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应用MODIS地表反照率产品MCD43C3,结合青藏高原自然带数据、积雪覆盖率和植被指数数据,采用一元线性回归方法分析了2000~2016年青藏高原地表反照率的分布及变化特征,结果表明:1）高原地表反照率空间分布差异大,整体上东南部低、西北部高,受地形和地表覆盖影响较大。2）高原地表反照率四季的空间分布变化明显,高海拔山脉和高寒灌丛草甸是高原地表反照率年内和年际变化的敏感地区。3）高原地表反照率年变化介于0.19~0.26,一定程度上表现为“双峰单谷”型,与地表覆盖类型的季节变化密切相关。4）高原地表反照率年际变化整体呈缓慢波动减小的趋势,平均变率约为－0.4×10-3 a-1,减小的区域约占高原总面积的66%,川西 —藏东针叶林带的西南部地区减小得最快,减小速率超过1.0×10-2 a-1。5）高原地表反照率减小与冰川消融和积雪减少密切相关,高原植被覆盖改善也是一个重要因素。 相似文献
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本文在利用NOAA/AVHRR数据反演得到1982～2000年青藏高原地区地表反照率时空分布的基础上,分析了地表反照率的时空变化及其与温度和降水之间的关系,得到地表反照率与温度和降水之间的统计方程,并用此方程计算了青藏高原地区地表反照率的时空分布。研究结果表明：青藏高原地区年均地表反照率的分布与高原自然地理带的分布特征大致吻合;地表反照率与温度和降水均有较好的相关性,相关性因下垫面植被类型的不同而有较大的差异,滞后1个月的温度和滞后2个月的降水的综合作用与地表反照率的相关性最好;月均地表反照率与温度和降水之间的二元曲线回归方程可以比较好的统计回归计算出青藏高原地区地表反照率的空间分布,该模型的系统偏差比较小,回归计算的效果比较好。 相似文献
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利用MODIS卫星资料反演中国地区晴空地表短波反照率及其特征分析 总被引：16，自引：0，他引：16
利用MODIS地表双向反照率产品(MOD43B1),结合地表海拔高度和地表覆盖类型资料,计算并分析了中国地区晴空反照率的时空分布,以及地表反照率与地形和地表覆盖的关系.首先,利用改则自动气象站的地基观测对MODIS地表反照率进行了对比验证.验证结果表明卫星观测可以较好地反映反照率随时间的变化,MODIS地表反照率与地表实测反照率符合较好.年平均地表反照率与海拔高度有很好的相关,反照率的高值出现在高海拔山区.冬春季节,我国高海拔山区因积雪覆盖成为反照率的高值区;夏秋季节,地表反照率主要受地表土壤湿度和植被盖度的影响,沙地和沙漠地带反照率最高.最后,计算了中国典型地表类型的反照率随时间的变化,结果表明大部分地表类型的反照率具有较大的时间变化,地表反照率在春秋季节较大,夏季反照率较小. 相似文献
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青藏高原地表特征时空分布 总被引：12，自引：3，他引：9
通过利用地理信息数据库、卫星反演参数、气象观测数据,分析了我国青藏高原地区地表植被覆盖、地表反照率分布、地表蒸发分布、地表积雪分布.结果显示,随着青藏高原地表年平均气温的显著升高,青藏高原部分区域地表覆盖特征也发生了改变.在青藏高原南缘湿润大区降水充分地区,地表反照率相对较低,潜热蒸发量最大,1982～2000年期间地表植被覆盖呈明显增加趋势.青藏高原地区积雪覆盖在各个气候区域也呈现同步变化特征,自1970～1989期间,降雪量呈持续增加趋势,但之后至2000年期间,全区降雪量呈下降趋势,其中积雪覆盖变化最强烈的时段发生在10月～4月之间,变化幅度最大的区域位于青藏高原的东南部区域. 相似文献
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为了揭示青藏高原三江源区草地退化对生态系统地表反照率的影响,利用2006年12月至2007年11月一整年的观测数据,分析了地表反照率的季和日变化特征及其影响因子。退化草地生态系统的年均地表反照率为0.22,生长季(5～9月)的平均地表反照率为0.18,非生长季为0.25。在植物生长初期的5月,地表反照率主要受土壤水分影响,5月末至6月初出现全年最低值;植物生长旺季的7～8月,受植被的影响地表反照率相对较稳定,并略高于生长季中其它各月。地表反照率的日变化呈"U"型,阴天的地表反照率高于晴天。全年地表反照率出现的最大频率集中在0.20附近,非生长季在0.22附近,生长季在0.18附近。退化草地生态系统生长季地表反照率的变化受土壤水分和植被的的影响,而非生长季受积雪的影响较大。 相似文献
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城市热岛效应的卫星遥感分析 总被引：16，自引：1，他引：16
利用MODIS资料研究了2004年4月南京城市热岛特征及其影响因子,结合地表覆盖类型分析了植被归一化指数(Normalized Difference Vegetation Index,NDVI)、地表温度(ts)、地表反照率(α)的城乡差异及其相互关系,探讨了城市热岛(Urban Heat Island,UHI)效应形成的机制.结果表明:南京城区存在着明显的城市热岛效应;城市平均ts比乡村高约10.83%;城市NDVI和α分别比乡村低约为62%和18.75%;NDVI与ts呈负相关,相关系数为-0.73,而NDVI与α之间关系与波段有关;城乡植被覆盖差异是造成UHI的主要原因,其次是地表反照率. 相似文献
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城市环境日益受到人们重视, 南京是长江下游人口密集的城市, 研究南京市地表温度分布对了解南京城市气候, 改善生活环境, 为城市发展规划提供有效的气象服务具有一定科学意义。该文利用2002年8月21日10:30 (北京时) ASTER热红外数据, 在ENVI软件的支持下, 通过劈窗算法反演南京城市地表温度, 进一步生成城市地表温度分布等温线图。用同时相ETM+数据进行验证, 二者十分吻合, 说明ASTER反演结果可靠。结果表明:南京市存在明显的热岛效应, 城市地表温度分布差异大; 不同下垫面的地表温度差异明显, 城区地表温度总体高于郊区, 植被覆盖密集区地表温度低于植被稀疏地, 具有较大水域面积和较密植被的城中各大公园形成多个冷岛, 长江水体温度最低; 随着城市的扩大, 新城区热岛效应更加明显。水体和密集植被能显著改善城市环境。 相似文献
10.
南京市夏季热岛特征及其与土地利用覆盖关系研究 总被引：4，自引：0，他引：4
利用南京市7月的Landsat TM热红外波段数据,根据单窗算法反演得到南京市地表温度,讨论了南京市热岛特征,并分析了产生这种现象的原因。通过遥感和地理信息系统相结合,运用Landsat TM数据,提取出南京市下垫面类型,分析了不同地表覆盖类型的热辐射特征并定量地分析了土地利用及植被对地表温度的影响。结果显示,南京市夏季主要存在3个热岛中心,分别是建成区、大厂区和八卦洲。南京城区地表温度明显比郊区地表温度高,通过地表温度对比分析发现,城区平均地表温度比城市边缘和远郊区地表温度分别高出3.5℃和5.7℃,城市热岛效应明显。不同地表覆盖类型的地表温度也有显著差异,从高到低依次为：城镇建设用地、耕地、草地、林地、水体。城镇建设用地与水体的表面温度最大相差14℃。城市地表温度与植被覆盖度具有明显的负相关关系,城市地表植被覆盖度低是城市热岛出现的主要原因,今后应当更加注重城市绿地建设,提高植被覆盖率。 相似文献
11.
Statistical and dynamical characteristics of the urban heat island intensity in Seoul 总被引：2，自引：0，他引：2
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. 相似文献
12.
Urban-rural difference of land cover is the key determinant of urban heat island (UHI). In order to evaluate the impact of land cover data on the simulation of UHI, a comparative study between up-to-date CORINE land cover (CLC) and Urban Atlas (UA) with fine resolution (100 and 10 m) and old US Geological Survey (USGS) data with coarse resolution (30 s) was conducted using the Weather Research and Forecasting model (WRF) coupled with bulk approach of Noah-LSM for Berlin. The comparison between old data and new data partly reveals the effect of urbanization on UHI and the historical evolution of UHI, while the comparison between different resolution data reveals the impact of resolution of land cover on the simulation of UHI. Given the high heterogeneity of urban surface and the fine-resolution land cover data, the mosaic approach was implemented in this study to calculate the sub-grid variability in land cover compositions. Results showed that the simulations using UA and CLC data perform better than that using USGS data for both air and land surface temperatures. USGS-based simulation underestimates the temperature, especially in rural areas. The longitudinal variations of both temperature and land surface temperature show good agreement with urban fraction for all the three simulations. To better study the comprehensive characteristic of UHI over Berlin, the UHI curves (UHIC) are developed for all the three simulations based on the relationship between temperature and urban fraction. CLC- and UA-based simulations show smoother UHICs than USGS-based simulation. The simulation with old USGS data obviously underestimates the extent of UHI, while the up-to-date CLC and UA data better reflect the real urbanization and simulate the spatial distribution of UHI more accurately. However, the intensity of UHI simulated by CLC and UA data is not higher than that simulated by USGS data. The simulated air temperature is not dominated by the land cover as much as the land surface temperature, as air temperature is also affected by air advection. 相似文献
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A NUMERICAL STUDY ON THE INFLUENCES OF URBAN PLANNING AND
CONSTRUCTION ON THE SUMMER URBAN HEAT ISLAND IN THE
METROPOLIS OF SHENZHEN 总被引：3，自引：3，他引：0
By means of the regional boundary layer model (RBLM), a study on the influences of the urban planning and construction on the summer urban heat island (UHI) in the metropolis of Shenzhen is performed. In the study, the current summer UHI distribution, the influences of the increasing high-density construction and the energy consumption on the summer air temperature distribution, and the influences of the urban ventilation corridor on the summer air temperature distribution are numerically analyzed. Some conclusions are drawn in the light of the study: (1) The summer UHI is more obvious in day time than that in night time in the summer of Shenzhen, and the maximum values of UHI intensity in the day time appear in the areas with high-density construction, which are located in Nanshan, Futian and Luohu and western Bao′an districts. (2) The increase of construction density and energy consumption in the urban area will lead to the increase of temperature near the ground, and the increase of temperature at nighttime is more obvious than that at daytime. (3) The ventilation corridor can effectively reduce the UHI intensity and can be taken as a method to eliminate the negative climatic effect caused by the increase of high-density construction and energy consumption in the future. 相似文献
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Urban Heat Island and Boundary Layer Structures under Hot Weather Synoptic Conditions: A Case Study of Suzhou City, China 总被引：3，自引：0，他引：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
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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
16.
Large-Eddy Simulation of Mesoscale Circulations Forced by Inhomogeneous Urban Heat Island 总被引：1，自引：1，他引：0
The large-eddy simulation mode of the Weather Research and Forecasting model is employed to simulate the planetary boundary-layer characteristics and mesoscale circulations forced by an ideal urban heat island (UHI). In our simulations, the horizontal heterogeneity of the UHI intensity distribution in urban areas is considered and idealized as a cosine function. Results indicate that the UHI heating rate and the UHI intensity heterogeneity affect directly the spatial distribution of the wind field; a stronger UHI intensity produces a maximum horizontal wind speed closer to the urban centre. The strong advection of warm air from the urban area to the rural area in the upper part of the planetary boundary-layer causes a more stable atmospheric stratification over both the urban and rural areas. The mesoscale sensible heat flux caused by the UHI circulation increases with UHI intensity but vanishes when the background wind speed is sufficiently high $(>$ 3.0 $\mathrm{{m\,s}}^{-1})$ . 相似文献
17.
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
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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
19.
Response of London’s Urban Heat Island to a Marine Air Intrusion in an Easterly Wind Regime 总被引：1，自引：0，他引：1
Numerical simulations are conducted using the Weather Research and Forecast numerical model to examine the effects of a marine air intrusion (including a sea-breeze front), in an easterly wind regime on 7 May 2008, on the structure of London??s urban heat island (UHI). A sensitivity study is undertaken to assess how the representation of the urban area of London in the model, with a horizontal grid resolution of 1?km, affects its performance characteristics for the near-surface air temperature, dewpoint depression, and wind fields. No single simulation is found to provide the overall best or worst performance for all the near-surface fields considered. Using a multilayer (rather than single layer or bulk) urban canopy model does not clearly improve the prediction of the intensity of the UHI but it does improve the prediction of its spatial pattern. Providing surface-cover fractions leads to improved predictions of the UHI intensity. The advection of cooler air from the North Sea reduces the intensity of the UHI in the windward suburbs and displaces it several kilometres to the west, in good agreement with observations. Frontal advection across London effectively replaces the air in the urban area. Results indicate that there is a delicate balance between the effects of thermal advection and urbanization on near-surface fields, which depend, inter alia, on the parametrization of the urban canopy and the urban land-cover distribution. 相似文献