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为探讨气候变化对石羊河流域生态环境的影响，利用流域多年（1959-2018年）气象、水文和卫星遥感资料，采用线性倾向率、滑动t检验等方法,分析流域气温、降水、河流流量、植被覆盖、沙尘暴的变化事实及趋势，并使用相关系数（pearson）法研究气温和降水分别与环境要素的关系，得到气候变化对流域生态环境的影响程度。结果表明:气温呈显著上升趋势，增温速度为下游0.42℃．（10a）-1＞中游0.36℃．（10a）-1＞上游0.35℃．（10a）-1, 近10年增温最显著，较60年代升高了1.67℃。四季气温均呈显著上升趋势，增温速度为冬季＞秋季＞春季＞夏季。降水呈波浪略增加趋势，增幅为上游8.3mm．（10a）-1＞中游7.0mm．（10a）-1＞下游4.1mm．（10a）-1，近10年增加最显著，较60年代增加了17%。四季降水呈弱增加趋势，增加幅度为夏季＞春季＞秋季＞冬季。河流流量以波浪式持平变化；植被覆盖面积和归一化差异植被指数（NDVI）显著增大；沙尘暴频次显著减少，近10年较60年代减少了13.05d。流域气候暖湿化近20年较显著，气候变化有利于增加本地水资源总量、提高地表植被覆盖率、抑制沙尘暴的发生，对生态环境和大气环境质量改善有积极作用。 相似文献
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王存亮 《沙漠与绿洲气象(新疆气象)》2011,5(5)
本文通过利用常规气象探测资料、自动站资料和石河子CINRAD/CC多普勒天气雷达观测资料,对2010年5月2日发生在准葛尔盆地南缘的一次强对流天气进行了分析。结果表明：在多普勒雷达反射率因子PPI图出现了＞50 dBz强回波区及＞60 dBz强回波中心;在RHI图出现了穹窿结构,且＞50 dBz强回波区高度远高于当天０℃层的高度;在平均径向速度图上出现了中气旋、逆风区;在不同仰角的PPI上气流表现出强烈的旋转和上升;垂直累积液态含水量（VIL）产品对冰雹落区预报有很好的指示作用;风暴跟踪信息（STI）对冰雹天气的出现具有很好预警意义,对今后的防雹减灾工作有较好的应用价值。 相似文献
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利用三江源区1961-2020年逐日气象数据、2006-2020年EOS/MODS监测资料,基于概率密度分布函数、线性趋势分析等方法,分析了气温、降水、极端气候指数变化趋势。结果表明：（1）1961-2020年三江源区气温明显向高温方向漂移,年平均、最高和最低气温升温率分别为0.38℃·（10a）-1、0.28℃·（10a）-1和0.45℃·（10a）-1（P<0.01）,最高和最低气温升温幅度存在不对称现象。同时极端气温暖事件（暖昼日数、暖夜日数）明显增多,极端气温冷事件（冷昼日数、冷夜日数）迅速减少。（2）与前一气候态（1961-1990年）相比,1991-2020年平均、最高和最低气温分别上升了1.28℃、1.12℃和1.60℃,且概率密度分布更加扁平,说明气温离散程度更大,气候不稳定性增强。（3）近60年来,三江源区降水量总体呈增多趋势,增加率为10.3 mm·（10a）-1,且随着降水量级的增加,降水量变化趋势越来越明显。进入21世纪以来,降水增多趋强表现更加明显。（4）在气温显著升... 相似文献
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青藏高原四季划分方法探讨 总被引：2，自引：0，他引：2
利用中国气象局国家气象信息中心提供的青藏高原60个测站1961~2007年逐日气温资料,分析常用的四季划分方法在高原的适用性,指出各种四季划分方法的不足和局限,并根据四季持续时间的合理性、物候特征、海拔高度、气候（温度）分布特征等因素提出了针对不同的生产、生活目的而建立的新四季划分方法。探讨认为：（1）根据高原物候特征和气温相结合的方式得到的＂物候四季划分方法＂即＂4℃-12℃-10℃-1℃＂对高原农牧业尤为适合;（2）＂海拔季节划分方法＂对高原旅游和人们衣着尤为适合,海拔季节划分方法把高原分成二个区：海拔4000m以上四季划分方法为＂5℃-12℃-12℃-5℃＂,4000m以下四季划分方法为＂5℃-15℃-15℃-5℃;＂（3）＂生活季节划分方法＂对高原不同区域的生产生活尤为适合,生活季节划分方法将高原分为三个区：Ⅰ区四季划分方法为＂6℃-16℃-16℃-6℃＂,Ⅱ区四季划分方法为＂5℃-12℃-12℃-5℃＂,Ⅲ区四季划分方法＂7℃-7℃＂划分春冬和秋冬,不存在夏季。最后,综合以上各种方法的优缺点,初步定义＂高原普适季节划分方法＂即＂5℃-15℃-15℃-5℃＂为高原总体的四季划分方法,对高原整体的国民经济和政府活动、旅游、人们的衣着、生活生产、季节类产品的销售具有总体的指导意义。 相似文献
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首先利用上海77个区域站2011—2014年逐时气温和风资料,研究了地面风对上海城市热岛(urban heat island,UHI)的影响及UHI季节性空间分布特征的成因,并从海陆热力差异初步揭示了向岸风对热岛强度(urban heat island intensity,I_(UHI))的影响。其次利用上海7个国家站1961—2014年逐月气温和风资料,研究了上海各季地面风速与I_(UHI)的年际变化关系。结果表明:(1)UHI中心出现的位置与风向、风速有密切的关系,特别是夜间UHI中心有向城市下风方向漂移的特征,其平均漂移风速阈值为2 m·s~(-1),UHI区域随风速增大向城市下风方向延伸,I_(UHI)随风速的增大而减小。(2)上海各季夜间UHI特征明显,尤以秋冬季最为明显,春季次之,夏季最弱。春夏季夜间UHI中心出现在城区西北侧,而秋冬季夜间UHI中心稳定在城区,表现为典型UHI。各季白天均表现为下风方大范围增暖现象。季节地面盛行风决定了UHI季节性空间分布特征。(3)白天向岸风具有抑制升温作用(春夏季最为明显),受其影响气温大值区易出现在内陆地区,春夏季城市偏东区I_(UHI)小于偏西区;夜间向岸风具有抑制降温作用(秋冬季最为明显),受其影响秋冬季东部沿海地区出现明显增暖且城市偏东区I_(UHI)大于偏西区。海陆热力差随季节不同和盛行风风速大小决定了向岸风这种作用的大小及影响范围。(4)各季年平均地面风速与I_(UHI)均呈显著负相关,1961—2014年上海各季风速均表现为递减趋势(春冬季最明显),为I_(UHI)增大提供有利条件。21世纪以来各季I_(UHI)均呈现减缓特征(夏秋季最明显),风速并不是导致I_(UHI)减缓的主要因素。 相似文献
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利用石家庄市区站和4个郊区站1962—2009年的气温资料,采用城乡气温对比和线性趋势分析方法,探讨了石家庄站地面城市热岛(UHI)强度特征及其随时间变化情况,以及城市化因素对城市站地面气温长期变化趋势影响.结果表明:石家庄站地面UHI效应明显,且UHI效应在最低气温上表现更突出;UHI强度冬季1月最大,夏季7月最小;UHI强度具有明显的日变化,最高值出现在早晨7—8时,最低值出现在午后14—16时;近48 a,石家庄站附近UHI强度呈显著增加趋势,且最低气温UHI强度比最高气温的增加趋势更明显;从UHI强度增加对地面气温观测记录的影响来看,石家庄站附近1962—2009年期间年平均UHI增温率达到0.19 ℃/(10 a),UHI增温贡献率为67.9％,即该站近48 a记录的年平均地面气温上升趋势,有2/3以上可归因于城市化因素影响. 相似文献
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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
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利用石河子棉区4个气象站1971-2020年的逐日气象资料,采用气候倾向率、累计距平、均方差、Mann-Kendall突变检验等方法,分析了石河子棉区10℃积温的时空变化特征。结果表明;石河子棉区各地及全区≥10℃初日呈显著提前趋势,≥10℃终日略微推迟,≥10℃持续日数显著延长,≥10℃积温明显增多。≥10℃积温及持续日数均在1964年发生了由少到多的突变,≥10℃积温主要在5-9月,7月为高峰值。≥10℃积温正常年份最多,概率超过64%,依次向两端递减。≥10℃积温偏低地区主要在莫索湾,≥10℃积温偏高地区主要在乌兰乌苏。阶段Ⅱ（1995-2020年）与阶段Ⅰ（1961-1994年）相比,≥10℃积温3500-3800℃·d明显减少,3800-4100℃·d明显增多。气候变化背景下,石河子棉区热量条件有较好的改善,棉花低温冷害会有所减轻,石河子棉区品中布局仍应以早熟或特早熟为主。 相似文献
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气候变暖对河南省蚱蝉始鸣期的影响 总被引：1，自引：0，他引：1
利用河南省驻马店、沈丘和太康3个农业气象观测站1990-2004年的蚱蝉物候观测资料和气象资料,研究了气候变暖对蚱蝉始鸣期的影响。结果表明：在气温升高的气候背景下,蚱蝉始鸣期呈提前趋势;3-6月平均气温对蚱蝉始鸣期有显著的影响,始鸣期与1月1日至平均始鸣期期间＞5℃有效积温关系最为密切。用积温法以5℃为发育起点温度,＞5℃初日为起始日期对各站蚱蝉始鸣期进行模拟和预报,其效果优于平均法。 相似文献
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利用拉萨、墨竹工卡、尼木建站以来的多年历史资料和近两年新建的区域自动站、8个城市热岛效应自动气象站资料分析拉萨城市热岛强度日、季、年变化,时空分布及其可能的影响因子。分析表明:拉萨城市热岛强度呈显著的逐年增强趋势,在1978~2011年间平均每10年增加0.24℃;多年热岛强度冬季最强(2.0℃),其次是春季(1.8℃)和秋季(1.7℃),夏季强度最小(1.6℃);拉萨城市高温中心主要在城市中心,气温分布沿着高值区向两侧呈递减状态,郊外的气温比城区平均低0.9℃左右,夜间热岛效应强度明显高于白天。随着城市化进程的不断增强,大量改变的下垫面状况,不断增多的城市建筑群,骤增的人类活动和能源消耗,导致城市热岛强度不断增强。 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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采用2000～2011年6月MODIS地表温度产品和拉萨市4个气象站6月平均地表温度对拉萨市地表温度的时空变化进行了分析.结果表明：拉萨市在近12年内地表温度呈明显上升趋势,2009年地表温度达到最高为28.49℃,最小值出现在2003年为14.12℃.在空间分布上高温区主要集中在城市中心和城市周边区域,并随着时间推移不断向外扩张,在2007年6月拉萨市地表温度高温区分布范围最大,其中纳木错东部和林周县的高温区增加最显著;在利用实测的地表温度与MO-DIS反演的地表温度做相关分析发现,两者的相关系数为0.64通过了0.001的显著性检验,两种地表温度的时间变化趋势也较为一致,因此MODIS地表温度反演产品适用于大范围地表温度和城市热环境监测是可行的. 相似文献
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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
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This paper describes the statistical characteristics and temporal variability of the urban heat island (UHI) intensity in Buenos Aires using 32-year surface meteorological data with 1-h time intervals. Seasonal analyses show that the UHI intensity is strongest during summer months and an “inverse” effect is found frequently during the afternoon hours of the same season. During winter, the UHI effect is in the minimal. The interannual trend and the seasonal variation of the UHI for the main synoptic hours for a longer record of 48?years are studied and associated to changes in meteorological factors as low-level circulation and cloud amount. Despite the population growth, it was found a negative trend in the nocturnal UHI intensity that could be explained by a decline of near clear-sky conditions, a negative trend in the calm frequencies and an increase in wind speed. Urban to rural temperature differences and rural temperatures are negatively correlated for diurnal and nocturnal hours both for annual and seasonal scales. This result is due to the lower interannual variability of urban temperatures in comparison to rural ones. 相似文献
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利用阳泉市3个国家级气象站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年-2011年平均热岛强度0．554℃。阳泉市热岛强度冬、秋季强,春、夏季弱;12月最强,5月最弱;阳泉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年-2011年最强热岛强度出现在2010年1月14日08时达7．9℃。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,城市化发展可能使阳泉城市温度增高,城市绿地面积的增加可能对热岛效应有缓解。 相似文献
17.
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
18.
Petr Dobrovolný 《Theoretical and Applied Climatology》2013,112(1-2):89-98
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.
Heatwave intensity and frequency are predicted to increase in the coming years, and this will bear adverse consequences to the environmental well-being and the socio-economic fabric in urbanized areas. The hazardous combination of increased heat storage and reduced water retention capacities of the land surface make the urban areas warmer than the surrounding rural areas in what is commonly known as the urban heat island (UHI) effect. The primary motives of this study are to quantify the interaction of this city-scale UHI with synoptic-scale heatwave episodes and to analyze the factors that mediate this interaction. A modified version of the Weather Research and Forecasting model (WRF) is utilized to simulate two heatwave episodes in New York City. The land surface scheme in the default WRF model is modified to better represent the surface to atmosphere exchanges over urban areas. Our results indicate that during the heatwave episodes, the daily-averaged UHI in NYC increased by 1.5 K. Furthermore, most of this amplification occurs in the mid-afternoon period when the temperatures peak. Wind direction and urban-rural contrasts in available energy and moisture availability are found to have significant and systematic effects on the UHI, but wind speed plays a secondary role. 相似文献
20.
A multiple linear statistical model for estimating the mean maximum urban heat island 总被引：4，自引：0，他引：4
Summary ¶This study examines the spatial and quantitative influence of urban factors on the surface air temperature field of the medium-sized of Szeged, Hungary, using mobile measurements under different weather conditions in the periods of March 1999–February 2000 and April–October 2002. Efforts have been concentrated on the development of the urban heat island (UHI) in its peak development during the diurnal cycle. Tasks included: (1) determination of spatial distribution of mean maximum UHI intensity and some urban surface parameters (built-up and water surface ratios, sky view factor, building height) using the standard Kriging procedure, as well as (2) development of a statistical model in the so-called heating and non-heating seasons using the above mentioned parameters and their areal extensions. In both seasons the spatial distribution of the mean maximum UHI intensity fields had a concentric shape with some local irregularities. The intensity reaches more than 2.1°C (heating season) and 3.1°C (non-heating season) in the centre of the city. For both seasons statistical model equations were determined by means of stepwise multiple linear regression analysis. As the measured and calculated mean maximum UHI intensity patterns show, there is a clear connection between the spatial distribution of the urban thermal excess and the examined land-use parameters, so these parameters play an important role in the evolution of the strong UHI intensity field. From the above mentioned parameters the sky-view factor and the building height were the most determining factors which are in line with the urban surface energy balance. Therefore in the future, using our model it will be possible to predict mean maximum UHI intensity in other cities, which have land-use features similar to Szeged.Received September 26, 2002; revised February 25, 2003; accepted March 22, 2003
Published online July 30, 2003 相似文献