How will the urban heat island in growing cities behave under climate change?

热岛热岛主要是由于建筑物吸收热量，将热量困在封闭空间中，以及与自然植被相比，建筑区域的蒸发量减少。其他热源包括柏油路面的热量和建筑物在冬季排放的热量。利用数十年至百年的长时间配对数据序列（城市/农村），或利用基于卫星观测的局部温度空间变化，对欧洲（Jones and Lister, 2009）、美国和中国的一些城市的热岛指数进行了记录（Zhou et al., 2013）。由于具体的数据要求和区域利益，全民健康保险的特点一般是在地方到区域一级。已发表的研究表明，它最初随着城市的发展而增长，但当城市化达到一定成熟水平时，它趋于饱和。然而，这些研究只涵盖有限数量的城市和地理/气候环境。因此，我们并不完全了解是什么因素决定了热岛指数的增长率和饱和水平，以及这些因素在沿海或干旱环境中可能产生的不同影响程度。最初将根据所有现有的长时间序列成对台站数据（即包括城市内外的数据），对热岛升温进行系统评估。然而，无论是在个别城市还是在地理上，高质量的城乡站对的可用性都是有限的。因此，也建议使用陆地表面温度（LST）数据，例如MODIS光谱辐射计。地表温度在绝对意义上不能直接与2米的气温测量相比较，但可以用来探索空间模式，并有助于解释有限数量的较长站记录。通过将热岛数据与有关城市环境和社会经济特征的数据（如规模、土地利用、气候制度、地理环境、绿/蓝空间、反照率）结合起来，将确定热岛特征与潜在驱动因素之间的机制关系。高分辨率全球（CMIP5和CMIP6）和区域（CORDEX）气候模式的输出也将被使用。除了一些有限的敏感性研究（McCarthy et al., 2012），这些模型没有隐含地模拟城市热岛指数，因此，如果时间允许，将探索使用相对简单的标度方法的可能性，其中使用模型的温度变化统计数据来修改当前的城市气候统计数据。这将使气候预测能够考虑到热岛指数，从而更适合于影响研究。该项目还将探讨本世纪预计的热岛效应对与热有关的健康负担的影响（使用与热应力有关的指数，如湿球温度），并可能提出将其最小化的解决方案。虽然该项目将侧重于热，但也将对湿度给予一些关注，因为它对健康和人体舒适有重要影响（蒸发冷却的程度有助于确定城市热岛的大小）。

The UHI is caused primarily by the absorption of heat by buildings, the trapping of that heat in enclosed spaces, and the reduced evaporation from built areas compared to natural vegetation. Further heat sources include heat from tarmac and heat emissions by buildings in winter. The UHI has been documented for a number of European (Jones and Lister, 2009), American, and Chinese cities using long time series of paired data (urban/rural) covering multiple-decades to century, or using local spatial variations in temperature based on satellite observations (Zhou et al., 2013). The UHI is generally characterised at the local-to-regional level because of the specific data requirements and regional interests. Published studies indicate that it grows initially as the city develops, but it tends to saturate when urbanization reaches a certain level of maturity. However, these studies cover a limited number of cities and geographical/climate settings. Thus we do not fully understand what factors determine the rate of growth and the saturation level of the UHI and the extent to which these factors may have a different influence in say coastal or arid settings. A systematic assessment of UHI warming will be undertaken, initially based on all available long time-series paired station data (i.e. including data within and outside cities). The availability of high-quality rural-city station pairs is however limited both for individual cities and geographically. Thus it is also proposed to use Land Surface Temperature (LST) data, for example from the MODIS spectroradiometer. LST is not directly comparable in absolute terms to 2m air temperature measurements but can be used to explore spatial patterns and to help in the interpretation of the limited number of longer station records. By combining this UHI data with data on the environmental and socio-economic characteristics of cities (such as size, land use, climate regime, geographic setting, green/blue space, albedo) mechanistic relationships will be identified between the characteristics of the UHI and the underlying drivers. Outputs from high-resolution global (CMIP5 and CMIP6) and regional (CORDEX) climate models will also be used. Apart from some limited sensitivity studies (McCarthy et al., 2012) such models do not implicitly model the UHI, so, if time permits, the possibility of using a relatively simple scaling approach in which temperature change statistics from the models are used to modify the present-day urban climate statistics will be explored. This would allow the development of climate projections which do account for the UHI and thus are more appropriate for impact studies.The project will also explore the implications of projected UHI effects this century for heat-related health burden (using heat stress related indices such as Wet Bulb Globe Temperature), and possibly propose solutions to minimise it. Although the project will focus on heat, some attention will also be given to humidity as it has important implications for health and human comfort (and the extent of evaporative cooling helps to determine the magnitude of the UHI).