An urban heat island (UHI) is a phenomenon whereby urban areas experience elevated temperatures relative to the surrounding rural hinterland. This thermal contrast is brought about by anthropogenic modification of the environment. For example, there is little bare earth and vegetation in urban areas. This means that less energy is used in evaporating water, less of the Sun’s energy is reflected and more heat is stored by buildings and the ground in urban than in rural areas. The heat generated by heating, cooling systems, transport and other energy uses also contributes, particularly in winter, as does the complex three-dimensional structure of the urban landscape which can reduce air flow. The magnitude of the urban-rural temperature difference depends upon a range of meteorological and geomorphological variables, but the maximum UHI is generally observed under night-time, calm, clear-sky conditions following a day of similar weather. In this scenario, the lack of cloud means daytime solar radiation receipt is at its greatest, leading to a large component of stored heat in the urban fabric. This heat is later released into the surrounding environment as the external air temperature drops after sunset. Meanwhile, net longwave radiation losses are at a maximum during the evening in rural areas but remain comparatively low in the city owing to higher levels of air pollution and radiation becoming trapped by tall urban structures. When the wind is light, nocturnal cooling is inhibited by the lack of available ventilation to transport the warmer air away from the urban environment, further accentuating the difference. The alteration of the urban radiative energy balance and the reduction of heat loss by wind-driven turbulence in a city environment are both consequences of the urban surface geometry. Although complex, the relationship between urban morphology and the urbanrural temperature difference has been shown to display an inverse linear association under the idealised UHI conditions outlined above for a range of mid-latitude, developed, cities (Oke, 1981). Spatial temperature variations within a city, however, may not correspond quite so simply with building height and/or density owing to other factors that are present at the microscale (Eliasson, 1996). For instance, a key difference in the surface energy budget is in the ratio of latent to sensible heat fluxes. In rural areas the surface is dominated by evapotranspiring vegetation, but in an urban environment much of the surface has undergone some level of waterproofing through the use of impervious materials, thereby significantly reducing the latent heat flux (Grimmond and Oke, 1999; 2002). Differences in land use, irrigation, wind speed and rainfall mean that evaporative cooling varies within urban environments. On a local scale, the presence of a vegetated area or water body within a city can have a significant cooling effect (SpronkenSmith and Oke, 1999; Graves et al., 2001). Temperature patterns are dominated by an inverse relationship between temperature and distance from the city centre, but are also strongly related to land use, which is often a surrogate for urban morphology, geometry and the availability of water (Landsberg, 1981; Eliasson and Svensson, 2003; Wilby, 2003). The significance of UHIs was brought to the attention of city planners and the wider public by the heatwave of August 2003. In London, for example, night-time temperatures were six to nine degrees higher than in the surrounding countryside during the heatwave. This contributed to an estimated 600 excess deaths (Mayor of London, 2006). Buildings and transport infrastructure, which typically have a long life cycle, are not designed to withstand such extreme temperatures, as the UHI effect is generally not considered during the design process. Consequently, when heatwaves are exacerbated by the UHI, the infrastructure can be subject to over-heating, structural damage, changed energy consumption patterns and disrupted service provision. Increasing urban development and population compounded by projected temperature changes, mean that the resulting economic costs will be significant unless the UHI effect is considered in future design. The detailed structure of UHIs must therefore be quantified. While the causes of the UHI are generally well understood (Landsberg, 1981; Oke, 1987), it is often difficult to quantify the magnitude and spatial variation of the effect due to the lack of standardised longterm meteorological observations in urban areas and the sparse network of monitoring stations. In the UK, studies of UHIs have tended to focus on London (Wilby, 2003; Mayor of London, 2006; Jones and Lister, 2009), although limited data also exist for Reading (Parry, 1955; Melhuish and Pedder, 1998) and Birmingham (Unwin, 1980). The aim of a project currently underway at the University of Manchester (SCORCHIO: Sustainable Cities: Options for Responding to climate CHange Impacts and Outcomes), in partnership with the University of Sheffield, University of Newcastle, University of East Anglia and the Hadley Centre is to develop a suite of Geographic Information System (GIS)-based decision-support tools which will allow for the analysis of climate change adaptation options in urban areas, with a particular emphasis on heat and human comfort. As part of this work, a detailed picture of the spatial temperature patterns across Greater Manchester is being developed (Kilsby et al., 2007; Smith et al., 2010). The results collected so far suggest a maximum Manchester UHI effect of ~3 degC during the day which increases to 5 degC at night (Smith et al., 2010).