摘要
高寒地区交通线路风吹雪灾害严重,对交通线路全线天气状况的预测对于该类灾害的预测至关重要,目前该方面的研究仍然比较缺乏。该文采用WRF(天气研究预报模型)中尺度天气数值模拟,以新疆克塔铁路为研究对象,模拟该线路所在区域2018年−2019年冬季的天气状况。通过水平分辨率10 km~2 km的双重嵌套模拟,调整微物理方案及行星边界层方案,得到铁路沿线不同路段风速分布概率以及相应的主导风向。研究表明:WRF模拟结果能够较好的反映出道路沿线各路段不同的风速概率分布,结合主导风向与线路夹角,为预测不同路段发生风吹雪灾害的概率提供更加精确地依据,并为道路选线以及路段形式的设计提供参考。
The traffic line in the alpine region is deeply affected by drifting snow disasters.The weather along the entire traffic line is very important on predicting the snowdrift disaster,but there is still a lack of research in this area.In the present study,the mesoscale model WRF(the Weather Research and Forecasting Model)is used to predicate the weather in the winter of the Karamay-Tacheng Railway in Xinjiang from 2018 to 2019.This simulation is mainly two-level nested with a horizontal resolution of 10 km-2 km and adopts different microphysics and planetary boundary layer physics to obtain different distribution probability of wind velocity and dominant wind direction along the railway line.The results show that the WRF simulation results can reflect different probability distribution of wind speeds in different sections along the railway.Combined with the angle between the dominant wind direction and the traffic line,it can provide a more accurate basis for predicting the probability of drifting snow disasters in different sections and a reference for the design of traffic lines and sections form.
作者
骆颜
马文勇
孙元春
LUO Yan;MA Wen-yong;SUN Yuan-chun(School of Civil Engineering,Shijiazhuang Tiedao University,Shijiazhuang,Hebei 050043,China;Innovation Center for Wind Engineering and Wind Energy Technology of Hebei Province,Shijiazhuang,Hebei 050043,China;Key Laboratory of Roads and Railway Engineering Safety Control of Ministry of Education,Shijiazhuang Tiedao University,Shijiazhuang,Hebei 050043,China;China Railway Design Corporation,Tianjin 300251,China)
出处
《工程力学》
EI
CSCD
北大核心
2022年第S01期195-201,共7页
Engineering Mechanics
基金
河北省引进留学人员资助项目(C20200359)
石家庄铁道大学研究生创新资助项目(YC2021019)。
关键词
道路与铁道工程
天气预测
WRF模式
风吹雪
概率分布
highway and railway engineering
weather prediction
WRF
drifting snow
probability distribution
