利用区域边界层模式对杭州市热岛的模拟研究

利用一个三维非静力区域边界层数值模式,对杭州地区城市热岛现象进行了数值模拟。数值模拟结果表明,杭州地区存在明显的城市热岛现象。夏季城市热岛现象较强,春秋季次之,冬季较弱。利用资源卫星遥感资料反演所得的地表温度,以及与地面气象站观测资料和数值模拟结果相比较,数值模拟结果和实测结果吻合得较好。在此基础上,模拟并探讨了人为热源、风速、地面粗糙度等因素对城市热岛强度的影响。     

基于自动站观测资料的深圳城市热岛研究

利用103个自动站气温观测资料,对深圳的城市热岛现象进行了研究.分析表明:1)高速的城市化进程造成自动站周边下垫面属性的变化,对气温造成了显著影响,这种影响即使是在仅仅10年内也表现得较为明显.2)由于深圳地处海滨,深圳的近地层气温分布是海陆作用叠加城市热岛效应形成的结果.按照传统定义的深圳城市热岛,其空间分布在不同季...     

哈尔滨市热岛效应研究

1引言城市化进程的不断加快,对城市气候有着深远的影响,由其引起的城市热岛现象已经引起了广泛的关注。城市热岛效应是指当城市发展到一定规模,由于城市下垫面性质的改变、大气污染以及人工废热的排放等使城市温度明显高于郊区,形成的类似高温孤岛现象。     

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。     

昆明城市热岛效应变化特征研究

利用昆明周边多个自动气象站观测的2004~2012年温度序列,研究了昆明城市热岛效应的日、季节和年际变化特征,并分析了昆明城市热岛水平分布和变化趋势。昆明城市热岛强度具有明显的日变化,夜间较强,白天较弱。城市热岛强度一般在早上08:00(北京时间,下同)达到最大值,在午后14:00减弱或消失。城市热岛强度在冬季最强,春、秋季次之,夏季最弱。昆明城市热岛强度多年平均值为1.27°C,在2004~2009年期间表现为逐年递减的趋势,其年际变化的主要影响因子是云量。2004~2007年昆明城市热岛中心主要分布在主城区。2008年以后,由于中小城镇经济和人口的迅速发展,昆明城市热岛面积不断扩大,并出现热岛中心向呈贡、石林一带偏移的现象。     

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。     

廊坊市城市热岛效应的昼夜变化特征分析

利用2005年9月～2008年8月廊坊市区域加密自动站逐小时气温资料,采用城、郊气温对比法研究了廊坊城市热岛效应,结果表明:廊坊城市热岛强度夜间大于白天,但变化幅度白天大于夜间,但在四季不同时段也存在"城市冷岛"现象.不同气象条件下,廊坊城市热岛强度及变化存在明显差异,晴朗无风时城市平均热岛强度最大,平均强度达1.25℃,阴雨天气条件下城市平均热岛强度最小,平均强度仅有0.10℃.     

规划建设对深圳夏季城市热岛影响的数值模拟研究

以区域边界层模式RBLM为工具,研究了城市规划建设对深圳夏季城市热岛的影响。分别模拟了当前的城市热岛、高密度建设和能耗增加后的城市热岛、以及布设通风走廊后的城市热岛,得到了以下结论:(1)深圳夏季存在城市热岛现象,且昼间热岛比夜间更为明显,高温中心集中在建设密度较高的南山、福田、罗湖和宝安西部等区;(2)建设密度加大及能源消费增加会导致深圳夏季近地面气温出现大面积的升高,并且夜间升温比昼间更为明显;(3)通风走廊的设置可以在一定程度上抵消高密度建设和能耗增加带来的负面效应。     

城市大气边界层的数值研究

本文利用能量闭合的二维非线性、非定常模式,结合地面热量平衡方程,研究了城市热岛和城市热岛环流以及其它相关的城市边界层参量的发展演变规律;同时探讨了在城市污染面源的情况下,污染物的扩散、输送问题.模拟结果得到了天津市城市热岛观测资料的证实.     

夜间城市边界层发展的数值研究

本文使用非定常非线性二维数值模式,研究夜间气流流经城市热岛上空引起的风场、温度场和垂直涡旋扩散参数的调整以及城市热岛环流的发展演变.     

基于ENVI-met模式的城市近地表气温模拟与分析-以南京市部分区域为例

城市不同下垫面与建筑物空间形态对近地表气温等微气候要素产生了重要影响。开展城市气温时空变化模拟与影响因素分析,对于城市热环境评价与城市规划具有重要意义。论文基于高空间分辨率Geoeye-1立体影像,在建筑物高度、下垫面覆盖类型信息提取的基础上,选择南京一中、光华东街、玄武湖、头陀岭4个区域,采用ENVI-met微气候模式,以城市基本气象站南京站的实时气象数据作为背景气象场,模拟不同区域近地表气温的时空分布特征,并利用区域自动气象站观测数据进行精度检验。结果表明:在时间变化上,ENVI-met模拟气温与实测值之间吻合程度较高;在空间分布上,南京一中与光华东街区域气温时空分布规律总体相似,但城市空间形态的差异使得局部区域气温变化不同,玄武湖区域气温由陆地中心向外围呈递减趋势,而头陀岭地形复杂多变,白天气温变化剧烈,夜间空间变化较小。     

Mesoscale Meteorological Simulations In Paris: Comparisons With Observations During The Experiment Eclap

This paper analyses the meteorological numerical simulation in Paris during two days (March 10 and 13, 1995) observed during ECLAP (Etude de la Couche Limite en Agglomération Parisienne– the boundary-layer study of the Paris area), a recent measurement campaign over the Paris area, in which both in-situ and remote-sensing devices at urban and rural locations have been deployed in addition to the operational meteorological network. The chosen days are well documented and correspond to different meteorological situations leading to pollution events (regarding wind direction, cloud cover, surface and synoptic inversion strength).Comparisons of three-dimensional mesoscale model results with the ECLAP observation data are presented, focusing on the temperature field and turbulent fluxes along with the urban heat island and the evolution of the mixing height. It is shown that the model correctly reproduces the main characteristics of the temperature field, its diurnal evolution (near the ground and higher up) especially the gradient between Paris and the surrounding countryside. The mixing-height evolutions are in a good agreement with the observations and the model is also able to reproduce the turbulent features of the atmosphere. The small difference observed between the urban and rural mixing-height evolution is also well reproduced.     

Moscow Urban Heat Island: Detection,boundaries, and variability

The determination of the anthropogenic impact on the thermal regime of a megalopolis is discussed. The nominal boundaries of the megalopolis thermal effects are determined taking into account orographic and landscape effects and the variability of temperature difference between the center of the city and its suburbs. It is proposed to use the data of stations located within 40-50 km from the urban agglomeration boundaries for calculating the anthropogenic component of the urban heat island. The parameters of the heat island in Moscow are determined from the measurement data on maximum and minimum daily surface air temperature in 2012-2016, and their significant seasonal and intradaily variability is revealed. It is corroborated that anthropogenic causes for the higher air temperature in Moscow as compared with suburbs during the cold season are the release and loss of heat of heating systems; in the absence of snow cover the anthropogenic effect of these sources is enhanced by the thermal radiation of the urban surface.     

Urban Bias in Temperature Time Series – a Case Study for the City of Vienna, Austria

Compared with other large cities Vienna shows different urban development characteristics. The city has had a zero population growth during 1951–1995, a period of rapid growth elsewhere. In spite of its stagnating population of about 1,6 million Vienna has had development in other areas: a doubling of living floor space, a two and a half-fold increase in total energy consumption, a 60% rise of traffic area. In contrast, forests have been reduced by 20% and grasslands within the city borders by 30%. Of the 34 temperature recording stations in the study area of 1450 km², nine series passed the quality tests after careful homogenization. Three of these were in the rural environment and were used as reference series for the urban temperature excess at the other six stations in the urbanized area. The urban excess temperatures vary from site to site: from 0.2 K in suburban areas up to 1.6 K in densely built-up areas. The Vienna case study illustrates two features of more than local interest which should be considered in urban climatology as well as in time series studies where the urban temperature excess is regarded as a bias. Firstly, in a city with constant population the urban heat excess shows significant to strongly significant trends of up to 0.6 K in 45 years due to changes in urban morphology and energy consumption. Secondly, the urban heat island and its trend cannot be regarded simply for the city as a whole. There are different absolute levels, different annual variations and different increases of the urban temperature excess in different parts of a city. The urban effect is more strongly influenced by the local surroundings of the site than by the city as a whole. So, if possible, urban heat islands should not be described by a two station approach only (the typical airport-downtown comparison), nor should it rely on regression between population number and heat island.     

Intelligent urban forms (IUF) a new climate-concerned,urban planning strategy

Summary Adaptive geometrical configurations are presented, which aim to create intelligent urban forms, and which include screening methods applicable to the linear- and grid-type building layouts. They are especially suitable for mid-latitude cities characterized by seasonally swinging climates which necessitate heating in winter and cooling in summer. The screens are envisaged as shading devices in the summer blocking the incoming solar radiation during day-time (that is, on-position), while being removed at night to enhance nocturnal radiative cooling (that is, off-position). In winter they are assumed to be in off-position during sunshine hours to promote the access of solar radiation and in on-position at night to obstruct the sky energy sink and reduce radiant heat losses. Their implications for the urban street canyon climate and the thermal performance of the built environment are simulated using the cluster thermal time constant (CTTC) model. The diurnal variation of both the ambient air temperature and net radiant flux within the urban canopy layer serve as criteria by which the climatetempering effectiveness of the screens is assessed.With 9 Figures     

Assessment of urban heat island effect for different land use–land cover from micrometeorological measurements and remote sensing data for megacity Delhi

Urban heat island intensities (UHI) have been assessed based on in situ measurements and satellite-derived observations for the megacity Delhi during a selected period in March 2010. A network of micrometeorological observational stations was set up across the city. Site selection for stations was based on dominant land use–land cover (LULC) classification. Observed UHI intensities could be classified into high, medium and low categories which overall correlated well with the LULC categories viz. dense built-up, medium dense built-up and green/open areas, respectively. Dense urban areas and highly commercial areas were observed to have highest UHI with maximum hourly magnitude peaking up to 10.7 °C and average daily maximum UHI reaching 8.3 °C. UHI obtained in the study was also compared with satellite-derived land surface temperatures (LST). UHI based on in situ ambient temperatures and satellite-derived land surface temperatures show reasonable comparison during nighttime in terms of UHI magnitude and hotspots. However, the relation was found to be poor during daytime. Further, MODIS-derived LSTs showed overestimation during daytime and underestimation during nighttime when compared with in situ skin temperature measurements. Impact of LULC was also reflected in the difference between ambient temperature and skin temperature at the observation stations as built-up canopies reported largest gradient between air and skin temperature. Also, a comparison of intra-city spatial temperature variations based UHI vis-à-vis a reference rural site temperature-based UHI indicated that UHI can be computed with respect to the station measuring lowest temperature within the urban area in the absence of a reference station in the rural area close to the study area. Comparison with maximum and average UHI of other cities of the world revealed that UHI in Delhi is comparable to other major cities of the world such as London, Tokyo and Beijing and calls for mitigation action plans.     

A Model to Calculate what a Remote Sensor `Sees' of an Urban Surface

Whilst the measurement of radiation emissions from a surface is relativelystraightforward, correct interpretation and proper utilization of the informationrequires that the surface area `seen' be known accurately. This becomes non-trivialwhen the target is an urban surface, due to its complex three-dimensional form andthe different thermal, radiative and moisture properties of its myriad surface facets.The geometric structure creates shade patterns in combination with the solar beamand obscures portions of the surface from the sensor, depending on where it is pointing and its field-of-view (FOV). A model to calculate these surface-sensor-sun relations (SUM) is described. SUM is tested against field and scale model observations, and theoretical calculations, and found to perform well. It can predict the surface area`seen' by a sensor of known FOV pointing in any direction when placed at any pointin space above a specified urban surface structure. Moreover, SUM can predict theview factors of the roof, wall and ground facets `seen' and whether they are sunlit orshaded at any location and time of day. SUM can be used to determine the optimalplacement and orientation of remote sensors to study urban radiation emissions; ifthe facet temperatures are known or modelled it can calculate the average temperatureof the system, and it can determine the directional variation of temperature (anisotropy) due to any particular surface-sensor-sun geometric combination. Thepresent surface geometry used in SUM is relatively simple, but there is scope to makeit increasingly realistic.     

城市建筑布局要素对区域热环境影响的ENVI-met模拟与分析——以南京江北新区部分区域为例

开展城市建筑物方位、高度等建筑布局要素对局地热环境时空变化的影响研究,对于合理的城市规划布局具有重要理论意义与实践参考价值。采用ENVI-met 微气候模式,在南京江北新区顶山街道某区域微气候模拟的基础上,选择一个二类居住用地并设计不同的建筑布局要素作为规划场景,模拟分析了建筑物高度与建筑间距之比（H/W）、建筑布局变化对区域热环境的影响。结果表明:ENVI-met 能够以较高精度模拟2 m高度气温;H/W与建筑布局形式都会影响区域热环境,适当增加H/W可在一定程度上降低夏季气温,H/W为1.4时的热环境更为舒适,而不同建筑布局形式下的不同区域温度差异较大。