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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
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鄱阳湖流域径流模型 总被引:4,自引:4,他引:4
流域径流是鄱阳湖主要来水,建立鄱阳湖流域径流模型对揭示湖泊水量平衡及其受流域自然和人类活动的影响具有重要意义.针对鄱阳湖-流域系统的特点:流域面积大(16.22×104km2)、多条入湖河流、湖滨区坡面入湖径流等,研究了相应的模拟方法,建立了考虑流域土壤属性和土地利用空间变化的鄱阳湖流域分布式径流模型.采用6个水文站1991-2001年的实测河道径流对模型进行了率定和验证.结果显示,模型整体模拟精度较高.其中,赣江、信江和饶河均取得了较好的模拟结果,月效率系数为0.82-0.95;抚河和修水模拟精度略低,为0.65-0.78.模型揭示了研究时段内年平均入湖径流总量为1623×108m3,其中,赣江最多,占47%,其次为信江和抚河,分别占13%和12%,湖滨区坡面入湖径流约占4%,其余24%来自饶河、修水以及其它入湖支流.模型将用于评估流域下垫面或气候变化引起的入湖水量变化,为湖泊水量平衡计算提供依据. 相似文献
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利用2003-2007年国家气象中心T213L31全球中期数值预报模式逐日输出产品与青海地区25个气象站的观测数据作为试验资料, 利用相关系数和逐步回归进行因子选择, 并以单隐层神经网络和多元回归作为降尺度方法进行对比研究, 用2003-2006年间的11月1日~次年3月1日的资料作为训练样本, 以数值预报产品和前一日观测的最低温度作为因子, 建立青海省25个气候站的冬季最低温度的24, 48, 72 h预报模型, 并且以2006年12月和2007年的1、 2月作为24, 48, 72 h逐日最低温度预报试验时段。试验表明, 对于青海地区来说, 青海北部地区的预报命中率总体好于南部高原地区; 在4种对比方案中, 以选择数值预报资料结合前一日地面观测的最低温度作为主要因子的方法相对较优, 随着预报时效的延长, 24 h历史实况的作用逐渐减弱; 对于所有台站来说, 这4种方案各有优缺点, 没有一种方案可以完全代替其他所有方案; 在实际业务运行中, 对不同的台站应采用不同的预报方案进行实际业务预报。 相似文献
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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