摘要
上海徐家汇地区建筑分布密集且高低不一,是典型的具有非均一下垫面特征的城市地貌。本文利用该地区的地理信息研究了粗糙度长度的分布规律,并基于80m高度的风速实测数据,对台风"灿鸿"和良态风作用下的平均风速、湍流强度、阵风因子等参数与粗糙度长度之间的关系进行了分析。结果表明:不同风向角对应的计算扇区内建筑物高度、分布密度的差别导致了粗糙度长度值随风向角发生明显变化,但是变化幅度随着计算扇区的增大而减小;台风"灿鸿"作用下的平均风速最大值大于良态风,两者对应的粗糙度长度变化范围差别甚微,但是台风作用下的粗糙度长度中位数较小且分布相对集中;台风"灿鸿"作用下各向湍流强度均随着平均风速的增加呈明显的减小趋势,但不随粗糙度长度变化;良态风作用下,各向湍流强度不随平均风速变化,而随着粗糙度长度的增加而增加;台风"灿鸿"和良态风作用下,各向阵风因子均随湍流强度的增加而增大,但前者作用下的阵风因子略大于后者。
The Xujiahui district of Shanghai is a typical non-homogeneous urban terrain,with densely distributed architectures of different heights.In this paper,the distribution characteristics of roughness length are studied by using the geographic information of this area.Based on the measured wind data at the height of 80 m,the relationships among the mean wind velocity,turbulence intensity,gust factor and roughness length under the Typhoon Chan-hom and the normal wind are analyzed.The results show that the differences of building heights and distribution densities in the calculated sectors corresponding to different wind directions led to the obvious variation of roughness length with wind direction,but the variation amplitude decreased with the increase of calculated sectors.The maximum value of mean wind velocity under Typhoon Chan-hom was larger than that under normal winds,and there was little difference in the range of roughness length variation,but the median value of the roughness length under Typhoon Chan-hom was small and the distribution was relatively concentrated.Under Typhoon Chan-hom,the turbulence intensity in all directions decreased with the increase of mean wind velocity,but did not change with the roughness length.Under normal wind,the turbulence intensity in each direction does not change with the mean wind velocity,but increases with the increase of roughness length.Under typhoon Chanhom and normal wind,the gust factor in all directions increases with the increase of turbulence intensity,but the former values are slightly larger than the latter.
作者
韩志惠
王旭
唐玉琪
岳彩军
敖翔宇
HAN Zhihui;WANG Xu;TANG Yuqi;YUE Caijun;AO Xiangyu(Shanghai Ecological Forecasting and Remote Sensing Center,Shanghai 200030;Chongqing Jiaotong University,College of Civil Engineering,Chongqing 400074)
出处
《气象科技》
2020年第4期529-536,共8页
Meteorological Science and Technology
基金
国家自然科学基金项目(41875059)
上海市科学技术委员会科研计划项目(17DZ1205300)资助。
