吴息,吴文倩,王彬滨. 2016. 城市化对近地层风速概率分布及参数的影响[J]. 气象学报, 74(4):623-632, doi:10.11676/qxxb2016.042
城市化对近地层风速概率分布及参数的影响
Effects of urbanization on surface layer wind speed probability distribution and its parameters
投稿时间:2015-12-14  修订日期:2016-04-21
DOI:10.11676/qxxb2016.042
中文关键词:  城市化  地面风速  概率分布律  Weibull分布参数
英文关键词:Urbanization  Surface wind speed  Probability distribution law  Weibull distribution parameters
基金项目:国家重点基础研究发展规划项目(2010CB428505)、国家自然科学基金重点项目(41230528)。
作者单位
吴息 南京信息工程大学 气象灾害预报预警与评估协同创新中心 气象灾害教育部重点实验室, 南京, 210044 
吴文倩 南京信息工程大学 气象灾害预报预警与评估协同创新中心 气象灾害教育部重点实验室, 南京, 210044 
王彬滨 中国电力建设集团 四川电力设计咨询有限责任公司, 成都, 610041 
摘要点击次数: 2016
全文下载次数: 2060
中文摘要:
      通过地面风速Weibull概率分布参数的阶段变化来描述城市化对地面风速的影响,并通过理论分析得出城市化进程导致其尺度参数c缩小,位置参数r增大的趋势效应的结论。将北京等8个城市1982-2005年地面天气资料定时数据按时间划分为前、后两个时段,分别拟合分布曲线的参数,对比前、后两个时段的拟合结果,验证了理论分析所得结论,即随城市的发展,各城市风参数c不同程度地缩小,r不同程度地增大,同时概率密度曲线的峰值均增大;不同城市的风速概率密度函数曲线变化特征有所不同,根据前、后时段概率密度曲线变化的特征,8个城市风速概率分布变化大致可分为A、B两种类型,两者的主要差异是A型变化特征为在曲线两端(大风和静风)的概率都减少,曲线分布更加集中;B型则是大风概率减少而静风的概率则增大,曲线向左移动;A型变化城市的r参数平均增大46.3%,明显大于B型城市的15.7%。初步资料分析还表明,风参数cr变化幅度与城市化扩张速度有关。
英文摘要:
      In this paper, parameters of Weibull distribution were used to describe effects of urbanization on surface wind speed. Theoretical analysis indicated that urbanization could lead to a decrease in the scale parameter c and an increase in the location parameter r. Surface weather timing mode observations collected at Beijing and other 8 cities during 1982-2005 were divided into 2 segments based on different time periods and parameters of distribution curve were fitted respectively. Fitting results confirmed the conclusions that with the development of the city, parameter c decreased and parameter r increased in varying degrees, and their probability density peaks both increased. Characteristics of wind speed probability density function curves in different cities could be different. According to this feature, city wind speed probability distribution changes in the 8 cities could be divided into Type A and Type B approximately. The main difference in the features of the curves between the two types was that for Type A, both the strong and calm wind probabilities decreased as shown in both sides of the curve and the distribution become more concentrated; for Type B, the strong wind probability decreased but the calm wind probability increased and the curve moved to the left;r parameter increased by 46.3% in average in Type A cities, which was greater than that in Type B cities by 15.7%. Initial data analysis also indicated that the variation degree of wind speed parameter c and parameter r was related to the speed of urban expansion.
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