城市热岛效应热点问题研究进展

概述了国内外城市热岛效应研究热点及不足,探讨了时空替代性、评价指标合理性、模拟空间尺度适宜性及理论与应用研究相结合等问题,指出未来城市热岛效应研究应注重新方法与新思路的集成、城市群热岛效应监测、城市热岛与全球异常环境要素间的生态关联性、缓解城市热岛效应的生态途径与技术方法。     

城市热岛效应的研究进展与展望

随着世界各国城市化的进展,城市热岛效应已经成为一个跨学科领域的问题,受到包括大气环境、区域气候、水文和生态等多学科科学家的关注。在过去半个多世纪中,城市热岛问题的研究获得了相当丰富的研究成果,通过对这些成果的综合分析,归纳出城市热岛研究中采用的3类主要方法——观测(外场试验和遥感技术)、数值模拟以及实验室仿真法。系统地回顾了城市热岛效应的研究历史,重点对与城市热岛关系最密切的城市边界层、热岛环流与复杂地形的相互作用以及能量平衡研究所取得的成果进行了总结和评述。最后对城市热岛问题未来8个可能的研究方向进行了探讨,其中,包括沿海和复杂地形附近的城市热岛问题、城市群间热岛环流的相互作用、城市化与空气污染问题、城市热岛效应对平均降水的影响、城市化对雾和闪电的影响、城市天气预报的精细化、城市气候变化预测以及城市热岛效应减缓方案的制定,并对其发展前景进行了粗略的展望。     

城市景观格局与热岛效应研究进展

概述了城市景观格局和城市热岛效应及城市景观格局对城市热岛效应影响等领域的研究现状,探讨了城市景观格局对城市热岛效应的影响作用,并结合城市景观格局研究中的新领域——景观格局优化,提出了解决城市热岛问题的新思路,即通过优化景观格局来达到缓解甚至消除热岛效应。展望了城市景观格局和城市热岛效应研究领域存在的问题和面临的任务。     

城市热岛效应研究概况

随着我国城市化进程的不断加快,城市中的环境污染问题也日益严重,表现为城市比周围非城市化地区的地表和大气温度要高的热岛效应作为这些环境问题中的典型代表有着重要的研究意义。近几十年来国内外的有关专家从微观及宏观层面上对城市热岛效应的产生原因、造成影响、变化规律、缓解措施等方面进行了一系列的研究与探索。由于城市测点有限,过去的研究尚不能全面反映出研究区热岛效应。遥感科学和技术的发展,为城市热岛效应的研究提供了有利条件。本文介绍了热红外遥感技术在热岛研究中的应用及城市规划对城市热岛效应的影响,并展望了该领域的发展前景。     

城市热岛效应研究概况

随着我国城市化进程的不断加快,城市中的环境污染问题也日益严重,表现为城市比周围非城市化地区的地表和大气温度要高的热岛效应作为这些环境问题中的典型代表有着重要的研究意义。近几十年来国内外的有关专家从微观及宏观层面上对城市热岛效应的产生原因、造成影响、变化规律、缓解措施等方面进行了一系列的研究与探索。由于城市测点有限,过去的研究尚不能全面反映出研究区热岛效应。遥感科学和技术的发展,为城市热岛效应的研究提供了有利条件。本文介绍了热红外遥感技术在热岛研究中的应用及城市规划对城市热岛效应的影响,并展望了该领域的发展前景。     

城市热岛效应研究进展

随着城市规模的高速发展和城市人口的急剧膨胀,因城市下垫面结构的急剧变化和城市人为热排放的迅速增加所引起的城市热岛效应已逐渐成为严重影响城市人居环境和居民健康的重要因素。城市热岛效应研究已成为城市气候和区域气候研究中的热点问题。为更好地研究城市热岛效应,及时追踪国内外最新进展,综述了城市热岛的概念和形成机制,重点介绍了地面气象资料观测法、遥感监测法和边界层数值模式模拟法等3种城市热岛效应研究方法,总结了城市热岛效应国内外最新研究进展。最后基于现有城市热岛效应研究不够完善和深入,研究过于简单化和表面化,尺度局限于宏观大尺度以及各种方法自身的局限性等不足,指出在未来的城市热岛效应研究中,应突破现有的大中尺度,注意结合高分辨率卫星遥感影像进行多尺度多平台监测以及综合考虑气溶胶粒子对辐射强迫的影响等。     

短期大规模人口流动对上海市城市热岛效应的影响

城市热岛效应是一种非常重要的局地气候现象,随着全球变暖和城市化快速发展,城市热岛效应受到越来越多的关注和研究。以往的研究表明人口聚集和人口数量对城市热岛效应和区域城市气候会产生显著的影响。但是,人口短期的快速迁移流动对城市气候是否存在影响以及影响的程度多大尚不清楚。本文利用世界上每年最大规模的人类迁徙——春节人口流动来探讨人口短期快速流动对国际化大都市上海城市热岛效应的影响。研究结果表明,2000~2015年上海市春节周日最高温、日均温和日最低温城市热岛强度分别为0.35℃、0.90℃和1.53℃,相对于背景场(春节前2~4周和春节后2~4周的平均值),分别低了0.16℃、0.11℃和0.15℃,相对变化分别为31.4%、10.9%和8.9%。由此可见,人口短期快速迁移流动是影响热岛效应和城市气候一个重要因素,但是人口流动对城市热岛效应的影响是复杂的,其效应与气候背景、天气状况、城市规模、城市人口流动特征及分布甚至城市烟花爆竹燃放(通过影响气溶胶、云量及废热影响城市热岛效应)等因素交织在一起,未来仍需开展进一步的深入研究。     

基于Landsat 8 TIRS地表温度数据反演的深圳城市热岛效应时空分布及土地利用的影响

基于2014～2021年Landsat 8 TIRS卫星遥感影像数据,分别采用劈窗算法(SWA)和大气校正法(ARC)反演了深圳市地表辐射温度,并利用地面站点监测数据对反演结果进行了验证,探讨了该期间深圳城市热岛效应的时空分布特征及其影响因素。研究结果表明,这两种算法反演的地表温度(T_SWA、T_ARC)与地面站点监测气温(T_M)都存在显著线性相关(T_SWA=1.01×T_M+2.65,T_ARC=0.85×T_M+5.51,p<0.01),但劈窗算法更接近地面站点监测数据。在2014～2021年间深圳城市热岛面积(HI>0.01)未观察到显著增加的趋势(p=0.94)。深圳市城市热岛分布与城市发展格局关系密切,城市规划用地类型对城市热岛效应有显著影响。生态水域和生态绿地缓解了城市热岛效应,而交通道路和工业仓储等城市用地强化了城市热岛的形成,并且城市路网的分布和密度对城市热岛的形成有强显著性影响(p=0.003)。     

北京城市热岛效应的昼夜变化特征分析

利用最新获取的1998年3月~2001年12月北京地区自动站资料,对北京城市热岛效应进行了细致、完整的研究。选取城区的官园站和郊区密云站的气温差作为城市热岛效应强度指标。在验证了资料可靠性的基础上,研究了热岛强度昼夜变化的年、季、月及日变化特征,以及几种极端天气事件的逐时及平均热岛强度的变化,最后制作了连续3年的月平均逐时热岛强度变化的三维立体图。     

重庆市城市热岛效应变化特征及减缓措施

利用1961～2016年重庆市逐日气温资料,分析讨论了重庆市主城区56年城市热岛效应的变化趋势和年变化特征,并利用2009～2016年的逐时气温资料分析讨论了城市热岛效应的日变化特征。结果表明:56年来重庆市城市热岛效应总体呈上升趋势,各季节中盛夏上升最明显;重庆市城市热岛效应存在明显的年变化特征,盛夏的热岛效应最强,初春次之,仲春至初夏的热岛效应最弱;重庆市城市热岛效应具有较明显的日变化特征,各季节热岛效应均表现为白天弱,夜间强。重庆市城市热岛效应的形成及其变化,既受到地理位置、气象条件等自然因素的影响,更由城市下垫面变化(绿地和水体的面积及分布)、大气污染、人为热排放等城市化进程因素所决定。结合重庆城市特点综合运用多种措施可以减缓重庆城市热岛效应。      

山西省阳泉市城市热岛效应特征分析

利用1972－2011年阳泉市3个国家级气象站资料、2011年36个乡镇区域自动站气温资料,分析了阳泉市城市热岛效应的年际变化、季节变化、月变化和日变化特征。结果表明：阳泉市存在弱的城市热岛效应,1972－2011年平均热岛强度0.554 ℃。阳泉市城市热岛强度整体呈显著上升趋势,热岛强度的增加主要是由于夏季热岛强度的增强;热岛强度冬、秋季强,春、夏季弱;12月最强,5月最弱;热岛强度日变化表现为12时最小,从傍晚开始随降温逐渐增大,到早晨气温降到最低时最大,日出之后迅速减小;2008－2011年最强热岛强度出现在2010年1月14日08时,达7.9 ℃。阳泉在升温天气热岛强度变幅增大,易在早晨形成较强城市热岛,下午形成城市冷岛;降温天气热岛强度变幅减小;温度变化较小时则易维持弱的城市热岛。阳泉市主要城市发展因子与霾日数、气温呈显著正相关,在目前的经济发展水平条件下,阳泉市城市化发展可能使城市温度增高,城市绿地面积的增加可能对热岛效应有缓解作用。     

Trends in extreme rainfall events of Bangladesh

Previous studies have shown that urbanization in the Pearl River Delta (PRD) region in southern China can have significant effect on the land-sea breeze circulation in the region. In this study, some characteristics of this urban heat island (UHI) effect are further investigated by some idealized numerical experiments. This study focuses on three aspects of the UHI effects. Firstly, the interaction of UHI effects associated with different city clusters in the PRD region. Secondly, the UHI effect and the strength of the background wind field. Thirdly, seasonal variation of the UHI effect. Experiment results suggest that the interaction of the UHI effects due to the closely distributed city clusters in the PRD region is not significant, while the UHI effect in the region may depend on the strength of the background wind. The seasonal-mean UHI effect in the region shows a significant variation associated with the change of seasons.     

The urban heat island of a city in an arid zone: the case of Eilat, Israel

Summary This study presents the results of a preliminary research that was conducted in the city of Eilat, located in an extreme hot and arid zone on the northern coast of the Red Sea. The purpose was to analyse the characteristics of the local urban heat island (UHI). Diurnal pre-dawn and early-afternoon measurements were taken in winter and summer weather conditions on three separate occasions for two consecutive years. The results show the development of a moderate UHI located around the most intensive area of human activity; the city business centre and dense hotel belt. The UHI is more significant at midday during the summer period, while early morning inversions in winter have a weakening effect on the UHI intensity. It was found that the topography and wind regime have a dominant effect on the location and intensity of the UHI, while the sea has a very marginal effect. Due to the UHI influences on the spatial distribution of the heat stress in the city, it is suggested that further applied UHI research should be focused on the summer period.     

站点选择对城市热岛效应的影响分析

根据城郊站间距离等对辽宁56个气象站进行筛选,采用城郊温差法对选站和未选站时郊区站点数量有变化的大连、丹东、锦州和铁岭4个城市的月和年热岛特征进行分析。结果表明：对于年热岛特征而言,1980-2011年,大连、丹东、锦州和铁岭4个城市选站和未选站时热岛强度大小明显不同,但其变化趋势基本一致。4城市相比,选站和未选站时后均表现为铁岭年热岛强度最大,多年平均值分别为1.53 ℃和1.85 ℃,其变化范围分别为1.17-1.80 ℃和1.55-2.15 ℃,变化幅度分别为0.63 ℃和0.60 ℃。1980-2011年,铁岭热岛强度等级发生变化的年份最多,占25 %。总体来讲,选站对年热岛特征影响不是很大。对于月热岛特征而言,大连选站和未选站时热岛强度变化较大,但其他3个城市选站选站和未选站时变化不大,尤其是锦州选站和未选站时变化基本一致。4城市均有冬半年热岛效应明显,夏半年热岛效应不明显的特征。1980-2011年,各月平均热岛强度等级在选站和未选站时变化均较大,最大为丹东10月和11月,等级变化的年份占90.6 %,总体而言,选站对月热岛强度特征影响较大。     

苏州-无锡-常州城市带热岛效应个例研究

应用WRF（weather research and forecasting）及其耦合的多层城市冠层模式BEP（building energy parameterization）,对2013年8月13日长江三角洲地区一次高温天气过程进行了模拟.此次过程盛行东南风,风向与苏州-无锡-常州城市带走向一致.模拟结果表明：苏州-无锡-常州城市带热岛效应明显,热岛强度向下游城市逐渐增加;在东南风作用下,三座城市的热岛连成一片,形成了一个更强大的热岛环流.夜晚,边界层逐渐趋于稳定,热岛环流减弱,有利于热岛温度向下游地区输送.热岛效应导致城市边界层高度明显上升.白天太湖产生强盛的湖风对其周边城市影响显著,来自太湖的冷气团导致无锡和常州边界层内热岛强度明显下降,抑制城市热岛向上发展,削弱了无锡与常州两城市热岛间的联系.白天太湖使得无锡和常州边界层高度明显下降.     

苏州—无锡—常州城市带热岛效应个例研究

应用WRF(weather research and forecasting)及其耦合的多层城市冠层模式BEP(building energy parameterization),对2013年8月13日长江三角洲地区一次高温天气过程进行了模拟。此次过程盛行东南风,风向与苏州—无锡—常州城市带走向一致。模拟结果表明:苏州—无锡—常州城市带热岛效应明显,热岛强度向下游城市逐渐增加;在东南风作用下,三座城市的热岛连成一片,形成了一个更强大的热岛环流。夜晚,边界层逐渐趋于稳定,热岛环流减弱,有利于热岛温度向下游地区输送。热岛效应导致城市边界层高度明显上升。白天太湖产生强盛的湖风对其周边城市影响显著,来自太湖的冷气团导致无锡和常州边界层内热岛强度明显下降,抑制城市热岛向上发展,削弱了无锡与常州两城市热岛间的联系。白天太湖使得无锡和常州边界层高度明显下降。     

Characterization and estimation of urban heat island at Toronto: impact of the choice of rural sites

In this study, the urban heat island of Toronto was characterized and estimated in order to examine the impact of the selection of rural sites on the estimation of urban heat island (UHI) intensity (?T _u-r). Three rural stations, King Smoke Tree (KST), Albion Hill, and Millgrove, were used for the analysis of UHI intensity for two urban stations, Toronto downtown (Toronto) and Toronto Pearson (Pearson) using data from 1970 to 2000. The UHI intensity was characterized as winter dominating and summer dominating, depending on the choice of the rural station. The analyses of annual and seasonal trends of ?T _u-r suggested that urban heat island clearly appears in winter at both Toronto and Pearson. However, due to the mitigating effect on temperature from Lake Ontario, the estimated trend of UHI intensity was found to be less at Toronto compared to that at Pearson which has no direct lake effect. In terms of the impacts of the rural stations, for both KST and Millgrove, the trends in UHI intensity were found to be statistically significant and also were in good agreement with the estimates of UHI intensities reported for other large cities in the USA. Depending on the choice of the rural station, the estimated trend for the UHI intensity at Toronto ranges from 0.01°C/decade to 0.02°C/decade, and that at Pearson ranges from 0.03°C/decade to 0.035°C/decade during 1970–2000. From the analysis of the seasonal distribution of ?T _u-r, the UHI intensity was found to be higher at Toronto in winter than that at Pearson for all three rural stations. This was likely accounted for by the lower amount of anthropogenic heat flux at Pearson. Considering the results from the statistical analysis with respect to the geographic and surface features for each rural station, KST was suggested to be a better choice to estimate UHI intensity at Toronto compared to the other rural stations. The analysis from the current study suggests that the selection of a unique urban–rural pair to estimate UHI intensity for a city like Toronto is a critical task, as it will be for any city, and it is imperative to consider some key features such as the physiography, surface characteristics of the urban and rural stations, the climatology such as the trends in annual and seasonal variation of UHI with respect to the physical characteristics of the stations, and also more importantly the objectives of a particular study in the context of UHI effect.     

Mesoscale and macroscale aspects of the morning Urban Heat Island around Athens,Greece

Summary This paper examines the characteristics of the morning Urban Heat Island (UHI) in Athens basin, Greece. The study is performed by using and analyzing mesoscale and synoptic data covering the period 1990–2001. The UHI was estimated using the 0600 Local Time (LT) minimum temperature differences between rural and urban areas of the city. The analysis results in 7 UHI classes. A strong UHI was found for the 1/3 of days. The specific meteorological characteristics (surface and upper air, cooling rate) of each UHI class were revealed and examined. The spatial and temporal characteristics of the UHI were also identified. The UHI is largest on nights with clear skies and low relative humidity. In all seasons the UHI switches on rapidly in afternoon. During spring and summer, sea breeze commonly reduces and delays the UHI. Cases documenting the sensitivity and rapidity of changes of the UHI to changes in classes (cloud cover, wind) are also presented. The cooling rate is higher in the urban area under negative and lower under positive UHI conditions. Mesoscale and macroscale phenomena were examined during the different UHI classes through a weather type scheme. It was emerged that high UHI classes are associated with anticyclonic conditions or advection in the lower troposphere, while low UHI classes are associated with strong northeasterly winds. Anticyclonic conditions which frequently occur in spring and early summer, reduce or reverse the UHI to Urban Cooling Island.     

Climate Change driven evolution of hazards to Europe’s transport infrastructure throughout the twenty-first century

Air circulation due to the urban heat island (UHI) effect can influence the dispersion of air pollutants in a metropolis. This study focusses on the influence of the UHI effect on particulate matter (PM; including PM_2.5 and PM_2.5–10) between May and September 2010–2012 in the Taipei basin. Meteorological and PM data were obtained from the sites, owned by the governmental authorities. The analysis was carried out using t test, relative indices (RIs), Pearson product–moment correlation and stepwise regression. The results show that the RI values for PM were the highest at moderate UHI intensity (MUI; 2 °C ≤ UHI < 4 °C) rather than at strong UHI intensity (SUI; 4 °C ≤ UHI) during the peak time for anthropogenic emissions (20:00 LST). Neither the accumulation of PM nor the surface convergence occurred in the hot centre, as shown by the case study. At MUI, more than 89 % of the synoptic weather patterns showed that the weather was clear and hot or that the atmosphere was stable. The variation in PM was associated with horizontal and vertical air dispersion. Poor horizontal air dispersion, with subsidence, caused an increase in PM at MUI. However, the updraft motion diluted the PM at SUI. The stepwise regression models show that the cloud index and surface air pressure determined the variation in PM_2.5–10, while cloud index, wind speed and mixing height influenced the variation in PM_2.5. In conclusion, a direct relationship between UHI effect and PM was not obvious.