全球变暖和城市化共同影响下城市极端高温风险研究

Although the urban heat island (UHI) is a well-documented phenomenon, relatively little information in the literature is available about its characteristics during extreme heat events. With global warming forecast to continue into the foreseeable future, extreme heat events will become more intense, more frequent, and longer lasting with climate change. The potential exposure of urban populations to climate change will be enhanced by local factors with the development of urbanization. However, urban warming in addition to greenhouse gas-induced warming has not explicitly been taken into account in climate change simulations to date. Under the background of rapid urbanization in China, the magnitude of future warming and the health risk of extreme heat events may be significantly underestimated. This proposed study focuses on urban agglomeration around Hangzhou Bay. Based on diagnostic analysis of observational data from a dense network of automatic weather stations, we will identify climatological attributes of the UHI under extremely high temperature conditions during summer and assess heat health risk including the UHI under current climate condition. Based on heterogeneous anthropogenic heat release data and a series of WRF/UCM simulations, the extreme heat event-UHI interaction and the impact of urbanization on heat stress during heat waves will be deeply investigated. The coupled WRF/UCM model will be further used to project the urban climate in the 2050s considering both climate change and urbanization effects and the pseudo global warming method will be used to reduce GCM climate bias. The dynamical downscaling for urban climate projections will be applied to assess future heat health risk. Finally, the benefits of different UHI mitigation strategies will be assessed. Results from the proposed project will contribute to improve the predictive capability of high temperature in urban areas and provide scientific foundation for implementing effective heat risk management and climate change adaptation strategies.

目前有关城市热岛效应（UHI）的时空分布特征及其对气温变化趋势的影响已有大量研究，但是对于极端高温-UHI相互作用、城市化对高温热胁迫的影响研究还不够深入，进行未来气候变化预估时也很少考虑城市的影响。在我国城市化快速发展的背景下，这将严重低估城市未来的变暖幅度以及极端高温的健康风险。本项目以环杭州湾城市群为研究区，利用密集的自动气象站观测数据分析极端高温期间的UHI特征，采用WRF/UCM模式进行数值模拟试验，阐明极端高温-UHI相互作用及城市化影响极端高温热胁迫的物理机制，在此基础上，利用经过系统误差订正后的GCM气候变化情景驱动WRF/UCM，进行动力降尺度模拟，预估气候变化和城市化共同影响下的高分辨率未来城市气候情景和极端高温事件变化，从风险管理的角度实施高温风险评估，并提出降低风险的对策。以期为提高城市极端高温预报水平、降低极端气候事件风险和制定区域应对气候变化策略提供科学依据。

本项目以环杭州湾地区为研究对象，利用密集的自动气象站观测数据分析极端高温期间的 UHI 特征，采用 WRF/UCM模式进行数值模拟试验，阐明极端高温—UHI相互作用及城市化影响极端高温热胁迫的物理机制，在此基础上，预估气候变化和城市化共同影响下的高分辨率未来城市气候情景和极端高温事件变化，从风险管理的角度实施高温风险评估，并提出降低风险的对策。主要结论如下：（1）分析了研究区快速城市化进程对极端高温事件长期变化趋势的影响，城市化对长三角地区1971-2013年极端高温强度增加趋势的贡献超过了三分之一，城乡气温PDF分布在2000年以后的快速城市化阶段差异更为显著；（2）基于多源遥感数据对杭州市的城市土地利用类型进行了精细化分，并对研究区的人为热排放量进行了空间化模拟，获得了1km分辨率的人为热排放量栅格数据；（3）选取了典型极端高温热浪事件，设计数值模拟试验，利用 WRF /UCM对杭州典型高温热浪期间的城市热岛效应进行模拟，下垫面变化和人为热排放对极端高温期间 UHI 强度的相对贡献分别为70%和30%；（4）基于人为热栅格数据，设计模拟实验来分析人为热和城市土地利用对杭州冬季和夏季城市气候的影响，人为热对UHI的贡献在夏季为17.47%，冬季则达到65.26%；（5）使用CESM误差订正未来气候情景数据和未来城市发展情景驱动WRF/UCM进行未来城市气候的高分辨率动力降尺度模拟，未来长三角地区将经历更多持续时间更长、强度更大的极端高温事件，对城市居民健康造成严重威胁；（6）建立了综合考虑UHI影响、承灾体脆弱性和暴露性的城市高温风险评估体系，对浙江省的高温健康风险进行了1km栅格尺度的精细化评估，人群健康风险等级较高的地区主要集中在中心城区，这是较高的人口暴露度和城市高温共同作用的结果；值得注意的是一些相对欠发达地区虽然高温危险性等级和人口暴露程度相对较低，但人口的社会经济脆弱性决定了其也存在较高的高温风险。上述成果可以为提高城市极端高温预报水平、降低城市居民极端高温健康风险提供科学依据。