共查询到20条相似文献，搜索用时 140 毫秒
1.
本文首先采用模糊c-均值聚类法和剔除法,筛选出用于计算绵阳城市热岛强度的10个城市站和15个郊区站,然后利用这25个自动气象站的逐时气温资料,分析2018年绵阳城市热岛效应不同时间尺度的变化特征。结果表明:2018年绵阳存在城市热岛效应,平均热岛强度为0.64℃,表现为弱热岛等级;四季热岛效应冬季最强,其次是春季,夏季和秋季相当;逐月热岛强度3月最大、7月最小;绵阳城市热岛效应存在明显的日变化,热岛强度夜间大于白天,日最大热岛强度几乎均出现在晚上。 相似文献
2.
3.
4.
天津城市热岛效应的时空变化特征 总被引：7，自引：2，他引：5
应用2008年天津市14个自动气象站逐小时资料和6h一次的地面常规资料,对天津城市热岛效应的时空特征进行了分析,结果表明：天津市热岛强度的日变化、月变化和年、季特征显著,且天津市热岛强度与城郊站的选择方法有密切关系。通过多元线性回归方法,分析了天津市热岛强度与云量、云高、风向、风速和相对湿度这5种气象要素的相关性,发现风速是影响天津城市热岛效应的显著气象因子,但总体而言气象要素对天津城市热岛效应的影响相对较小。 相似文献
5.
6.
金丽娜 《沙漠与绿洲气象(新疆气象)》2021,15(1):97-102
选取1971—2017年7个国家级气象站的气温资料,分析年代际气温变化特征及城郊温差、城县温差;选取2014—2017年103个国家考核区域气象站及7个国家级气象站逐时气温资料,利用标准化相对气温法,研究西安市城市热岛、冷岛的年、季平均空间分布特征,以及逐日热岛、冷岛变化规律。结果显示:1971—2017年城区、郊区和郊县气温均呈上升趋势,城区增温速率最大,郊县增温速率最小,进入21世纪后,城市热岛效应较为显著。西安市城市热岛、冷岛现象明显,且均呈"多中心"特征,热岛中心多为老城区及旅游中心,建筑物面积和人口密度占绝对优势;冷岛中心多为地势较高、水域绿被覆盖较大、非人口密集区的秦岭坡脚线附近。城区代表站的年、春季、夏季、秋季基本处于平稳状态,年、春季、夏季06—07时热岛强度最大,秋季、冬季23时热岛强度最大;郊区代表站和郊县代表站的年及四季热岛、冷岛强度均有明显的日变化特征,且变化趋势相反;郊区代表站10时热岛转为冷岛,春、夏季16—17时转为热岛,年及秋、冬两季19—20时转为热岛;郊县代表站年、春季、夏季06—07时冷岛强度最大,秋季、冬季2时冷岛强度最大,08时后冷岛开始减弱,12—13时为最弱后开始增强。 相似文献
7.
文章选取1981—2015年呼和浩特市及周边地区气温和地表温度等资料,通过其年际变化趋势,分析了呼和浩特市夏季城市热岛效应的时空变化特征。结果表明:2004—2012年呼和浩特市夏季城市热岛效应明显加剧,其中2010年是热岛效应最强的一年;以最低气温表征的热岛强度更能明显地反映出热岛效应加剧的趋势,热岛强度的变化趋势与月平均最高气温的变化趋势更为一致;在热岛效应加剧的背景下,月平均最高地表温度的变化尤为显著。 相似文献
8.
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。 相似文献
9.
利用1981—2013年济宁、兖州、嘉祥、汶上站逐日4个时次的平均气温、平均风速、降水量、云量和能见度资料,对不同天气条件下济宁市的城市热岛效应进行研究.结果表明:济宁城市热岛效应具有明显的月季变化特征和日变化特征,具体为冬半年明显高于夏半年,白天的热岛强度明显低于夜间,中午前后最弱;济宁市四季热岛强度的变化规律是冬季最强,夏季最弱,春秋居中,除秋季外均呈现缓慢上升趋势.在不同气象条件下,济宁城市热岛强度也存在很大差异,其中在晴朗无风气象条件下表现最为突出,平均值达到0.79 ℃,其昼夜变化幅度也最大;在降雨时城市热岛强度最小,平均仅有0.09 ℃,其昼夜变化幅度也最小;大于等于4.0 m/s大风天气和雾均多发生在秋冬季,且雾对城市热岛的形成和昼夜变化影响明显大于风对城市热岛的影响;在晴朗无风和大雾条件下,02时热岛强度最强,当有降水出现时,20时热岛强度最强,出现大风天气时,08时热岛强度最强,所有研究天气条件下,14时热岛强度均表现为最弱. 相似文献
10.
利用2008年全年渤海湾西岸(天津)14个自动气象站逐小时资料和6 h一次的地面常规资料,采用统计分析的方法,研究了天津城市热岛效应对渤海湾西岸海陆风的影响.结果表明:在冷岛和强热岛条件下,渤海湾西岸海风的发生频率较低,强热岛阻碍了海风向内陆的传播;内陆站在弱热岛条件下出现最大海风的频次较高,但其海风强度与无热岛或冷岛状况下相比要小一些;城市热岛效应的出现,推迟了城市周围郊区站海风的开始时间,缩短了海风的持续时间;城市站的海风风速与热岛强度呈负相关关系,但热岛效应对陆风风速的影响较强,陆风风速在热岛强度小于2.6℃时,随着其值的增大而减小,反之则增加;当海风向内陆延伸时,热岛强度会在午后海风盛行时段内增强,并与传播到此处的海风环流叠加,导致近地层海风风速增强,并可西伸至城市中心. 相似文献
11.
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. 相似文献
12.
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。 相似文献
13.
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. 相似文献
14.
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。 相似文献
15.
北京春季城市热岛特征及强热岛影响因子 总被引：11，自引：0，他引：11
应用北京地区地面气象观测台1990-2004年4月的气温资料,分析了近15a北京春季城市热岛特征,结果表明：春季夜间城市热岛要强于白天。还分析了春季一个强热岛形成和减弱消失过程的气象影响因子,结果表明：北京春季夜间特定条件下存在强热岛,强热岛中心在白家庄、天安门、公主坟连线的主城区;白天强热岛会减弱消失。强热岛在夜间形成的原因是日落后郊区地面大气降温速率和幅度远大于城区地面大气。白天有日照的晴夜北京城、郊地面风场很弱（≤1．0m／s）,多个测站甚至出现静风,同时城区垂直方向上15m高度以下持续存在很弱（≤1．5m／s）的风场,城区320m高度以下大气持续存在强逆温,这些因素共同促使春季强热岛的形成和维持。强热岛在白天减弱消失的原因是日出后太阳辐射的加热作用引起郊区地面大气升温速率和幅度大于城区地面大气,同时城区大气稳定度减弱、城区大气逆温消失、城郊地面风速增加。 相似文献
16.
Characterization and estimation of urban heat island at Toronto: impact of the choice of rural sites 总被引：3，自引：2，他引：1
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. 相似文献
17.
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。 相似文献
18.
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。 相似文献
19.
20.
Manju Mohan Yukihiro Kikegawa B. R. Gurjar Shweta Bhati Narendra Reddy Kolli 《Theoretical and Applied Climatology》2013,112(3-4):647-658
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. 相似文献