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71.
近30年夏季亚欧大陆中高纬度阻塞高压的统计特征 总被引:10,自引:0,他引:10
文中利用1970~2001年NCEP再分析500 hPa逐日高度场资料,根据阻塞高压的天气学定义,采用客观统计方法检索出近32 a亚欧中高纬度392个阻塞高压个例,对其进行了气候学分析.结果表明,亚欧中高纬地区夏季阻塞高压活动频繁,10 d以下的过程占绝对多数,地理分布主要集中在45~70°N之间,纬向上可划分5个高发区,其中乌拉尔山和贝加尔湖东部阻高活动频次最高,同时,每个区域中又存在着相应的阻高活跃区.亚欧中高纬地区夏季阻高活动具有明显的季节内变化特征.6月份,阻塞活动多发生在乌拉尔山地区和鄂霍次克海地区,以双阻为主要形势;7月份,欧洲区和贝加尔湖地区的阻塞活动有所增多,尤其贝加尔湖东部地区增多明显,而乌拉尔山地区的阻塞形势明显减少,鄂霍次克海地区的阻塞活动位置向北移动,多发生在60°N以北,双阻形势逐渐减弱,贝加尔湖地区的中阻形势有所增强.8月份,阻塞形势主要存在于贝加尔湖东西两区,中阻形势占据主导地位.亚欧中高纬地区夏季阻塞高压活动年际变化特征也很突出,且这种年际振荡有明显的地理差异.另外,研究表明亚洲北部的阻高活动多以稳定型为主,移动型阻高个例仅占6.6%.移动型阻高以起源于乌拉尔山地区最多,移距最长,生命期最长.偶极子类阻高多集中在贝加尔湖东部与乌拉尔山地区,约占该地区总阻高频次的62.0%和49.7%,平均生命期分别达到7 d/次和9 d/次以上. 相似文献
72.
多孔介质非饱和导水率是地下水污染预测与评价的重要参数。根据分形几何的基本原理和方法,推导出了与Campbell经验公式在形式上完全一致的多孔介质非饱和导水率的预测公式。公式中的幂指数为介质孔隙分维和随机行走分维的函数,分别体现了多孔介质的静态性质与动态性质对其中水分运动的影响,但静态性质的影响是主要的,即导水率主要受多孔介质的结构控制。根据文献中报道的大量数据,利用笔者推导的预测公式计算得到的幂指数的统计值与试验测定的幂指数的统计值基本一致,说明推导的理论公式预测多孔介质非饱和导水率是较为可靠的。 相似文献
73.
沼泽湿地环境演变研究回顾与展望——纪念中国科学东北地理与农业生态研究所建所50周年 总被引:1,自引:0,他引:1
沼泽湿地是地球表层功能独特的生态系统,在其形成发育、时空演化及分异等方面与其它生态系统存在明显差异。中国科学院东北地理所(原长春地理所)在沼泽湿地形成发育、时空演化研究方面有丰富的学科积累。1958年,中国科学院确定沼泽为该所的主攻方向,成为中国最早的专门性沼泽研究机构之一,至今已满50周年。50年来,几代科研人员为沼泽湿地环境演变研究工作贡献了他们的青春年华,取得了丰硕的研究成果。 相似文献
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本文以 1996年 12月 31日和 1981年 5月 1日为例 ,对冬、春季节发生在江苏的较大范围的切变类冰雹天气过程作了对比分析。结果指出 ,无论冬季或春季当高原东部有深槽东移 ,冷暖空气在江淮地区交汇 ,地面抬升系统为暖切 ,并有大气层结不稳定 (Δθse( 50 0 - 850 ) <0℃ =中心和较强的风向和风速垂直切变、85 0hPa西南急流轴、85 0hPa最大水汽通量轴线、5 0 0和 85 0hPa正涡度中心等相配置时 ,就可能导致江苏地区较大范围强对流天气的发生。 相似文献
79.
DING Guoan CHAN Chuenyu GAO Zhiqiu YAO Wenqing LI Yoksheung CHENG Xinghong MENG Zhaoyang YU Haiqing WONG Kamhang WANG Shufeng MIAO Qiuju 《中国科学D辑(英文版)》2005,48(Z2)
The vertical structures and their dynamical character of PM2.5 and PM10 over Beijing urban areas are revealed using the 1 min mean continuous mass concentration data of PM2.5 and PM10 at 8, 100, and 320 m heights of the meteorological observation tower of 325 m at Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP CAS tower hereafter) on 10―26 August, 2003, as well as the daily mean mass concentration data of PM2.5 and PM10 and the continuous data of CO and NO2 at 8, 100 (low layer), 200 (middle layer), and 320 m (high layer) heights, in combination with the same period meteorological field observation data of the meteorological tower. The vertical distributions of aerosols observed on IAP CAS tower in Beijing can be roughly divided into two patterns: gradually and rapidly decreasing patterns, I.e. The vertical distribution of aerosols in calm weather or on pollution day belongs to the gradually decreasing pattern, while one on clean day or weak cold air day belongs to the rapidly decreasing pattern. The vertical distributive characters of aerosols were closely related with the dynamical/thermal structure and turbulence character of the atmosphere boundary layer. On the clean day, the low layer PM2.5 and PM10 concentrations were close to those at 8 m height, while the concentrations rapidly decreased at the high layer, and their values were only one half of those at 8 m, especially, the concentration of PM2.5 dropped even more. On the clean day, there existed stronger turbulence below 150 m, aerosols were well mixed, but blocked by the more stronger inversion layer aloft, and meanwhile, at various heights, especially in the high layer, the horizontal wind speed was larger, resulting in the rapid decrease of aerosol concentration, I.e. Resulting in the obvious vertical difference of aerosol concentrations between the low and high layers. On the pollution day, the concentrations of PM2.5 and PM10 at the low, middle, and high layers dropped successively by, on average, about 10% for each layer in comparison with those at 8 m height. On pollution days, in company with the low wind speed, there existed two shallow inversion layers in the boundary layer, but aerosols might be, to some extent, mixed below the inversion layer, therefore, on the pollution day the concentrations of PM2.5 and PM10 dropped with height slowly; and the observational results also show that the concentrations at 320 m height were obviously high under SW and SE winds, but at other heights, the concentrations were not correlated with wind directions. The computational results of footprint analysis suggest that this was due to the fact that the 320 m height was impacted by the pollutants transfer of southerly flow from the southern peripheral heavier polluted areas, such as Baoding, and Shijiazhuang of Hebei Province, Tianjin, and Shandong Province, etc., while the low layer was only affected by Beijing's local pollution source. The computational results of power spectra and periods preliminarily reveal that under the condition of calm weather, the periods of PM10 concentration at various heights of the tower were on the order of minutes, while in cases of larger wind speed, the concentrations of PM2.5 and PM10 at 320 m height not only had the short periods of minute-order, but also the longer periods of hour order. Consistent with the conclusion previously drawn by Ding et al., that air pollutants at different heights and at different sites in Beijing had the character of "in-phase" variation, was also observed for the diurnal variation and mean diurnal variation of PM2.5 and PM10 at various heights of the tower in this experiment, again confirming the "in-phase" temporal/spatial distributive character of air pollutants in the urban canopy of Beijing. The gentle double-peak character of the mean diurnal variation of PM2.5 and PM10 was closely related with the evident/similar diurnal variation of turbulent momentum fluxes, sensible heat fluxes, and turbulent kinetic energy at various heights in the urban canopy. Besides, under the condition of calm weather, the concentration of PM2.5 and PM10 declined with height slowly, it was 90% of 8 m concentration at the low layer, a little lesser than 90% at the middle layer, and 80% at the high layer, respectively. Under the condition of weak cold air weather, the concentration remarkably dropped with height, it was 70% of 8 m concentration at the low layer, and 20%―30% at the middle and high layers, especially the concentration of PM2.5 was even lower. 相似文献
80.
LIU Min HE HongLin YU GuiRui LUO YiQi SUN XiaoMin & WANG HuiMin Institute of Geographic Sciences Natural Resources Research Chinese Academy of Sciences Beijing China Gradute School of the Chinese Academy of Sciences Beijing School of Geography Science Nanjing Normal University Nanjing 《中国科学D辑(英文版)》2009,(2)
We present an uncertainty analysis of ecological process parameters and CO2 flux components (Reco, NEE and gross ecosystem exchange (GEE)) derived from 3 years’ continuous eddy covariance meas-urements of CO2 fluxes at subtropical evergreen coniferous plantation, Qianyanzhou of ChinaFlux. Daily-differencing approach was used to analyze the random error of CO2 fluxes measurements and bootstrapping method was used to quantify the uncertainties of three CO2 flux components. In addition, we evaluated different ... 相似文献