Maximum urban heat island intensity in a medium-sized coastal Mediterranean city

This paper studies the maximum intensity of the urban heat island (UHI) that develops in Volos urban area, a medium-sized coastal city in central Greece. The maximum temperature difference between the city center and a suburb is 3.4°C and 3.1°C during winter and summer, respectively, while during both seasons the average maximum UHI intensity is 2.0°C. The UHI usually starts developing after sunset during both seasons. It could be attributed to the different nocturnal radiative cooling rate and to the different anthropogenic heat emission rate that are observed at the city center and at the suburb, as well as to meteorological conditions. The analysis reveals that during both seasons the daily maximum hourly (DMH) UHI intensity is positively correlated with solar radiation and with previous day’s maximum hourly UHI intensity and negatively correlated with wind speed. It is also negatively correlated with relative humidity during winter but positively correlated with it during summer. This difference could be attributed to the different mechanisms that mainly drive humidity levels (i.e., evaporation in winter and sea breeze (SB) in summer). Moreover, it is found that SB development triggers a delay in UHI formation in summer. The impact of atmospheric pollution on maximum UHI intensity is also examined. An increase in PM10 concentration is associated with an increase in maximum UHI intensity during winter and with a decrease during summer. The impact of PM10 on UHI is caused by the attenuation of the incoming and the outgoing radiation. Additionally, this study shows that the weekly cycle of the city activities induces a weekly variation in maximum UHI intensity levels. The weekly range of DMH UHI intensity is not very large, being more pronounced during winter (0.4°C). Moreover, a first attempt is made to predict the DMH UHI intensity by applying regression models, whose success is rather promising.     

阳泉市城市热岛效应特征分析

利用阳泉市3个国家级气象站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年-2011年平均热岛强度0．554℃。阳泉市热岛强度冬、秋季强,春、夏季弱;12月最强,5月最弱;阳泉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年-2011年最强热岛强度出现在2010年1月14日08时达7．9℃。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,城市化发展可能使阳泉城市温度增高,城市绿地面积的增加可能对热岛效应有缓解。     

基于MODIS资料分析近15年广州城市热岛特征及演变规律

利用MODIS地表温度数据,计算城市热岛强度指数,分析近15年广州市城市热岛的时空分布特征及演变规律,并结合气象观测数据、社会统计数据定性分析其主要影响因素。结果表明:广州市城市热岛的空间分布受地形地貌影响明显,负热岛区主要分布于森林密集的北部山区,无热岛区主要分布于中部低山丘陵区域,热岛区主要分布于高度城市化的中南部平原区。关于城市热岛的日变化规律,白天热岛区、负热岛区面积均小于夜间,但白天热岛区强度、负热岛区强度大于夜间。关于城市热岛的季节变化规律,冬季热岛区面积最大,热岛强度最小,夏季热岛区面积最小,热岛强度最大;冬季负热岛区面积最小,负热岛强度最小,夏季负热岛区面积最大,负热岛强度最大。对于城市热岛的年际变化规律,近15年来广州市的热岛区、负热岛区占全市总面积的百分比呈上升趋势,无热岛区所占百分比呈下降趋势,人为热排放在城市中心区域的持续增长,加上区内建筑物密度大、植被覆盖度低,导致了热岛区的增加,而北部山区至中部丘陵山区的植被的持续好转,加上地理特征限制了该区域的城市化发展,导致了负热岛区的增加。      

拉萨市城市热岛效应分析研究

利用拉萨、墨竹工卡、尼木建站以来的多年历史资料和近两年新建的区域自动站、8个城市热岛效应自动气象站资料分析拉萨城市热岛强度日、季、年变化,时空分布及其可能的影响因子。分析表明:拉萨城市热岛强度呈显著的逐年增强趋势,在1978~2011年间平均每10年增加0.24℃;多年热岛强度冬季最强(2.0℃),其次是春季(1.8℃)和秋季(1.7℃),夏季强度最小(1.6℃);拉萨城市高温中心主要在城市中心,气温分布沿着高值区向两侧呈递减状态,郊外的气温比城区平均低0.9℃左右,夜间热岛效应强度明显高于白天。随着城市化进程的不断增强,大量改变的下垫面状况,不断增多的城市建筑群,骤增的人类活动和能源消耗,导致城市热岛强度不断增强。      

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.     

基于MODIS数据的拉萨市地表温度变化研究

采用2000～2011年6月MODIS地表温度产品和拉萨市4个气象站6月平均地表温度对拉萨市地表温度的时空变化进行了分析.结果表明：拉萨市在近12年内地表温度呈明显上升趋势,2009年地表温度达到最高为28.49℃,最小值出现在2003年为14.12℃.在空间分布上高温区主要集中在城市中心和城市周边区域,并随着时间推移不断向外扩张,在2007年6月拉萨市地表温度高温区分布范围最大,其中纳木错东部和林周县的高温区增加最显著;在利用实测的地表温度与MO-DIS反演的地表温度做相关分析发现,两者的相关系数为0.64通过了0.001的显著性检验,两种地表温度的时间变化趋势也较为一致,因此MODIS地表温度反演产品适用于大范围地表温度和城市热环境监测是可行的.     

北京"城市热岛"效应现状及特征

利用2002年北京自动气象站资料,对北京“城市热岛”效应现状进行了分析。为了与20世纪70年代的结果相比较,选择城区代表站为天安门广场站,城郊代表站为朝阳气象站站。与20世纪70年代相比,目前北京的“城市热岛”表现出一些新特点:1)利用城区与城郊日均温差表示的“城市热岛”强度的统计结果表明,现在北京的“城市热岛”效应在夏季最强,秋、冬季次之,春季最弱,2)除夏季“城市热岛”整天存在(午后的平均强度在2℃左右)以外,其他季节的午后,天安门广场地区经常出现“城市冷岛”现象。3)北京“城市热岛”消失的极限风速没有发生系统性变化,当风速>3级时,北京“城市热岛”基本上消失。作者还研究了北京“城市热岛”形成和消失的日变化特征,以及“城市热岛”强度对风速等气象要素变化的响应特征。值得指出的是,对强“城市热岛”的个案分析显示,冬季夜晚“城市热岛”强度经常表现出较大的波动性,与此相伴随,城郊地面风出现风向突变和风速的阵性现象。     

Desert heat island study in winter by mobile transect and remote sensing techniques

A familiar problem in urban environments is the urban heat island (UHI), which potentially increases air conditioning demands, raise pollution levels, and could modify precipitation patterns. The magnitude and pattern of UHI effects have been major concerns of a lot of urban environment studies. Typically, research on UHI magnitudes in arid regions (such as Phoenix, AZ, USA) focuses on summer. UHI magnitudes in Phoenix (more than three million population) attain values in excess of 5°C. This study investigated the early winter period—a time when summer potential evapotranspiration >250 mm has diminished to <90 mm. An analysis of the winter magnitude of the heat island in Phoenix has been studied very little, and therefore with the aid of automobile transects, fixed stations, and remote sensing techniques, we investigated a portion of the large Phoenix metropolitan area known as the East Valley. The eastern fringes of the metropolitan area abut against breaks in sloping terrain. The highest UHI intensity observed was >8.0°C, comparable to summertime UHI conditions. Through analysis of the Oke (1998) weather factor Φ_W, it was determined thermally induced nighttime cool drainage winds could account for inflating the UHI magnitude in winter.     

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。     

基于Landsat TM/ETM＋数据的北京城市热岛季节特征研究

利用1988—2006年20景LandsatTM和ETM＋数据分析了北京市城市热岛的季节变化特征。通过反演地表温度,建立统一的城市和农村区域,计算了城市热岛强度,并采用多项式拟合获取了城市热岛强度的季节变化曲线;同时,分析了热岛强度季节特征与气候因子的关系。另外利用4景2005—2006年不同季节Landsat TM影像,分析了不同季节城市热岛的空间变化特征,并选择穿越北京城区的两条不同方向剖线（SE-NW和SW-NE）,分析了沿剖线方向城市热岛与地表类型的关系。结果显示,北京城市热岛具有明显的季节变化特征,与总云量的季节变化关系显著。最大热岛强度出现在夏季,呈现片状发散和零星热岛并存的空间分布特征。冬季为冷岛特征,其空间分布与夏季热岛一致。春秋两季热岛强度最小,但春季热岛空间差异较大。在相同季节,城市热岛强度和空间尺度在不同剖线方向具有明显的差异,这与不同地类的空间分布有关。     

基于气温日较差的城市热岛强度指标初探

选取1951—2004年中国东部地区9个大城市和较近距离的9个小城市,对城市逐月平均最高、最低和平均气温资料进行不同季节的城市热岛效应分析,对描述热岛效应的热岛强度指标进行研究,并提出一种基于气温日较差的新的热岛强度指标。结果表明,1980年以后,无论大、小城市,城市化的热岛影响均有所加强。大城市年热岛强度10a约增加0．20～0．34℃,小城市约增加0．14～0．20℃。大城市的热岛强度无论季节或年增加幅度均比小城市大,特别是冬、秋季,而小城市则主要表现在夏、秋季。     

URBANIZATION EFFECTS ON OBSERVED CHANGES IN SUMMER EXTREME HEAT EVENTS OVER ZHEJIANG PROVINCE, EAST CHINA

Although the urban heat island (UHI) is a well-documented phenomenon, relatively little information in the literature is available about its impact on summer extreme heat event (EHE). As UHI is characterized by increased temperature, it can potentially increase the magnitude and duration of EHEs within cities. Based on daily maximum temperature records from 62 observation stations in Zhejiang province from the period 1971-2011 and satellite-measured nighttime light imagery from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) during 1992-2010, we analyzed the long-term change of summer EHEs and its association with the rapid urbanization process. The results could be concluded as follows: (1) Zhejiang has experienced rapid urbanization and dramatic growth in urban areas in the past two decades, especially after 2000. (2) The summer mean maximum temperature and the 95th percentile of summer daily maximum temperature in most of its stations have increased, with the most significant increase occurring in the highly urbanized areas including the city belt around Hangzhou Bay, Taizhou–Wenzhou and Jinghua–Yiwu city belts. (3) The hot days and hot-day degrees, defined by both daily 95th percentile and the threshold of 35℃, show that the UHI effect causes additional hot days and heat stress in urban stations compared to rural stations. The results in this study suggest that the UHI effect should be determined and incorporated in preparing high temperature forecasts in cities.     

北京中央商务区(CBD)城市热岛效应的研究

利用2012~2013年北京中央商务区（Central Business District,CBD）加密观测资料,分析CBD区域城市热岛（Urban Heat Island,UHI）强度日变化和空间变化特征及其影响因子。研究发现,CBD区域气温高于周边自动站气温,平均偏高0.64℃;CBD区域城市热岛强度呈现夜间强、白天弱的现象,中午甚至存在“城市冷岛”现象。季节平均UHI日变化表现为:在夜间,秋季最强,冬季次之,春季和夏季较弱;在白天,夏季最强,冬季次之,春季和秋季较弱。相对于晴朗无风天气,雾、雨、大风等天气对城市热岛有抑制作用,并结合小波分析结果发现,秋季城市热岛强度强于冬季是由于冬季雾、雨、大风等天气过程发生比例较高的缘故。CBD区域城市热岛空间变化特征研究发现,花园、学校等绿地有助于缓解城市热岛效应。雾日、雨日和大风日的CBD区域城市热岛强度空间变化标准差比晴朗无风日小。     

不同天气条件下沈阳城市热岛特征

利用1992—2008年沈阳站和新城子站逐日4个时次的平均气温、平均风速、降水量、云量和能见度资料,对不同天气条件下沈阳的城市热岛效应进行研究。结果表明：除雾和浓雾天气条件下,沈阳城市热岛强度在08时最弱外,其他天气条件下均表现为20时最强,14时最弱;不同天气条件下,夜间城市热岛强度均高于白天;晴朗无风条件下昼夜城市热岛强度差最大,为0.73℃。四季相比,除雾条件下秋季城市热岛强度最强外,其他天气条件下均为冬季最强;除大雨条件下春季城市热岛强度最弱外,其他条件下均为夏季最弱。沈阳城市热岛强度随降水量的增加而减弱,随能见度的降低而减弱,随着风速的增加而减弱。白天和夜间两个时次的差值表现为,1～3级风夜间变化幅度大于白天,0级和4～5级风速有相反规律,其他天气条件下无明显规律。     

Temporal variability of the Buenos Aires, Argentina, urban heat island

This paper describes the statistical characteristics and temporal variability of the urban heat island (UHI) intensity in Buenos Aires using 32-year surface meteorological data with 1-h time intervals. Seasonal analyses show that the UHI intensity is strongest during summer months and an “inverse” effect is found frequently during the afternoon hours of the same season. During winter, the UHI effect is in the minimal. The interannual trend and the seasonal variation of the UHI for the main synoptic hours for a longer record of 48?years are studied and associated to changes in meteorological factors as low-level circulation and cloud amount. Despite the population growth, it was found a negative trend in the nocturnal UHI intensity that could be explained by a decline of near clear-sky conditions, a negative trend in the calm frequencies and an increase in wind speed. Urban to rural temperature differences and rural temperatures are negatively correlated for diurnal and nocturnal hours both for annual and seasonal scales. This result is due to the lower interannual variability of urban temperatures in comparison to rural ones.     

Daily maximum urban heat island intensity in large cities of Korea

Summary This study investigates the characteristics of the daily maximum urban heat island (UHI) intensity in the six largest cities of South Korea (Seoul, Incheon, Daejeon, Daegu, Gwangju, and Busan) during the period 1973–2001. The annually-averaged daily maximum UHI intensity in all cities tends to increase with time, but the rate of increase differs. It is found that the average annual daily maximum UHI intensity tends to be smaller in coastal cities (Incheon and Busan) than in inland cities (Daejeon, Daegu, and Gwangju), even if a coastal city is larger than an inland city.A spectral analysis shows a prominent diurnal cycle in the UHI intensity in all cities and a prominent annual cycle in coastal cities. A multiple linear regression analysis is undertaken in order to relate the daily maximum UHI intensity to the maximum UHI intensity on the previous day (PER), wind speed (WS), cloudiness (CL), and relative humidity (RH). In all cities, the PER variable is positively correlated with the daily maximum UHI intensity, while WS, CL, and RH variables are negatively correlated with it. The most important variable in all cities is PER, but the relative importance of the other three variables differs depending on city. The total variance explained by the multiple linear regression equation ranges from 29.9% in Daejeon to 44.7% in Seoul. A multidimensional scaling analysis performed with a correlation matrix obtained using the daily maximum UHI intensity data appears to distinguish three city groups. These groupings are closely connected with distances between cities. A multidimensional scaling analysis undertaken using the normalized regression coefficients obtained from the multiple linear regression analysis distinguishes three city groups. Notably, Incheon and Busan form one group, whose points in the two-dimensional space are very close. The results of a cluster analysis performed using the multivariate data of PER, WS, RH, and CL are consistent with those of the multidimensional scaling analysis. The analysis results in this study indicate that the characteristics of the UHI intensity in a coastal city are in several aspects different from those in an inland city.     

2008年南京市热岛效应演变特征及其对城市居民生活影响

利用2008年南京市23个自动气象观测站观测的气温资料,分析南京市城市热岛效应的空间分布及其变化特征。结果表明：南京市的热岛中心主要分布在人口和建筑物密集的鼓楼,白下和建邺区,下关、江宁和浦口等城区气温较低;2008年南京市平均城市热岛强度为1.6℃,四季热岛强度呈秋季、春季、冬季、夏季依次减弱;南京市城市热岛效应对城市居民生活影响较大。南京市热岛效应的逐渐增强,将导致夏季空调使用量的增加,增加能耗对创建低碳城市、建设和谐城市生活产生消极影响。     

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.     

2008年南京市热岛效应演变特征及其对城市居民生活影响

利用2008年南京市23个自动气象观测站气温资料,分析南京市城市热岛效应的空间分布及其变化特征。结果表明：南京市的热岛中心主要分布在人口和建筑物密集的鼓楼、白下区和建邺区,下关、江宁和浦口等城区气温较低;2008年南京市平均城市热岛强度为1.6℃,四季热岛强度呈秋季、春季、冬季和夏季依次减弱;南京市城市热岛效应对城市居民生活影响较大。南京市热岛效应的逐渐增强,将导致夏季空调使用量的增加,增加能耗对创建低碳城市、建设和谐城市生活产生消极影响。     

Statistical and dynamical characteristics of the urban heat island intensity in Seoul

The statistical and dynamical characteristics of the urban heat island (UHI) intensity in Seoul are investigated for non-precipitation days and precipitation days using 4-year surface meteorological data with 1-h time intervals. Furthermore, the quantitative influence of synoptic pressure pattern on the UHI intensity is examined using a synoptic condition clustering method. The statistical analysis shows that the daily maximum UHI intensity in Seoul for non-precipitation days is strongest in autumn (4.8°C) and weakest in summer (3.5°C). The daily maximum UHI intensity is observed around midnight in all seasons except in winter when the maximum occurrence frequency is found around 08 LST. This implies that anthropogenic heating contributes to the UHI in the cold season. The occurrence frequency of the UHI intensity has a negatively skewed distribution for non-precipitation days but a positively skewed distribution for precipitation days. The amplitude of the heating/cooling rate and the difference in the heating/cooling rate between the urban and rural areas are smaller in all seasons for precipitation days than for non-precipitation days, resulting in weaker UHI intensities for precipitation days. The urban cool island occurs very often in the daytime, with an occurrence frequency being 77% of the total non-precipitation days in spring. The analysis of the impact of large-scale dynamical forcing shows that the daily maximum UHI intensity varies with synoptic pressure pattern, ranging from ?22% in spring to 28% in summer relative to the seasonal mean daily maximum UHI intensity. Comparison of the UHI intensity calculated using station-averaged temperatures to that based on the conventional two-station approach indicates that local effects on the UHI intensity are minimized by using multiple-station data. Accordingly, an estimation of the UHI intensity using station-averaged temperatures for both urban and rural areas is suggested.