scale (in smaller urban areas), the UHII reaches up to 20 degree-hours per day (DH/day; °C.hr/day), whereas at the higher end (in larger areas), it reaches up to 125 DH/day or greater. The average largest temperature difference (urban heat island) within each region ranges from 0.5–1.0 °C in smaller areas to up to 5 °C or more at the higher end, such as in urban-climate archipelagos. Furthermore, urban heat is exacerbated during warmer weather and that, in turn, can worsen the health impacts of heat events presently and in the future, for which it is expected that both the frequency and duration of heat waves will increase.

To identify and characterize localized urban heat- and cool-island signals embedded within the temperature field of a large urban-climate archipelago, fine-resolution simulations with a modified urbanized version of the WRF meteorological model were carried out as basis for siting fixed weather monitors and designing mobile-observation transects. The goal was to characterize variations in urban heat during summer in Los Angeles, California. Air temperatures measured with a shielded sensor mounted atop an automobile in the summers of 2016 and 2017 were compared to model output and also correlated to surface physical properties focusing on neighborhood-scale albedo and vegetation canopy cover. The study modeled and measured the temperature response to variations in surface properties that already exist in the real world, i.e., realistic variations in albedo and canopy cover that are attainable through current building and urban design practices. The simulated along-transect temperature from a modified urbanized WRF model was compared to the along-transect observed temperature from 15 mobile traverses in one area near downtown Los Angeles and another in an inland basin (San Fernando Valley). The observed transect temperature was also correlated to surface physical properties characterizations that were developed for input to the model. Both comparisons were favorable, suggesting that (1) the model can reliably be used in siting fixed weather stations and designing mobile-transect routes to characterize urban heat and (2) that except for a few cases with opposite co-varying influences, the correlations between observed temperature and albedo and between observed temperature and canopy cover were each negative, ranging from −1.0 to −9.0 °C per 0.1 increase in albedo and from −0.1 to −2.2 °C per 0.1 increase in canopy cover. Observational data from the analysis domains pointed to a wind speed threshold of 3 m/s. Below this threshold the variations in air temperature could be explained by land use and surface properties within a 500-m radius of each observation point. Above the threshold, air temperature was influenced by the properties of the surface within a 1-km upwind fetch. Of relevance to policy recommendations, the study demonstrates the significant real-world cooling effects of increasing urban albedo and vegetation canopy cover. Based on correlations between the observed temperature (from mobile transects) and surface physical properties in the study domains, the analysis shows that neighborhood-scale (500-m) cooling of up to 2.8 °C during the daytime can be achieved by increasing albedo. A neighborhood can also be cooled by up to 2.3 °C during the day and up to 3.3 °C at night by increasing canopy cover. The analysis also demonstrates the suitability of using fine-resolution meteorological models to design mobile-transect routes or site-fixed weather monitors in order to quantify urban heat and the efficacy of albedo and canopy cover countermeasures. The results also show that the model is capable of accurately predicting the geographical locations and the magnitudes of localized urban heat and cool islands. Thus the model results can also be used to devise urban-heat mitigation measures.

There exists a number of environmental and energy measures that, when deployed at urban scale, can directly impact energy use and emissions from power generation and indirectly affect the atmospheric environment which, in turn, impacts energy demand, emissions of greenhouse gas and ozone precursors and photochemical production of ozone. Atmospheric modeling is an important tool in evaluating the indirect effects, both beneficial and inadvertent, of urban heat-island mitigation. In this article, we provide a brief background discussion of heat-island research and modeling and present findings from three recent projects we have completed for California.