北京城市化进程对城市热岛的影响研究

利用1971～2000年北京20个气象观测站逐日４个时次（02:00、08:00、14:00、20:00）的温度资料，选取具有代表性的城区和郊区多个站点的平均值对北京城市化进程对城市热岛效应的影响、城市热岛强度的日变化和长期变化进行了研究.分析结果指出：（1）北京城市热岛强度和总人口对数呈线性相关关系，其长期变化相关系数为076；（2）北京城市建成区的范围与城市热岛影响范围呈同步变化趋势；(3)不同时次城市热岛强度的长期变化指出，北京城市热岛强度以平均每10年022℃的速率加剧，其中1999年北京热岛强度达113℃（夜间，02:00）；(4)夜间热岛强度明显大于日间.就10年平均而言, 20世纪80年代和90年代夜戒热岛强度均超过05℃；(5)一天4个时次热岛强度的季节变化趋势基本一致，均表现为冬季强、夏季弱.并且，夜间02:00时热岛最强，中午14:00时热岛最弱.     

北京城市热岛“尺度”变化与城市发展

用北京地区20个气象观测站、1960~2000年的温度资料研究了北京城市热岛的季节变化, 年际变化, 进而用北京的城市化指数, 讨论了它与热岛强度与尺度范围变化之间的关系, 得到如下几点结论: (i) 北京城市热岛存在明显的季节变化, 其中以冬季为最强, 春、秋季次之, 夏季为最小, 城市热岛的季节变化主要发生在市区, 冬季市中心的温度在0.8℃以上, 夏季只有0.5℃. (ii) 北京城市热岛强度具有清楚年际增温, 年平均热岛强度的增温率为0.3088℃/10a, 其中冬季的增温率最大, 春、秋季次之, 夏季为最小, 热岛强度的增加主要由市区的温度上升引起的. (iii) 改革开放以来, 城市化指数成几十倍乃至百倍的增长, 热岛强度也出现了跃变式的增加, 且随城市建筑群扩大, 热岛“尺度”范围亦显著扩大. (iv) 城市化指数的年际变化与城市热岛强度的年际变化非常相似, 具有良好的线性关系, 它们与热岛强度之间的相关系数都已超过了0.1%信度.     

近10年来北京夏季城市热岛的变化及环境效应的分析研究

根据1993～2003年北京地区气象台站7、8月的温度资料，分析研究了近10年来北京夏季城市热岛的变化及其环境效应.结果表明：北京夏季城市热岛的水平范围扩大到近郊区和远郊区的通州，分布特征也由“单中心”转变为“多中心”；平均热岛强度呈逐渐增强趋势，在夏季出现了强热岛；北京夏季出现热岛和强热岛的天数激增，7月最大热岛强度也呈逐年上升趋势；热岛的强度和水平分布都有明显的日变化；由于热岛效应使城区增温显著，北京夏季的高温日（Tmax≥35℃）也逐年增多. 本文还指出朝阳区气象观测站由于周围高大植被的影响，观测资料已不具备城区代表性.同时也证明绿化对降低城市热岛效应是极为有效的.本文的研究成果对北京城市发展和规划有一定的科学参考价值.     

污染天气下成都城市热岛环流结构的数值模拟

本文利用中尺度模式WRF V3.9对2016年7月16日成都一次污染天气下的城市热岛环流个例进行了数值模拟,分析了城市热岛环流的三维结构及演变特征.并通过设计减少气溶胶光学厚度的敏感性试验,研究了污染对城市热岛环流的可能影响.结果表明:当地时间17∶00城市热岛环流开始形成.随着热岛强度增强,环流增强,城乡边界处的城市风锋不断向城市中心推进.19∶00热岛环流结构最显著.21∶00环流结构被破坏,仅低层存在微弱的乡村风.在热岛环流结构最显著时刻,近地面风场由郊区向城市辐合,地面以上2.0km处风场由城市向乡村辐散,辐散中心与辐合中心位置大致对应.此时城市风锋在城市处合并,环流的水平尺度约为城市尺度的2～2.5倍.当气溶胶光学厚度减小后,城市热岛环流尺度和强度以减小为主.特别是在热岛环流最显著时刻,低层乡村风风速减小,城市风锋最大上升速度降低,环流的水平尺度在西、南、北三个方向均减小,且高空回流高度降低.可能的影响机制是,气溶胶光学厚度减小后,净辐射通量增大,城乡地表能量通量差异增大,城市边界层高度升高.但城市边界层高度升高对城市热岛的抑制作用超过了城乡地表能量通量差异增加对城市热岛的增强作用,最终造成城市热岛减弱,环流减弱.     

无参考序列条件下地面气温观测资料城市化偏差订正方法：以北京站为例

本文以北京气象站长期地面气温观测资料为例,发展了一种无早期参考序列条件下城镇站城市化偏差评价和订正方法.首先对北京站逐月平均最高、最低气温资料进行质量控制和均一化处理,并借助卫星遥感亮度温度资料遴选附近乡村站;然后利用最近3年逐时地面气温资料,计算观象台和5个乡村站各月平均地面气温的差值,把其作为北京站1915-2012年期间的城市化累积影响;最后假设城市化累积影响在整个研究时期呈匀速增长,采用线性订正法对地面月平均气温序列中的城市化偏差进行订正.分析表明：资料均一化处理后,北京站近百年最高、最低和平均气温多年平均值有所下降,气温日较差则有所提高,但三种年平均气温序列增温趋势和年平均气温日较差序列下降趋势有所增强.北京站年平均最低气温、平均气温和气温日较差序列中均存在较大的城市化累积影响,其中最低气温和平均气温四个季节均为正值,冬季最大,秋季次之,夏季最小,四季和年平均气温日较差均为较大的负值.订正城市化偏差后,最低气温和平均气温增加速率均明显下降,年平均气温日较差下降趋势则明显变弱.     

安徽女山湖自然保护区浮游生物群落生态

2007年4月-2009年5月对安徽女山湖自然保护区浮游生物群落生态进行调查研究,共检出浮游植物8门45属113种;浮游动物包括原生动物、轮虫、枝角类、桡足类,共检出33属78种.分析表明女山湖不同季节浮游生物种类组成的变化趋势不同,但整体看来,浮游植物组成以蓝藻为主,浮游动物以轮虫为主;浮游生物量在不同季节波动较大,表现为夏季春季秋季冬季,而不同年份同一季节的生物量变化不大.浮游生物的多样性指数在不同季节的变化较大,而丰富度指数D在不同季节变化不大,大多数在1.3-3.9之间,均匀度指数J′在0.5-0.8之间.平均溶氧量PG达2.62mg/L.综合判定,女山湖属于中富营养型,浮游动物群落结构和组成相对稳定,具有较大的开发利用潜力.     

北半球电离层中纬槽发生率及其槽极小位置变化的统计研究

本文利用2014年9月到2017年8月全球高时空分辨率TEC数据对北半球四个经度带电离层中纬槽的发生率和槽极小位置的变化进行了统计研究.基于Kp指数,我们引入了一个包含地磁活动变化历史效应的地磁指数(Kp 9)来分析中纬槽位置变化与地磁活动水平的关系.通过与其他地磁活动指数的对比,发现槽极小纬度与Kp 9指数的相关性最好.此外,本文重点分析了中纬槽发生率及槽极小纬度的经度差异、季节变化、地方时变化以及与地磁活动强度等的关系.结果表明,中纬槽的发生率与经度关系不大,主要受到季节、地方时与地磁活动的影响.午夜中纬槽发生率在夏季较低,其随地方时的变化则呈现出负偏态分布的特点,在后半夜发生率更高,而地磁活动增强对中纬槽的发生具有明显的促进作用.对于槽极小纬度,其在四个经度带的分布差异不大,但月变化各不相同,其中-120°经度带呈单峰分布,在夏季槽极小纬度更高,而0°经度带夏季槽极小纬度更低.槽极小的位置显著依赖于地磁活动、地方时以及季节变化.一般说来,地磁活动越强,中纬槽纬度越低.中纬槽位置随地方时的变化有明显的季节差异,冬季昏侧槽极小纬度随地方时变化较快,弱地磁活动条件下22∶00 LT前即达到最低纬度,其后位置几乎保持不变,而两分季槽极小纬度从昏侧至午夜都在降低,夏季槽极小纬度从昏侧连续下降至03∶00 LT左右.     

上海近50年气温变化与城市化发展的关系

根据上海地区2个气象站近50年的年均气温数据,采用回归分析、滑动平均和Mann\|Kendall检验法研究上海地区气温的年代际变化与跃变,城郊温差的年际变化;采用趋势拟合与相关分析,研究城郊温差与城市人口、GDP、能源消耗量、建成区面积和住宅竣工面积等各项城市发展指标的关系.结果表明：（1）近50年来,上海地区年均气温缓慢上升,20世纪90年代后城郊温差呈锯齿状上升趋势,若以徐家汇代表城区,奉贤代表郊区,则近50年来,城郊温差增温率为0.23℃/10a.（2）1989~1990年为上海城区气温的跃变年份,而郊区的气温跃变出现在20世纪90年代中期.（3）各项城市发展指标均与上海城郊温差有着显著的相关性,表明它们与上海城市热岛的发展关系密切,其中,住宅建设是上海城市热岛最主要的驱动因素,城市人口和经济发展也具有重要影响.     

淮河流域焦岗湖水质参数时空变化及影响因素

焦岗湖是淮河左岸一个天然湖泊,集防洪、灌溉、养殖、旅游等多种功能于一体.利用焦岗湖4个季节水质监测数据,运用Kriging方法,分析焦岗湖水质参数的时空变化及影响因素.结果表明:由于受水文季节变化过程及人类活动等综合影响,焦岗湖水质参数在时间及空间上均存在一定差异.从时间变化来看,夏季透明度较低、秋季较高;溶解氧浓度在春、冬季显著高于夏、秋季;总氮、总磷浓度与高锰酸盐指数均表现为夏季最高、秋季最低.从空间变化来看,4个季节的透明度空间差异较为显著;溶解氧浓度在春、冬季空间分布较为均匀,夏季呈现中心高周围低的变化趋势,秋季则表现为西高东低;总磷浓度春季分布较为均匀,夏、秋及冬季则呈西高东低之势;高锰酸盐指数在春、秋季节呈现东高西低之势,夏季高浓度主要集中在湖区北部,冬季浓度变化不大.     

纳木错水温变化及热力学分层特征初步研究

水温变化是湖泊的重要物理特性,对湖泊的水质特征、湖水能量循环、水生生态系统研究具有重要意义.基于不同季节的实地观测资料,分析青藏高原高海拔、深水大湖纳木错的水温变化特征及季节差异,并着重分析湖水热力学分层的季节变化.结果显示纳木错中部、东部两个湖盆冬季封冻,夏季存在稳定分层,春、秋季混合,是一个典型双季对流、完全混合型湖泊.但两个湖盆水温变化与热力学分层又有各自的特征,东部浅湖盆湖水在春季升温快,夏季分层与秋季翻转均比中部湖盆早,且秋季翻转时水温也比中部湖盆高.初步分析认为两个湖盆不同的湖盆形状及水深分布可能是造成其热力学特征差异的主要原因.     

Changes in the spatial scale of Beijing UHI and urban development

The seasonal and interannual variations of Beijing urban heat island (UHI) are investigated in this paper using the temperature data from 1960 to 2000 at 20 meteorological stations in the Beijing region, and then the relationship between the intensity and spatial scale of UHI and Beijing urbanization indices is analyzed and discussed. Main conclusions are the followings. First, Beijing UHI shows obvious seasonal variations, and it is strongest in winter, next in spring and autumn, and least in summer. The seasonal variation of the UHI mainly occurs in the urban area. The UHI intensity at the center of Beijing is more than 0.8℃ in winter, and only 0.5℃ in summer. Second, the intensity of Beijing HUI exhibits a clear interannual warming trend with its mean growth rate (MGR) being 0.3088℃/10 a. The MGR of HUI is largest in winter, next in spring and autumn, and least in summer, and the urban temperature increase makes a major contribution to the growth of HUI intensity. Third, since the Reform and Opening, the urbanization indices have grown several ten times or even one hundred times, the intensity of HUI has increased dramatically, and its spatial scale also expanded distinctively along with the expansion of urban architectural complexes. Fourth, the interannual variation of urbanization indices is very similar with that of HUI intensity, and their linear correlation coefficients are significant at a more than 0.001 confidence level.     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Assessing spatial pattern of urban thermal environment in Shanghai, China

The aggravating urban thermal environment has considerable adverse effects on urban physical environment, energy consumption, and public health. Due to the complexity of factors contributing to the urban thermal environment, traditional statistical methods are insufficient for acquiring data and analyzing the impacts of human activities on the thermal environment, especially for identifying dominant factors. Based on thermal remote sensing imageries and Geographic Information System analysis, we assessed spatial pattern of urban thermal environment in Shanghai in 2008, and analyzed the factors contributing to the generation of urban heat island (UHI) using principal component analysis (PCA). We found that Shanghai had obvious UHI with uneven spatial pattern in 2008. Further, we identified three most important components leading to the variances of Shanghai’s UHI: the gradient from man-made to natural land cover, landscape configuration, and anthropogenic heat release. A linear model has thus been successfully constructed, implying that PCA is helpful in identifying major contributors to UHI. The findings are of significance for policy implication to urban thermal environment mitigation.     

Using temperature effect on seepage variations as proxy for phenological processes of basin‐scale vegetation communities

The identification of vegetation community growth season is critical for measuring the response of ecosystems to climate change. In this study, vegetation community growth season is measured via fixed‐point monitoring of dynamic short‐time processes of rock‐fissure seepage in the Taihang Mountain Region (TMR). The hydrometeorological data used in the study are obtained from tipping‐bucket flowmeters and automated weather stations in the region. Significant differences are noted in daily rock‐fissure seepage for different growth seasons. The study shows that during growth seasons, seepage processes in the TMR study area vary with air temperature. Although seepage in the region gradually decreases from 06:20 to 17:00 h, it increases from 18:00 to 06:00 h. Analysis shows a significant (R² > 0.8) negative correlation between seepage and air temperature during growth seasons. For nongrowth seasons, however, seepage processes exhibit near‐harmonic variations with air temperature. Also, although seepage during nongrowth seasons gradually increases from 02:30 to 12:30 h, it gradually decreases from 13:30 to 02:20 h. A significant (R² > 0.8) positive correlation also exists between seepage and air temperature during nongrowth seasons. During seasonal crop rotations, however, significant disorders and inconsistencies occur in the seepage processes in the study area. The observed seasonal variations in daily rock‐fissure seepages could lay the scientific basis for the adapting trends in crop growth seasons to climate change. Information on this process is critical for crop production and food security for the millions of people in China and beyond. Copyright © 2012 John Wiley & Sons, Ltd.     

城市化对石家庄站日气温变化的影响

利用1962—2011年逐日平均、最低和最高气温资料,对比分析了石家庄站和藁城站平均、最低和最高气温的概率分布特征.石家庄站是我国少有的自建站以来从未迁址的城市气象站,而附近的藁城站可近似看作乡村气象站.结果表明:城市化致使石家庄站1962—2011年平均、最低和最高气温的概率密度分布向高温方向偏移,其中对最低气温分布的影响尤其明显,对最高气温分布的影响很小;受城市化影响,石家庄站最低气温概率密度分布的高温部分增温比低温部分增温更加明显,最低气温分布形状更加扁平;相对于1962—1986年,1987—2011年石家庄站平均、最低和最高气温概率密度分布均向高温方向偏移,其中最低气温偏移最为明显,并导致1962—2011年整个分析时期最低气温分布出现非正态性;城市化对石家庄站气温分布的影响在冬、春季比夏、秋季更显著,最显著的城市化影响出现在冬季最低气温上;石家庄站基于最低气温的极端气温指数趋势受城市化影响严重,冷夜日数和暖夜日数的城市化影响分别为-1.13d/10a、1.48d/10a,但基于最高气温的冷昼和暖昼日数等极端气温指数变化趋势受城市化影响不明显.出现这种现象的主要原因是城市化对最低、最高气温分布的影响存在差异.     

盐碱池塘浮游动物的群落演替和多样性

于1997年4月5日至1998年9月1日对山东高青赵店乡渔场34个盐碱池浮游动物群落演替及其多样性进行了研究,采集了389个浮游动物定量水样。结果表明,轮虫主要是在夏秋高温季节占主导地位,桡足类在春季和秋末冬初在大部分养鱼池和所有无鱼对照池中占绝对优势,原生动物在养鱼池浮游动物中占相当比重,浮游动物生物量的冬季变动一般都有放养早期的春季生物量峰值和盛夏至初秋的生物量高峰,浮游动物多样性指数的季节变动形式与浮游动物生物量的季节变动不尽相同,其季节变动的总趋势是,冬季最低,春季开始上扬,夏季最高,秋季又开始下降;浮游动物多样性指数在浮游动物生物量峰值时多是低谷,而生物量下降时多样性指数又上升,无鱼对照池和新挖池塘的浮游动物多样性指数和生物量均较一般养鱼池塘的高。     

Seasonal evaluation of rainfall estimation by four cumulus parameterization schemes and their sensitivity analysis

Sustainable water resources management require scientifically sound information on precipitation, as it plays a key role in hydrological responses in a catchment. In recent years, mesoscale weather models in conjunction with hydrological models have gained great attention as they can provide high‐resolution downscaled weather variables. Many cumulus parameterization schemes (CPSs) have been developed and incorporated into three‐dimensional Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model 5 (MM5). This study has performed a comprehensive evaluation of four CPSs (the Anthes–Kuo, Grell, Betts–Miller and Kain–Fritsch93 schemes) to identify how their inclusion influences the mesoscale model's precipitation estimation capabilities. The study has also compared these four CPSs in terms of variability in rainfall estimation at various horizontal and vertical levels. For this purpose, the MM5 was nested down to resolution of 81 km for Domain 1 (domain span 21 × 81 km) and 3 km for Domain 4 (domain span 16 × 3 km), respectively, with vertical resolutions at 23, 40 and 53 vertical levels. The study was carried out at the Brue catchment in Southwest England using both the ERA‐40 reanalysis data and the land‐based observation data. The performances of four CPs were evaluated in terms of their ability to simulate the amount of cumulative rainfall in 4 months in 1995 representing the four seasonal months, namely, January (winter), March (spring), July (summer) and October (autumn). It is observed that the Anthes–Kuo scheme has produced inferior precipitation values during spring and autumn seasons while simulations during winter and summer were consistently good. The Betts–Miller scheme has produced some reasonable results, particularly at the small‐scale domain (3 km grid size) during winter and summer. The KF2 scheme was the best scheme for the larger‐scale (81 km grid size) domain during winter season at both 23 and 53 vertical levels. This scheme tended to underestimate rainfall for other seasons including the small‐scale domain (3 km grid size) in the mesoscale. The Grell scheme was the best scheme in simulating rainfall rates, and was found to be superior to other three schemes with consistently better results in all four seasons and in different domain scales. Copyright © 2011 John Wiley & Sons, Ltd.