Recent developments in computational software and public accessibility of gridded climatological data have enabled researchers to study Urban Heat Island (UHI) effects more systematically and at a higher spatial resolution. Previous studies have analyzed UHI and identified significant contributors at the regional level for cities, within the topology of urban canyons, and for different construction materials.

In UHIs, air is heated by the convective energy transfer from land surface materials and anthropogenic activities. Convection is dependent upon the temperature of the surface, temperature of the air, wind speed, and relative humidity. At the same time, air temperature is also influenced by greenhouse gases (GHG) in the atmosphere. Climatologists project a 1-5°C increase in near-surface air temperature over the next several decades, and 1-4°C specifically for Los Angeles and Maricopa during summertime due to GHG effects. With higher ambient air temperatures, we seek to understand how convection will change in cities and to what ends.

In this paper we develop a spatially explicit methodology for quantifying UHI by estimating the daily convection thermal energy transfer from land to air using publicly-available gridded climatological data, and we estimate how much additional energy will be retained due to lack of convective cooling in scenarios of higher ambient air temperature.

A web-based software tool has been developed to assist urban planners and air quality management officials in assessing the potential ofurban heat island mitigation strategies to affect the urban climate, air quality, and energy consumption within their cities. The user of thetool can select from over 170 US cities for which to conduct the analysis, and can specify city-wide changes in surface reflectivity and/or veg-etative cover. The Mitigation Impact Screening Tool (MIST) then extrapolates results from a suite of simulations for 20 cities to estimate airtemperature changes associated with the specified changes in surface characteristics for the selected city. Alternatively the user can simply definea nominal air temperature reduction that they hope to achieve with an unspecified mitigation scenario. These air temperature changes are theninput to energy and ozone models to estimate the impact that the mitigation action may have on the selected city. The results presented by MISTinclude a high degree of uncertainty and are intended only as a first-order estimate that urban planners can use to assess the viability of heatisland mitigation strategies for their cities. As appropriate, MIST analyses should be supplemented by more detailed modeling.