共查询到19条相似文献,搜索用时 93 毫秒
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介绍了柳州市区排水现状,对柳州市四种不同类型降水过程造成的渍涝灾害进行了数值模拟,将模拟结果与实测数据进行了对比分析,得出了柳州市渍涝灾害特征,并针对渍涝灾害的成因提出了防涝治涝对策,这对拓展城市灾害预报服务领域具有一定的参考作用。 相似文献
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近58年柳州市汛期降水特征分析 总被引:6,自引:1,他引:5
利用柳州市1951~2008年的月降水量资料,采用线性倾向估计和小波分析方法,分析了近58a柳州市汛期(4~9月)降水的变化特征。结果表明:近58a来柳州市汛期降水主要呈波动性变化,线性趋势变化不明显,但前汛期降水总体呈上升趋势,降水量约增加87mm;后汛期降水量总体呈下降趋势,约减少了89mm。因此,前汛期有变涝趋势,后汛期有变旱趋势。近58年柳州市汛期降水年代际变化的主要周期为20~25a,20世纪80年代以后,汛期降水存在周期10-15a的年代际变化。20世纪80年代以前,柳州市汛期降水主要的年际变化周期2~4a,以后的年际变化周期是4~8a。 相似文献
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利用1986-2015年柳州市区和五县一区观测站资料,采用考虑了气温、风速、相对湿度等要素的人体舒适度计算方法,计算了柳州市境内的逐日人体舒适度指数,统计不同舒适等级天数,并分季节分别对市区和县(区)的舒适度指数进行了统计分析。结果表明:(1)柳州的年舒适日数较多,全境都达到229d以上,占全年的约2/3的时间,各县区的年平均舒适度指数都有逐年增高趋势,趋近人体感觉很好。(2)年舒适日数最多的区域在柳州市区和三江、融水、柳城、柳江的西侧。(3)柳州市人体舒适度在春季、秋季最舒适,夏季在融水、三江海拔较高的山区人体舒适度较高,冬季柳州市区和柳江大部地区较为舒适。 相似文献
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本文利用1992年12月“柳州市大气环境监测点位优化研究”中20天网格监测资料与当时对应的气象条件进行分析,得出了各气象要素对柳州市1992年12月大气污染的影响关系。 相似文献
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达坂城风力发电厂风的天气气候特征及预报问题研究 总被引:4,自引:0,他引:4
陈勇航 《沙漠与绿洲气象(新疆气象)》2000,23(5):5-7
对达坂城风力发电厂提供的1998年该厂单点风速资料进行统计分析,总结出天气气候特征,并运用天气学方法对其进行研究,找出预报指标,强调了单点风速预报制作过程中的实验问题。 相似文献
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Summary This work presents a statistical study of the wind power potential of three stations in the Catalonia area (Spain) over the 1973–1982 period. These stations correspond to three airports (Barcelona, Palma de Mallorca and Girona), which obviously do not present a high wind power potential and are not the suitable locations for wind power utilization, but which have been chosen for the long record of data stored (10 years). The aim of this work is to provide a model of wind potential in terms of the speed and wind direction, which may be applied to other sites. The wind speed has been modelled by a Weibull distribution function and the wind direction by a normal two-dimensional function. A spectral analysis of both variables has also been carried out. The present study provides an evaluation of the local wind power in the geographic area of Catalonia.With 10 Figures 相似文献
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分析广西风能资源评价工作取得的主要成绩和存在问题,为进一步做好广西风能资源评价工作,提出一些探讨性思路。 相似文献
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Robert J. Davy Milton J. Woods Christopher J. Russell Peter A. Coppin 《Boundary-Layer Meteorology》2010,135(1):161-175
Measurements show that on numerous occasions the low-level wind is highly variable across a large portion of south-eastern Australia. Under such conditions the risk of a large rapid change in total wind power is increased. While variability tends to increase with mean wind speed, a large component of wind variability is not explained by wind speed alone. In this work, reanalysis fields from the US National Centers for Environmental Prediction (NCEP) are statistically downscaled to model wind variability at a coastal location in Victoria, Australia. In order to reduce the dimensionality of the problem, the NCEP fields are each decomposed using empirical orthogonal function (EOF) techniques. The downscaling technique is applied to two periods in the seasonal cycle, namely (i) winter to early spring, and (ii) summer. In each case, data representing 2 years are used to form a model that is then validated using independent data from another year. The EOFs that best predict wind variability are examined. To allow for non-linearity and complex interaction between variables, all empirical models are built using random forests. Quantitatively, the model compares favourably with a simple regression of wind variability against wind speed, as well as multiple linear regression models. 相似文献