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1.
The July urban heat island of Bucharest as derived from modis images   总被引：2，自引：1，他引：1  
The urban heat island (UHI) of the city of Bucharest (Romania) is analyzed in terms of its extension, geometry, and magnitude using the surface thermal data provided by the moderate resolution imaging spectroradiometer (MODIS) sensors. An objective method is developed that allows to delineate the UHI. The study focuses on the months of July from the 2000–2006 time interval. The average surface temperatures obtained for each pixel (1 km resolution) were analyzed on cross-profiles that helped us to determine the outline of the UHI. The shifting points identified by the Rodionov test in the temperature series of each profile were considered as possible limits of the UHI. Seemingly, the land cover has a major influence on the extension and the geometry of the Bucharest UHI in July. The magnitude of the heat island was calculated by comparing the average temperature inside its limits and the average temperature of the 5 km (a) and of the 10 km (b) buffers around it. The thermal difference between the UHI and the surrounding area of Bucharest is higher and more variable during the daytime, and is noticeably related to the land cover.  相似文献   

2.
基于MODIS数据的城市热岛动态监测及时空变化分析   总被引：6，自引：1，他引：6  
以人口密集、经济快速发展的福建省沿海地区为研究区，在遥感和地理信息系统技术支持下，采用经优选的MODIS遥感数据反演的地表温度，提取城市热岛和植被覆盖信息，对研究区城市热岛进行动态监测和时空变化分析，并对地表温度与植被覆盖的互动关系进行定性与定量分析。结果表明：福建沿海城市热岛面积整体上呈逐年增长趋势，福州和莆田更为明显；城市热岛主要集中在人口密集、工商业发达的区域，同时沿海平原的热岛效应比内陆山区更为显著；地表温度与植被覆盖呈负相关，并且相关系数逐年增长。  相似文献   

3.
A strong urban heat island (UHI) appeared in a hot weather episode in Suzhou City during the period from 25 July to 1 August 2007. This paper analyzes the urban heat island characteristics of Suzhou City under this hot weather episode. Both meteorological station observations and MODIS satellite observations show a strong urban heat island in this area. The maximum UHI intensity in this hot weather episode is 2.2℃, which is much greater than the summer average of 1.0℃ in this year and the 37-year (from 1970 to 2006) average of 0.35℃. The Weather Research and Forecasting (WRF) model simulation results demonstrate that the rapid urbanization processes in this area will enhance the UHI in intensity, horizontal distribution, and vertical extension. The UHI spatial distribution expands as the urban size increases. The vertical extension of UHI in the afternoon increases about 50 m higher under the year 2006 urban land cover than that under the 1986 urban land cover. The conversion from rural land use to urban land type also strengthens the local lake-land breeze circulations in this area and modifies the vertical wind speed field.  相似文献   

4.
The urban heat island (UHI) is a well-documented effect of urbanization on local climate, identified by higher temperatures compared to surrounding areas, especially at night and during the warm season. The details of a UHI are city-specific, and microclimates may even exist within a given city. Thus, investigating the spatiotemporal variability of a city’s UHI is an ongoing and critical research need. We deploy ten weather stations across Knoxville, Tennessee, to analyze the city’s UHI and its differential impacts across urban neighborhoods: two each in four neighborhoods, one in more dense tree cover and one in less dense tree cover, and one each in downtown Knoxville and Ijams Nature Center that serve as control locations. Three months of temperature data (beginning 2 July 2014) are analyzed using paired-sample t tests and a three-way analysis of variance. Major findings include the following: (1) Within a given neighborhood, tree cover helps negate daytime heat (resulting in up to 1.19 °C lower maximum temperature), but does not have as large of an influence on minimum temperature; (2) largest temperature differences between neighborhoods occur during the day (0.38–1.16 °C difference), but larger differences between neighborhoods and the downtown control occur at night (1.04–1.88 °C difference); (3) presiding weather (i.e., air mass type) has a significant, consistent impact on the temperature in a given city, and lacks the differential impacts found at a larger-scale in previous studies; (4) distance from city center does not impact temperature as much as land use factors. This is a preliminary step towards informing local planning with a scientific understanding of how mitigation strategies may help minimize the UHI and reduce the effects of extreme weather on public health and well-being.  相似文献   

5.
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 PM2.5 and PM2.5–10) 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 PM2.5–10, while cloud index, wind speed and mixing height influenced the variation in PM2.5. In conclusion, a direct relationship between UHI effect and PM was not obvious.  相似文献   

6.
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   

7.
以辽宁地表温度为研究对象,采用普适性单通道算法,利用FY-3A/MERSI数据,并结合MODIS 1000 m分辨率数据,反演了2009年和2010年4-9月间10个时次晴空或局部晴空时的地表温度。结果表明：计算验证了模型的反演精度与同期NASA所发布MODIS地表温度产品的精度相当,其结果与相应的56个气象站点的实际观测数据相一致。多源遥感数据的综合应用,可获得较合理的地表温度反演结果;不同土地覆盖类型间地表温度的高低在相同时间内存在显著差异;研究期内,林地、水田、旱地和建设用地的NDVI与地表温度具有负相关性。综合利用遥感、地理信息系统技术,可以表征地表温度与土地利用类型以及地表温度与归一化植被指数(NDVI)之间的关系。  相似文献   

8.
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   

9.
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   

10.
Although previous studies show that urbanization contributes to less than 10 % of the long-term regional total warming trend of mean surface air temperature in northeast China (Li et al. 2010), the urban heat island (UHI) impact on extreme temperatures could be more significant. This paper examines the urbanization impact on extreme winter minimum temperatures from 33 stations in North China during the period of 1957–2010. We use the Generalized Extreme Value (GEV) distribution to analyze the distribution of extreme minimum temperatures and the long-term variations of the three distributional characteristics parameters. Results suggest that among the three distribution parameters, the position parameter is the most representative in terms of the long-term extreme minimum temperature change. A new classification method based on the intercommunity (factors analysis method) of the temperature change is developed to detect the urbanization effect on winter extreme minimum temperatures in different cities. During the period of rapid urbanization (after 1980), the magnitude of variations of the three distribution parameters for the urban station group is larger than that for the reference station group, indicating a higher chance of occurrence of warmer weather and a larger fluctuation of temperatures. Among different types of cities, the three parameters of extreme minimum temperature distribution of the urban station group are, without exception, higher than those of the reference station group. The urbanization of different types of cities all show a warming effect, with small-size cities have the most evident effects on extreme minimum temperatures.  相似文献   

11.
基于2001～2018年中分辨率成像光谱仪（MODIS）探测的白天地面温度（简称MODIS 白天地温）资料,与青藏高原（简称高原）122个气象站点观测的最高气温资料,在年尺度上评估了MODIS 白天地温在高原的适用性,研究了高原五个干湿分区下MODIS 白天地温的海拔依赖型变暖特征,得到以下主要结论:（1）MODIS白天地温能够基本再现观测的最高气温的时空以及海拔依赖型变暖特征;（2）高原整体上,MODIS白天地温存在显著的海拔依赖型变暖特征,平均海拔每增加100 m,其趋势增加0.02°C (10a)?1,且受积雪—反照率反馈主导;（3）干湿分区下,海拔依赖型变暖特征在高原表现为偏湿润地区强于偏干旱地区;季风区强于西风区。海拔依赖型特征强弱:半湿润地区＞湿润半湿润地区＞半干旱地区＞湿润地区＞干旱地区。平均海拔每增加100 m,以上区域的地温趋势分别增加0.06,0.03,0.03,0.01,0.01°C (10a)?1。半湿润和湿润半湿润地区年均温在0°C左右,在气候变暖背景下积雪—反照率反馈作用最为强烈,是其海拔依赖型变暖的主导因素;干旱与半干旱地区年均温相对更低,气候变暖程度对积雪影响相对较小,积雪—反照率反馈作用被限制,但仍对上述地区的海拔依赖型变暖起主导作用;而湿润地区的积雪覆盖率的上升可能是由于降雪（固态降水）增加抵消了积雪融化损耗,云辐射、水汽等其他因素主导了其海拔依赖型变暖。  相似文献   

12.
A number of indices have been employed to describe weather extremes on the basis of climate regimes and public concerns. In this study, we combined these traditional indices into four groups according to whether they relate to warm (Twarm), cold (Tcold), wet (Pwet), or dry (Pdry) extremes. Analysis of the combined indices calculated for the daily temperatures and precipitation at 750 meteorological stations in Korea, China, and Japan for 1960s?C2000s shows increasing trends in Twarm and Pdry events and decreasing trends in Tcold events in recent decades, particularly in the northern part of East Asia. A notable regional variation is an increase in the Pwet events in the Korean Peninsula. We applied the same analysis to a 200-year global climate model simulation for 1900?C2099 using the National Center for Atmospheric Research-Community Climate System Model 3. During the 20th century, the changes in Twarm and Tcold calculated from the model data are largely consistent with those calculated from the observations, especially in northern East Asia. The model projections for the 21st century indicate statistically significant increasing Twarm and decreasing Tcold trends in extreme events over the region. Results obtained from historical archives and model simulations using our combined weather extreme indices suggest that northern East Asia will be subject to increased warm and dry extremes and the Korea Peninsula will experience more wet extremes.  相似文献   

13.
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   

14.
基于MODIS的安徽省代表城市热岛效应时空特征   总被引：2，自引：0，他引：2       下载免费PDF全文
利用2001—2010年覆盖安徽省的MODIS数据,选取在气候、地理、城市化等方面具有代表性的合肥、芜湖、阜阳作为研究对象,并结合GIS技术,分析地表温度的日变化及季节变化特征,得到安徽省代表城市热岛效应的时空分布。结果表明:安徽省省会合肥的热岛效应最为显著,安徽省南部代表城市芜湖的热岛效应强于北部代表城市阜阳, 同时具有显著的日变化和季节变化特征。近10年来,安徽代表城市热岛面积和热岛强度均呈增加趋势,但合肥热岛强度大于3 ℃的极端热岛效应有一定缓解。白天大片水体对缓解城市的热岛效应作用明显,而夜晚则不明显,甚至成为地表温度的高值中心。夏季地表温度与归一化植被指数的负相关最显著,即提高城市植被覆盖度对降低地表温度和缓解城市热岛效应有重要影响。  相似文献   

15.
城市热岛强度变化对安徽省气温序列的影响   总被引：1，自引：0，他引：1  
根据安徽省81个气象台站的资料研究了其气温序列特点,并选取了其中46个台站,划分为城市站、乡村站、国家基本/基准站等类别,对1966～2005年期间平均、最高、最低气温的年、季变化进行了分析比较.结果表明:两个时段各类型台站3项气温的增温率、热岛增温率、热岛增温贡献率均表现为城市站最大,国家基本/基准站次之,乡村站最小...  相似文献   

16.
利用ASTER数据反演南京城市地表温度   总被引：3，自引：1，他引：2  
利用针对ASTER数据的分裂窗算法,反演了南京城市地表温度,并用实际观测资料和同步的MODIS数据对反演结果进行了验证,结果表明：基于ASTER数据的地表温度反演结果与实际观测资料相差0.9℃,与MODIS数据的反演结果具有较好的空间一致性;基于ASTER数据反演的当日南京地表温度在23～56℃范围内,城市地表温度普遍高于35℃,市内公园地表温度略低,多位于30～35℃,长江水体温度低于30℃,地表温度存在明显的空间差异;南京城市夏季白天存在明显＂热岛效应＂,热岛强度的空间差异与南京城市发展、规划有关。  相似文献   

17.
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 ΦW, it was determined thermally induced nighttime cool drainage winds could account for inflating the UHI magnitude in winter.  相似文献   

18.
Thermal infrared images from Landsat satellites are used to derive land surface temperatures (LST) and to calculate the intensity of the surface urban heat island (UHI) during the summer season in and around the city of Brno (Czech Republic). Overall relief, land use structure, and the distribution of built-up areas determine LST and UHI spatial variability in the study area. Land-cover classes, amount and vigor of vegetation, and density of built-up areas are used as explanatory variables. The highest LST values typically occur in industrial and commercial areas, which contribute significantly to surface UHI intensity. The intensity of surface UHI, defined as the difference between mean LST for urban and rural areas, reached 4.2 and 6.7 °C in the two images analyzed. Analysis of two surface characteristics in terms of the amount of vegetation cover, represented by normalized difference vegetation index, demonstrates the predominance of LST variability (56–67 % of explained variance) over the degree of urbanization as represented by density of buildings (37–40 % of LST variance).  相似文献   

19.
The statistical scheme is proposed for the forecast of surface air temperature and humidity using operative weather forecasts with 3–5-day lead time from the best forecasting hydrodynamic models as well as the archives of forecasts of these models and observational data from 2800 weather stations of Russia, Eastern Europe, and Central Asia. The output of the scheme includes the forecasts of air temperature for the standard observation moments with the period of 6 hours and extreme temperatures with the lead times of 12–120 hours. The accuracy of temperature and humidity forecasts for the period from July 2014 till June 2017 is much higher than that for the forecasts of original hydrodynamic models. The skill scores for extreme temperature forecasts based on the proposed method are compared with the similar results of the Weather Element Computation (WEC) forecasting scheme and forecasts by weathermen.  相似文献   

20.
应用卫星资料分析苏州夏季城市热岛效应   总被引：5，自引：3，他引：2  
朱焱  朱莲芳 《气象科学》2009,29(1):77-83
利用苏州2004-2007年自动气象站资料以及购自中国科学院对地观测与数字地球科学中心的Landsat 5卫星(25 m分辨率)资料,分析研究苏州地区城市热岛总体特点以及分布规律,并对可能变化做一些探讨.分析认为,由于城市热岛效应,苏州地区气温呈中间高两侧低的分布特征,气温高值中心呈西北-东南走向,沿太湖及沿江地区气温相对较低;苏州城市地表温度呈明显的放射型分布,以市区中心向四周呈放射状分布.  相似文献   

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