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81.
利用塔克拉玛干沙漠腹地塔中和巴丹吉林沙漠北缘拐子湖两个陆气通量监测站2013年2月-2014年1月地面辐射观测数据及相应气象资料,对比分析塔中和拐子湖两地的太阳辐射通量和地表反照率差异特征,同时也探究了两地太阳辐射通量和地表反照率与太阳高度角之间的关系。结果表明:(1)塔中和拐子湖两地各辐射通量均呈较为同步的季节变化特征;具有太阳辐射优势的塔中地区因沙尘天气的影响在部分月份地表总辐射小于拐子湖地区;拐子湖由于地表沙粒相对较粗且包含大量透明度较高的石英颗粒,地表反照率和反射辐射均大于塔中地区;两地各辐射通量月平均日变化均呈现出标准倒"U"型结构;(2)拐子湖较粗的地表沙粒导致沙尘天气过后不易形成浮尘,沙尘天气过后各辐射通量恢复至发生之前的状态较塔中地区迅速;(3)两地太阳高度角夏季最大,冬季最小,最大值均可达75°左右,最小值塔中和拐子湖地区分别为45°和40°;各辐射通量随着太阳高度角的升高而增加,地表反照率随之减小,但受多种因素影响各辐射通量最大值并未出现在太阳高度角最大的时候。  相似文献   
82.
乌鲁木齐市低层大气稳定度分布特征的统计分析   总被引:2,自引:1,他引:1  
利用乌鲁木齐市4座100 m梯度气象塔2013年6月至2014年4月10 min气象资料,对比分析了温差法、温差-风速法、风速比法、理查森数法和总体理查森数法计算的A~F类大气稳定度的适用性,表明温差-风速法更适合乌鲁木齐市大气稳定度的分类,运用该方法计算出的A~F类稳定度进而统计分析乌鲁木齐市城区和郊区稳定度的频率分布特征。结果表明:郊区稳定类所占比例高于城区,城区中性类高于郊区,南郊和城区不稳定类高于北郊。中性类在冬季较大,春季和秋季较低;不稳定类在6月最高、9和1月最低;稳定类在10和1月最高、6和7月最低。白天以不稳定为主(占全天88.3%~96.3%)、夜间以稳定为主(占全天51.3%~60%),夏季最明显。不稳定与中性、稳定的日变化相反,郊区日出时和城区日出后2 h左右稳定类频率最大。中性(D类)在日出和日落后1~3 h分别出现两个峰值。寒潮天气稳定性比高温天气强,静风天气郊区稳定类比大风天气强,扬沙发生前以中性和稳定类稳定度为主、发生时和发生后以不稳定为主,降雨天气不稳定类比暴雪天气强。春季和夏季重污染天气B、C和F类为主,夏季南郊和近北郊C和F类约45%,秋季B和E类为主,约40%~50%;冬季城区D类频率最大,南郊、北郊和近北郊F类频率最大。  相似文献   
83.
选取塔克拉玛干沙漠腹地塔中地区和北缘过渡带肖塘地区2013年土壤热通量观测资料,初步比较分析了塔克拉玛干沙漠两种下垫面的土壤热通量变化特征。结果表明:(1)在日变化尺度上,两个站点都有明显的日变化特征,1月份塔中站土壤热通量日平均变化幅度小于肖塘站,日较差分别为58.9 W.m2和72.4 W.m2,4月份两站土壤热通量变化幅度较为接近,日较差分别为88.1W.m2、100.1 W.m2。7、10月份塔中站土壤热通量变化幅度明显高于肖塘站,日较差分别为99.0 W.m2、53.7W.m2,100.3 W.m2、73.3W.m2。(2)不同天气条件下两个站点土壤热通量变化都有很大差异。晴天,塔中站和肖塘站土壤热通量变化都呈现出单峰型,变化幅度较一致,日较差分别为119.7 W.m2、119.1 W.m2。沙尘天和雨天受云层或降水的影响土壤热通量变化波动较大,沙尘天塔中站变化幅度小于肖塘站,日较差分别为83.6 W.m2、133.1 W.m2;雨天塔中站和肖塘站变化幅度都很剧烈,日较差分别为70.6 W.m2、66.6 W.m2。(3)年变化尺度上,塔中站土壤热通量在7月份达到最大值(7.7 W.m2),在11月出现最小值(-5.3 W.m2),肖塘站7月份出现最大值(4.2 W.m2),11月份出现最小值(-10.2 W.m2)。塔中站和肖塘站土壤热通量年总量差异很大,塔中站为16.8 W.m2,能量由大气向土壤传递,土壤为热汇,而肖塘站则为-34.9 W.m2,能量由土壤向大气传播,土壤表现为热源。  相似文献   
84.
利用塔克拉玛干沙漠北缘流动沙漠—古河床过渡带肖糖地区2012年6—8月土壤40 cm深处CO_2 浓度和相关气象要素资料,对该区域的土壤CO_2 浓度变化特征及影响因子进行了分析。结果表明:(1)肖塘地区夏季土壤40 cm深处CO_2 浓度的日变化过程中呈现出夜间低、白天高的单峰型,日最高值出现在18:00左右,最低值出现在6:30左右,浓度平均值保持在506.97~518.14 ppm之间;(2)随着土壤温度和土壤湿度的变大,土壤CO_2 浓度增大,两者呈显著正相关;(3)风速和土壤CO_2 浓度之间存在一定的滞后性;(4)大气压力对土壤CO_2 浓度变化产生显著影响,两者呈负相关。  相似文献   
85.
Based on automatic continuous surface ozone concentration observation data from June 10, 2010 to March 20, 2012 in the Taklimakan Desert hinterland, combined with corresponding meteorological data, the temporal, seasonal and daily variation characteristics of surface ozone concentrations under different weather conditions were analyzed. At the same time, the main fac- tors affecting ozone variation are discussed. Results show that: (1) Daily variation of ozone concentration was characterized by one obvious peak, with gentle changes during the night and dramatic changes during the day. The lowest concentration was at 09:00 and the highest was at 18:00. Compared to urban areas, there was a slight time delay. (2) Ozone concentration variation had a weekend effect phenomenon. Weekly variation of ozone concentration decreased from Monday to Wednesday with the lowest in Wednesday, and increased after Thursday with the highest in Sunday. (3) The highest monthly average concentration was 89.6 I.tg/m3 in June 2010, and the lowest was 32.0 ~g/m3 in January 2012. Ozone concentration reduced month by month from June to December in 2010. (4) Ozone concentration in spring and summer was higher than in autumn and winter. The variation trend agreed with those in other large and medium-sized cities. (5) Under four different types of weather, daily ozone concentration var- ied most dramatically in sunny days, followed by slight variation in rain days, and varied gently in cloudy days. Ozone concentra- tion varied inconspicuously before a sandstorm appearance, and dropped rapidly at the onset of a sandstorm. (6) Daily variation of radiation was also characterized by a single peak, and the variation was significantly earlier than ozone concentration variation. Sun radiation intensity had a direct influence on the photochemical reaction speed, leading to variation of ozone concentration. (7) Daily average ozone concentration in dust weather was higher than in slight rain and clear days. The variation of near surface ozone concentration could also be affected by meteorological factors such as relative humidity, wind speed, wind direction and sunshine hours. Thus, numerous factors working together led to ozone pollution.  相似文献   
86.
The different height mass concentrations of dust aerosol data from the atmosphere environment observation station (Ta- zhong Station) was continuously observed by instruments of Grimm 1.108, Thermo RP 1400a and TSP from January of 2009 to February of 2010 in the Taklimakan Desert hinterland. Results show that: (1) The mass concentration value of 80 m PMl0 was higher, but PM2.5 and PM1.0 concentrations at 80 m was obviously lower than 4 m PMl0, and the value of 80 m PM1.0 mass concentration was the lowest. (2) The PM mass concentrations gradually decreased from night to sunrise, with the lowest concentration at 08:00, with the mass concentration gradually increased, up to the highest concentration around 18:00, and then decreased again. It was exactly the same with the changes of wind speed. (3) The high monthly average mass concentration of TSP mainly appeared from March to September, and the highest concentration was in April and May, subsequently gradually decreased. Also, March-September was a period with high value area of PM monthly average mass concentration, with the highest monthly average mass concentration of 846.0 p.g/m3 for 4 m PM~0 appeared in May. The concentration of PM10 was much higher than those of PM2.5 and PM1.0 at 80 m. There is a small difference between the concentration of PM2.5 and PM~ 0. Dust weather was the main factor which influenced the concentration content of the different diameter dust aerosol, and the more dust weather days, the higher content of coarse particle, conversely, fine particle was more. (4) The mass concentration of different diameter aerosols had the following sequence during dust weather: clear day 〈 blowing dust 〈 floating and blowing dust 〈 sandstorm. In different dust weather, the value of PM~o/TSP in fine weather was higher than that in floating weather, and much higher than those in blowing dust and sandstorm weather. (5) During the dust weather process, dust aerosol concentration gradually decreased with particle size decreasing. The dust aerosol mass concentration at different heights and diameter would have a peak value area every 3-4 days according to the strengthening process of dust weather.  相似文献   
87.
利用新源县风电场周边气象站及测风塔观测资料、ERA5-Land再分析资料和数值模拟结果,分析新源县风电场的风场结构特征。结果表明:(1)风电场周边气象站的逐小时10m风速均呈现出早、晚偏低,中午偏高的变化规律。喀拉布拉镇站和公安农场站的风向主要以东风和南风为主,肖尔布拉克沟站的风向则以南风为主。测风塔4302的风速随着高度变化不明显。测风塔4301-4306均存在南风和北风,但各风向占比有一定差异。随高度升高,测风塔南风风向呈现出东南转西南的趋势。(2)ERA5-Land资料不能很好地再现研究区域风场变化。(3)数值模拟的风场变化具有一定山谷风特征。夜间的风向以东南风为主,白天则低海拔河谷地带风吹向山顶,北部谷风逐渐主导东北风向。20时,风电场区域主要以西北风为主。  相似文献   
88.
In recent years, the physical and chemical properties of dust aerosols from the dust source area in northern China have attracted increased attention. In this paper, Thermo RP 1400a was used for online continuous observation and study of the hinterland of Taklimakan, Tazhong, and surrounding areas of Kumul and Hotan from 2004 to 2006. In combination with weather analysis during a sandstorm in the Tazhong area, basic characteristics and influencing factors of dust aerosol PM10 have been summarized as below: (1) The occurrence days of floating dust and blowing dust appeared with an increasing trend in Kumul, Tazhong and Hotan, while the number of dust storm days did not significantly change. The frequency and intensity of dust weather were major factors affecting the concentration of dust aerosol PM10 in the desert. (2) The mass concentration of PM10 had significant regional distribution characteristics, and the mass concentration at the eastern edge of Taklimakan, Kumul, was the lowest; second was the southern edge of the desert, Hotan; and the highest was in the hinterland of the desert, Tazhong. (3) High values of PM10 mass concentration in Kumul was from March to September each year; high values of PM10 mass concentration in Tazhong and Hotan were distributed from March to August and the average concentration changed from 500 to 1,000 g/m3, respectively. (4) The average seasonal concentration changes of PM10 in Kumul, Tazhong and Hotan were: spring > summer > autumn > winter; the highest average concentration of PM10 in Tazhong, was about 1,000 g/m3 in spring and between 400 and 900 g/m3 in summer, and the average concentration was lower in autumn and winter, basically between 200 and 400 g/m3. (5) PM10 concentration during the sandstorm season was just over two times the concentration of the non-sandstorm season in Kumul, Tazhong and Hotan. The average concentrations of sandstorm season in Tazhong were 6.2 and 3.6 times the average concentrations of non-sandstorm season in 2004 and 2008, respectively. (6) The mass concentration of PM10 had the following sequence during the dust weather: clear day < floating dust < floating and blowing dust < sandstorm. The wind speed directly affects the concentration of PM10 in the atmosphere, the higher the wind speed, the higher the mass concentration. Temperature, relative humidity and barometric pressure are important factors affecting the strength of storms, which could also indirectly affect the concentration change of PM10 in the atmosphere.  相似文献   
89.
This study includes the results of a set of numerical simulations carried out for sands containing plastic/non-plastic fines, and silts with relative densities of approximately 30?40% under different surcharges on the shallow foundation using FLAC 2D. Each model was subjected to three ground motion events, obtained by scaling the amplitude of the El Centro (1940), Kobe (1995) and Kocaeli (1999) Q12earthquakes. Dynamic behaviour of loose deposits underlying shallow foundations is evaluated through fully coupled nonlinear effective stress dynamic analyses. Effects of nonlinear soil structure interaction (SSI) were also considered by using interface elements. This parametric study evaluates the effects of soil type, structure weight, liquefiable soil layer thickness, event parameters (e.g., moment magnitude of earthquake (M w ), peak ground acceleration PGA, PGV/PGA ratio and the duration of strong motion (D 5?95) and their interactions on the seismic responses. Investigation on the effects of these parameters and their complex interactions can be a valuable tool to gain new insights for improved seismic design and construction.  相似文献   
90.
沙漠中水分条件是决定生态分异的关键因素,地表凝结水的产生对沙漠植物与结皮生物的水分补充有重要的作用。利用微渗计对古尔班通古特沙漠土壤表层凝结水形成特征及影响因素进行分析。研究表明沙漠土壤凝结水形成总量随着表层土壤生物演替从流沙、藻类、地衣和苔藓依次增加。分析影响凝结水形成的因素表明土壤中细粒物质以及地衣和苔藓生物相对土壤粗粒物质更有利于凝结水形成。在土壤结皮演替过程中土壤中的细粒颗粒含量增加的同时生物有机体含量也在增加,因而随着表层土壤生物演替凝结水形成量呈增加趋势。凝结水形成量与日均相对湿度、土壤湿度呈显著正相关,而与日均风速、日均温度、土壤温度呈负相关。研究说明在干旱的沙漠地带土壤凝结水是除降水以外补充表层土壤水分重要的水分来源。  相似文献   
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